Log file created at: 2017/07/07 18:30:29
Running on machine: SPA-90-72-58
Log line format: [IWEF]mmdd hh:mm:ss.uuuuuu threadid file:line] msg
I0707 18:30:29.933169 99468 caffe.cpp:218] Using GPUs 0
I0707 18:30:41.790043 99468 caffe.cpp:223] GPU 0: Tesla K40c
I0707 18:30:42.571486 99468 solver.cpp:44] Initializing solver from parameters: 
test_iter: 2344
test_interval: 4000
base_lr: 0.001
display: 40
max_iter: 50000
lr_policy: "step"
gamma: 0.96
momentum: 0.9
weight_decay: 0.0002
stepsize: 120000
snapshot: 40000
snapshot_prefix: "/data04/googlenet/caffemodel/"
solver_mode: GPU
device_id: 0
net: "/data04/googlenet/stn_train_val.prototxt"
train_state {
  level: 0
  stage: ""
}
test_initialization: false
average_loss: 40
iter_size: 2
I0707 18:30:42.572002 99468 solver.cpp:87] Creating training net from net file: /data04/googlenet/stn_train_val.prototxt
I0707 18:30:42.576721 99468 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer data
I0707 18:30:42.576803 99468 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer loss1/top-1
I0707 18:30:42.576861 99468 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer loss1/top-5
I0707 18:30:42.576910 99468 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer loss2/top-1
I0707 18:30:42.576921 99468 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer loss2/top-5
I0707 18:30:42.576967 99468 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer loss3/top-1
I0707 18:30:42.576990 99468 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer loss3/top-5
I0707 18:30:42.578212 99468 net.cpp:51] Initializing net from parameters: 
name: "GoogleNet"
state {
  phase: TRAIN
  level: 0
  stage: ""
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "/data04/data/img_train_lmdb"
    batch_size: 64
    backend: LMDB
  }
}
layer {
  name: "loc_conv1"
  type: "Convolution"
  bottom: "data"
  top: "loc_conv1"
  convolution_param {
    num_output: 20
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "loc_pool1"
  type: "Pooling"
  bottom: "loc_conv1"
  top: "loc_pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "loc_relu1"
  type: "ReLU"
  bottom: "loc_pool1"
  top: "loc_pool1"
}
layer {
  name: "loc_conv2"
  type: "Convolution"
  bottom: "loc_pool1"
  top: "loc_conv2"
  convolution_param {
    num_output: 20
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "loc_pool2"
  type: "Pooling"
  bottom: "loc_conv2"
  top: "loc_pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "loc_relu2"
  type: "ReLU"
  bottom: "loc_pool2"
  top: "loc_pool2"
}
layer {
  name: "loc_ip1"
  type: "InnerProduct"
  bottom: "loc_pool2"
  top: "loc_ip1"
  inner_product_param {
    num_output: 20
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "loc_relu3"
  type: "ReLU"
  bottom: "loc_ip1"
  top: "loc_ip1"
}
layer {
  name: "loc_reg"
  type: "InnerProduct"
  bottom: "loc_ip1"
  top: "theta"
  inner_product_param {
    num_output: 6
    weight_filler {
      type: "constant"
      value: 0
    }
    bias_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "st_layer"
  type: "SpatialTransformer"
  bottom: "data"
  bottom: "theta"
  top: "st_output"
}
layer {
  name: "conv1/7x7_s2"
  type: "Convolution"
  bottom: "st_output"
  top: "conv1/7x7_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 3
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/relu_7x7"
  type: "ReLU"
  bottom: "conv1/7x7_s2"
  top: "conv1/7x7_s2"
}
layer {
  name: "pool1/3x3_s2"
  type: "Pooling"
  bottom: "conv1/7x7_s2"
  top: "pool1/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "pool1/norm1"
  type: "LRN"
  bottom: "pool1/3x3_s2"
  top: "pool1/norm1"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv2/3x3_reduce"
  type: "Convolution"
  bottom: "pool1/norm1"
  top: "conv2/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_reduce"
  type: "ReLU"
  bottom: "conv2/3x3_reduce"
  top: "conv2/3x3_reduce"
}
layer {
  name: "conv2/3x3"
  type: "Convolution"
  bottom: "conv2/3x3_reduce"
  top: "conv2/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3"
  type: "ReLU"
  bottom: "conv2/3x3"
  top: "conv2/3x3"
}
layer {
  name: "conv2/norm2"
  type: "LRN"
  bottom: "conv2/3x3"
  top: "conv2/norm2"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "pool2/3x3_s2"
  type: "Pooling"
  bottom: "conv2/norm2"
  top: "pool2/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_3a/1x1"
  type: "Convolution"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_1x1"
  type: "ReLU"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
}
layer {
  name: "inception_3a/3x3_reduce"
  type: "Convolution"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_3a/3x3_reduce"
  top: "inception_3a/3x3_reduce"
}
layer {
  name: "inception_3a/3x3"
  type: "Convolution"
  bottom: "inception_3a/3x3_reduce"
  top: "inception_3a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3"
  type: "ReLU"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
}
layer {
  name: "inception_3a/5x5_reduce"
  type: "Convolution"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_3a/5x5_reduce"
  top: "inception_3a/5x5_reduce"
}
layer {
  name: "inception_3a/5x5"
  type: "Convolution"
  bottom: "inception_3a/5x5_reduce"
  top: "inception_3a/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5"
  type: "ReLU"
  bottom: "inception_3a/5x5"
  top: "inception_3a/5x5"
}
layer {
  name: "inception_3a/pool"
  type: "Pooling"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3a/pool_proj"
  type: "Convolution"
  bottom: "inception_3a/pool"
  top: "inception_3a/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_3a/pool_proj"
  top: "inception_3a/pool_proj"
}
layer {
  name: "inception_3a/output"
  type: "Concat"
  bottom: "inception_3a/1x1"
  bottom: "inception_3a/3x3"
  bottom: "inception_3a/5x5"
  bottom: "inception_3a/pool_proj"
  top: "inception_3a/output"
}
layer {
  name: "inception_3b/1x1"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "inception_3b/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_1x1"
  type: "ReLU"
  bottom: "inception_3b/1x1"
  top: "inception_3b/1x1"
}
layer {
  name: "inception_3b/3x3_reduce"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "inception_3b/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_3b/3x3_reduce"
  top: "inception_3b/3x3_reduce"
}
layer {
  name: "inception_3b/3x3"
  type: "Convolution"
  bottom: "inception_3b/3x3_reduce"
  top: "inception_3b/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3"
  type: "ReLU"
  bottom: "inception_3b/3x3"
  top: "inception_3b/3x3"
}
layer {
  name: "inception_3b/5x5_reduce"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "inception_3b/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_3b/5x5_reduce"
  top: "inception_3b/5x5_reduce"
}
layer {
  name: "inception_3b/5x5"
  type: "Convolution"
  bottom: "inception_3b/5x5_reduce"
  top: "inception_3b/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5"
  type: "ReLU"
  bottom: "inception_3b/5x5"
  top: "inception_3b/5x5"
}
layer {
  name: "inception_3b/pool"
  type: "Pooling"
  bottom: "inception_3a/output"
  top: "inception_3b/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3b/pool_proj"
  type: "Convolution"
  bottom: "inception_3b/pool"
  top: "inception_3b/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_3b/pool_proj"
  top: "inception_3b/pool_proj"
}
layer {
  name: "inception_3b/output"
  type: "Concat"
  bottom: "inception_3b/1x1"
  bottom: "inception_3b/3x3"
  bottom: "inception_3b/5x5"
  bottom: "inception_3b/pool_proj"
  top: "inception_3b/output"
}
layer {
  name: "pool3/3x3_s2"
  type: "Pooling"
  bottom: "inception_3b/output"
  top: "pool3/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_4a/1x1"
  type: "Convolution"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_1x1"
  type: "ReLU"
  bottom: "inception_4a/1x1"
  top: "inception_4a/1x1"
}
layer {
  name: "inception_4a/3x3_reduce"
  type: "Convolution"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4a/3x3_reduce"
  top: "inception_4a/3x3_reduce"
}
layer {
  name: "inception_4a/3x3"
  type: "Convolution"
  bottom: "inception_4a/3x3_reduce"
  top: "inception_4a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 208
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3"
  type: "ReLU"
  bottom: "inception_4a/3x3"
  top: "inception_4a/3x3"
}
layer {
  name: "inception_4a/5x5_reduce"
  type: "Convolution"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4a/5x5_reduce"
  top: "inception_4a/5x5_reduce"
}
layer {
  name: "inception_4a/5x5"
  type: "Convolution"
  bottom: "inception_4a/5x5_reduce"
  top: "inception_4a/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5"
  type: "ReLU"
  bottom: "inception_4a/5x5"
  top: "inception_4a/5x5"
}
layer {
  name: "inception_4a/pool"
  type: "Pooling"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4a/pool_proj"
  type: "Convolution"
  bottom: "inception_4a/pool"
  top: "inception_4a/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4a/pool_proj"
  top: "inception_4a/pool_proj"
}
layer {
  name: "inception_4a/output"
  type: "Concat"
  bottom: "inception_4a/1x1"
  bottom: "inception_4a/3x3"
  bottom: "inception_4a/5x5"
  bottom: "inception_4a/pool_proj"
  top: "inception_4a/output"
}
layer {
  name: "loss1/ave_pool"
  type: "Pooling"
  bottom: "inception_4a/output"
  top: "loss1/ave_pool"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss1/conv"
  type: "Convolution"
  bottom: "loss1/ave_pool"
  top: "loss1/conv"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_conv"
  type: "ReLU"
  bottom: "loss1/conv"
  top: "loss1/conv"
}
layer {
  name: "loss1/fc"
  type: "InnerProduct"
  bottom: "loss1/conv"
  top: "loss1/fc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_fc"
  type: "ReLU"
  bottom: "loss1/fc"
  top: "loss1/fc"
}
layer {
  name: "loss1/drop_fc"
  type: "Dropout"
  bottom: "loss1/fc"
  top: "loss1/fc"
  dropout_param {
    dropout_ratio: 0.7
  }
}
layer {
  name: "loss1/classifier_my"
  type: "InnerProduct"
  bottom: "loss1/fc"
  top: "loss1/classifier"
  param {
    lr_mult: 10
    decay_mult: 1
  }
  param {
    lr_mult: 20
    decay_mult: 0
  }
  inner_product_param {
    num_output: 39
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "loss1/loss"
  type: "SoftmaxWithLoss"
  bottom: "loss1/classifier"
  bottom: "label"
  top: "loss1/loss1"
  loss_weight: 0.3
}
layer {
  name: "inception_4b/1x1"
  type: "Convolution"
  bottom: "inception_4a/output"
  top: "inception_4b/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_1x1"
  type: "ReLU"
  bottom: "inception_4b/1x1"
  top: "inception_4b/1x1"
}
layer {
  name: "inception_4b/3x3_reduce"
  type: "Convolution"
  bottom: "inception_4a/output"
  top: "inception_4b/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4b/3x3_reduce"
  top: "inception_4b/3x3_reduce"
}
layer {
  name: "inception_4b/3x3"
  type: "Convolution"
  bottom: "inception_4b/3x3_reduce"
  top: "inception_4b/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 224
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3"
  type: "ReLU"
  bottom: "inception_4b/3x3"
  top: "inception_4b/3x3"
}
layer {
  name: "inception_4b/5x5_reduce"
  type: "Convolution"
  bottom: "inception_4a/output"
  top: "inception_4b/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4b/5x5_reduce"
  top: "inception_4b/5x5_reduce"
}
layer {
  name: "inception_4b/5x5"
  type: "Convolution"
  bottom: "inception_4b/5x5_reduce"
  top: "inception_4b/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5"
  type: "ReLU"
  bottom: "inception_4b/5x5"
  top: "inception_4b/5x5"
}
layer {
  name: "inception_4b/pool"
  type: "Pooling"
  bottom: "inception_4a/output"
  top: "inception_4b/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4b/pool_proj"
  type: "Convolution"
  bottom: "inception_4b/pool"
  top: "inception_4b/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4b/pool_proj"
  top: "inception_4b/pool_proj"
}
layer {
  name: "inception_4b/output"
  type: "Concat"
  bottom: "inception_4b/1x1"
  bottom: "inception_4b/3x3"
  bottom: "inception_4b/5x5"
  bottom: "inception_4b/pool_proj"
  top: "inception_4b/output"
}
layer {
  name: "inception_4c/1x1"
  type: "Convolution"
  bottom: "inception_4b/output"
  top: "inception_4c/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_1x1"
  type: "ReLU"
  bottom: "inception_4c/1x1"
  top: "inception_4c/1x1"
}
layer {
  name: "inception_4c/3x3_reduce"
  type: "Convolution"
  bottom: "inception_4b/output"
  top: "inception_4c/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4c/3x3_reduce"
  top: "inception_4c/3x3_reduce"
}
layer {
  name: "inception_4c/3x3"
  type: "Convolution"
  bottom: "inception_4c/3x3_reduce"
  top: "inception_4c/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3"
  type: "ReLU"
  bottom: "inception_4c/3x3"
  top: "inception_4c/3x3"
}
layer {
  name: "inception_4c/5x5_reduce"
  type: "Convolution"
  bottom: "inception_4b/output"
  top: "inception_4c/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4c/5x5_reduce"
  top: "inception_4c/5x5_reduce"
}
layer {
  name: "inception_4c/5x5"
  type: "Convolution"
  bottom: "inception_4c/5x5_reduce"
  top: "inception_4c/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5"
  type: "ReLU"
  bottom: "inception_4c/5x5"
  top: "inception_4c/5x5"
}
layer {
  name: "inception_4c/pool"
  type: "Pooling"
  bottom: "inception_4b/output"
  top: "inception_4c/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4c/pool_proj"
  type: "Convolution"
  bottom: "inception_4c/pool"
  top: "inception_4c/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4c/pool_proj"
  top: "inception_4c/pool_proj"
}
layer {
  name: "inception_4c/output"
  type: "Concat"
  bottom: "inception_4c/1x1"
  bottom: "inception_4c/3x3"
  bottom: "inception_4c/5x5"
  bottom: "inception_4c/pool_proj"
  top: "inception_4c/output"
}
layer {
  name: "inception_4d/1x1"
  type: "Convolution"
  bottom: "inception_4c/output"
  top: "inception_4d/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_1x1"
  type: "ReLU"
  bottom: "inception_4d/1x1"
  top: "inception_4d/1x1"
}
layer {
  name: "inception_4d/3x3_reduce"
  type: "Convolution"
  bottom: "inception_4c/output"
  top: "inception_4d/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 144
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4d/3x3_reduce"
  top: "inception_4d/3x3_reduce"
}
layer {
  name: "inception_4d/3x3"
  type: "Convolution"
  bottom: "inception_4d/3x3_reduce"
  top: "inception_4d/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 288
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3"
  type: "ReLU"
  bottom: "inception_4d/3x3"
  top: "inception_4d/3x3"
}
layer {
  name: "inception_4d/5x5_reduce"
  type: "Convolution"
  bottom: "inception_4c/output"
  top: "inception_4d/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4d/5x5_reduce"
  top: "inception_4d/5x5_reduce"
}
layer {
  name: "inception_4d/5x5"
  type: "Convolution"
  bottom: "inception_4d/5x5_reduce"
  top: "inception_4d/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5"
  type: "ReLU"
  bottom: "inception_4d/5x5"
  top: "inception_4d/5x5"
}
layer {
  name: "inception_4d/pool"
  type: "Pooling"
  bottom: "inception_4c/output"
  top: "inception_4d/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4d/pool_proj"
  type: "Convolution"
  bottom: "inception_4d/pool"
  top: "inception_4d/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4d/pool_proj"
  top: "inception_4d/pool_proj"
}
layer {
  name: "inception_4d/output"
  type: "Concat"
  bottom: "inception_4d/1x1"
  bottom: "inception_4d/3x3"
  bottom: "inception_4d/5x5"
  bottom: "inception_4d/pool_proj"
  top: "inception_4d/output"
}
layer {
  name: "loss2/ave_pool"
  type: "Pooling"
  bottom: "inception_4d/output"
  top: "loss2/ave_pool"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss2/conv"
  type: "Convolution"
  bottom: "loss2/ave_pool"
  top: "loss2/conv"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_conv"
  type: "ReLU"
  bottom: "loss2/conv"
  top: "loss2/conv"
}
layer {
  name: "loss2/fc"
  type: "InnerProduct"
  bottom: "loss2/conv"
  top: "loss2/fc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_fc"
  type: "ReLU"
  bottom: "loss2/fc"
  top: "loss2/fc"
}
layer {
  name: "loss2/drop_fc"
  type: "Dropout"
  bottom: "loss2/fc"
  top: "loss2/fc"
  dropout_param {
    dropout_ratio: 0.7
  }
}
layer {
  name: "loss2/classifier_my"
  type: "InnerProduct"
  bottom: "loss2/fc"
  top: "loss2/classifier"
  param {
    lr_mult: 10
    decay_mult: 1
  }
  param {
    lr_mult: 20
    decay_mult: 0
  }
  inner_product_param {
    num_output: 39
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "loss2/loss"
  type: "SoftmaxWithLoss"
  bottom: "loss2/classifier"
  bottom: "label"
  top: "loss2/loss2"
  loss_weight: 0.3
}
layer {
  name: "inception_4e/1x1"
  type: "Convolution"
  bottom: "inception_4d/output"
  top: "inception_4e/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_1x1"
  type: "ReLU"
  bottom: "inception_4e/1x1"
  top: "inception_4e/1x1"
}
layer {
  name: "inception_4e/3x3_reduce"
  type: "Convolution"
  bottom: "inception_4d/output"
  top: "inception_4e/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4e/3x3_reduce"
  top: "inception_4e/3x3_reduce"
}
layer {
  name: "inception_4e/3x3"
 
I0707 18:30:42.588506 99468 layer_factory.hpp:77] Creating layer data
I0707 18:30:42.588727 99468 db_lmdb.cpp:35] Opened lmdb /data04/data/img_train_lmdb
I0707 18:30:42.588795 99468 net.cpp:84] Creating Layer data
I0707 18:30:42.588820 99468 net.cpp:380] data -> data
I0707 18:30:42.588862 99468 net.cpp:380] data -> label
I0707 18:30:42.590739 99468 data_layer.cpp:45] output data size: 64,3,224,224
I0707 18:30:42.725538 99468 net.cpp:122] Setting up data
I0707 18:30:42.725636 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:42.725652 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:42.725663 99468 net.cpp:137] Memory required for data: 38535424
I0707 18:30:42.725688 99468 layer_factory.hpp:77] Creating layer data_data_0_split
I0707 18:30:42.725744 99468 net.cpp:84] Creating Layer data_data_0_split
I0707 18:30:42.725769 99468 net.cpp:406] data_data_0_split <- data
I0707 18:30:42.725827 99468 net.cpp:380] data_data_0_split -> data_data_0_split_0
I0707 18:30:42.725853 99468 net.cpp:380] data_data_0_split -> data_data_0_split_1
I0707 18:30:42.725973 99468 net.cpp:122] Setting up data_data_0_split
I0707 18:30:42.725993 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:42.726058 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:42.726084 99468 net.cpp:137] Memory required for data: 115605760
I0707 18:30:42.726094 99468 layer_factory.hpp:77] Creating layer label_data_1_split
I0707 18:30:42.726117 99468 net.cpp:84] Creating Layer label_data_1_split
I0707 18:30:42.726128 99468 net.cpp:406] label_data_1_split <- label
I0707 18:30:42.726147 99468 net.cpp:380] label_data_1_split -> label_data_1_split_0
I0707 18:30:42.726168 99468 net.cpp:380] label_data_1_split -> label_data_1_split_1
I0707 18:30:42.726184 99468 net.cpp:380] label_data_1_split -> label_data_1_split_2
I0707 18:30:42.726250 99468 net.cpp:122] Setting up label_data_1_split
I0707 18:30:42.726266 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:42.726281 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:42.726294 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:42.726305 99468 net.cpp:137] Memory required for data: 115606528
I0707 18:30:42.726312 99468 layer_factory.hpp:77] Creating layer loc_conv1
I0707 18:30:42.726349 99468 net.cpp:84] Creating Layer loc_conv1
I0707 18:30:42.726363 99468 net.cpp:406] loc_conv1 <- data_data_0_split_0
I0707 18:30:42.726382 99468 net.cpp:380] loc_conv1 -> loc_conv1
I0707 18:30:43.005429 99468 net.cpp:122] Setting up loc_conv1
I0707 18:30:43.005512 99468 net.cpp:129] Top shape: 64 20 220 220 (61952000)
I0707 18:30:43.005523 99468 net.cpp:137] Memory required for data: 363414528
I0707 18:30:43.005566 99468 layer_factory.hpp:77] Creating layer loc_pool1
I0707 18:30:43.005599 99468 net.cpp:84] Creating Layer loc_pool1
I0707 18:30:43.005612 99468 net.cpp:406] loc_pool1 <- loc_conv1
I0707 18:30:43.005633 99468 net.cpp:380] loc_pool1 -> loc_pool1
I0707 18:30:43.005761 99468 net.cpp:122] Setting up loc_pool1
I0707 18:30:43.005781 99468 net.cpp:129] Top shape: 64 20 110 110 (15488000)
I0707 18:30:43.005795 99468 net.cpp:137] Memory required for data: 425366528
I0707 18:30:43.005807 99468 layer_factory.hpp:77] Creating layer loc_relu1
I0707 18:30:43.005841 99468 net.cpp:84] Creating Layer loc_relu1
I0707 18:30:43.005872 99468 net.cpp:406] loc_relu1 <- loc_pool1
I0707 18:30:43.005900 99468 net.cpp:367] loc_relu1 -> loc_pool1 (in-place)
I0707 18:30:43.006783 99468 net.cpp:122] Setting up loc_relu1
I0707 18:30:43.006815 99468 net.cpp:129] Top shape: 64 20 110 110 (15488000)
I0707 18:30:43.006825 99468 net.cpp:137] Memory required for data: 487318528
I0707 18:30:43.006834 99468 layer_factory.hpp:77] Creating layer loc_conv2
I0707 18:30:43.006891 99468 net.cpp:84] Creating Layer loc_conv2
I0707 18:30:43.006906 99468 net.cpp:406] loc_conv2 <- loc_pool1
I0707 18:30:43.006920 99468 net.cpp:380] loc_conv2 -> loc_conv2
I0707 18:30:43.010056 99468 net.cpp:122] Setting up loc_conv2
I0707 18:30:43.010087 99468 net.cpp:129] Top shape: 64 20 106 106 (14382080)
I0707 18:30:43.010097 99468 net.cpp:137] Memory required for data: 544846848
I0707 18:30:43.010113 99468 layer_factory.hpp:77] Creating layer loc_pool2
I0707 18:30:43.010129 99468 net.cpp:84] Creating Layer loc_pool2
I0707 18:30:43.010140 99468 net.cpp:406] loc_pool2 <- loc_conv2
I0707 18:30:43.010186 99468 net.cpp:380] loc_pool2 -> loc_pool2
I0707 18:30:43.010247 99468 net.cpp:122] Setting up loc_pool2
I0707 18:30:43.010268 99468 net.cpp:129] Top shape: 64 20 53 53 (3595520)
I0707 18:30:43.010303 99468 net.cpp:137] Memory required for data: 559228928
I0707 18:30:43.010329 99468 layer_factory.hpp:77] Creating layer loc_relu2
I0707 18:30:43.010344 99468 net.cpp:84] Creating Layer loc_relu2
I0707 18:30:43.010360 99468 net.cpp:406] loc_relu2 <- loc_pool2
I0707 18:30:43.010375 99468 net.cpp:367] loc_relu2 -> loc_pool2 (in-place)
I0707 18:30:43.010613 99468 net.cpp:122] Setting up loc_relu2
I0707 18:30:43.010635 99468 net.cpp:129] Top shape: 64 20 53 53 (3595520)
I0707 18:30:43.010648 99468 net.cpp:137] Memory required for data: 573611008
I0707 18:30:43.010659 99468 layer_factory.hpp:77] Creating layer loc_ip1
I0707 18:30:43.010679 99468 net.cpp:84] Creating Layer loc_ip1
I0707 18:30:43.010694 99468 net.cpp:406] loc_ip1 <- loc_pool2
I0707 18:30:43.010766 99468 net.cpp:380] loc_ip1 -> loc_ip1
I0707 18:30:43.021580 99468 net.cpp:122] Setting up loc_ip1
I0707 18:30:43.021607 99468 net.cpp:129] Top shape: 64 20 (1280)
I0707 18:30:43.021616 99468 net.cpp:137] Memory required for data: 573616128
I0707 18:30:43.021633 99468 layer_factory.hpp:77] Creating layer loc_relu3
I0707 18:30:43.021648 99468 net.cpp:84] Creating Layer loc_relu3
I0707 18:30:43.021664 99468 net.cpp:406] loc_relu3 <- loc_ip1
I0707 18:30:43.021677 99468 net.cpp:367] loc_relu3 -> loc_ip1 (in-place)
I0707 18:30:43.022568 99468 net.cpp:122] Setting up loc_relu3
I0707 18:30:43.022596 99468 net.cpp:129] Top shape: 64 20 (1280)
I0707 18:30:43.022606 99468 net.cpp:137] Memory required for data: 573621248
I0707 18:30:43.022614 99468 layer_factory.hpp:77] Creating layer loc_reg
I0707 18:30:43.022629 99468 net.cpp:84] Creating Layer loc_reg
I0707 18:30:43.022640 99468 net.cpp:406] loc_reg <- loc_ip1
I0707 18:30:43.022656 99468 net.cpp:380] loc_reg -> theta
I0707 18:30:43.022799 99468 net.cpp:122] Setting up loc_reg
I0707 18:30:43.022817 99468 net.cpp:129] Top shape: 64 6 (384)
I0707 18:30:43.022856 99468 net.cpp:137] Memory required for data: 573622784
I0707 18:30:43.022869 99468 layer_factory.hpp:77] Creating layer st_layer
I0707 18:30:43.022895 99468 net.cpp:84] Creating Layer st_layer
I0707 18:30:43.022907 99468 net.cpp:406] st_layer <- data_data_0_split_1
I0707 18:30:43.022940 99468 net.cpp:406] st_layer <- theta
I0707 18:30:43.022971 99468 net.cpp:380] st_layer -> st_output
I0707 18:30:43.025364 99468 net.cpp:122] Setting up st_layer
I0707 18:30:43.025388 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:43.025401 99468 net.cpp:137] Memory required for data: 612157952
I0707 18:30:43.025414 99468 layer_factory.hpp:77] Creating layer conv1/7x7_s2
I0707 18:30:43.025435 99468 net.cpp:84] Creating Layer conv1/7x7_s2
I0707 18:30:43.025449 99468 net.cpp:406] conv1/7x7_s2 <- st_output
I0707 18:30:43.025463 99468 net.cpp:380] conv1/7x7_s2 -> conv1/7x7_s2
I0707 18:30:43.027151 99468 net.cpp:122] Setting up conv1/7x7_s2
I0707 18:30:43.027179 99468 net.cpp:129] Top shape: 64 64 112 112 (51380224)
I0707 18:30:43.027189 99468 net.cpp:137] Memory required for data: 817678848
I0707 18:30:43.027205 99468 layer_factory.hpp:77] Creating layer conv1/relu_7x7
I0707 18:30:43.027230 99468 net.cpp:84] Creating Layer conv1/relu_7x7
I0707 18:30:43.027245 99468 net.cpp:406] conv1/relu_7x7 <- conv1/7x7_s2
I0707 18:30:43.027256 99468 net.cpp:367] conv1/relu_7x7 -> conv1/7x7_s2 (in-place)
I0707 18:30:43.028115 99468 net.cpp:122] Setting up conv1/relu_7x7
I0707 18:30:43.028144 99468 net.cpp:129] Top shape: 64 64 112 112 (51380224)
I0707 18:30:43.028153 99468 net.cpp:137] Memory required for data: 1023199744
I0707 18:30:43.028162 99468 layer_factory.hpp:77] Creating layer pool1/3x3_s2
I0707 18:30:43.028174 99468 net.cpp:84] Creating Layer pool1/3x3_s2
I0707 18:30:43.028185 99468 net.cpp:406] pool1/3x3_s2 <- conv1/7x7_s2
I0707 18:30:43.028203 99468 net.cpp:380] pool1/3x3_s2 -> pool1/3x3_s2
I0707 18:30:43.028265 99468 net.cpp:122] Setting up pool1/3x3_s2
I0707 18:30:43.028282 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.028296 99468 net.cpp:137] Memory required for data: 1074579968
I0707 18:30:43.028306 99468 layer_factory.hpp:77] Creating layer pool1/norm1
I0707 18:30:43.028331 99468 net.cpp:84] Creating Layer pool1/norm1
I0707 18:30:43.028352 99468 net.cpp:406] pool1/norm1 <- pool1/3x3_s2
I0707 18:30:43.028376 99468 net.cpp:380] pool1/norm1 -> pool1/norm1
I0707 18:30:43.028661 99468 net.cpp:122] Setting up pool1/norm1
I0707 18:30:43.028686 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.028704 99468 net.cpp:137] Memory required for data: 1125960192
I0707 18:30:43.028718 99468 layer_factory.hpp:77] Creating layer conv2/3x3_reduce
I0707 18:30:43.028741 99468 net.cpp:84] Creating Layer conv2/3x3_reduce
I0707 18:30:43.028754 99468 net.cpp:406] conv2/3x3_reduce <- pool1/norm1
I0707 18:30:43.028772 99468 net.cpp:380] conv2/3x3_reduce -> conv2/3x3_reduce
I0707 18:30:43.031046 99468 net.cpp:122] Setting up conv2/3x3_reduce
I0707 18:30:43.031095 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.031105 99468 net.cpp:137] Memory required for data: 1177340416
I0707 18:30:43.031117 99468 layer_factory.hpp:77] Creating layer conv2/relu_3x3_reduce
I0707 18:30:43.031141 99468 net.cpp:84] Creating Layer conv2/relu_3x3_reduce
I0707 18:30:43.031157 99468 net.cpp:406] conv2/relu_3x3_reduce <- conv2/3x3_reduce
I0707 18:30:43.031167 99468 net.cpp:367] conv2/relu_3x3_reduce -> conv2/3x3_reduce (in-place)
I0707 18:30:43.032034 99468 net.cpp:122] Setting up conv2/relu_3x3_reduce
I0707 18:30:43.032060 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.032068 99468 net.cpp:137] Memory required for data: 1228720640
I0707 18:30:43.032078 99468 layer_factory.hpp:77] Creating layer conv2/3x3
I0707 18:30:43.032096 99468 net.cpp:84] Creating Layer conv2/3x3
I0707 18:30:43.032109 99468 net.cpp:406] conv2/3x3 <- conv2/3x3_reduce
I0707 18:30:43.032125 99468 net.cpp:380] conv2/3x3 -> conv2/3x3
I0707 18:30:43.035826 99468 net.cpp:122] Setting up conv2/3x3
I0707 18:30:43.035854 99468 net.cpp:129] Top shape: 64 192 56 56 (38535168)
I0707 18:30:43.035864 99468 net.cpp:137] Memory required for data: 1382861312
I0707 18:30:43.035877 99468 layer_factory.hpp:77] Creating layer conv2/relu_3x3
I0707 18:30:43.035890 99468 net.cpp:84] Creating Layer conv2/relu_3x3
I0707 18:30:43.035902 99468 net.cpp:406] conv2/relu_3x3 <- conv2/3x3
I0707 18:30:43.035917 99468 net.cpp:367] conv2/relu_3x3 -> conv2/3x3 (in-place)
I0707 18:30:43.036190 99468 net.cpp:122] Setting up conv2/relu_3x3
I0707 18:30:43.036211 99468 net.cpp:129] Top shape: 64 192 56 56 (38535168)
I0707 18:30:43.036239 99468 net.cpp:137] Memory required for data: 1537001984
I0707 18:30:43.036248 99468 layer_factory.hpp:77] Creating layer conv2/norm2
I0707 18:30:43.036269 99468 net.cpp:84] Creating Layer conv2/norm2
I0707 18:30:43.036281 99468 net.cpp:406] conv2/norm2 <- conv2/3x3
I0707 18:30:43.036309 99468 net.cpp:380] conv2/norm2 -> conv2/norm2
I0707 18:30:43.037250 99468 net.cpp:122] Setting up conv2/norm2
I0707 18:30:43.037276 99468 net.cpp:129] Top shape: 64 192 56 56 (38535168)
I0707 18:30:43.037286 99468 net.cpp:137] Memory required for data: 1691142656
I0707 18:30:43.037294 99468 layer_factory.hpp:77] Creating layer pool2/3x3_s2
I0707 18:30:43.037309 99468 net.cpp:84] Creating Layer pool2/3x3_s2
I0707 18:30:43.037320 99468 net.cpp:406] pool2/3x3_s2 <- conv2/norm2
I0707 18:30:43.037338 99468 net.cpp:380] pool2/3x3_s2 -> pool2/3x3_s2
I0707 18:30:43.037392 99468 net.cpp:122] Setting up pool2/3x3_s2
I0707 18:30:43.037425 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.037451 99468 net.cpp:137] Memory required for data: 1729677824
I0707 18:30:43.037461 99468 layer_factory.hpp:77] Creating layer pool2/3x3_s2_pool2/3x3_s2_0_split
I0707 18:30:43.037477 99468 net.cpp:84] Creating Layer pool2/3x3_s2_pool2/3x3_s2_0_split
I0707 18:30:43.037489 99468 net.cpp:406] pool2/3x3_s2_pool2/3x3_s2_0_split <- pool2/3x3_s2
I0707 18:30:43.037500 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_0
I0707 18:30:43.037521 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_1
I0707 18:30:43.037535 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_2
I0707 18:30:43.037551 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_3
I0707 18:30:43.037638 99468 net.cpp:122] Setting up pool2/3x3_s2_pool2/3x3_s2_0_split
I0707 18:30:43.037654 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.037668 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.037683 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.037696 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.037708 99468 net.cpp:137] Memory required for data: 1883818496
I0707 18:30:43.037715 99468 layer_factory.hpp:77] Creating layer inception_3a/1x1
I0707 18:30:43.037739 99468 net.cpp:84] Creating Layer inception_3a/1x1
I0707 18:30:43.037775 99468 net.cpp:406] inception_3a/1x1 <- pool2/3x3_s2_pool2/3x3_s2_0_split_0
I0707 18:30:43.037796 99468 net.cpp:380] inception_3a/1x1 -> inception_3a/1x1
I0707 18:30:43.040302 99468 net.cpp:122] Setting up inception_3a/1x1
I0707 18:30:43.040333 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.040347 99468 net.cpp:137] Memory required for data: 1896663552
I0707 18:30:43.040392 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_1x1
I0707 18:30:43.040410 99468 net.cpp:84] Creating Layer inception_3a/relu_1x1
I0707 18:30:43.040437 99468 net.cpp:406] inception_3a/relu_1x1 <- inception_3a/1x1
I0707 18:30:43.040468 99468 net.cpp:367] inception_3a/relu_1x1 -> inception_3a/1x1 (in-place)
I0707 18:30:43.041328 99468 net.cpp:122] Setting up inception_3a/relu_1x1
I0707 18:30:43.041355 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.041368 99468 net.cpp:137] Memory required for data: 1909508608
I0707 18:30:43.041376 99468 layer_factory.hpp:77] Creating layer inception_3a/3x3_reduce
I0707 18:30:43.041394 99468 net.cpp:84] Creating Layer inception_3a/3x3_reduce
I0707 18:30:43.041405 99468 net.cpp:406] inception_3a/3x3_reduce <- pool2/3x3_s2_pool2/3x3_s2_0_split_1
I0707 18:30:43.041455 99468 net.cpp:380] inception_3a/3x3_reduce -> inception_3a/3x3_reduce
I0707 18:30:43.044514 99468 net.cpp:122] Setting up inception_3a/3x3_reduce
I0707 18:30:43.044543 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.044559 99468 net.cpp:137] Memory required for data: 1928776192
I0707 18:30:43.044585 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_3x3_reduce
I0707 18:30:43.044601 99468 net.cpp:84] Creating Layer inception_3a/relu_3x3_reduce
I0707 18:30:43.044612 99468 net.cpp:406] inception_3a/relu_3x3_reduce <- inception_3a/3x3_reduce
I0707 18:30:43.044628 99468 net.cpp:367] inception_3a/relu_3x3_reduce -> inception_3a/3x3_reduce (in-place)
I0707 18:30:43.045560 99468 net.cpp:122] Setting up inception_3a/relu_3x3_reduce
I0707 18:30:43.045586 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.045595 99468 net.cpp:137] Memory required for data: 1948043776
I0707 18:30:43.045603 99468 layer_factory.hpp:77] Creating layer inception_3a/3x3
I0707 18:30:43.045622 99468 net.cpp:84] Creating Layer inception_3a/3x3
I0707 18:30:43.045667 99468 net.cpp:406] inception_3a/3x3 <- inception_3a/3x3_reduce
I0707 18:30:43.045687 99468 net.cpp:380] inception_3a/3x3 -> inception_3a/3x3
I0707 18:30:43.050027 99468 net.cpp:122] Setting up inception_3a/3x3
I0707 18:30:43.050057 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.050067 99468 net.cpp:137] Memory required for data: 1973733888
I0707 18:30:43.050081 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_3x3
I0707 18:30:43.050096 99468 net.cpp:84] Creating Layer inception_3a/relu_3x3
I0707 18:30:43.050107 99468 net.cpp:406] inception_3a/relu_3x3 <- inception_3a/3x3
I0707 18:30:43.050123 99468 net.cpp:367] inception_3a/relu_3x3 -> inception_3a/3x3 (in-place)
I0707 18:30:43.051024 99468 net.cpp:122] Setting up inception_3a/relu_3x3
I0707 18:30:43.051053 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.051061 99468 net.cpp:137] Memory required for data: 1999424000
I0707 18:30:43.051070 99468 layer_factory.hpp:77] Creating layer inception_3a/5x5_reduce
I0707 18:30:43.051089 99468 net.cpp:84] Creating Layer inception_3a/5x5_reduce
I0707 18:30:43.051100 99468 net.cpp:406] inception_3a/5x5_reduce <- pool2/3x3_s2_pool2/3x3_s2_0_split_2
I0707 18:30:43.051115 99468 net.cpp:380] inception_3a/5x5_reduce -> inception_3a/5x5_reduce
I0707 18:30:43.052814 99468 net.cpp:122] Setting up inception_3a/5x5_reduce
I0707 18:30:43.052844 99468 net.cpp:129] Top shape: 64 16 28 28 (802816)
I0707 18:30:43.052852 99468 net.cpp:137] Memory required for data: 2002635264
I0707 18:30:43.052865 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_5x5_reduce
I0707 18:30:43.052881 99468 net.cpp:84] Creating Layer inception_3a/relu_5x5_reduce
I0707 18:30:43.052925 99468 net.cpp:406] inception_3a/relu_5x5_reduce <- inception_3a/5x5_reduce
I0707 18:30:43.052974 99468 net.cpp:367] inception_3a/relu_5x5_reduce -> inception_3a/5x5_reduce (in-place)
I0707 18:30:43.053840 99468 net.cpp:122] Setting up inception_3a/relu_5x5_reduce
I0707 18:30:43.053866 99468 net.cpp:129] Top shape: 64 16 28 28 (802816)
I0707 18:30:43.053875 99468 net.cpp:137] Memory required for data: 2005846528
I0707 18:30:43.053884 99468 layer_factory.hpp:77] Creating layer inception_3a/5x5
I0707 18:30:43.053910 99468 net.cpp:84] Creating Layer inception_3a/5x5
I0707 18:30:43.053953 99468 net.cpp:406] inception_3a/5x5 <- inception_3a/5x5_reduce
I0707 18:30:43.053968 99468 net.cpp:380] inception_3a/5x5 -> inception_3a/5x5
I0707 18:30:43.056319 99468 net.cpp:122] Setting up inception_3a/5x5
I0707 18:30:43.056349 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.056357 99468 net.cpp:137] Memory required for data: 2012269056
I0707 18:30:43.056370 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_5x5
I0707 18:30:43.056383 99468 net.cpp:84] Creating Layer inception_3a/relu_5x5
I0707 18:30:43.056394 99468 net.cpp:406] inception_3a/relu_5x5 <- inception_3a/5x5
I0707 18:30:43.056411 99468 net.cpp:367] inception_3a/relu_5x5 -> inception_3a/5x5 (in-place)
I0707 18:30:43.056684 99468 net.cpp:122] Setting up inception_3a/relu_5x5
I0707 18:30:43.056704 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.056736 99468 net.cpp:137] Memory required for data: 2018691584
I0707 18:30:43.056746 99468 layer_factory.hpp:77] Creating layer inception_3a/pool
I0707 18:30:43.056757 99468 net.cpp:84] Creating Layer inception_3a/pool
I0707 18:30:43.056789 99468 net.cpp:406] inception_3a/pool <- pool2/3x3_s2_pool2/3x3_s2_0_split_3
I0707 18:30:43.056818 99468 net.cpp:380] inception_3a/pool -> inception_3a/pool
I0707 18:30:43.056881 99468 net.cpp:122] Setting up inception_3a/pool
I0707 18:30:43.056900 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.056908 99468 net.cpp:137] Memory required for data: 2057226752
I0707 18:30:43.056923 99468 layer_factory.hpp:77] Creating layer inception_3a/pool_proj
I0707 18:30:43.056942 99468 net.cpp:84] Creating Layer inception_3a/pool_proj
I0707 18:30:43.056957 99468 net.cpp:406] inception_3a/pool_proj <- inception_3a/pool
I0707 18:30:43.056975 99468 net.cpp:380] inception_3a/pool_proj -> inception_3a/pool_proj
I0707 18:30:43.070578 99468 net.cpp:122] Setting up inception_3a/pool_proj
I0707 18:30:43.070607 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.070621 99468 net.cpp:137] Memory required for data: 2063649280
I0707 18:30:43.070639 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_pool_proj
I0707 18:30:43.070657 99468 net.cpp:84] Creating Layer inception_3a/relu_pool_proj
I0707 18:30:43.070667 99468 net.cpp:406] inception_3a/relu_pool_proj <- inception_3a/pool_proj
I0707 18:30:43.070686 99468 net.cpp:367] inception_3a/relu_pool_proj -> inception_3a/pool_proj (in-place)
I0707 18:30:43.071550 99468 net.cpp:122] Setting up inception_3a/relu_pool_proj
I0707 18:30:43.071583 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.071591 99468 net.cpp:137] Memory required for data: 2070071808
I0707 18:30:43.071601 99468 layer_factory.hpp:77] Creating layer inception_3a/output
I0707 18:30:43.071620 99468 net.cpp:84] Creating Layer inception_3a/output
I0707 18:30:43.071663 99468 net.cpp:406] inception_3a/output <- inception_3a/1x1
I0707 18:30:43.071679 99468 net.cpp:406] inception_3a/output <- inception_3a/3x3
I0707 18:30:43.071691 99468 net.cpp:406] inception_3a/output <- inception_3a/5x5
I0707 18:30:43.071703 99468 net.cpp:406] inception_3a/output <- inception_3a/pool_proj
I0707 18:30:43.071718 99468 net.cpp:380] inception_3a/output -> inception_3a/output
I0707 18:30:43.071781 99468 net.cpp:122] Setting up inception_3a/output
I0707 18:30:43.071799 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.071828 99468 net.cpp:137] Memory required for data: 2121452032
I0707 18:30:43.071837 99468 layer_factory.hpp:77] Creating layer inception_3a/output_inception_3a/output_0_split
I0707 18:30:43.071882 99468 net.cpp:84] Creating Layer inception_3a/output_inception_3a/output_0_split
I0707 18:30:43.071898 99468 net.cpp:406] inception_3a/output_inception_3a/output_0_split <- inception_3a/output
I0707 18:30:43.071931 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_0
I0707 18:30:43.071946 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_1
I0707 18:30:43.071964 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_2
I0707 18:30:43.071976 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_3
I0707 18:30:43.072059 99468 net.cpp:122] Setting up inception_3a/output_inception_3a/output_0_split
I0707 18:30:43.072078 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.072091 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.072104 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.072116 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.072124 99468 net.cpp:137] Memory required for data: 2326972928
I0707 18:30:43.072139 99468 layer_factory.hpp:77] Creating layer inception_3b/1x1
I0707 18:30:43.072157 99468 net.cpp:84] Creating Layer inception_3b/1x1
I0707 18:30:43.072172 99468 net.cpp:406] inception_3b/1x1 <- inception_3a/output_inception_3a/output_0_split_0
I0707 18:30:43.072190 99468 net.cpp:380] inception_3b/1x1 -> inception_3b/1x1
I0707 18:30:43.074096 99468 net.cpp:122] Setting up inception_3b/1x1
I0707 18:30:43.074126 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.074134 99468 net.cpp:137] Memory required for data: 2352663040
I0707 18:30:43.074147 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_1x1
I0707 18:30:43.074169 99468 net.cpp:84] Creating Layer inception_3b/relu_1x1
I0707 18:30:43.074182 99468 net.cpp:406] inception_3b/relu_1x1 <- inception_3b/1x1
I0707 18:30:43.074225 99468 net.cpp:367] inception_3b/relu_1x1 -> inception_3b/1x1 (in-place)
I0707 18:30:43.075091 99468 net.cpp:122] Setting up inception_3b/relu_1x1
I0707 18:30:43.075117 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.075126 99468 net.cpp:137] Memory required for data: 2378353152
I0707 18:30:43.075135 99468 layer_factory.hpp:77] Creating layer inception_3b/3x3_reduce
I0707 18:30:43.075153 99468 net.cpp:84] Creating Layer inception_3b/3x3_reduce
I0707 18:30:43.075166 99468 net.cpp:406] inception_3b/3x3_reduce <- inception_3a/output_inception_3a/output_0_split_1
I0707 18:30:43.075183 99468 net.cpp:380] inception_3b/3x3_reduce -> inception_3b/3x3_reduce
I0707 18:30:43.077713 99468 net.cpp:122] Setting up inception_3b/3x3_reduce
I0707 18:30:43.077742 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.077751 99468 net.cpp:137] Memory required for data: 2404043264
I0707 18:30:43.077765 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_3x3_reduce
I0707 18:30:43.077814 99468 net.cpp:84] Creating Layer inception_3b/relu_3x3_reduce
I0707 18:30:43.077829 99468 net.cpp:406] inception_3b/relu_3x3_reduce <- inception_3b/3x3_reduce
I0707 18:30:43.077842 99468 net.cpp:367] inception_3b/relu_3x3_reduce -> inception_3b/3x3_reduce (in-place)
I0707 18:30:43.078094 99468 net.cpp:122] Setting up inception_3b/relu_3x3_reduce
I0707 18:30:43.078114 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.078141 99468 net.cpp:137] Memory required for data: 2429733376
I0707 18:30:43.078150 99468 layer_factory.hpp:77] Creating layer inception_3b/3x3
I0707 18:30:43.078176 99468 net.cpp:84] Creating Layer inception_3b/3x3
I0707 18:30:43.078186 99468 net.cpp:406] inception_3b/3x3 <- inception_3b/3x3_reduce
I0707 18:30:43.078203 99468 net.cpp:380] inception_3b/3x3 -> inception_3b/3x3
I0707 18:30:43.082880 99468 net.cpp:122] Setting up inception_3b/3x3
I0707 18:30:43.082926 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.082937 99468 net.cpp:137] Memory required for data: 2468268544
I0707 18:30:43.082948 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_3x3
I0707 18:30:43.082968 99468 net.cpp:84] Creating Layer inception_3b/relu_3x3
I0707 18:30:43.083022 99468 net.cpp:406] inception_3b/relu_3x3 <- inception_3b/3x3
I0707 18:30:43.083035 99468 net.cpp:367] inception_3b/relu_3x3 -> inception_3b/3x3 (in-place)
I0707 18:30:43.083921 99468 net.cpp:122] Setting up inception_3b/relu_3x3
I0707 18:30:43.083950 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.083959 99468 net.cpp:137] Memory required for data: 2506803712
I0707 18:30:43.083967 99468 layer_factory.hpp:77] Creating layer inception_3b/5x5_reduce
I0707 18:30:43.083984 99468 net.cpp:84] Creating Layer inception_3b/5x5_reduce
I0707 18:30:43.083997 99468 net.cpp:406] inception_3b/5x5_reduce <- inception_3a/output_inception_3a/output_0_split_2
I0707 18:30:43.084013 99468 net.cpp:380] inception_3b/5x5_reduce -> inception_3b/5x5_reduce
I0707 18:30:43.085728 99468 net.cpp:122] Setting up inception_3b/5x5_reduce
I0707 18:30:43.085757 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.085767 99468 net.cpp:137] Memory required for data: 2513226240
I0707 18:30:43.085794 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_5x5_reduce
I0707 18:30:43.085813 99468 net.cpp:84] Creating Layer inception_3b/relu_5x5_reduce
I0707 18:30:43.085822 99468 net.cpp:406] inception_3b/relu_5x5_reduce <- inception_3b/5x5_reduce
I0707 18:30:43.085840 99468 net.cpp:367] inception_3b/relu_5x5_reduce -> inception_3b/5x5_reduce (in-place)
I0707 18:30:43.087339 99468 net.cpp:122] Setting up inception_3b/relu_5x5_reduce
I0707 18:30:43.087369 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.087378 99468 net.cpp:137] Memory required for data: 2519648768
I0707 18:30:43.087388 99468 layer_factory.hpp:77] Creating layer inception_3b/5x5
I0707 18:30:43.087406 99468 net.cpp:84] Creating Layer inception_3b/5x5
I0707 18:30:43.087419 99468 net.cpp:406] inception_3b/5x5 <- inception_3b/5x5_reduce
I0707 18:30:43.087433 99468 net.cpp:380] inception_3b/5x5 -> inception_3b/5x5
I0707 18:30:43.090334 99468 net.cpp:122] Setting up inception_3b/5x5
I0707 18:30:43.090363 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.090373 99468 net.cpp:137] Memory required for data: 2538916352
I0707 18:30:43.090385 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_5x5
I0707 18:30:43.090402 99468 net.cpp:84] Creating Layer inception_3b/relu_5x5
I0707 18:30:43.090415 99468 net.cpp:406] inception_3b/relu_5x5 <- inception_3b/5x5
I0707 18:30:43.090430 99468 net.cpp:367] inception_3b/relu_5x5 -> inception_3b/5x5 (in-place)
I0707 18:30:43.090679 99468 net.cpp:122] Setting up inception_3b/relu_5x5
I0707 18:30:43.090700 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.090709 99468 net.cpp:137] Memory required for data: 2558183936
I0707 18:30:43.090718 99468 layer_factory.hpp:77] Creating layer inception_3b/pool
I0707 18:30:43.090734 99468 net.cpp:84] Creating Layer inception_3b/pool
I0707 18:30:43.090746 99468 net.cpp:406] inception_3b/pool <- inception_3a/output_inception_3a/output_0_split_3
I0707 18:30:43.090788 99468 net.cpp:380] inception_3b/pool -> inception_3b/pool
I0707 18:30:43.090855 99468 net.cpp:122] Setting up inception_3b/pool
I0707 18:30:43.090872 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.090898 99468 net.cpp:137] Memory required for data: 2609564160
I0707 18:30:43.090908 99468 layer_factory.hpp:77] Creating layer inception_3b/pool_proj
I0707 18:30:43.090943 99468 net.cpp:84] Creating Layer inception_3b/pool_proj
I0707 18:30:43.090970 99468 net.cpp:406] inception_3b/pool_proj <- inception_3b/pool
I0707 18:30:43.090988 99468 net.cpp:380] inception_3b/pool_proj -> inception_3b/pool_proj
I0707 18:30:43.093392 99468 net.cpp:122] Setting up inception_3b/pool_proj
I0707 18:30:43.093420 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.093447 99468 net.cpp:137] Memory required for data: 2622409216
I0707 18:30:43.093462 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_pool_proj
I0707 18:30:43.093513 99468 net.cpp:84] Creating Layer inception_3b/relu_pool_proj
I0707 18:30:43.093524 99468 net.cpp:406] inception_3b/relu_pool_proj <- inception_3b/pool_proj
I0707 18:30:43.093560 99468 net.cpp:367] inception_3b/relu_pool_proj -> inception_3b/pool_proj (in-place)
I0707 18:30:43.094429 99468 net.cpp:122] Setting up inception_3b/relu_pool_proj
I0707 18:30:43.094455 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.094465 99468 net.cpp:137] Memory required for data: 2635254272
I0707 18:30:43.094473 99468 layer_factory.hpp:77] Creating layer inception_3b/output
I0707 18:30:43.094512 99468 net.cpp:84] Creating Layer inception_3b/output
I0707 18:30:43.094527 99468 net.cpp:406] inception_3b/output <- inception_3b/1x1
I0707 18:30:43.094543 99468 net.cpp:406] inception_3b/output <- inception_3b/3x3
I0707 18:30:43.094560 99468 net.cpp:406] inception_3b/output <- inception_3b/5x5
I0707 18:30:43.094575 99468 net.cpp:406] inception_3b/output <- inception_3b/pool_proj
I0707 18:30:43.094590 99468 net.cpp:380] inception_3b/output -> inception_3b/output
I0707 18:30:43.094641 99468 net.cpp:122] Setting up inception_3b/output
I0707 18:30:43.094658 99468 net.cpp:129] Top shape: 64 480 28 28 (24084480)
I0707 18:30:43.094671 99468 net.cpp:137] Memory required for data: 2731592192
I0707 18:30:43.094683 99468 layer_factory.hpp:77] Creating layer pool3/3x3_s2
I0707 18:30:43.094700 99468 net.cpp:84] Creating Layer pool3/3x3_s2
I0707 18:30:43.094714 99468 net.cpp:406] pool3/3x3_s2 <- inception_3b/output
I0707 18:30:43.094728 99468 net.cpp:380] pool3/3x3_s2 -> pool3/3x3_s2
I0707 18:30:43.094794 99468 net.cpp:122] Setting up pool3/3x3_s2
I0707 18:30:43.094810 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.094821 99468 net.cpp:137] Memory required for data: 2755676672
I0707 18:30:43.094835 99468 layer_factory.hpp:77] Creating layer pool3/3x3_s2_pool3/3x3_s2_0_split
I0707 18:30:43.094847 99468 net.cpp:84] Creating Layer pool3/3x3_s2_pool3/3x3_s2_0_split
I0707 18:30:43.094861 99468 net.cpp:406] pool3/3x3_s2_pool3/3x3_s2_0_split <- pool3/3x3_s2
I0707 18:30:43.094877 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_0
I0707 18:30:43.094892 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_1
I0707 18:30:43.094903 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_2
I0707 18:30:43.094923 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_3
I0707 18:30:43.095006 99468 net.cpp:122] Setting up pool3/3x3_s2_pool3/3x3_s2_0_split
I0707 18:30:43.095022 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.095036 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.095051 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.095062 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.095075 99468 net.cpp:137] Memory required for data: 2852014592
I0707 18:30:43.095088 99468 layer_factory.hpp:77] Creating layer inception_4a/1x1
I0707 18:30:43.095105 99468 net.cpp:84] Creating Layer inception_4a/1x1
I0707 18:30:43.095118 99468 net.cpp:406] inception_4a/1x1 <- pool3/3x3_s2_pool3/3x3_s2_0_split_0
I0707 18:30:43.095139 99468 net.cpp:380] inception_4a/1x1 -> inception_4a/1x1
I0707 18:30:43.098309 99468 net.cpp:122] Setting up inception_4a/1x1
I0707 18:30:43.098341 99468 net.cpp:129] Top shape: 64 192 14 14 (2408448)
I0707 18:30:43.098357 99468 net.cpp:137] Memory required for data: 2861648384
I0707 18:30:43.098374 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_1x1
I0707 18:30:43.098395 99468 net.cpp:84] Creating Layer inception_4a/relu_1x1
I0707 18:30:43.098407 99468 net.cpp:406] inception_4a/relu_1x1 <- inception_4a/1x1
I0707 18:30:43.098424 99468 net.cpp:367] inception_4a/relu_1x1 -> inception_4a/1x1 (in-place)
I0707 18:30:43.099313 99468 net.cpp:122] Setting up inception_4a/relu_1x1
I0707 18:30:43.099339 99468 net.cpp:129] Top shape: 64 192 14 14 (2408448)
I0707 18:30:43.099347 99468 net.cpp:137] Memory required for data: 2871282176
I0707 18:30:43.099356 99468 layer_factory.hpp:77] Creating layer inception_4a/3x3_reduce
I0707 18:30:43.099375 99468 net.cpp:84] Creating Layer inception_4a/3x3_reduce
I0707 18:30:43.099392 99468 net.cpp:406] inception_4a/3x3_reduce <- pool3/3x3_s2_pool3/3x3_s2_0_split_1
I0707 18:30:43.099408 99468 net.cpp:380] inception_4a/3x3_reduce -> inception_4a/3x3_reduce
I0707 18:30:43.102092 99468 net.cpp:122] Setting up inception_4a/3x3_reduce
I0707 18:30:43.102120 99468 net.cpp:129] Top shape: 64 96 14 14 (1204224)
I0707 18:30:43.102129 99468 net.cpp:137] Memory required for data: 2876099072
I0707 18:30:43.102141 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_3x3_reduce
I0707 18:30:43.102154 99468 net.cpp:84] Creating Layer inception_4a/relu_3x3_reduce
I0707 18:30:43.102165 99468 net.cpp:406] inception_4a/relu_3x3_reduce <- inception_4a/3x3_reduce
I0707 18:30:43.102192 99468 net.cpp:367] inception_4a/relu_3x3_reduce -> inception_4a/3x3_reduce (in-place)
I0707 18:30:43.102433 99468 net.cpp:122] Setting up inception_4a/relu_3x3_reduce
I0707 18:30:43.102454 99468 net.cpp:129] Top shape: 64 96 14 14 (1204224)
I0707 18:30:43.102491 99468 net.cpp:137] Memory required for data: 2880915968
I0707 18:30:43.102500 99468 layer_factory.hpp:77] Creating layer inception_4a/3x3
I0707 18:30:43.102519 99468 net.cpp:84] Creating Layer inception_4a/3x3
I0707 18:30:43.102532 99468 net.cpp:406] inception_4a/3x3 <- inception_4a/3x3_reduce
I0707 18:30:43.102577 99468 net.cpp:380] inception_4a/3x3 -> inception_4a/3x3
I0707 18:30:43.106995 99468 net.cpp:122] Setting up inception_4a/3x3
I0707 18:30:43.107025 99468 net.cpp:129] Top shape: 64 208 14 14 (2609152)
I0707 18:30:43.107034 99468 net.cpp:137] Memory required for data: 2891352576
I0707 18:30:43.107048 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_3x3
I0707 18:30:43.107059 99468 net.cpp:84] Creating Layer inception_4a/relu_3x3
I0707 18:30:43.107071 99468 net.cpp:406] inception_4a/relu_3x3 <- inception_4a/3x3
I0707 18:30:43.107091 99468 net.cpp:367] inception_4a/relu_3x3 -> inception_4a/3x3 (in-place)
I0707 18:30:43.107967 99468 net.cpp:122] Setting up inception_4a/relu_3x3
I0707 18:30:43.107993 99468 net.cpp:129] Top shape: 64 208 14 14 (2609152)
I0707 18:30:43.108002 99468 net.cpp:137] Memory required for data: 2901789184
I0707 18:30:43.108011 99468 layer_factory.hpp:77] Creating layer inception_4a/5x5_reduce
I0707 18:30:43.108029 99468 net.cpp:84] Creating Layer inception_4a/5x5_reduce
I0707 18:30:43.108042 99468 net.cpp:406] inception_4a/5x5_reduce <- pool3/3x3_s2_pool3/3x3_s2_0_split_2
I0707 18:30:43.108059 99468 net.cpp:380] inception_4a/5x5_reduce -> inception_4a/5x5_reduce
I0707 18:30:43.109840 99468 net.cpp:122] Setting up inception_4a/5x5_reduce
I0707 18:30:43.109869 99468 net.cpp:129] Top shape: 64 16 14 14 (200704)
I0707 18:30:43.109877 99468 net.cpp:137] Memory required for data: 2902592000
I0707 18:30:43.109890 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_5x5_reduce
I0707 18:30:43.109905 99468 net.cpp:84] Creating Layer inception_4a/relu_5x5_reduce
I0707 18:30:43.109916 99468 net.cpp:406] inception_4a/relu_5x5_reduce <- inception_4a/5x5_reduce
I0707 18:30:43.109930 99468 net.cpp:367] inception_4a/relu_5x5_reduce -> inception_4a/5x5_reduce (in-place)
I0707 18:30:43.110831 99468 net.cpp:122] Setting up inception_4a/relu_5x5_reduce
I0707 18:30:43.110858 99468 net.cpp:129] Top shape: 64 16 14 14 (200704)
I0707 18:30:43.110868 99468 net.cpp:137] Memory required for data: 2903394816
I0707 18:30:43.110877 99468 layer_factory.hpp:77] Creating layer inception_4a/5x5
I0707 18:30:43.110895 99468 net.cpp:84] Creating Layer inception_4a/5x5
I0707 18:30:43.110911 99468 net.cpp:406] inception_4a/5x5 <- inception_4a/5x5_reduce
I0707 18:30:43.110925 99468 net.cpp:380] inception_4a/5x5 -> inception_4a/5x5
I0707 18:30:43.113379 99468 net.cpp:122] Setting up inception_4a/5x5
I0707 18:30:43.113425 99468 net.cpp:129] Top shape: 64 48 14 14 (602112)
I0707 18:30:43.113435 99468 net.cpp:137] Memory required for data: 2905803264
I0707 18:30:43.113448 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_5x5
I0707 18:30:43.113468 99468 net.cpp:84] Creating Layer inception_4a/relu_5x5
I0707 18:30:43.113481 99468 net.cpp:406] inception_4a/relu_5x5 <- inception_4a/5x5
I0707 18:30:43.113525 99468 net.cpp:367] inception_4a/relu_5x5 -> inception_4a/5x5 (in-place)
I0707 18:30:43.113798 99468 net.cpp:122] Setting up inception_4a/relu_5x5
I0707 18:30:43.113819 99468 net.cpp:129] Top shape: 64 48 14 14 (602112)
I0707 18:30:43.113827 99468 net.cpp:137] Memory required for data: 2908211712
I0707 18:30:43.113839 99468 layer_factory.hpp:77] Creating layer inception_4a/pool
I0707 18:30:43.113878 99468 net.cpp:84] Creating Layer inception_4a/pool
I0707 18:30:43.113888 99468 net.cpp:406] inception_4a/pool <- pool3/3x3_s2_pool3/3x3_s2_0_split_3
I0707 18:30:43.113916 99468 net.cpp:380] inception_4a/pool -> inception_4a/pool
I0707 18:30:43.113989 99468 net.cpp:122] Setting up inception_4a/pool
I0707 18:30:43.114006 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.114030 99468 net.cpp:137] Memory required for data: 2932296192
I0707 18:30:43.114040 99468 layer_factory.hpp:77] Creating layer inception_4a/pool_proj
I0707 18:30:43.114063 99468 net.cpp:84] Creating Layer inception_4a/pool_proj
I0707 18:30:43.114079 99468 net.cpp:406] inception_4a/pool_proj <- inception_4a/pool
I0707 18:30:43.114099 99468 net.cpp:380] inception_4a/pool_proj -> inception_4a/pool_proj
I0707 18:30:43.116636 99468 net.cpp:122] Setting up inception_4a/pool_proj
I0707 18:30:43.116664 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.116673 99468 net.cpp:137] Memory required for data: 2935507456
I0707 18:30:43.116685 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_pool_proj
I0707 18:30:43.116704 99468 net.cpp:84] Creating Layer inception_4a/relu_pool_proj
I0707 18:30:43.116716 99468 net.cpp:406] inception_4a/relu_pool_proj <- inception_4a/pool_proj
I0707 18:30:43.116757 99468 net.cpp:367] inception_4a/relu_pool_proj -> inception_4a/pool_proj (in-place)
I0707 18:30:43.118281 99468 net.cpp:122] Setting up inception_4a/relu_pool_proj
I0707 18:30:43.118309 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.118319 99468 net.cpp:137] Memory required for data: 2938718720
I0707 18:30:43.118327 99468 layer_factory.hpp:77] Creating layer inception_4a/output
I0707 18:30:43.118343 99468 net.cpp:84] Creating Layer inception_4a/output
I0707 18:30:43.118355 99468 net.cpp:406] inception_4a/output <- inception_4a/1x1
I0707 18:30:43.118369 99468 net.cpp:406] inception_4a/output <- inception_4a/3x3
I0707 18:30:43.118410 99468 net.cpp:406] inception_4a/output <- inception_4a/5x5
I0707 18:30:43.118424 99468 net.cpp:406] inception_4a/output <- inception_4a/pool_proj
I0707 18:30:43.118434 99468 net.cpp:380] inception_4a/output -> inception_4a/output
I0707 18:30:43.118480 99468 net.cpp:122] Setting up inception_4a/output
I0707 18:30:43.118505 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.118530 99468 net.cpp:137] Memory required for data: 2964408832
I0707 18:30:43.118543 99468 layer_factory.hpp:77] Creating layer inception_4a/output_inception_4a/output_0_split
I0707 18:30:43.118568 99468 net.cpp:84] Creating Layer inception_4a/output_inception_4a/output_0_split
I0707 18:30:43.118580 99468 net.cpp:406] inception_4a/output_inception_4a/output_0_split <- inception_4a/output
I0707 18:30:43.118598 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_0
I0707 18:30:43.118613 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_1
I0707 18:30:43.118626 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_2
I0707 18:30:43.118640 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_3
I0707 18:30:43.118675 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_4
I0707 18:30:43.118788 99468 net.cpp:122] Setting up inception_4a/output_inception_4a/output_0_split
I0707 18:30:43.118803 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.118813 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.118826 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.118836 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.118850 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.118857 99468 net.cpp:137] Memory required for data: 3092859392
I0707 18:30:43.118867 99468 layer_factory.hpp:77] Creating layer loss1/ave_pool
I0707 18:30:43.118883 99468 net.cpp:84] Creating Layer loss1/ave_pool
I0707 18:30:43.118893 99468 net.cpp:406] loss1/ave_pool <- inception_4a/output_inception_4a/output_0_split_0
I0707 18:30:43.118911 99468 net.cpp:380] loss1/ave_pool -> loss1/ave_pool
I0707 18:30:43.119202 99468 net.cpp:122] Setting up loss1/ave_pool
I0707 18:30:43.119223 99468 net.cpp:129] Top shape: 64 512 4 4 (524288)
I0707 18:30:43.119236 99468 net.cpp:137] Memory required for data: 3094956544
I0707 18:30:43.119246 99468 layer_factory.hpp:77] Creating layer loss1/conv
I0707 18:30:43.119268 99468 net.cpp:84] Creating Layer loss1/conv
I0707 18:30:43.119280 99468 net.cpp:406] loss1/conv <- loss1/ave_pool
I0707 18:30:43.119292 99468 net.cpp:380] loss1/conv -> loss1/conv
I0707 18:30:43.122908 99468 net.cpp:122] Setting up loss1/conv
I0707 18:30:43.122939 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.122948 99468 net.cpp:137] Memory required for data: 3095480832
I0707 18:30:43.122961 99468 layer_factory.hpp:77] Creating layer loss1/relu_conv
I0707 18:30:43.122977 99468 net.cpp:84] Creating Layer loss1/relu_conv
I0707 18:30:43.123023 99468 net.cpp:406] loss1/relu_conv <- loss1/conv
I0707 18:30:43.123037 99468 net.cpp:367] loss1/relu_conv -> loss1/conv (in-place)
I0707 18:30:43.123929 99468 net.cpp:122] Setting up loss1/relu_conv
I0707 18:30:43.123955 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.123963 99468 net.cpp:137] Memory required for data: 3096005120
I0707 18:30:43.123972 99468 layer_factory.hpp:77] Creating layer loss1/fc
I0707 18:30:43.123988 99468 net.cpp:84] Creating Layer loss1/fc
I0707 18:30:43.124001 99468 net.cpp:406] loss1/fc <- loss1/conv
I0707 18:30:43.124017 99468 net.cpp:380] loss1/fc -> loss1/fc
I0707 18:30:43.143690 99468 net.cpp:122] Setting up loss1/fc
I0707 18:30:43.143718 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.143726 99468 net.cpp:137] Memory required for data: 3096267264
I0707 18:30:43.143738 99468 layer_factory.hpp:77] Creating layer loss1/relu_fc
I0707 18:30:43.143750 99468 net.cpp:84] Creating Layer loss1/relu_fc
I0707 18:30:43.143762 99468 net.cpp:406] loss1/relu_fc <- loss1/fc
I0707 18:30:43.143780 99468 net.cpp:367] loss1/relu_fc -> loss1/fc (in-place)
I0707 18:30:43.144029 99468 net.cpp:122] Setting up loss1/relu_fc
I0707 18:30:43.144049 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.144098 99468 net.cpp:137] Memory required for data: 3096529408
I0707 18:30:43.144107 99468 layer_factory.hpp:77] Creating layer loss1/drop_fc
I0707 18:30:43.144127 99468 net.cpp:84] Creating Layer loss1/drop_fc
I0707 18:30:43.144140 99468 net.cpp:406] loss1/drop_fc <- loss1/fc
I0707 18:30:43.144150 99468 net.cpp:367] loss1/drop_fc -> loss1/fc (in-place)
I0707 18:30:43.144198 99468 net.cpp:122] Setting up loss1/drop_fc
I0707 18:30:43.144214 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.144223 99468 net.cpp:137] Memory required for data: 3096791552
I0707 18:30:43.144249 99468 layer_factory.hpp:77] Creating layer loss1/classifier_my
I0707 18:30:43.144282 99468 net.cpp:84] Creating Layer loss1/classifier_my
I0707 18:30:43.144307 99468 net.cpp:406] loss1/classifier_my <- loss1/fc
I0707 18:30:43.144322 99468 net.cpp:380] loss1/classifier_my -> loss1/classifier
I0707 18:30:43.144786 99468 net.cpp:122] Setting up loss1/classifier_my
I0707 18:30:43.144807 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.144820 99468 net.cpp:137] Memory required for data: 3096801536
I0707 18:30:43.144845 99468 layer_factory.hpp:77] Creating layer loss1/loss
I0707 18:30:43.144860 99468 net.cpp:84] Creating Layer loss1/loss
I0707 18:30:43.144872 99468 net.cpp:406] loss1/loss <- loss1/classifier
I0707 18:30:43.144887 99468 net.cpp:406] loss1/loss <- label_data_1_split_0
I0707 18:30:43.144901 99468 net.cpp:380] loss1/loss -> loss1/loss1
I0707 18:30:43.144925 99468 layer_factory.hpp:77] Creating layer loss1/loss
I0707 18:30:43.145946 99468 net.cpp:122] Setting up loss1/loss
I0707 18:30:43.145973 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.145982 99468 net.cpp:132]     with loss weight 0.3
I0707 18:30:43.146029 99468 net.cpp:137] Memory required for data: 3096801540
I0707 18:30:43.146044 99468 layer_factory.hpp:77] Creating layer inception_4b/1x1
I0707 18:30:43.146070 99468 net.cpp:84] Creating Layer inception_4b/1x1
I0707 18:30:43.146080 99468 net.cpp:406] inception_4b/1x1 <- inception_4a/output_inception_4a/output_0_split_1
I0707 18:30:43.146097 99468 net.cpp:380] inception_4b/1x1 -> inception_4b/1x1
I0707 18:30:43.148373 99468 net.cpp:122] Setting up inception_4b/1x1
I0707 18:30:43.148401 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.148411 99468 net.cpp:137] Memory required for data: 3104829700
I0707 18:30:43.148422 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_1x1
I0707 18:30:43.148434 99468 net.cpp:84] Creating Layer inception_4b/relu_1x1
I0707 18:30:43.148445 99468 net.cpp:406] inception_4b/relu_1x1 <- inception_4b/1x1
I0707 18:30:43.148463 99468 net.cpp:367] inception_4b/relu_1x1 -> inception_4b/1x1 (in-place)
I0707 18:30:43.149332 99468 net.cpp:122] Setting up inception_4b/relu_1x1
I0707 18:30:43.149356 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.149365 99468 net.cpp:137] Memory required for data: 3112857860
I0707 18:30:43.149374 99468 layer_factory.hpp:77] Creating layer inception_4b/3x3_reduce
I0707 18:30:43.149394 99468 net.cpp:84] Creating Layer inception_4b/3x3_reduce
I0707 18:30:43.149410 99468 net.cpp:406] inception_4b/3x3_reduce <- inception_4a/output_inception_4a/output_0_split_2
I0707 18:30:43.149425 99468 net.cpp:380] inception_4b/3x3_reduce -> inception_4b/3x3_reduce
I0707 18:30:43.152153 99468 net.cpp:122] Setting up inception_4b/3x3_reduce
I0707 18:30:43.152182 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.152191 99468 net.cpp:137] Memory required for data: 3118477572
I0707 18:30:43.152204 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_3x3_reduce
I0707 18:30:43.152216 99468 net.cpp:84] Creating Layer inception_4b/relu_3x3_reduce
I0707 18:30:43.152228 99468 net.cpp:406] inception_4b/relu_3x3_reduce <- inception_4b/3x3_reduce
I0707 18:30:43.152241 99468 net.cpp:367] inception_4b/relu_3x3_reduce -> inception_4b/3x3_reduce (in-place)
I0707 18:30:43.152509 99468 net.cpp:122] Setting up inception_4b/relu_3x3_reduce
I0707 18:30:43.152531 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.152566 99468 net.cpp:137] Memory required for data: 3124097284
I0707 18:30:43.152575 99468 layer_factory.hpp:77] Creating layer inception_4b/3x3
I0707 18:30:43.152592 99468 net.cpp:84] Creating Layer inception_4b/3x3
I0707 18:30:43.152604 99468 net.cpp:406] inception_4b/3x3 <- inception_4b/3x3_reduce
I0707 18:30:43.152622 99468 net.cpp:380] inception_4b/3x3 -> inception_4b/3x3
I0707 18:30:43.162705 99468 net.cpp:122] Setting up inception_4b/3x3
I0707 18:30:43.162734 99468 net.cpp:129] Top shape: 64 224 14 14 (2809856)
I0707 18:30:43.162744 99468 net.cpp:137] Memory required for data: 3135336708
I0707 18:30:43.162755 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_3x3
I0707 18:30:43.162771 99468 net.cpp:84] Creating Layer inception_4b/relu_3x3
I0707 18:30:43.162783 99468 net.cpp:406] inception_4b/relu_3x3 <- inception_4b/3x3
I0707 18:30:43.162850 99468 net.cpp:367] inception_4b/relu_3x3 -> inception_4b/3x3 (in-place)
I0707 18:30:43.163730 99468 net.cpp:122] Setting up inception_4b/relu_3x3
I0707 18:30:43.163754 99468 net.cpp:129] Top shape: 64 224 14 14 (2809856)
I0707 18:30:43.163763 99468 net.cpp:137] Memory required for data: 3146576132
I0707 18:30:43.163771 99468 layer_factory.hpp:77] Creating layer inception_4b/5x5_reduce
I0707 18:30:43.163790 99468 net.cpp:84] Creating Layer inception_4b/5x5_reduce
I0707 18:30:43.163833 99468 net.cpp:406] inception_4b/5x5_reduce <- inception_4a/output_inception_4a/output_0_split_3
I0707 18:30:43.163852 99468 net.cpp:380] inception_4b/5x5_reduce -> inception_4b/5x5_reduce
I0707 18:30:43.165725 99468 net.cpp:122] Setting up inception_4b/5x5_reduce
I0707 18:30:43.165751 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.165761 99468 net.cpp:137] Memory required for data: 3147780356
I0707 18:30:43.165773 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_5x5_reduce
I0707 18:30:43.165786 99468 net.cpp:84] Creating Layer inception_4b/relu_5x5_reduce
I0707 18:30:43.165797 99468 net.cpp:406] inception_4b/relu_5x5_reduce <- inception_4b/5x5_reduce
I0707 18:30:43.165810 99468 net.cpp:367] inception_4b/relu_5x5_reduce -> inception_4b/5x5_reduce (in-place)
I0707 18:30:43.166721 99468 net.cpp:122] Setting up inception_4b/relu_5x5_reduce
I0707 18:30:43.166746 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.166754 99468 net.cpp:137] Memory required for data: 3148984580
I0707 18:30:43.166764 99468 layer_factory.hpp:77] Creating layer inception_4b/5x5
I0707 18:30:43.166784 99468 net.cpp:84] Creating Layer inception_4b/5x5
I0707 18:30:43.166795 99468 net.cpp:406] inception_4b/5x5 <- inception_4b/5x5_reduce
I0707 18:30:43.166810 99468 net.cpp:380] inception_4b/5x5 -> inception_4b/5x5
I0707 18:30:43.169589 99468 net.cpp:122] Setting up inception_4b/5x5
I0707 18:30:43.169616 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.169625 99468 net.cpp:137] Memory required for data: 3152195844
I0707 18:30:43.169651 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_5x5
I0707 18:30:43.169698 99468 net.cpp:84] Creating Layer inception_4b/relu_5x5
I0707 18:30:43.169709 99468 net.cpp:406] inception_4b/relu_5x5 <- inception_4b/5x5
I0707 18:30:43.169741 99468 net.cpp:367] inception_4b/relu_5x5 -> inception_4b/5x5 (in-place)
I0707 18:30:43.169975 99468 net.cpp:122] Setting up inception_4b/relu_5x5
I0707 18:30:43.169994 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.170008 99468 net.cpp:137] Memory required for data: 3155407108
I0707 18:30:43.170022 99468 layer_factory.hpp:77] Creating layer inception_4b/pool
I0707 18:30:43.170035 99468 net.cpp:84] Creating Layer inception_4b/pool
I0707 18:30:43.170047 99468 net.cpp:406] inception_4b/pool <- inception_4a/output_inception_4a/output_0_split_4
I0707 18:30:43.170061 99468 net.cpp:380] inception_4b/pool -> inception_4b/pool
I0707 18:30:43.170126 99468 net.cpp:122] Setting up inception_4b/pool
I0707 18:30:43.170142 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.170167 99468 net.cpp:137] Memory required for data: 3181097220
I0707 18:30:43.170176 99468 layer_factory.hpp:77] Creating layer inception_4b/pool_proj
I0707 18:30:43.170198 99468 net.cpp:84] Creating Layer inception_4b/pool_proj
I0707 18:30:43.170214 99468 net.cpp:406] inception_4b/pool_proj <- inception_4b/pool
I0707 18:30:43.170231 99468 net.cpp:380] inception_4b/pool_proj -> inception_4b/pool_proj
I0707 18:30:43.173230 99468 net.cpp:122] Setting up inception_4b/pool_proj
I0707 18:30:43.173257 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.173266 99468 net.cpp:137] Memory required for data: 3184308484
I0707 18:30:43.173279 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_pool_proj
I0707 18:30:43.173298 99468 net.cpp:84] Creating Layer inception_4b/relu_pool_proj
I0707 18:30:43.173339 99468 net.cpp:406] inception_4b/relu_pool_proj <- inception_4b/pool_proj
I0707 18:30:43.173352 99468 net.cpp:367] inception_4b/relu_pool_proj -> inception_4b/pool_proj (in-place)
I0707 18:30:43.174253 99468 net.cpp:122] Setting up inception_4b/relu_pool_proj
I0707 18:30:43.174278 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.174286 99468 net.cpp:137] Memory required for data: 3187519748
I0707 18:30:43.174295 99468 layer_factory.hpp:77] Creating layer inception_4b/output
I0707 18:30:43.174307 99468 net.cpp:84] Creating Layer inception_4b/output
I0707 18:30:43.174346 99468 net.cpp:406] inception_4b/output <- inception_4b/1x1
I0707 18:30:43.174357 99468 net.cpp:406] inception_4b/output <- inception_4b/3x3
I0707 18:30:43.174371 99468 net.cpp:406] inception_4b/output <- inception_4b/5x5
I0707 18:30:43.174401 99468 net.cpp:406] inception_4b/output <- inception_4b/pool_proj
I0707 18:30:43.174429 99468 net.cpp:380] inception_4b/output -> inception_4b/output
I0707 18:30:43.174476 99468 net.cpp:122] Setting up inception_4b/output
I0707 18:30:43.174494 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.174502 99468 net.cpp:137] Memory required for data: 3213209860
I0707 18:30:43.174515 99468 layer_factory.hpp:77] Creating layer inception_4b/output_inception_4b/output_0_split
I0707 18:30:43.174527 99468 net.cpp:84] Creating Layer inception_4b/output_inception_4b/output_0_split
I0707 18:30:43.174540 99468 net.cpp:406] inception_4b/output_inception_4b/output_0_split <- inception_4b/output
I0707 18:30:43.174551 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_0
I0707 18:30:43.174572 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_1
I0707 18:30:43.174587 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_2
I0707 18:30:43.174603 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_3
I0707 18:30:43.174697 99468 net.cpp:122] Setting up inception_4b/output_inception_4b/output_0_split
I0707 18:30:43.174712 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.174721 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.174731 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.174742 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.174754 99468 net.cpp:137] Memory required for data: 3315970308
I0707 18:30:43.174765 99468 layer_factory.hpp:77] Creating layer inception_4c/1x1
I0707 18:30:43.174782 99468 net.cpp:84] Creating Layer inception_4c/1x1
I0707 18:30:43.174793 99468 net.cpp:406] inception_4c/1x1 <- inception_4b/output_inception_4b/output_0_split_0
I0707 18:30:43.174811 99468 net.cpp:380] inception_4c/1x1 -> inception_4c/1x1
I0707 18:30:43.178383 99468 net.cpp:122] Setting up inception_4c/1x1
I0707 18:30:43.178412 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.178452 99468 net.cpp:137] Memory required for data: 3322392836
I0707 18:30:43.178467 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_1x1
I0707 18:30:43.178498 99468 net.cpp:84] Creating Layer inception_4c/relu_1x1
I0707 18:30:43.178508 99468 net.cpp:406] inception_4c/relu_1x1 <- inception_4c/1x1
I0707 18:30:43.178524 99468 net.cpp:367] inception_4c/relu_1x1 -> inception_4c/1x1 (in-place)
I0707 18:30:43.179397 99468 net.cpp:122] Setting up inception_4c/relu_1x1
I0707 18:30:43.179421 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.179430 99468 net.cpp:137] Memory required for data: 3328815364
I0707 18:30:43.179440 99468 layer_factory.hpp:77] Creating layer inception_4c/3x3_reduce
I0707 18:30:43.179463 99468 net.cpp:84] Creating Layer inception_4c/3x3_reduce
I0707 18:30:43.179479 99468 net.cpp:406] inception_4c/3x3_reduce <- inception_4b/output_inception_4b/output_0_split_1
I0707 18:30:43.179499 99468 net.cpp:380] inception_4c/3x3_reduce -> inception_4c/3x3_reduce
I0707 18:30:43.182301 99468 net.cpp:122] Setting up inception_4c/3x3_reduce
I0707 18:30:43.182330 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.182356 99468 net.cpp:137] Memory required for data: 3335237892
I0707 18:30:43.182402 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_3x3_reduce
I0707 18:30:43.182420 99468 net.cpp:84] Creating Layer inception_4c/relu_3x3_reduce
I0707 18:30:43.182430 99468 net.cpp:406] inception_4c/relu_3x3_reduce <- inception_4c/3x3_reduce
I0707 18:30:43.182446 99468 net.cpp:367] inception_4c/relu_3x3_reduce -> inception_4c/3x3_reduce (in-place)
I0707 18:30:43.182698 99468 net.cpp:122] Setting up inception_4c/relu_3x3_reduce
I0707 18:30:43.182719 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.182730 99468 net.cpp:137] Memory required for data: 3341660420
I0707 18:30:43.182744 99468 layer_factory.hpp:77] Creating layer inception_4c/3x3
I0707 18:30:43.182765 99468 net.cpp:84] Creating Layer inception_4c/3x3
I0707 18:30:43.182778 99468 net.cpp:406] inception_4c/3x3 <- inception_4c/3x3_reduce
I0707 18:30:43.182797 99468 net.cpp:380] inception_4c/3x3 -> inception_4c/3x3
I0707 18:30:43.188001 99468 net.cpp:122] Setting up inception_4c/3x3
I0707 18:30:43.188030 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.188038 99468 net.cpp:137] Memory required for data: 3354505476
I0707 18:30:43.188050 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_3x3
I0707 18:30:43.188062 99468 net.cpp:84] Creating Layer inception_4c/relu_3x3
I0707 18:30:43.188073 99468 net.cpp:406] inception_4c/relu_3x3 <- inception_4c/3x3
I0707 18:30:43.188093 99468 net.cpp:367] inception_4c/relu_3x3 -> inception_4c/3x3 (in-place)
I0707 18:30:43.188993 99468 net.cpp:122] Setting up inception_4c/relu_3x3
I0707 18:30:43.189018 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.189026 99468 net.cpp:137] Memory required for data: 3367350532
I0707 18:30:43.189035 99468 layer_factory.hpp:77] Creating layer inception_4c/5x5_reduce
I0707 18:30:43.189054 99468 net.cpp:84] Creating Layer inception_4c/5x5_reduce
I0707 18:30:43.189065 99468 net.cpp:406] inception_4c/5x5_reduce <- inception_4b/output_inception_4b/output_0_split_2
I0707 18:30:43.189081 99468 net.cpp:380] inception_4c/5x5_reduce -> inception_4c/5x5_reduce
I0707 18:30:43.190889 99468 net.cpp:122] Setting up inception_4c/5x5_reduce
I0707 18:30:43.190918 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.190927 99468 net.cpp:137] Memory required for data: 3368554756
I0707 18:30:43.190939 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_5x5_reduce
I0707 18:30:43.190953 99468 net.cpp:84] Creating Layer inception_4c/relu_5x5_reduce
I0707 18:30:43.190995 99468 net.cpp:406] inception_4c/relu_5x5_reduce <- inception_4c/5x5_reduce
I0707 18:30:43.191011 99468 net.cpp:367] inception_4c/relu_5x5_reduce -> inception_4c/5x5_reduce (in-place)
I0707 18:30:43.191911 99468 net.cpp:122] Setting up inception_4c/relu_5x5_reduce
I0707 18:30:43.191934 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.191943 99468 net.cpp:137] Memory required for data: 3369758980
I0707 18:30:43.191951 99468 layer_factory.hpp:77] Creating layer inception_4c/5x5
I0707 18:30:43.191973 99468 net.cpp:84] Creating Layer inception_4c/5x5
I0707 18:30:43.192016 99468 net.cpp:406] inception_4c/5x5 <- inception_4c/5x5_reduce
I0707 18:30:43.192030 99468 net.cpp:380] inception_4c/5x5 -> inception_4c/5x5
I0707 18:30:43.194639 99468 net.cpp:122] Setting up inception_4c/5x5
I0707 18:30:43.194669 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.194679 99468 net.cpp:137] Memory required for data: 3372970244
I0707 18:30:43.194690 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_5x5
I0707 18:30:43.194703 99468 net.cpp:84] Creating Layer inception_4c/relu_5x5
I0707 18:30:43.194744 99468 net.cpp:406] inception_4c/relu_5x5 <- inception_4c/5x5
I0707 18:30:43.194759 99468 net.cpp:367] inception_4c/relu_5x5 -> inception_4c/5x5 (in-place)
I0707 18:30:43.195010 99468 net.cpp:122] Setting up inception_4c/relu_5x5
I0707 18:30:43.195029 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.195055 99468 net.cpp:137] Memory required for data: 3376181508
I0707 18:30:43.195096 99468 layer_factory.hpp:77] Creating layer inception_4c/pool
I0707 18:30:43.195108 99468 net.cpp:84] Creating Layer inception_4c/pool
I0707 18:30:43.195117 99468 net.cpp:406] inception_4c/pool <- inception_4b/output_inception_4b/output_0_split_3
I0707 18:30:43.195137 99468 net.cpp:380] inception_4c/pool -> inception_4c/pool
I0707 18:30:43.195211 99468 net.cpp:122] Setting up inception_4c/pool
I0707 18:30:43.195230 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.195243 99468 net.cpp:137] Memory required for data: 3401871620
I0707 18:30:43.195255 99468 layer_factory.hpp:77] Creating layer inception_4c/pool_proj
I0707 18:30:43.195274 99468 net.cpp:84] Creating Layer inception_4c/pool_proj
I0707 18:30:43.195286 99468 net.cpp:406] inception_4c/pool_proj <- inception_4c/pool
I0707 18:30:43.195302 99468 net.cpp:380] inception_4c/pool_proj -> inception_4c/pool_proj
I0707 18:30:43.197876 99468 net.cpp:122] Setting up inception_4c/pool_proj
I0707 18:30:43.197904 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.197913 99468 net.cpp:137] Memory required for data: 3405082884
I0707 18:30:43.197926 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_pool_proj
I0707 18:30:43.197938 99468 net.cpp:84] Creating Layer inception_4c/relu_pool_proj
I0707 18:30:43.197949 99468 net.cpp:406] inception_4c/relu_pool_proj <- inception_4c/pool_proj
I0707 18:30:43.197962 99468 net.cpp:367] inception_4c/relu_pool_proj -> inception_4c/pool_proj (in-place)
I0707 18:30:43.198848 99468 net.cpp:122] Setting up inception_4c/relu_pool_proj
I0707 18:30:43.198871 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.198880 99468 net.cpp:137] Memory required for data: 3408294148
I0707 18:30:43.198889 99468 layer_factory.hpp:77] Creating layer inception_4c/output
I0707 18:30:43.198902 99468 net.cpp:84] Creating Layer inception_4c/output
I0707 18:30:43.198914 99468 net.cpp:406] inception_4c/output <- inception_4c/1x1
I0707 18:30:43.198928 99468 net.cpp:406] inception_4c/output <- inception_4c/3x3
I0707 18:30:43.198938 99468 net.cpp:406] inception_4c/output <- inception_4c/5x5
I0707 18:30:43.198949 99468 net.cpp:406] inception_4c/output <- inception_4c/pool_proj
I0707 18:30:43.198961 99468 net.cpp:380] inception_4c/output -> inception_4c/output
I0707 18:30:43.199009 99468 net.cpp:122] Setting up inception_4c/output
I0707 18:30:43.199025 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.199035 99468 net.cpp:137] Memory required for data: 3433984260
I0707 18:30:43.199074 99468 layer_factory.hpp:77] Creating layer inception_4c/output_inception_4c/output_0_split
I0707 18:30:43.199087 99468 net.cpp:84] Creating Layer inception_4c/output_inception_4c/output_0_split
I0707 18:30:43.199100 99468 net.cpp:406] inception_4c/output_inception_4c/output_0_split <- inception_4c/output
I0707 18:30:43.199118 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_0
I0707 18:30:43.199132 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_1
I0707 18:30:43.199146 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_2
I0707 18:30:43.199159 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_3
I0707 18:30:43.199259 99468 net.cpp:122] Setting up inception_4c/output_inception_4c/output_0_split
I0707 18:30:43.199275 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.199290 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.199300 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.199309 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.199318 99468 net.cpp:137] Memory required for data: 3536744708
I0707 18:30:43.199331 99468 layer_factory.hpp:77] Creating layer inception_4d/1x1
I0707 18:30:43.199349 99468 net.cpp:84] Creating Layer inception_4d/1x1
I0707 18:30:43.199378 99468 net.cpp:406] inception_4d/1x1 <- inception_4c/output_inception_4c/output_0_split_0
I0707 18:30:43.199391 99468 net.cpp:380] inception_4d/1x1 -> inception_4d/1x1
I0707 18:30:43.201529 99468 net.cpp:122] Setting up inception_4d/1x1
I0707 18:30:43.201561 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.201593 99468 net.cpp:137] Memory required for data: 3542364420
I0707 18:30:43.201617 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_1x1
I0707 18:30:43.201634 99468 net.cpp:84] Creating Layer inception_4d/relu_1x1
I0707 18:30:43.201647 99468 net.cpp:406] inception_4d/relu_1x1 <- inception_4d/1x1
I0707 18:30:43.201661 99468 net.cpp:367] inception_4d/relu_1x1 -> inception_4d/1x1 (in-place)
I0707 18:30:43.202523 99468 net.cpp:122] Setting up inception_4d/relu_1x1
I0707 18:30:43.202549 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.202571 99468 net.cpp:137] Memory required for data: 3547984132
I0707 18:30:43.202580 99468 layer_factory.hpp:77] Creating layer inception_4d/3x3_reduce
I0707 18:30:43.202603 99468 net.cpp:84] Creating Layer inception_4d/3x3_reduce
I0707 18:30:43.202618 99468 net.cpp:406] inception_4d/3x3_reduce <- inception_4c/output_inception_4c/output_0_split_1
I0707 18:30:43.202632 99468 net.cpp:380] inception_4d/3x3_reduce -> inception_4d/3x3_reduce
I0707 18:30:43.205538 99468 net.cpp:122] Setting up inception_4d/3x3_reduce
I0707 18:30:43.205572 99468 net.cpp:129] Top shape: 64 144 14 14 (1806336)
I0707 18:30:43.205605 99468 net.cpp:137] Memory required for data: 3555209476
I0707 18:30:43.205634 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_3x3_reduce
I0707 18:30:43.205647 99468 net.cpp:84] Creating Layer inception_4d/relu_3x3_reduce
I0707 18:30:43.205658 99468 net.cpp:406] inception_4d/relu_3x3_reduce <- inception_4d/3x3_reduce
I0707 18:30:43.205677 99468 net.cpp:367] inception_4d/relu_3x3_reduce -> inception_4d/3x3_reduce (in-place)
I0707 18:30:43.205915 99468 net.cpp:122] Setting up inception_4d/relu_3x3_reduce
I0707 18:30:43.205935 99468 net.cpp:129] Top shape: 64 144 14 14 (1806336)
I0707 18:30:43.205946 99468 net.cpp:137] Memory required for data: 3562434820
I0707 18:30:43.205960 99468 layer_factory.hpp:77] Creating layer inception_4d/3x3
I0707 18:30:43.205977 99468 net.cpp:84] Creating Layer inception_4d/3x3
I0707 18:30:43.205996 99468 net.cpp:406] inception_4d/3x3 <- inception_4d/3x3_reduce
I0707 18:30:43.206012 99468 net.cpp:380] inception_4d/3x3 -> inception_4d/3x3
I0707 18:30:43.212600 99468 net.cpp:122] Setting up inception_4d/3x3
I0707 18:30:43.212628 99468 net.cpp:129] Top shape: 64 288 14 14 (3612672)
I0707 18:30:43.212641 99468 net.cpp:137] Memory required for data: 3576885508
I0707 18:30:43.212654 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_3x3
I0707 18:30:43.212671 99468 net.cpp:84] Creating Layer inception_4d/relu_3x3
I0707 18:30:43.212708 99468 net.cpp:406] inception_4d/relu_3x3 <- inception_4d/3x3
I0707 18:30:43.212736 99468 net.cpp:367] inception_4d/relu_3x3 -> inception_4d/3x3 (in-place)
I0707 18:30:43.213611 99468 net.cpp:122] Setting up inception_4d/relu_3x3
I0707 18:30:43.213635 99468 net.cpp:129] Top shape: 64 288 14 14 (3612672)
I0707 18:30:43.213644 99468 net.cpp:137] Memory required for data: 3591336196
I0707 18:30:43.213654 99468 layer_factory.hpp:77] Creating layer inception_4d/5x5_reduce
I0707 18:30:43.213670 99468 net.cpp:84] Creating Layer inception_4d/5x5_reduce
I0707 18:30:43.213682 99468 net.cpp:406] inception_4d/5x5_reduce <- inception_4c/output_inception_4c/output_0_split_2
I0707 18:30:43.213699 99468 net.cpp:380] inception_4d/5x5_reduce -> inception_4d/5x5_reduce
I0707 18:30:43.215536 99468 net.cpp:122] Setting up inception_4d/5x5_reduce
I0707 18:30:43.215569 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.215579 99468 net.cpp:137] Memory required for data: 3592941828
I0707 18:30:43.215591 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_5x5_reduce
I0707 18:30:43.215605 99468 net.cpp:84] Creating Layer inception_4d/relu_5x5_reduce
I0707 18:30:43.215632 99468 net.cpp:406] inception_4d/relu_5x5_reduce <- inception_4d/5x5_reduce
I0707 18:30:43.215682 99468 net.cpp:367] inception_4d/relu_5x5_reduce -> inception_4d/5x5_reduce (in-place)
I0707 18:30:43.216562 99468 net.cpp:122] Setting up inception_4d/relu_5x5_reduce
I0707 18:30:43.216585 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.216594 99468 net.cpp:137] Memory required for data: 3594547460
I0707 18:30:43.216603 99468 layer_factory.hpp:77] Creating layer inception_4d/5x5
I0707 18:30:43.216621 99468 net.cpp:84] Creating Layer inception_4d/5x5
I0707 18:30:43.216634 99468 net.cpp:406] inception_4d/5x5 <- inception_4d/5x5_reduce
I0707 18:30:43.216650 99468 net.cpp:380] inception_4d/5x5 -> inception_4d/5x5
I0707 18:30:43.220098 99468 net.cpp:122] Setting up inception_4d/5x5
I0707 18:30:43.220125 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.220134 99468 net.cpp:137] Memory required for data: 3597758724
I0707 18:30:43.220146 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_5x5
I0707 18:30:43.220161 99468 net.cpp:84] Creating Layer inception_4d/relu_5x5
I0707 18:30:43.220177 99468 net.cpp:406] inception_4d/relu_5x5 <- inception_4d/5x5
I0707 18:30:43.220190 99468 net.cpp:367] inception_4d/relu_5x5 -> inception_4d/5x5 (in-place)
I0707 18:30:43.220458 99468 net.cpp:122] Setting up inception_4d/relu_5x5
I0707 18:30:43.220477 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.220490 99468 net.cpp:137] Memory required for data: 3600969988
I0707 18:30:43.220501 99468 layer_factory.hpp:77] Creating layer inception_4d/pool
I0707 18:30:43.220532 99468 net.cpp:84] Creating Layer inception_4d/pool
I0707 18:30:43.220543 99468 net.cpp:406] inception_4d/pool <- inception_4c/output_inception_4c/output_0_split_3
I0707 18:30:43.220561 99468 net.cpp:380] inception_4d/pool -> inception_4d/pool
I0707 18:30:43.220639 99468 net.cpp:122] Setting up inception_4d/pool
I0707 18:30:43.220656 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.220669 99468 net.cpp:137] Memory required for data: 3626660100
I0707 18:30:43.220679 99468 layer_factory.hpp:77] Creating layer inception_4d/pool_proj
I0707 18:30:43.220716 99468 net.cpp:84] Creating Layer inception_4d/pool_proj
I0707 18:30:43.220743 99468 net.cpp:406] inception_4d/pool_proj <- inception_4d/pool
I0707 18:30:43.220757 99468 net.cpp:380] inception_4d/pool_proj -> inception_4d/pool_proj
I0707 18:30:43.223333 99468 net.cpp:122] Setting up inception_4d/pool_proj
I0707 18:30:43.223359 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.223369 99468 net.cpp:137] Memory required for data: 3629871364
I0707 18:30:43.223409 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_pool_proj
I0707 18:30:43.223425 99468 net.cpp:84] Creating Layer inception_4d/relu_pool_proj
I0707 18:30:43.223438 99468 net.cpp:406] inception_4d/relu_pool_proj <- inception_4d/pool_proj
I0707 18:30:43.223467 99468 net.cpp:367] inception_4d/relu_pool_proj -> inception_4d/pool_proj (in-place)
I0707 18:30:43.224345 99468 net.cpp:122] Setting up inception_4d/relu_pool_proj
I0707 18:30:43.224370 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.224377 99468 net.cpp:137] Memory required for data: 3633082628
I0707 18:30:43.224386 99468 layer_factory.hpp:77] Creating layer inception_4d/output
I0707 18:30:43.224398 99468 net.cpp:84] Creating Layer inception_4d/output
I0707 18:30:43.224411 99468 net.cpp:406] inception_4d/output <- inception_4d/1x1
I0707 18:30:43.224426 99468 net.cpp:406] inception_4d/output <- inception_4d/3x3
I0707 18:30:43.224436 99468 net.cpp:406] inception_4d/output <- inception_4d/5x5
I0707 18:30:43.224447 99468 net.cpp:406] inception_4d/output <- inception_4d/pool_proj
I0707 18:30:43.224457 99468 net.cpp:380] inception_4d/output -> inception_4d/output
I0707 18:30:43.224539 99468 net.cpp:122] Setting up inception_4d/output
I0707 18:30:43.224565 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.224578 99468 net.cpp:137] Memory required for data: 3659575556
I0707 18:30:43.224606 99468 layer_factory.hpp:77] Creating layer inception_4d/output_inception_4d/output_0_split
I0707 18:30:43.224627 99468 net.cpp:84] Creating Layer inception_4d/output_inception_4d/output_0_split
I0707 18:30:43.224637 99468 net.cpp:406] inception_4d/output_inception_4d/output_0_split <- inception_4d/output
I0707 18:30:43.224656 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_0
I0707 18:30:43.224673 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_1
I0707 18:30:43.224686 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_2
I0707 18:30:43.224702 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_3
I0707 18:30:43.224722 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_4
I0707 18:30:43.224850 99468 net.cpp:122] Setting up inception_4d/output_inception_4d/output_0_split
I0707 18:30:43.224867 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.224880 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.224890 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.224905 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.224915 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.224925 99468 net.cpp:137] Memory required for data: 3792040196
I0707 18:30:43.224936 99468 layer_factory.hpp:77] Creating layer loss2/ave_pool
I0707 18:30:43.224949 99468 net.cpp:84] Creating Layer loss2/ave_pool
I0707 18:30:43.224967 99468 net.cpp:406] loss2/ave_pool <- inception_4d/output_inception_4d/output_0_split_0
I0707 18:30:43.224980 99468 net.cpp:380] loss2/ave_pool -> loss2/ave_pool
I0707 18:30:43.225245 99468 net.cpp:122] Setting up loss2/ave_pool
I0707 18:30:43.225266 99468 net.cpp:129] Top shape: 64 528 4 4 (540672)
I0707 18:30:43.225280 99468 net.cpp:137] Memory required for data: 3794202884
I0707 18:30:43.225289 99468 layer_factory.hpp:77] Creating layer loss2/conv
I0707 18:30:43.225313 99468 net.cpp:84] Creating Layer loss2/conv
I0707 18:30:43.225327 99468 net.cpp:406] loss2/conv <- loss2/ave_pool
I0707 18:30:43.225342 99468 net.cpp:380] loss2/conv -> loss2/conv
I0707 18:30:43.228219 99468 net.cpp:122] Setting up loss2/conv
I0707 18:30:43.228245 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.228255 99468 net.cpp:137] Memory required for data: 3794727172
I0707 18:30:43.228266 99468 layer_factory.hpp:77] Creating layer loss2/relu_conv
I0707 18:30:43.228281 99468 net.cpp:84] Creating Layer loss2/relu_conv
I0707 18:30:43.228292 99468 net.cpp:406] loss2/relu_conv <- loss2/conv
I0707 18:30:43.228305 99468 net.cpp:367] loss2/relu_conv -> loss2/conv (in-place)
I0707 18:30:43.228543 99468 net.cpp:122] Setting up loss2/relu_conv
I0707 18:30:43.228569 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.228580 99468 net.cpp:137] Memory required for data: 3795251460
I0707 18:30:43.228588 99468 layer_factory.hpp:77] Creating layer loss2/fc
I0707 18:30:43.228605 99468 net.cpp:84] Creating Layer loss2/fc
I0707 18:30:43.228615 99468 net.cpp:406] loss2/fc <- loss2/conv
I0707 18:30:43.228634 99468 net.cpp:380] loss2/fc -> loss2/fc
I0707 18:30:43.247887 99468 net.cpp:122] Setting up loss2/fc
I0707 18:30:43.247913 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.247921 99468 net.cpp:137] Memory required for data: 3795513604
I0707 18:30:43.247933 99468 layer_factory.hpp:77] Creating layer loss2/relu_fc
I0707 18:30:43.247946 99468 net.cpp:84] Creating Layer loss2/relu_fc
I0707 18:30:43.247956 99468 net.cpp:406] loss2/relu_fc <- loss2/fc
I0707 18:30:43.247974 99468 net.cpp:367] loss2/relu_fc -> loss2/fc (in-place)
I0707 18:30:43.248860 99468 net.cpp:122] Setting up loss2/relu_fc
I0707 18:30:43.248884 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.248893 99468 net.cpp:137] Memory required for data: 3795775748
I0707 18:30:43.248919 99468 layer_factory.hpp:77] Creating layer loss2/drop_fc
I0707 18:30:43.248957 99468 net.cpp:84] Creating Layer loss2/drop_fc
I0707 18:30:43.248970 99468 net.cpp:406] loss2/drop_fc <- loss2/fc
I0707 18:30:43.248986 99468 net.cpp:367] loss2/drop_fc -> loss2/fc (in-place)
I0707 18:30:43.249037 99468 net.cpp:122] Setting up loss2/drop_fc
I0707 18:30:43.249053 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.249091 99468 net.cpp:137] Memory required for data: 3796037892
I0707 18:30:43.249102 99468 layer_factory.hpp:77] Creating layer loss2/classifier_my
I0707 18:30:43.249122 99468 net.cpp:84] Creating Layer loss2/classifier_my
I0707 18:30:43.249132 99468 net.cpp:406] loss2/classifier_my <- loss2/fc
I0707 18:30:43.249146 99468 net.cpp:380] loss2/classifier_my -> loss2/classifier
I0707 18:30:43.249630 99468 net.cpp:122] Setting up loss2/classifier_my
I0707 18:30:43.249649 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.249656 99468 net.cpp:137] Memory required for data: 3796047876
I0707 18:30:43.249667 99468 layer_factory.hpp:77] Creating layer loss2/loss
I0707 18:30:43.249680 99468 net.cpp:84] Creating Layer loss2/loss
I0707 18:30:43.249688 99468 net.cpp:406] loss2/loss <- loss2/classifier
I0707 18:30:43.249701 99468 net.cpp:406] loss2/loss <- label_data_1_split_1
I0707 18:30:43.249716 99468 net.cpp:380] loss2/loss -> loss2/loss2
I0707 18:30:43.249761 99468 layer_factory.hpp:77] Creating layer loss2/loss
I0707 18:30:43.250795 99468 net.cpp:122] Setting up loss2/loss
I0707 18:30:43.250820 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.250828 99468 net.cpp:132]     with loss weight 0.3
I0707 18:30:43.250846 99468 net.cpp:137] Memory required for data: 3796047880
I0707 18:30:43.250855 99468 layer_factory.hpp:77] Creating layer inception_4e/1x1
I0707 18:30:43.250875 99468 net.cpp:84] Creating Layer inception_4e/1x1
I0707 18:30:43.250890 99468 net.cpp:406] inception_4e/1x1 <- inception_4d/output_inception_4d/output_0_split_1
I0707 18:30:43.250905 99468 net.cpp:380] inception_4e/1x1 -> inception_4e/1x1
I0707 18:30:43.254354 99468 net.cpp:122] Setting up inception_4e/1x1
I0707 18:30:43.254381 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.254390 99468 net.cpp:137] Memory required for data: 3808892936
I0707 18:30:43.254403 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_1x1
I0707 18:30:43.254418 99468 net.cpp:84] Creating Layer inception_4e/relu_1x1
I0707 18:30:43.254432 99468 net.cpp:406] inception_4e/relu_1x1 <- inception_4e/1x1
I0707 18:30:43.254446 99468 net.cpp:367] inception_4e/relu_1x1 -> inception_4e/1x1 (in-place)
I0707 18:30:43.255348 99468 net.cpp:122] Setting up inception_4e/relu_1x1
I0707 18:30:43.255373 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.255380 99468 net.cpp:137] Memory required for data: 3821737992
I0707 18:30:43.255389 99468 layer_factory.hpp:77] Creating layer inception_4e/3x3_reduce
I0707 18:30:43.255408 99468 net.cpp:84] Creating Layer inception_4e/3x3_reduce
I0707 18:30:43.255419 99468 net.cpp:406] inception_4e/3x3_reduce <- inception_4d/output_inception_4d/output_0_split_2
I0707 18:30:43.255439 99468 net.cpp:380] inception_4e/3x3_reduce -> inception_4e/3x3_reduce
I0707 18:30:43.258424 99468 net.cpp:122] Setting up inception_4e/3x3_reduce
I0707 18:30:43.258450 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.258460 99468 net.cpp:137] Memory required for data: 3829766152
I0707 18:30:43.258471 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_3x3_reduce
I0707 18:30:43.258484 99468 net.cpp:84] Creating Layer inception_4e/relu_3x3_reduce
I0707 18:30:43.258496 99468 net.cpp:406] inception_4e/relu_3x3_reduce <- inception_4e/3x3_reduce
I0707 18:30:43.258512 99468 net.cpp:367] inception_4e/relu_3x3_reduce -> inception_4e/3x3_reduce (in-place)
I0707 18:30:43.258764 99468 net.cpp:122] Setting up inception_4e/relu_3x3_reduce
I0707 18:30:43.258785 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.258793 99468 net.cpp:137] Memory required for data: 3837794312
I0707 18:30:43.258847 99468 layer_factory.hpp:77] Creating layer inception_4e/3x3
I0707 18:30:43.258870 99468 net.cpp:84] Creating Layer inception_4e/3x3
I0707 18:30:43.258883 99468 net.cpp:406] inception_4e/3x3 <- inception_4e/3x3_reduce
I0707 18:30:43.258915 99468 net.cpp:380] inception_4e/3x3 -> inception_4e/3x3
I0707 18:30:43.266299 99468 net.cpp:122] Setting up inception_4e/3x3
I0707 18:30:43.266326 99468 net.cpp:129] Top shape: 64 320 14 14 (4014080)
I0707 18:30:43.266335 99468 net.cpp:137] Memory required for data: 3853850632
I0707 18:30:43.266348 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_3x3
I0707 18:30:43.266363 99468 net.cpp:84] Creating Layer inception_4e/relu_3x3
I0707 18:30:43.266407 99468 net.cpp:406] inception_4e/relu_3x3 <- inception_4e/3x3
I0707 18:30:43.266424 99468 net.cpp:367] inception_4e/relu_3x3 -> inception_4e/3x3 (in-place)
I0707 18:30:43.267329 99468 net.cpp:122] Setting up inception_4e/relu_3x3
I0707 18:30:43.267354 99468 net.cpp:129] Top shape: 64 320 14 14 (4014080)
I0707 18:30:43.267365 99468 net.cpp:137] Memory required for data: 3869906952
I0707 18:30:43.267374 99468 layer_factory.hpp:77] Creating layer inception_4e/5x5_reduce
I0707 18:30:43.267390 99468 net.cpp:84] Creating Layer inception_4e/5x5_reduce
I0707 18:30:43.267405 99468 net.cpp:406] inception_4e/5x5_reduce <- inception_4d/output_inception_4d/output_0_split_3
I0707 18:30:43.267424 99468 net.cpp:380] inception_4e/5x5_reduce -> inception_4e/5x5_reduce
I0707 18:30:43.269301 99468 net.cpp:122] Setting up inception_4e/5x5_reduce
I0707 18:30:43.269327 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.269336 99468 net.cpp:137] Memory required for data: 3871512584
I0707 18:30:43.269348 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_5x5_reduce
I0707 18:30:43.269361 99468 net.cpp:84] Creating Layer inception_4e/relu_5x5_reduce
I0707 18:30:43.269371 99468 net.cpp:406] inception_4e/relu_5x5_reduce <- inception_4e/5x5_reduce
I0707 18:30:43.269428 99468 net.cpp:367] inception_4e/relu_5x5_reduce -> inception_4e/5x5_reduce (in-place)
I0707 18:30:43.270319 99468 net.cpp:122] Setting up inception_4e/relu_5x5_reduce
I0707 18:30:43.270344 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.270352 99468 net.cpp:137] Memory required for data: 3873118216
I0707 18:30:43.270360 99468 layer_factory.hpp:77] Creating layer inception_4e/5x5
I0707 18:30:43.270378 99468 net.cpp:84] Creating Layer inception_4e/5x5
I0707 18:30:43.270390 99468 net.cpp:406] inception_4e/5x5 <- inception_4e/5x5_reduce
I0707 18:30:43.270408 99468 net.cpp:380] inception_4e/5x5 -> inception_4e/5x5
I0707 18:30:43.274255 99468 net.cpp:122] Setting up inception_4e/5x5
I0707 18:30:43.274282 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.274291 99468 net.cpp:137] Memory required for data: 3879540744
I0707 18:30:43.274303 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_5x5
I0707 18:30:43.274318 99468 net.cpp:84] Creating Layer inception_4e/relu_5x5
I0707 18:30:43.274329 99468 net.cpp:406] inception_4e/relu_5x5 <- inception_4e/5x5
I0707 18:30:43.274343 99468 net.cpp:367] inception_4e/relu_5x5 -> inception_4e/5x5 (in-place)
I0707 18:30:43.274631 99468 net.cpp:122] Setting up inception_4e/relu_5x5
I0707 18:30:43.274652 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.274663 99468 net.cpp:137] Memory required for data: 3885963272
I0707 18:30:43.274672 99468 layer_factory.hpp:77] Creating layer inception_4e/pool
I0707 18:30:43.274688 99468 net.cpp:84] Creating Layer inception_4e/pool
I0707 18:30:43.274698 99468 net.cpp:406] inception_4e/pool <- inception_4d/output_inception_4d/output_0_split_4
I0707 18:30:43.274732 99468 net.cpp:380] inception_4e/pool -> inception_4e/pool
I0707 18:30:43.274807 99468 net.cpp:122] Setting up inception_4e/pool
I0707 18:30:43.274823 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.274847 99468 net.cpp:137] Memory required for data: 3912456200
I0707 18:30:43.274857 99468 layer_factory.hpp:77] Creating layer inception_4e/pool_proj
I0707 18:30:43.274906 99468 net.cpp:84] Creating Layer inception_4e/pool_proj
I0707 18:30:43.274920 99468 net.cpp:406] inception_4e/pool_proj <- inception_4e/pool
I0707 18:30:43.274938 99468 net.cpp:380] inception_4e/pool_proj -> inception_4e/pool_proj
I0707 18:30:43.277819 99468 net.cpp:122] Setting up inception_4e/pool_proj
I0707 18:30:43.277848 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.277858 99468 net.cpp:137] Memory required for data: 3918878728
I0707 18:30:43.277873 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_pool_proj
I0707 18:30:43.277889 99468 net.cpp:84] Creating Layer inception_4e/relu_pool_proj
I0707 18:30:43.277901 99468 net.cpp:406] inception_4e/relu_pool_proj <- inception_4e/pool_proj
I0707 18:30:43.277935 99468 net.cpp:367] inception_4e/relu_pool_proj -> inception_4e/pool_proj (in-place)
I0707 18:30:43.278812 99468 net.cpp:122] Setting up inception_4e/relu_pool_proj
I0707 18:30:43.278836 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.278846 99468 net.cpp:137] Memory required for data: 3925301256
I0707 18:30:43.278853 99468 layer_factory.hpp:77] Creating layer inception_4e/output
I0707 18:30:43.278867 99468 net.cpp:84] Creating Layer inception_4e/output
I0707 18:30:43.278879 99468 net.cpp:406] inception_4e/output <- inception_4e/1x1
I0707 18:30:43.278893 99468 net.cpp:406] inception_4e/output <- inception_4e/3x3
I0707 18:30:43.278903 99468 net.cpp:406] inception_4e/output <- inception_4e/5x5
I0707 18:30:43.278914 99468 net.cpp:406] inception_4e/output <- inception_4e/pool_proj
I0707 18:30:43.278925 99468 net.cpp:380] inception_4e/output -> inception_4e/output
I0707 18:30:43.278977 99468 net.cpp:122] Setting up inception_4e/output
I0707 18:30:43.278995 99468 net.cpp:129] Top shape: 64 832 14 14 (10436608)
I0707 18:30:43.279027 99468 net.cpp:137] Memory required for data: 3967047688
I0707 18:30:43.279040 99468 layer_factory.hpp:77] Creating layer pool4/3x3_s2
I0707 18:30:43.279054 99468 net.cpp:84] Creating Layer pool4/3x3_s2
I0707 18:30:43.279065 99468 net.cpp:406] pool4/3x3_s2 <- inception_4e/output
I0707 18:30:43.279079 99468 net.cpp:380] pool4/3x3_s2 -> pool4/3x3_s2
I0707 18:30:43.279151 99468 net.cpp:122] Setting up pool4/3x3_s2
I0707 18:30:43.279170 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.279181 99468 net.cpp:137] Memory required for data: 3977484296
I0707 18:30:43.279192 99468 layer_factory.hpp:77] Creating layer pool4/3x3_s2_pool4/3x3_s2_0_split
I0707 18:30:43.279203 99468 net.cpp:84] Creating Layer pool4/3x3_s2_pool4/3x3_s2_0_split
I0707 18:30:43.279212 99468 net.cpp:406] pool4/3x3_s2_pool4/3x3_s2_0_split <- pool4/3x3_s2
I0707 18:30:43.279227 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_0
I0707 18:30:43.279242 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_1
I0707 18:30:43.279254 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_2
I0707 18:30:43.279273 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_3
I0707 18:30:43.279376 99468 net.cpp:122] Setting up pool4/3x3_s2_pool4/3x3_s2_0_split
I0707 18:30:43.279391 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.279404 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.279417 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.279429 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.279441 99468 net.cpp:137] Memory required for data: 4019230728
I0707 18:30:43.279450 99468 layer_factory.hpp:77] Creating layer inception_5a/1x1
I0707 18:30:43.279467 99468 net.cpp:84] Creating Layer inception_5a/1x1
I0707 18:30:43.279481 99468 net.cpp:406] inception_5a/1x1 <- pool4/3x3_s2_pool4/3x3_s2_0_split_0
I0707 18:30:43.279495 99468 net.cpp:380] inception_5a/1x1 -> inception_5a/1x1
I0707 18:30:43.283502 99468 net.cpp:122] Setting up inception_5a/1x1
I0707 18:30:43.283531 99468 net.cpp:129] Top shape: 64 256 7 7 (802816)
I0707 18:30:43.283576 99468 net.cpp:137] Memory required for data: 4022441992
I0707 18:30:43.283608 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_1x1
I0707 18:30:43.283627 99468 net.cpp:84] Creating Layer inception_5a/relu_1x1
I0707 18:30:43.283639 99468 net.cpp:406] inception_5a/relu_1x1 <- inception_5a/1x1
I0707 18:30:43.283654 99468 net.cpp:367] inception_5a/relu_1x1 -> inception_5a/1x1 (in-place)
I0707 18:30:43.284538 99468 net.cpp:122] Setting up inception_5a/relu_1x1
I0707 18:30:43.284569 99468 net.cpp:129] Top shape: 64 256 7 7 (802816)
I0707 18:30:43.284579 99468 net.cpp:137] Memory required for data: 4025653256
I0707 18:30:43.284587 99468 layer_factory.hpp:77] Creating layer inception_5a/3x3_reduce
I0707 18:30:43.284605 99468 net.cpp:84] Creating Layer inception_5a/3x3_reduce
I0707 18:30:43.284616 99468 net.cpp:406] inception_5a/3x3_reduce <- pool4/3x3_s2_pool4/3x3_s2_0_split_1
I0707 18:30:43.284633 99468 net.cpp:380] inception_5a/3x3_reduce -> inception_5a/3x3_reduce
I0707 18:30:43.288743 99468 net.cpp:122] Setting up inception_5a/3x3_reduce
I0707 18:30:43.288770 99468 net.cpp:129] Top shape: 64 160 7 7 (501760)
I0707 18:30:43.288779 99468 net.cpp:137] Memory required for data: 4027660296
I0707 18:30:43.288792 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_3x3_reduce
I0707 18:30:43.288805 99468 net.cpp:84] Creating Layer inception_5a/relu_3x3_reduce
I0707 18:30:43.288816 99468 net.cpp:406] inception_5a/relu_3x3_reduce <- inception_5a/3x3_reduce
I0707 18:30:43.288831 99468 net.cpp:367] inception_5a/relu_3x3_reduce -> inception_5a/3x3_reduce (in-place)
I0707 18:30:43.289114 99468 net.cpp:122] Setting up inception_5a/relu_3x3_reduce
I0707 18:30:43.289134 99468 net.cpp:129] Top shape: 64 160 7 7 (501760)
I0707 18:30:43.289142 99468 net.cpp:137] Memory required for data: 4029667336
I0707 18:30:43.289150 99468 layer_factory.hpp:77] Creating layer inception_5a/3x3
I0707 18:30:43.289175 99468 net.cpp:84] Creating Layer inception_5a/3x3
I0707 18:30:43.289186 99468 net.cpp:406] inception_5a/3x3 <- inception_5a/3x3_reduce
I0707 18:30:43.289203 99468 net.cpp:380] inception_5a/3x3 -> inception_5a/3x3
I0707 18:30:43.295981 99468 net.cpp:122] Setting up inception_5a/3x3
I0707 18:30:43.296008 99468 net.cpp:129] Top shape: 64 320 7 7 (1003520)
I0707 18:30:43.296017 99468 net.cpp:137] Memory required for data: 4033681416
I0707 18:30:43.296030 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_3x3
I0707 18:30:43.296042 99468 net.cpp:84] Creating Layer inception_5a/relu_3x3
I0707 18:30:43.296053 99468 net.cpp:406] inception_5a/relu_3x3 <- inception_5a/3x3
I0707 18:30:43.296069 99468 net.cpp:367] inception_5a/relu_3x3 -> inception_5a/3x3 (in-place)
I0707 18:30:43.297000 99468 net.cpp:122] Setting up inception_5a/relu_3x3
I0707 18:30:43.297024 99468 net.cpp:129] Top shape: 64 320 7 7 (1003520)
I0707 18:30:43.297034 99468 net.cpp:137] Memory required for data: 4037695496
I0707 18:30:43.297042 99468 layer_factory.hpp:77] Creating layer inception_5a/5x5_reduce
I0707 18:30:43.297060 99468 net.cpp:84] Creating Layer inception_5a/5x5_reduce
I0707 18:30:43.297072 99468 net.cpp:406] inception_5a/5x5_reduce <- pool4/3x3_s2_pool4/3x3_s2_0_split_2
I0707 18:30:43.297088 99468 net.cpp:380] inception_5a/5x5_reduce -> inception_5a/5x5_reduce
I0707 18:30:43.299255 99468 net.cpp:122] Setting up inception_5a/5x5_reduce
I0707 18:30:43.299278 99468 net.cpp:129] Top shape: 64 32 7 7 (100352)
I0707 18:30:43.299283 99468 net.cpp:137] Memory required for data: 4038096904
I0707 18:30:43.299293 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_5x5_reduce
I0707 18:30:43.299305 99468 net.cpp:84] Creating Layer inception_5a/relu_5x5_reduce
I0707 18:30:43.299314 99468 net.cpp:406] inception_5a/relu_5x5_reduce <- inception_5a/5x5_reduce
I0707 18:30:43.299324 99468 net.cpp:367] inception_5a/relu_5x5_reduce -> inception_5a/5x5_reduce (in-place)
I0707 18:30:43.300528 99468 net.cpp:122] Setting up inception_5a/relu_5x5_reduce
I0707 18:30:43.300547 99468 net.cpp:129] Top shape: 64 32 7 7 (100352)
I0707 18:30:43.300573 99468 net.cpp:137] Memory required for data: 4038498312
I0707 18:30:43.300581 99468 layer_factory.hpp:77] Creating layer inception_5a/5x5
I0707 18:30:43.300598 99468 net.cpp:84] Creating Layer inception_5a/5x5
I0707 18:30:43.300608 99468 net.cpp:406] inception_5a/5x5 <- inception_5a/5x5_reduce
I0707 18:30:43.300621 99468 net.cpp:380] inception_5a/5x5 -> inception_5a/5x5
I0707 18:30:43.303089 99468 net.cpp:122] Setting up inception_5a/5x5
I0707 18:30:43.303110 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.303117 99468 net.cpp:137] Memory required for data: 4040103944
I0707 18:30:43.303127 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_5x5
I0707 18:30:43.303136 99468 net.cpp:84] Creating Layer inception_5a/relu_5x5
I0707 18:30:43.303143 99468 net.cpp:406] inception_5a/relu_5x5 <- inception_5a/5x5
I0707 18:30:43.303154 99468 net.cpp:367] inception_5a/relu_5x5 -> inception_5a/5x5 (in-place)
I0707 18:30:43.303345 99468 net.cpp:122] Setting up inception_5a/relu_5x5
I0707 18:30:43.303360 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.303393 99468 net.cpp:137] Memory required for data: 4041709576
I0707 18:30:43.303401 99468 layer_factory.hpp:77] Creating layer inception_5a/pool
I0707 18:30:43.303413 99468 net.cpp:84] Creating Layer inception_5a/pool
I0707 18:30:43.303422 99468 net.cpp:406] inception_5a/pool <- pool4/3x3_s2_pool4/3x3_s2_0_split_3
I0707 18:30:43.303448 99468 net.cpp:380] inception_5a/pool -> inception_5a/pool
I0707 18:30:43.303539 99468 net.cpp:122] Setting up inception_5a/pool
I0707 18:30:43.303561 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.303588 99468 net.cpp:137] Memory required for data: 4052146184
I0707 18:30:43.303598 99468 layer_factory.hpp:77] Creating layer inception_5a/pool_proj
I0707 18:30:43.303614 99468 net.cpp:84] Creating Layer inception_5a/pool_proj
I0707 18:30:43.303622 99468 net.cpp:406] inception_5a/pool_proj <- inception_5a/pool
I0707 18:30:43.303637 99468 net.cpp:380] inception_5a/pool_proj -> inception_5a/pool_proj
I0707 18:30:43.306742 99468 net.cpp:122] Setting up inception_5a/pool_proj
I0707 18:30:43.306764 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.306771 99468 net.cpp:137] Memory required for data: 4053751816
I0707 18:30:43.306782 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_pool_proj
I0707 18:30:43.306821 99468 net.cpp:84] Creating Layer inception_5a/relu_pool_proj
I0707 18:30:43.306829 99468 net.cpp:406] inception_5a/relu_pool_proj <- inception_5a/pool_proj
I0707 18:30:43.306843 99468 net.cpp:367] inception_5a/relu_pool_proj -> inception_5a/pool_proj (in-place)
I0707 18:30:43.307566 99468 net.cpp:122] Setting up inception_5a/relu_pool_proj
I0707 18:30:43.307585 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.307592 99468 net.cpp:137] Memory required for data: 4055357448
I0707 18:30:43.307600 99468 layer_factory.hpp:77] Creating layer inception_5a/output
I0707 18:30:43.307610 99468 net.cpp:84] Creating Layer inception_5a/output
I0707 18:30:43.307618 99468 net.cpp:406] inception_5a/output <- inception_5a/1x1
I0707 18:30:43.307629 99468 net.cpp:406] inception_5a/output <- inception_5a/3x3
I0707 18:30:43.307641 99468 net.cpp:406] inception_5a/output <- inception_5a/5x5
I0707 18:30:43.307648 99468 net.cpp:406] inception_5a/output <- inception_5a/pool_proj
I0707 18:30:43.307657 99468 net.cpp:380] inception_5a/output -> inception_5a/output
I0707 18:30:43.307703 99468 net.cpp:122] Setting up inception_5a/output
I0707 18:30:43.307714 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.307754 99468 net.cpp:137] Memory required for data: 4065794056
I0707 18:30:43.307760 99468 layer_factory.hpp:77] Creating layer inception_5a/output_inception_5a/output_0_split
I0707 18:30:43.307771 99468 net.cpp:84] Creating Layer inception_5a/output_inception_5a/output_0_split
I0707 18:30:43.307782 99468 net.cpp:406] inception_5a/output_inception_5a/output_0_split <- inception_5a/output
I0707 18:30:43.307792 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_0
I0707 18:30:43.307834 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_1
I0707 18:30:43.307847 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_2
I0707 18:30:43.307857 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_3
I0707 18:30:43.307946 99468 net.cpp:122] Setting up inception_5a/output_inception_5a/output_0_split
I0707 18:30:43.307960 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.307968 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.307976 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.307986 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.307992 99468 net.cpp:137] Memory required for data: 4107540488
I0707 18:30:43.308002 99468 layer_factory.hpp:77] Creating layer inception_5b/1x1
I0707 18:30:43.308018 99468 net.cpp:84] Creating Layer inception_5b/1x1
I0707 18:30:43.308027 99468 net.cpp:406] inception_5b/1x1 <- inception_5a/output_inception_5a/output_0_split_0
I0707 18:30:43.308038 99468 net.cpp:380] inception_5b/1x1 -> inception_5b/1x1
I0707 18:30:43.311879 99468 net.cpp:122] Setting up inception_5b/1x1
I0707 18:30:43.311902 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.311908 99468 net.cpp:137] Memory required for data: 4112357384
I0707 18:30:43.311918 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_1x1
I0707 18:30:43.311928 99468 net.cpp:84] Creating Layer inception_5b/relu_1x1
I0707 18:30:43.311935 99468 net.cpp:406] inception_5b/relu_1x1 <- inception_5b/1x1
I0707 18:30:43.311975 99468 net.cpp:367] inception_5b/relu_1x1 -> inception_5b/1x1 (in-place)
I0707 18:30:43.312680 99468 net.cpp:122] Setting up inception_5b/relu_1x1
I0707 18:30:43.312700 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.312706 99468 net.cpp:137] Memory required for data: 4117174280
I0707 18:30:43.312713 99468 layer_factory.hpp:77] Creating layer inception_5b/3x3_reduce
I0707 18:30:43.312728 99468 net.cpp:84] Creating Layer inception_5b/3x3_reduce
I0707 18:30:43.312737 99468 net.cpp:406] inception_5b/3x3_reduce <- inception_5a/output_inception_5a/output_0_split_1
I0707 18:30:43.312749 99468 net.cpp:380] inception_5b/3x3_reduce -> inception_5b/3x3_reduce
I0707 18:30:43.316221 99468 net.cpp:122] Setting up inception_5b/3x3_reduce
I0707 18:30:43.316243 99468 net.cpp:129] Top shape: 64 192 7 7 (602112)
I0707 18:30:43.316251 99468 net.cpp:137] Memory required for data: 4119582728
I0707 18:30:43.316259 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_3x3_reduce
I0707 18:30:43.316272 99468 net.cpp:84] Creating Layer inception_5b/relu_3x3_reduce
I0707 18:30:43.316280 99468 net.cpp:406] inception_5b/relu_3x3_reduce <- inception_5b/3x3_reduce
I0707 18:30:43.316290 99468 net.cpp:367] inception_5b/relu_3x3_reduce -> inception_5b/3x3_reduce (in-place)
I0707 18:30:43.316483 99468 net.cpp:122] Setting up inception_5b/relu_3x3_reduce
I0707 18:30:43.316500 99468 net.cpp:129] Top shape: 64 192 7 7 (602112)
I0707 18:30:43.316510 99468 net.cpp:137] Memory required for data: 4121991176
I0707 18:30:43.316542 99468 layer_factory.hpp:77] Creating layer inception_5b/3x3
I0707 18:30:43.316570 99468 net.cpp:84] Creating Layer inception_5b/3x3
I0707 18:30:43.316578 99468 net.cpp:406] inception_5b/3x3 <- inception_5b/3x3_reduce
I0707 18:30:43.316593 99468 net.cpp:380] inception_5b/3x3 -> inception_5b/3x3
I0707 18:30:43.323334 99468 net.cpp:122] Setting up inception_5b/3x3
I0707 18:30:43.323357 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.323364 99468 net.cpp:137] Memory required for data: 4126808072
I0707 18:30:43.323374 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_3x3
I0707 18:30:43.323387 99468 net.cpp:84] Creating Layer inception_5b/relu_3x3
I0707 18:30:43.323431 99468 net.cpp:406] inception_5b/relu_3x3 <- inception_5b/3x3
I0707 18:30:43.323472 99468 net.cpp:367] inception_5b/relu_3x3 -> inception_5b/3x3 (in-place)
I0707 18:30:43.324185 99468 net.cpp:122] Setting up inception_5b/relu_3x3
I0707 18:30:43.324205 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.324214 99468 net.cpp:137] Memory required for data: 4131624968
I0707 18:30:43.324221 99468 layer_factory.hpp:77] Creating layer inception_5b/5x5_reduce
I0707 18:30:43.324234 99468 net.cpp:84] Creating Layer inception_5b/5x5_reduce
I0707 18:30:43.324244 99468 net.cpp:406] inception_5b/5x5_reduce <- inception_5a/output_inception_5a/output_0_split_2
I0707 18:30:43.324257 99468 net.cpp:380] inception_5b/5x5_reduce -> inception_5b/5x5_reduce
I0707 18:30:43.325922 99468 net.cpp:122] Setting up inception_5b/5x5_reduce
I0707 18:30:43.325943 99468 net.cpp:129] Top shape: 64 48 7 7 (150528)
I0707 18:30:43.325950 99468 net.cpp:137] Memory required for data: 4132227080
I0707 18:30:43.325984 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_5x5_reduce
I0707 18:30:43.326026 99468 net.cpp:84] Creating Layer inception_5b/relu_5x5_reduce
I0707 18:30:43.326035 99468 net.cpp:406] inception_5b/relu_5x5_reduce <- inception_5b/5x5_reduce
I0707 18:30:43.326043 99468 net.cpp:367] inception_5b/relu_5x5_reduce -> inception_5b/5x5_reduce (in-place)
I0707 18:30:43.326750 99468 net.cpp:122] Setting up inception_5b/relu_5x5_reduce
I0707 18:30:43.326771 99468 net.cpp:129] Top shape: 64 48 7 7 (150528)
I0707 18:30:43.326777 99468 net.cpp:137] Memory required for data: 4132829192
I0707 18:30:43.326784 99468 layer_factory.hpp:77] Creating layer inception_5b/5x5
I0707 18:30:43.326799 99468 net.cpp:84] Creating Layer inception_5b/5x5
I0707 18:30:43.326839 99468 net.cpp:406] inception_5b/5x5 <- inception_5b/5x5_reduce
I0707 18:30:43.326850 99468 net.cpp:380] inception_5b/5x5 -> inception_5b/5x5
I0707 18:30:43.329586 99468 net.cpp:122] Setting up inception_5b/5x5
I0707 18:30:43.329607 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.329614 99468 net.cpp:137] Memory required for data: 4134434824
I0707 18:30:43.329623 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_5x5
I0707 18:30:43.329635 99468 net.cpp:84] Creating Layer inception_5b/relu_5x5
I0707 18:30:43.329643 99468 net.cpp:406] inception_5b/relu_5x5 <- inception_5b/5x5
I0707 18:30:43.329653 99468 net.cpp:367] inception_5b/relu_5x5 -> inception_5b/5x5 (in-place)
I0707 18:30:43.329852 99468 net.cpp:122] Setting up inception_5b/relu_5x5
I0707 18:30:43.329869 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.329902 99468 net.cpp:137] Memory required for data: 4136040456
I0707 18:30:43.329910 99468 layer_factory.hpp:77] Creating layer inception_5b/pool
I0707 18:30:43.329936 99468 net.cpp:84] Creating Layer inception_5b/pool
I0707 18:30:43.329944 99468 net.cpp:406] inception_5b/pool <- inception_5a/output_inception_5a/output_0_split_3
I0707 18:30:43.329953 99468 net.cpp:380] inception_5b/pool -> inception_5b/pool
I0707 18:30:43.330018 99468 net.cpp:122] Setting up inception_5b/pool
I0707 18:30:43.330030 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.330039 99468 net.cpp:137] Memory required for data: 4146477064
I0707 18:30:43.330049 99468 layer_factory.hpp:77] Creating layer inception_5b/pool_proj
I0707 18:30:43.330067 99468 net.cpp:84] Creating Layer inception_5b/pool_proj
I0707 18:30:43.330076 99468 net.cpp:406] inception_5b/pool_proj <- inception_5b/pool
I0707 18:30:43.330109 99468 net.cpp:380] inception_5b/pool_proj -> inception_5b/pool_proj
I0707 18:30:43.333709 99468 net.cpp:122] Setting up inception_5b/pool_proj
I0707 18:30:43.333730 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.333737 99468 net.cpp:137] Memory required for data: 4148082696
I0707 18:30:43.333747 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_pool_proj
I0707 18:30:43.333756 99468 net.cpp:84] Creating Layer inception_5b/relu_pool_proj
I0707 18:30:43.333765 99468 net.cpp:406] inception_5b/relu_pool_proj <- inception_5b/pool_proj
I0707 18:30:43.333777 99468 net.cpp:367] inception_5b/relu_pool_proj -> inception_5b/pool_proj (in-place)
I0707 18:30:43.334530 99468 net.cpp:122] Setting up inception_5b/relu_pool_proj
I0707 18:30:43.334550 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.334563 99468 net.cpp:137] Memory required for data: 4149688328
I0707 18:30:43.334569 99468 layer_factory.hpp:77] Creating layer inception_5b/output
I0707 18:30:43.334579 99468 net.cpp:84] Creating Layer inception_5b/output
I0707 18:30:43.334588 99468 net.cpp:406] inception_5b/output <- inception_5b/1x1
I0707 18:30:43.334597 99468 net.cpp:406] inception_5b/output <- inception_5b/3x3
I0707 18:30:43.334609 99468 net.cpp:406] inception_5b/output <- inception_5b/5x5
I0707 18:30:43.334617 99468 net.cpp:406] inception_5b/output <- inception_5b/pool_proj
I0707 18:30:43.334661 99468 net.cpp:380] inception_5b/output -> inception_5b/output
I0707 18:30:43.334704 99468 net.cpp:122] Setting up inception_5b/output
I0707 18:30:43.334718 99468 net.cpp:129] Top shape: 64 1024 7 7 (3211264)
I0707 18:30:43.334743 99468 net.cpp:137] Memory required for data: 4162533384
I0707 18:30:43.334764 99468 layer_factory.hpp:77] Creating layer pool5/7x7_s1
I0707 18:30:43.334774 99468 net.cpp:84] Creating Layer pool5/7x7_s1
I0707 18:30:43.334799 99468 net.cpp:406] pool5/7x7_s1 <- inception_5b/output
I0707 18:30:43.334811 99468 net.cpp:380] pool5/7x7_s1 -> pool5/7x7_s1
I0707 18:30:43.335026 99468 net.cpp:122] Setting up pool5/7x7_s1
I0707 18:30:43.335042 99468 net.cpp:129] Top shape: 64 1024 1 1 (65536)
I0707 18:30:43.335052 99468 net.cpp:137] Memory required for data: 4162795528
I0707 18:30:43.335060 99468 layer_factory.hpp:77] Creating layer pool5/drop_7x7_s1
I0707 18:30:43.335072 99468 net.cpp:84] Creating Layer pool5/drop_7x7_s1
I0707 18:30:43.335083 99468 net.cpp:406] pool5/drop_7x7_s1 <- pool5/7x7_s1
I0707 18:30:43.335093 99468 net.cpp:367] pool5/drop_7x7_s1 -> pool5/7x7_s1 (in-place)
I0707 18:30:43.335130 99468 net.cpp:122] Setting up pool5/drop_7x7_s1
I0707 18:30:43.335142 99468 net.cpp:129] Top shape: 64 1024 1 1 (65536)
I0707 18:30:43.335153 99468 net.cpp:137] Memory required for data: 4163057672
I0707 18:30:43.335160 99468 layer_factory.hpp:77] Creating layer fc8_kevin
I0707 18:30:43.335172 99468 net.cpp:84] Creating Layer fc8_kevin
I0707 18:30:43.335180 99468 net.cpp:406] fc8_kevin <- pool5/7x7_s1
I0707 18:30:43.335196 99468 net.cpp:380] fc8_kevin -> fc8_pascal
I0707 18:30:43.336043 99468 net.cpp:122] Setting up fc8_kevin
I0707 18:30:43.336058 99468 net.cpp:129] Top shape: 64 128 (8192)
I0707 18:30:43.336071 99468 net.cpp:137] Memory required for data: 4163090440
I0707 18:30:43.336079 99468 layer_factory.hpp:77] Creating layer fc8_kevin_encode
I0707 18:30:43.336093 99468 net.cpp:84] Creating Layer fc8_kevin_encode
I0707 18:30:43.336103 99468 net.cpp:406] fc8_kevin_encode <- fc8_pascal
I0707 18:30:43.336112 99468 net.cpp:380] fc8_kevin_encode -> fc8_kevin_encode
I0707 18:30:43.336839 99468 net.cpp:122] Setting up fc8_kevin_encode
I0707 18:30:43.336859 99468 net.cpp:129] Top shape: 64 128 (8192)
I0707 18:30:43.336866 99468 net.cpp:137] Memory required for data: 4163123208
I0707 18:30:43.336872 99468 layer_factory.hpp:77] Creating layer loss3/classifier_my
I0707 18:30:43.336889 99468 net.cpp:84] Creating Layer loss3/classifier_my
I0707 18:30:43.336904 99468 net.cpp:406] loss3/classifier_my <- fc8_kevin_encode
I0707 18:30:43.336915 99468 net.cpp:380] loss3/classifier_my -> loss3/classifier
I0707 18:30:43.337098 99468 net.cpp:122] Setting up loss3/classifier_my
I0707 18:30:43.337116 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.337126 99468 net.cpp:137] Memory required for data: 4163133192
I0707 18:30:43.337136 99468 layer_factory.hpp:77] Creating layer loss3/loss3
I0707 18:30:43.337151 99468 net.cpp:84] Creating Layer loss3/loss3
I0707 18:30:43.337157 99468 net.cpp:406] loss3/loss3 <- loss3/classifier
I0707 18:30:43.337170 99468 net.cpp:406] loss3/loss3 <- label_data_1_split_2
I0707 18:30:43.337183 99468 net.cpp:380] loss3/loss3 -> loss3/loss3
I0707 18:30:43.337194 99468 layer_factory.hpp:77] Creating layer loss3/loss3
I0707 18:30:43.337530 99468 net.cpp:122] Setting up loss3/loss3
I0707 18:30:43.337548 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.337561 99468 net.cpp:132]     with loss weight 1
I0707 18:30:43.337574 99468 net.cpp:137] Memory required for data: 4163133196
I0707 18:30:43.337584 99468 net.cpp:198] loss3/loss3 needs backward computation.
I0707 18:30:43.337591 99468 net.cpp:198] loss3/classifier_my needs backward computation.
I0707 18:30:43.337601 99468 net.cpp:198] fc8_kevin_encode needs backward computation.
I0707 18:30:43.337607 99468 net.cpp:198] fc8_kevin needs backward computation.
I0707 18:30:43.337616 99468 net.cpp:198] pool5/drop_7x7_s1 needs backward computation.
I0707 18:30:43.337623 99468 net.cpp:198] pool5/7x7_s1 needs backward computation.
I0707 18:30:43.337632 99468 net.cpp:198] inception_5b/output needs backward computation.
I0707 18:30:43.337642 99468 net.cpp:198] inception_5b/relu_pool_proj needs backward computation.
I0707 18:30:43.337651 99468 net.cpp:198] inception_5b/pool_proj needs backward computation.
I0707 18:30:43.337658 99468 net.cpp:198] inception_5b/pool needs backward computation.
I0707 18:30:43.337668 99468 net.cpp:198] inception_5b/relu_5x5 needs backward computation.
I0707 18:30:43.337677 99468 net.cpp:198] inception_5b/5x5 needs backward computation.
I0707 18:30:43.337687 99468 net.cpp:198] inception_5b/relu_5x5_reduce needs backward computation.
I0707 18:30:43.337694 99468 net.cpp:198] inception_5b/5x5_reduce needs backward computation.
I0707 18:30:43.337702 99468 net.cpp:198] inception_5b/relu_3x3 needs backward computation.
I0707 18:30:43.337707 99468 net.cpp:198] inception_5b/3x3 needs backward computation.
I0707 18:30:43.337718 99468 net.cpp:198] inception_5b/relu_3x3_reduce needs backward computation.
I0707 18:30:43.337723 99468 net.cpp:198] inception_5b/3x3_reduce needs backward computation.
I0707 18:30:43.337731 99468 net.cpp:198] inception_5b/relu_1x1 needs backward computation.
I0707 18:30:43.337738 99468 net.cpp:198] inception_5b/1x1 needs backward computation.
I0707 18:30:43.337749 99468 net.cpp:198] inception_5a/output_inception_5a/output_0_split needs backward computation.
I0707 18:30:43.337755 99468 net.cpp:198] inception_5a/output needs backward computation.
I0707 18:30:43.337765 99468 net.cpp:198] inception_5a/relu_pool_proj needs backward computation.
I0707 18:30:43.337771 99468 net.cpp:198] inception_5a/pool_proj needs backward computation.
I0707 18:30:43.337782 99468 net.cpp:198] inception_5a/pool needs backward computation.
I0707 18:30:43.337790 99468 net.cpp:198] inception_5a/relu_5x5 needs backward computation.
I0707 18:30:43.337800 99468 net.cpp:198] inception_5a/5x5 needs backward computation.
I0707 18:30:43.337807 99468 net.cpp:198] inception_5a/relu_5x5_reduce needs backward computation.
I0707 18:30:43.337818 99468 net.cpp:198] inception_5a/5x5_reduce needs backward computation.
I0707 18:30:43.337824 99468 net.cpp:198] inception_5a/relu_3x3 needs backward computation.
I0707 18:30:43.337834 99468 net.cpp:198] inception_5a/3x3 needs backward computation.
I0707 18:30:43.337841 99468 net.cpp:198] inception_5a/relu_3x3_reduce needs backward computation.
I0707 18:30:43.337849 99468 net.cpp:198] inception_5a/3x3_reduce needs backward computation.
I0707 18:30:43.337855 99468 net.cpp:198] inception_5a/relu_1x1 needs backward computation.
I0707 18:30:43.337867 99468 net.cpp:198] inception_5a/1x1 needs backward computation.
I0707 18:30:43.337874 99468 net.cpp:198] pool4/3x3_s2_pool4/3x3_s2_0_split needs backward computation.
I0707 18:30:43.337880 99468 net.cpp:198] pool4/3x3_s2 needs backward computation.
I0707 18:30:43.337891 99468 net.cpp:198] inception_4e/output needs backward computation.
I0707 18:30:43.337898 99468 net.cpp:198] inception_4e/relu_pool_proj needs backward computation.
I0707 18:30:43.337905 99468 net.cpp:198] inception_4e/pool_proj needs backward computation.
I0707 18:30:43.337913 99468 net.cpp:198] inception_4e/pool needs backward computation.
I0707 18:30:43.337918 99468 net.cpp:198] inception_4e/relu_5x5 needs backward computation.
I0707 18:30:43.337926 99468 net.cpp:198] inception_4e/5x5 needs backward computation.
I0707 18:30:43.337945 99468 net.cpp:198] inception_4e/relu_5x5_reduce needs backward computation.
I0707 18:30:43.337956 99468 net.cpp:198] inception_4e/5x5_reduce needs backward computation.
I0707 18:30:43.337962 99468 net.cpp:198] inception_4e/relu_3x3 needs backward computation.
I0707 18:30:43.337968 99468 net.cpp:198] inception_4e/3x3 needs backward computation.
I0707 18:30:43.337975 99468 net.cpp:198] inception_4e/relu_3x3_reduce needs backward computation.
I0707 18:30:43.337981 99468 net.cpp:198] inception_4e/3x3_reduce needs backward computation.
I0707 18:30:43.337991 99468 net.cpp:198] inception_4e/relu_1x1 needs backward computation.
I0707 18:30:43.337999 99468 net.cpp:198] inception_4e/1x1 needs backward computation.
I0707 18:30:43.338006 99468 net.cpp:198] loss2/loss needs backward computation.
I0707 18:30:43.338013 99468 net.cpp:198] loss2/classifier_my needs backward computation.
I0707 18:30:43.338019 99468 net.cpp:198] loss2/drop_fc needs backward computation.
I0707 18:30:43.338030 99468 net.cpp:198] loss2/relu_fc needs backward computation.
I0707 18:30:43.338037 99468 net.cpp:198] loss2/fc needs backward computation.
I0707 18:30:43.338043 99468 net.cpp:198] loss2/relu_conv needs backward computation.
I0707 18:30:43.338049 99468 net.cpp:198] loss2/conv needs backward computation.
I0707 18:30:43.338057 99468 net.cpp:198] loss2/ave_pool needs backward computation.
I0707 18:30:43.338063 99468 net.cpp:198] inception_4d/output_inception_4d/output_0_split needs backward computation.
I0707 18:30:43.338071 99468 net.cpp:198] inception_4d/output needs backward computation.
I0707 18:30:43.338078 99468 net.cpp:198] inception_4d/relu_pool_proj needs backward computation.
I0707 18:30:43.338085 99468 net.cpp:198] inception_4d/pool_proj needs backward computation.
I0707 18:30:43.338094 99468 net.cpp:198] inception_4d/pool needs backward computation.
I0707 18:30:43.338102 99468 net.cpp:198] inception_4d/relu_5x5 needs backward computation.
I0707 18:30:43.338111 99468 net.cpp:198] inception_4d/5x5 needs backward computation.
I0707 18:30:43.338119 99468 net.cpp:198] inception_4d/relu_5x5_reduce needs backward computation.
I0707 18:30:43.338127 99468 net.cpp:198] inception_4d/5x5_reduce needs backward computation.
I0707 18:30:43.338135 99468 net.cpp:198] inception_4d/relu_3x3 needs backward computation.
I0707 18:30:43.338145 99468 net.cpp:198] inception_4d/3x3 needs backward computation.
I0707 18:30:43.338150 99468 net.cpp:198] inception_4d/relu_3x3_reduce needs backward computation.
I0707 18:30:43.338157 99468 net.cpp:198] inception_4d/3x3_reduce needs backward computation.
I0707 18:30:43.338167 99468 net.cpp:198] inception_4d/relu_1x1 needs backward computation.
I0707 18:30:43.338174 99468 net.cpp:198] inception_4d/1x1 needs backward computation.
I0707 18:30:43.338181 99468 net.cpp:198] inception_4c/output_inception_4c/output_0_split needs backward computation.
I0707 18:30:43.338187 99468 net.cpp:198] inception_4c/output needs backward computation.
I0707 18:30:43.338198 99468 net.cpp:198] inception_4c/relu_pool_proj needs backward computation.
I0707 18:30:43.338209 99468 net.cpp:198] inception_4c/pool_proj needs backward computation.
I0707 18:30:43.338217 99468 net.cpp:198] inception_4c/pool needs backward computation.
I0707 18:30:43.338227 99468 net.cpp:198] inception_4c/relu_5x5 needs backward computation.
I0707 18:30:43.338238 99468 net.cpp:198] inception_4c/5x5 needs backward computation.
I0707 18:30:43.338245 99468 net.cpp:198] inception_4c/relu_5x5_reduce needs backward computation.
I0707 18:30:43.338254 99468 net.cpp:198] inception_4c/5x5_reduce needs backward computation.
I0707 18:30:43.338260 99468 net.cpp:198] inception_4c/relu_3x3 needs backward computation.
I0707 18:30:43.338268 99468 net.cpp:198] inception_4c/3x3 needs backward computation.
I0707 18:30:43.338275 99468 net.cpp:198] inception_4c/relu_3x3_reduce needs backward computation.
I0707 18:30:43.338281 99468 net.cpp:198] inception_4c/3x3_reduce needs backward computation.
I0707 18:30:43.338291 99468 net.cpp:198] inception_4c/relu_1x1 needs backward computation.
I0707 18:30:43.338309 99468 net.cpp:198] inception_4c/1x1 needs backward computation.
I0707 18:30:43.338315 99468 net.cpp:198] inception_4b/output_inception_4b/output_0_split needs backward computation.
I0707 18:30:43.338325 99468 net.cpp:198] inception_4b/output needs backward computation.
I0707 18:30:43.338332 99468 net.cpp:198] inception_4b/relu_pool_proj needs backward computation.
I0707 18:30:43.338340 99468 net.cpp:198] inception_4b/pool_proj needs backward computation.
I0707 18:30:43.338349 99468 net.cpp:198] inception_4b/pool needs backward computation.
I0707 18:30:43.338356 99468 net.cpp:198] inception_4b/relu_5x5 needs backward computation.
I0707 18:30:43.338361 99468 net.cpp:198] inception_4b/5x5 needs backward computation.
I0707 18:30:43.338371 99468 net.cpp:198] inception_4b/relu_5x5_reduce needs backward computation.
I0707 18:30:43.338380 99468 net.cpp:198] inception_4b/5x5_reduce needs backward computation.
I0707 18:30:43.338387 99468 net.cpp:198] inception_4b/relu_3x3 needs backward computation.
I0707 18:30:43.338395 99468 net.cpp:198] inception_4b/3x3 needs backward computation.
I0707 18:30:43.338402 99468 net.cpp:198] inception_4b/relu_3x3_reduce needs backward computation.
I0707 18:30:43.338408 99468 net.cpp:198] inception_4b/3x3_reduce needs backward computation.
I0707 18:30:43.338418 99468 net.cpp:198] inception_4b/relu_1x1 needs backward computation.
I0707 18:30:43.338425 99468 net.cpp:198] inception_4b/1x1 needs backward computation.
I0707 18:30:43.338433 99468 net.cpp:198] loss1/loss needs backward computation.
I0707 18:30:43.338443 99468 net.cpp:198] loss1/classifier_my needs backward computation.
I0707 18:30:43.338454 99468 net.cpp:198] loss1/drop_fc needs backward computation.
I0707 18:30:43.338460 99468 net.cpp:198] loss1/relu_fc needs backward computation.
I0707 18:30:43.338466 99468 net.cpp:198] loss1/fc needs backward computation.
I0707 18:30:43.338475 99468 net.cpp:198] loss1/relu_conv needs backward computation.
I0707 18:30:43.338484 99468 net.cpp:198] loss1/conv needs backward computation.
I0707 18:30:43.338491 99468 net.cpp:198] loss1/ave_pool needs backward computation.
I0707 18:30:43.338497 99468 net.cpp:198] inception_4a/output_inception_4a/output_0_split needs backward computation.
I0707 18:30:43.338506 99468 net.cpp:198] inception_4a/output needs backward computation.
I0707 18:30:43.338516 99468 net.cpp:198] inception_4a/relu_pool_proj needs backward computation.
I0707 18:30:43.338523 99468 net.cpp:198] inception_4a/pool_proj needs backward computation.
I0707 18:30:43.338534 99468 net.cpp:198] inception_4a/pool needs backward computation.
I0707 18:30:43.338541 99468 net.cpp:198] inception_4a/relu_5x5 needs backward computation.
I0707 18:30:43.338551 99468 net.cpp:198] inception_4a/5x5 needs backward computation.
I0707 18:30:43.338563 99468 net.cpp:198] inception_4a/relu_5x5_reduce needs backward computation.
I0707 18:30:43.338569 99468 net.cpp:198] inception_4a/5x5_reduce needs backward computation.
I0707 18:30:43.338578 99468 net.cpp:198] inception_4a/relu_3x3 needs backward computation.
I0707 18:30:43.338585 99468 net.cpp:198] inception_4a/3x3 needs backward computation.
I0707 18:30:43.338595 99468 net.cpp:198] inception_4a/relu_3x3_reduce needs backward computation.
I0707 18:30:43.338604 99468 net.cpp:198] inception_4a/3x3_reduce needs backward computation.
I0707 18:30:43.338610 99468 net.cpp:198] inception_4a/relu_1x1 needs backward computation.
I0707 18:30:43.338620 99468 net.cpp:198] inception_4a/1x1 needs backward computation.
I0707 18:30:43.338627 99468 net.cpp:198] pool3/3x3_s2_pool3/3x3_s2_0_split needs backward computation.
I0707 18:30:43.338637 99468 net.cpp:198] pool3/3x3_s2 needs backward computation.
I0707 18:30:43.338644 99468 net.cpp:198] inception_3b/output needs backward computation.
I0707 18:30:43.338654 99468 net.cpp:198] inception_3b/relu_pool_proj needs backward computation.
I0707 18:30:43.338660 99468 net.cpp:198] inception_3b/pool_proj needs backward computation.
I0707 18:30:43.338671 99468 net.cpp:198] inception_3b/pool needs backward computation.
I0707 18:30:43.338690 99468 net.cpp:198] inception_3b/relu_5x5 needs backward computation.
I0707 18:30:43.338699 99468 net.cpp:198] inception_3b/5x5 needs backward computation.
I0707 18:30:43.338706 99468 net.cpp:198] inception_3b/relu_5x5_reduce needs backward computation.
I0707 18:30:43.338712 99468 net.cpp:198] inception_3b/5x5_reduce needs backward computation.
I0707 18:30:43.338721 99468 net.cpp:198] inception_3b/relu_3x3 needs backward computation.
I0707 18:30:43.338731 99468 net.cpp:198] inception_3b/3x3 needs backward computation.
I0707 18:30:43.338737 99468 net.cpp:198] inception_3b/relu_3x3_reduce needs backward computation.
I0707 18:30:43.338747 99468 net.cpp:198] inception_3b/3x3_reduce needs backward computation.
I0707 18:30:43.338753 99468 net.cpp:198] inception_3b/relu_1x1 needs backward computation.
I0707 18:30:43.338763 99468 net.cpp:198] inception_3b/1x1 needs backward computation.
I0707 18:30:43.338769 99468 net.cpp:198] inception_3a/output_inception_3a/output_0_split needs backward computation.
I0707 18:30:43.338779 99468 net.cpp:198] inception_3a/output needs backward computation.
I0707 18:30:43.338788 99468 net.cpp:198] inception_3a/relu_pool_proj needs backward computation.
I0707 18:30:43.338798 99468 net.cpp:198] inception_3a/pool_proj needs backward computation.
I0707 18:30:43.338804 99468 net.cpp:198] inception_3a/pool needs backward computation.
I0707 18:30:43.338811 99468 net.cpp:198] inception_3a/relu_5x5 needs backward computation.
I0707 18:30:43.338819 99468 net.cpp:198] inception_3a/5x5 needs backward computation.
I0707 18:30:43.338824 99468 net.cpp:198] inception_3a/relu_5x5_reduce needs backward computation.
I0707 18:30:43.338835 99468 net.cpp:198] inception_3a/5x5_reduce needs backward computation.
I0707 18:30:43.338845 99468 net.cpp:198] inception_3a/relu_3x3 needs backward computation.
I0707 18:30:43.338850 99468 net.cpp:198] inception_3a/3x3 needs backward computation.
I0707 18:30:43.338860 99468 net.cpp:198] inception_3a/relu_3x3_reduce needs backward computation.
I0707 18:30:43.338871 99468 net.cpp:198] inception_3a/3x3_reduce needs backward computation.
I0707 18:30:43.338877 99468 net.cpp:198] inception_3a/relu_1x1 needs backward computation.
I0707 18:30:43.338883 99468 net.cpp:198] inception_3a/1x1 needs backward computation.
I0707 18:30:43.338894 99468 net.cpp:198] pool2/3x3_s2_pool2/3x3_s2_0_split needs backward computation.
I0707 18:30:43.338903 99468 net.cpp:198] pool2/3x3_s2 needs backward computation.
I0707 18:30:43.338909 99468 net.cpp:198] conv2/norm2 needs backward computation.
I0707 18:30:43.338922 99468 net.cpp:198] conv2/relu_3x3 needs backward computation.
I0707 18:30:43.338930 99468 net.cpp:198] conv2/3x3 needs backward computation.
I0707 18:30:43.338940 99468 net.cpp:198] conv2/relu_3x3_reduce needs backward computation.
I0707 18:30:43.338948 99468 net.cpp:198] conv2/3x3_reduce needs backward computation.
I0707 18:30:43.338954 99468 net.cpp:198] pool1/norm1 needs backward computation.
I0707 18:30:43.338964 99468 net.cpp:198] pool1/3x3_s2 needs backward computation.
I0707 18:30:43.338977 99468 net.cpp:198] conv1/relu_7x7 needs backward computation.
I0707 18:30:43.338987 99468 net.cpp:198] conv1/7x7_s2 needs backward computation.
I0707 18:30:43.338994 99468 net.cpp:198] st_layer needs backward computation.
I0707 18:30:43.339004 99468 net.cpp:198] loc_reg needs backward computation.
I0707 18:30:43.339010 99468 net.cpp:198] loc_relu3 needs backward computation.
I0707 18:30:43.339016 99468 net.cpp:198] loc_ip1 needs backward computation.
I0707 18:30:43.339028 99468 net.cpp:198] loc_relu2 needs backward computation.
I0707 18:30:43.339037 99468 net.cpp:198] loc_pool2 needs backward computation.
I0707 18:30:43.339046 99468 net.cpp:198] loc_conv2 needs backward computation.
I0707 18:30:43.339057 99468 net.cpp:198] loc_relu1 needs backward computation.
I0707 18:30:43.339063 99468 net.cpp:198] loc_pool1 needs backward computation.
I0707 18:30:43.339073 99468 net.cpp:198] loc_conv1 needs backward computation.
I0707 18:30:43.339092 99468 net.cpp:200] label_data_1_split does not need backward computation.
I0707 18:30:43.339103 99468 net.cpp:200] data_data_0_split does not need backward computation.
I0707 18:30:43.339112 99468 net.cpp:200] data does not need backward computation.
I0707 18:30:43.339118 99468 net.cpp:242] This network produces output loss1/loss1
I0707 18:30:43.339126 99468 net.cpp:242] This network produces output loss2/loss2
I0707 18:30:43.339134 99468 net.cpp:242] This network produces output loss3/loss3
I0707 18:30:43.339258 99468 net.cpp:255] Network initialization done.
I0707 18:30:43.342805 99468 solver.cpp:172] Creating test net (#0) specified by net file: /data04/googlenet/stn_train_val.prototxt
I0707 18:30:43.343027 99468 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer data
I0707 18:30:43.344033 99468 net.cpp:51] Initializing net from parameters: 
name: "GoogleNet"
state {
  phase: TEST
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    mirror: false
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "/data04/data/img_test_lmdb"
    batch_size: 64
    backend: LMDB
  }
}
layer {
  name: "loc_conv1"
  type: "Convolution"
  bottom: "data"
  top: "loc_conv1"
  convolution_param {
    num_output: 20
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "loc_pool1"
  type: "Pooling"
  bottom: "loc_conv1"
  top: "loc_pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "loc_relu1"
  type: "ReLU"
  bottom: "loc_pool1"
  top: "loc_pool1"
}
layer {
  name: "loc_conv2"
  type: "Convolution"
  bottom: "loc_pool1"
  top: "loc_conv2"
  convolution_param {
    num_output: 20
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "loc_pool2"
  type: "Pooling"
  bottom: "loc_conv2"
  top: "loc_pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "loc_relu2"
  type: "ReLU"
  bottom: "loc_pool2"
  top: "loc_pool2"
}
layer {
  name: "loc_ip1"
  type: "InnerProduct"
  bottom: "loc_pool2"
  top: "loc_ip1"
  inner_product_param {
    num_output: 20
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "loc_relu3"
  type: "ReLU"
  bottom: "loc_ip1"
  top: "loc_ip1"
}
layer {
  name: "loc_reg"
  type: "InnerProduct"
  bottom: "loc_ip1"
  top: "theta"
  inner_product_param {
    num_output: 6
    weight_filler {
      type: "constant"
      value: 0
    }
    bias_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "st_layer"
  type: "SpatialTransformer"
  bottom: "data"
  bottom: "theta"
  top: "st_output"
}
layer {
  name: "conv1/7x7_s2"
  type: "Convolution"
  bottom: "st_output"
  top: "conv1/7x7_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 3
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/relu_7x7"
  type: "ReLU"
  bottom: "conv1/7x7_s2"
  top: "conv1/7x7_s2"
}
layer {
  name: "pool1/3x3_s2"
  type: "Pooling"
  bottom: "conv1/7x7_s2"
  top: "pool1/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "pool1/norm1"
  type: "LRN"
  bottom: "pool1/3x3_s2"
  top: "pool1/norm1"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv2/3x3_reduce"
  type: "Convolution"
  bottom: "pool1/norm1"
  top: "conv2/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_reduce"
  type: "ReLU"
  bottom: "conv2/3x3_reduce"
  top: "conv2/3x3_reduce"
}
layer {
  name: "conv2/3x3"
  type: "Convolution"
  bottom: "conv2/3x3_reduce"
  top: "conv2/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3"
  type: "ReLU"
  bottom: "conv2/3x3"
  top: "conv2/3x3"
}
layer {
  name: "conv2/norm2"
  type: "LRN"
  bottom: "conv2/3x3"
  top: "conv2/norm2"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "pool2/3x3_s2"
  type: "Pooling"
  bottom: "conv2/norm2"
  top: "pool2/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_3a/1x1"
  type: "Convolution"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_1x1"
  type: "ReLU"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
}
layer {
  name: "inception_3a/3x3_reduce"
  type: "Convolution"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_3a/3x3_reduce"
  top: "inception_3a/3x3_reduce"
}
layer {
  name: "inception_3a/3x3"
  type: "Convolution"
  bottom: "inception_3a/3x3_reduce"
  top: "inception_3a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3"
  type: "ReLU"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
}
layer {
  name: "inception_3a/5x5_reduce"
  type: "Convolution"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_3a/5x5_reduce"
  top: "inception_3a/5x5_reduce"
}
layer {
  name: "inception_3a/5x5"
  type: "Convolution"
  bottom: "inception_3a/5x5_reduce"
  top: "inception_3a/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5"
  type: "ReLU"
  bottom: "inception_3a/5x5"
  top: "inception_3a/5x5"
}
layer {
  name: "inception_3a/pool"
  type: "Pooling"
  bottom: "pool2/3x3_s2"
  top: "inception_3a/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3a/pool_proj"
  type: "Convolution"
  bottom: "inception_3a/pool"
  top: "inception_3a/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_3a/pool_proj"
  top: "inception_3a/pool_proj"
}
layer {
  name: "inception_3a/output"
  type: "Concat"
  bottom: "inception_3a/1x1"
  bottom: "inception_3a/3x3"
  bottom: "inception_3a/5x5"
  bottom: "inception_3a/pool_proj"
  top: "inception_3a/output"
}
layer {
  name: "inception_3b/1x1"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "inception_3b/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_1x1"
  type: "ReLU"
  bottom: "inception_3b/1x1"
  top: "inception_3b/1x1"
}
layer {
  name: "inception_3b/3x3_reduce"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "inception_3b/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_3b/3x3_reduce"
  top: "inception_3b/3x3_reduce"
}
layer {
  name: "inception_3b/3x3"
  type: "Convolution"
  bottom: "inception_3b/3x3_reduce"
  top: "inception_3b/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3"
  type: "ReLU"
  bottom: "inception_3b/3x3"
  top: "inception_3b/3x3"
}
layer {
  name: "inception_3b/5x5_reduce"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "inception_3b/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_3b/5x5_reduce"
  top: "inception_3b/5x5_reduce"
}
layer {
  name: "inception_3b/5x5"
  type: "Convolution"
  bottom: "inception_3b/5x5_reduce"
  top: "inception_3b/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5"
  type: "ReLU"
  bottom: "inception_3b/5x5"
  top: "inception_3b/5x5"
}
layer {
  name: "inception_3b/pool"
  type: "Pooling"
  bottom: "inception_3a/output"
  top: "inception_3b/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3b/pool_proj"
  type: "Convolution"
  bottom: "inception_3b/pool"
  top: "inception_3b/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_3b/pool_proj"
  top: "inception_3b/pool_proj"
}
layer {
  name: "inception_3b/output"
  type: "Concat"
  bottom: "inception_3b/1x1"
  bottom: "inception_3b/3x3"
  bottom: "inception_3b/5x5"
  bottom: "inception_3b/pool_proj"
  top: "inception_3b/output"
}
layer {
  name: "pool3/3x3_s2"
  type: "Pooling"
  bottom: "inception_3b/output"
  top: "pool3/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_4a/1x1"
  type: "Convolution"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_1x1"
  type: "ReLU"
  bottom: "inception_4a/1x1"
  top: "inception_4a/1x1"
}
layer {
  name: "inception_4a/3x3_reduce"
  type: "Convolution"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4a/3x3_reduce"
  top: "inception_4a/3x3_reduce"
}
layer {
  name: "inception_4a/3x3"
  type: "Convolution"
  bottom: "inception_4a/3x3_reduce"
  top: "inception_4a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 208
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3"
  type: "ReLU"
  bottom: "inception_4a/3x3"
  top: "inception_4a/3x3"
}
layer {
  name: "inception_4a/5x5_reduce"
  type: "Convolution"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4a/5x5_reduce"
  top: "inception_4a/5x5_reduce"
}
layer {
  name: "inception_4a/5x5"
  type: "Convolution"
  bottom: "inception_4a/5x5_reduce"
  top: "inception_4a/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5"
  type: "ReLU"
  bottom: "inception_4a/5x5"
  top: "inception_4a/5x5"
}
layer {
  name: "inception_4a/pool"
  type: "Pooling"
  bottom: "pool3/3x3_s2"
  top: "inception_4a/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4a/pool_proj"
  type: "Convolution"
  bottom: "inception_4a/pool"
  top: "inception_4a/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4a/pool_proj"
  top: "inception_4a/pool_proj"
}
layer {
  name: "inception_4a/output"
  type: "Concat"
  bottom: "inception_4a/1x1"
  bottom: "inception_4a/3x3"
  bottom: "inception_4a/5x5"
  bottom: "inception_4a/pool_proj"
  top: "inception_4a/output"
}
layer {
  name: "loss1/ave_pool"
  type: "Pooling"
  bottom: "inception_4a/output"
  top: "loss1/ave_pool"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss1/conv"
  type: "Convolution"
  bottom: "loss1/ave_pool"
  top: "loss1/conv"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_conv"
  type: "ReLU"
  bottom: "loss1/conv"
  top: "loss1/conv"
}
layer {
  name: "loss1/fc"
  type: "InnerProduct"
  bottom: "loss1/conv"
  top: "loss1/fc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_fc"
  type: "ReLU"
  bottom: "loss1/fc"
  top: "loss1/fc"
}
layer {
  name: "loss1/drop_fc"
  type: "Dropout"
  bottom: "loss1/fc"
  top: "loss1/fc"
  dropout_param {
    dropout_ratio: 0.7
  }
}
layer {
  name: "loss1/classifier_my"
  type: "InnerProduct"
  bottom: "loss1/fc"
  top: "loss1/classifier"
  param {
    lr_mult: 10
    decay_mult: 1
  }
  param {
    lr_mult: 20
    decay_mult: 0
  }
  inner_product_param {
    num_output: 39
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "loss1/loss"
  type: "SoftmaxWithLoss"
  bottom: "loss1/classifier"
  bottom: "label"
  top: "loss1/loss1"
  loss_weight: 0.3
}
layer {
  name: "loss1/top-1"
  type: "Accuracy"
  bottom: "loss1/classifier"
  bottom: "label"
  top: "loss1/top-1"
  include {
    phase: TEST
  }
}
layer {
  name: "loss1/top-5"
  type: "Accuracy"
  bottom: "loss1/classifier"
  bottom: "label"
  top: "loss1/top-5"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}
layer {
  name: "inception_4b/1x1"
  type: "Convolution"
  bottom: "inception_4a/output"
  top: "inception_4b/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_1x1"
  type: "ReLU"
  bottom: "inception_4b/1x1"
  top: "inception_4b/1x1"
}
layer {
  name: "inception_4b/3x3_reduce"
  type: "Convolution"
  bottom: "inception_4a/output"
  top: "inception_4b/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4b/3x3_reduce"
  top: "inception_4b/3x3_reduce"
}
layer {
  name: "inception_4b/3x3"
  type: "Convolution"
  bottom: "inception_4b/3x3_reduce"
  top: "inception_4b/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 224
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3"
  type: "ReLU"
  bottom: "inception_4b/3x3"
  top: "inception_4b/3x3"
}
layer {
  name: "inception_4b/5x5_reduce"
  type: "Convolution"
  bottom: "inception_4a/output"
  top: "inception_4b/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4b/5x5_reduce"
  top: "inception_4b/5x5_reduce"
}
layer {
  name: "inception_4b/5x5"
  type: "Convolution"
  bottom: "inception_4b/5x5_reduce"
  top: "inception_4b/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5"
  type: "ReLU"
  bottom: "inception_4b/5x5"
  top: "inception_4b/5x5"
}
layer {
  name: "inception_4b/pool"
  type: "Pooling"
  bottom: "inception_4a/output"
  top: "inception_4b/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4b/pool_proj"
  type: "Convolution"
  bottom: "inception_4b/pool"
  top: "inception_4b/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4b/pool_proj"
  top: "inception_4b/pool_proj"
}
layer {
  name: "inception_4b/output"
  type: "Concat"
  bottom: "inception_4b/1x1"
  bottom: "inception_4b/3x3"
  bottom: "inception_4b/5x5"
  bottom: "inception_4b/pool_proj"
  top: "inception_4b/output"
}
layer {
  name: "inception_4c/1x1"
  type: "Convolution"
  bottom: "inception_4b/output"
  top: "inception_4c/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_1x1"
  type: "ReLU"
  bottom: "inception_4c/1x1"
  top: "inception_4c/1x1"
}
layer {
  name: "inception_4c/3x3_reduce"
  type: "Convolution"
  bottom: "inception_4b/output"
  top: "inception_4c/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4c/3x3_reduce"
  top: "inception_4c/3x3_reduce"
}
layer {
  name: "inception_4c/3x3"
  type: "Convolution"
  bottom: "inception_4c/3x3_reduce"
  top: "inception_4c/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3"
  type: "ReLU"
  bottom: "inception_4c/3x3"
  top: "inception_4c/3x3"
}
layer {
  name: "inception_4c/5x5_reduce"
  type: "Convolution"
  bottom: "inception_4b/output"
  top: "inception_4c/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4c/5x5_reduce"
  top: "inception_4c/5x5_reduce"
}
layer {
  name: "inception_4c/5x5"
  type: "Convolution"
  bottom: "inception_4c/5x5_reduce"
  top: "inception_4c/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5"
  type: "ReLU"
  bottom: "inception_4c/5x5"
  top: "inception_4c/5x5"
}
layer {
  name: "inception_4c/pool"
  type: "Pooling"
  bottom: "inception_4b/output"
  top: "inception_4c/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4c/pool_proj"
  type: "Convolution"
  bottom: "inception_4c/pool"
  top: "inception_4c/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4c/pool_proj"
  top: "inception_4c/pool_proj"
}
layer {
  name: "inception_4c/output"
  type: "Concat"
  bottom: "inception_4c/1x1"
  bottom: "inception_4c/3x3"
  bottom: "inception_4c/5x5"
  bottom: "inception_4c/pool_proj"
  top: "inception_4c/output"
}
layer {
  name: "inception_4d/1x1"
  type: "Convolution"
  bottom: "inception_4c/output"
  top: "inception_4d/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_1x1"
  type: "ReLU"
  bottom: "inception_4d/1x1"
  top: "inception_4d/1x1"
}
layer {
  name: "inception_4d/3x3_reduce"
  type: "Convolution"
  bottom: "inception_4c/output"
  top: "inception_4d/3x3_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 144
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_reduce"
  type: "ReLU"
  bottom: "inception_4d/3x3_reduce"
  top: "inception_4d/3x3_reduce"
}
layer {
  name: "inception_4d/3x3"
  type: "Convolution"
  bottom: "inception_4d/3x3_reduce"
  top: "inception_4d/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 288
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3"
  type: "ReLU"
  bottom: "inception_4d/3x3"
  top: "inception_4d/3x3"
}
layer {
  name: "inception_4d/5x5_reduce"
  type: "Convolution"
  bottom: "inception_4c/output"
  top: "inception_4d/5x5_reduce"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_reduce"
  type: "ReLU"
  bottom: "inception_4d/5x5_reduce"
  top: "inception_4d/5x5_reduce"
}
layer {
  name: "inception_4d/5x5"
  type: "Convolution"
  bottom: "inception_4d/5x5_reduce"
  top: "inception_4d/5x5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5"
  type: "ReLU"
  bottom: "inception_4d/5x5"
  top: "inception_4d/5x5"
}
layer {
  name: "inception_4d/pool"
  type: "Pooling"
  bottom: "inception_4c/output"
  top: "inception_4d/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4d/pool_proj"
  type: "Convolution"
  bottom: "inception_4d/pool"
  top: "inception_4d/pool_proj"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_pool_proj"
  type: "ReLU"
  bottom: "inception_4d/pool_proj"
  top: "inception_4d/pool_proj"
}
layer {
  name: "inception_4d/output"
  type: "Concat"
  bottom: "inception_4d/1x1"
  bottom: "inception_4d/3x3"
  bottom: "inception_4d/5x5"
  bottom: "inception_4d/pool_proj"
  top: "inception_4d/output"
}
layer {
  name: "loss2/ave_pool"
  type: "Pooling"
  bottom: "inception_4d/output"
  top: "loss2/ave_pool"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss2/conv"
  type: "Convolution"
  bottom: "loss2/ave_pool"
  top: "loss2/conv"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_conv"
  type: "ReLU"
  bottom: "loss2/conv"
  top: "loss2/conv"
}
layer {
  name: "loss2/fc"
  type: "InnerProduct"
  bottom: "loss2/conv"
  top: "loss2/fc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_fc"
  type: "ReLU"
  bottom: "loss2/fc"
  top: "loss2/fc"
}
layer {
  name: "loss2/drop_fc"
  type: "Dropout"
  bottom: "loss2/fc"
  top: "loss2/fc"
  dropout_param {
    dropout_ratio: 0.7
  }
}
layer {
  name: "loss2/classifier_my"
  type: "InnerProduct"
  bottom: "loss2/fc"
  top: "loss2/classifier"
  param {
    lr_mult: 10
    decay_mult: 1
  }
  param {
    lr_mult: 20
    decay_mult: 0
  }
  inner_product_param {
    num_output: 39
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "loss2/loss"
  type: "SoftmaxWithLoss"
  bottom: "loss2/classifier"
  bottom: "label"
  top: "loss2/loss2"
  loss_weight: 0.3
}
layer {
  name: "loss2/top-1"
  type: "Accuracy"
  bottom: "loss2/classifier"
  bottom: "label"
  top: "loss2/top-1"
  include {
    phase: TEST
  }
}
layer {
  name: "loss2/top-5"
  type: "Accuracy"
  bottom: "loss2/classifier"
  bottom: "label"
  top: "loss2/top-5"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}
layer {
  name: "inception_4e/1x1"
  type: "Convolution"
  bottom: "inception_4d/output"
  top: "inception_4e/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/r
I0707 18:30:43.351438 99468 layer_factory.hpp:77] Creating layer data
I0707 18:30:43.351547 99468 db_lmdb.cpp:35] Opened lmdb /data04/data/img_test_lmdb
I0707 18:30:43.351589 99468 net.cpp:84] Creating Layer data
I0707 18:30:43.351603 99468 net.cpp:380] data -> data
I0707 18:30:43.351619 99468 net.cpp:380] data -> label
I0707 18:30:43.352036 99468 data_layer.cpp:45] output data size: 64,3,224,224
I0707 18:30:43.459412 99468 net.cpp:122] Setting up data
I0707 18:30:43.459493 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:43.459506 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.459512 99468 net.cpp:137] Memory required for data: 38535424
I0707 18:30:43.459527 99468 layer_factory.hpp:77] Creating layer data_data_0_split
I0707 18:30:43.459550 99468 net.cpp:84] Creating Layer data_data_0_split
I0707 18:30:43.459568 99468 net.cpp:406] data_data_0_split <- data
I0707 18:30:43.459581 99468 net.cpp:380] data_data_0_split -> data_data_0_split_0
I0707 18:30:43.459632 99468 net.cpp:380] data_data_0_split -> data_data_0_split_1
I0707 18:30:43.459789 99468 net.cpp:122] Setting up data_data_0_split
I0707 18:30:43.459805 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:43.459815 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:43.459839 99468 net.cpp:137] Memory required for data: 115605760
I0707 18:30:43.459848 99468 layer_factory.hpp:77] Creating layer label_data_1_split
I0707 18:30:43.459861 99468 net.cpp:84] Creating Layer label_data_1_split
I0707 18:30:43.459869 99468 net.cpp:406] label_data_1_split <- label
I0707 18:30:43.459879 99468 net.cpp:380] label_data_1_split -> label_data_1_split_0
I0707 18:30:43.459893 99468 net.cpp:380] label_data_1_split -> label_data_1_split_1
I0707 18:30:43.459904 99468 net.cpp:380] label_data_1_split -> label_data_1_split_2
I0707 18:30:43.459915 99468 net.cpp:380] label_data_1_split -> label_data_1_split_3
I0707 18:30:43.459975 99468 net.cpp:380] label_data_1_split -> label_data_1_split_4
I0707 18:30:43.460003 99468 net.cpp:380] label_data_1_split -> label_data_1_split_5
I0707 18:30:43.460029 99468 net.cpp:380] label_data_1_split -> label_data_1_split_6
I0707 18:30:43.460041 99468 net.cpp:380] label_data_1_split -> label_data_1_split_7
I0707 18:30:43.460052 99468 net.cpp:380] label_data_1_split -> label_data_1_split_8
I0707 18:30:43.460239 99468 net.cpp:122] Setting up label_data_1_split
I0707 18:30:43.460253 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460265 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460273 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460279 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460290 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460297 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460307 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460314 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460319 99468 net.cpp:129] Top shape: 64 (64)
I0707 18:30:43.460331 99468 net.cpp:137] Memory required for data: 115608064
I0707 18:30:43.460338 99468 layer_factory.hpp:77] Creating layer loc_conv1
I0707 18:30:43.460358 99468 net.cpp:84] Creating Layer loc_conv1
I0707 18:30:43.460366 99468 net.cpp:406] loc_conv1 <- data_data_0_split_0
I0707 18:30:43.460381 99468 net.cpp:380] loc_conv1 -> loc_conv1
I0707 18:30:43.462853 99468 net.cpp:122] Setting up loc_conv1
I0707 18:30:43.462878 99468 net.cpp:129] Top shape: 64 20 220 220 (61952000)
I0707 18:30:43.462889 99468 net.cpp:137] Memory required for data: 363416064
I0707 18:30:43.462910 99468 layer_factory.hpp:77] Creating layer loc_pool1
I0707 18:30:43.462952 99468 net.cpp:84] Creating Layer loc_pool1
I0707 18:30:43.462960 99468 net.cpp:406] loc_pool1 <- loc_conv1
I0707 18:30:43.462975 99468 net.cpp:380] loc_pool1 -> loc_pool1
I0707 18:30:43.463044 99468 net.cpp:122] Setting up loc_pool1
I0707 18:30:43.463059 99468 net.cpp:129] Top shape: 64 20 110 110 (15488000)
I0707 18:30:43.463069 99468 net.cpp:137] Memory required for data: 425368064
I0707 18:30:43.463079 99468 layer_factory.hpp:77] Creating layer loc_relu1
I0707 18:30:43.463095 99468 net.cpp:84] Creating Layer loc_relu1
I0707 18:30:43.463109 99468 net.cpp:406] loc_relu1 <- loc_pool1
I0707 18:30:43.463121 99468 net.cpp:367] loc_relu1 -> loc_pool1 (in-place)
I0707 18:30:43.469543 99468 net.cpp:122] Setting up loc_relu1
I0707 18:30:43.469570 99468 net.cpp:129] Top shape: 64 20 110 110 (15488000)
I0707 18:30:43.469601 99468 net.cpp:137] Memory required for data: 487320064
I0707 18:30:43.469611 99468 layer_factory.hpp:77] Creating layer loc_conv2
I0707 18:30:43.469642 99468 net.cpp:84] Creating Layer loc_conv2
I0707 18:30:43.469651 99468 net.cpp:406] loc_conv2 <- loc_pool1
I0707 18:30:43.469666 99468 net.cpp:380] loc_conv2 -> loc_conv2
I0707 18:30:43.471253 99468 net.cpp:122] Setting up loc_conv2
I0707 18:30:43.471276 99468 net.cpp:129] Top shape: 64 20 106 106 (14382080)
I0707 18:30:43.471310 99468 net.cpp:137] Memory required for data: 544848384
I0707 18:30:43.471326 99468 layer_factory.hpp:77] Creating layer loc_pool2
I0707 18:30:43.471357 99468 net.cpp:84] Creating Layer loc_pool2
I0707 18:30:43.471382 99468 net.cpp:406] loc_pool2 <- loc_conv2
I0707 18:30:43.471395 99468 net.cpp:380] loc_pool2 -> loc_pool2
I0707 18:30:43.471473 99468 net.cpp:122] Setting up loc_pool2
I0707 18:30:43.471490 99468 net.cpp:129] Top shape: 64 20 53 53 (3595520)
I0707 18:30:43.471500 99468 net.cpp:137] Memory required for data: 559230464
I0707 18:30:43.471510 99468 layer_factory.hpp:77] Creating layer loc_relu2
I0707 18:30:43.471520 99468 net.cpp:84] Creating Layer loc_relu2
I0707 18:30:43.471529 99468 net.cpp:406] loc_relu2 <- loc_pool2
I0707 18:30:43.471542 99468 net.cpp:367] loc_relu2 -> loc_pool2 (in-place)
I0707 18:30:43.472242 99468 net.cpp:122] Setting up loc_relu2
I0707 18:30:43.472262 99468 net.cpp:129] Top shape: 64 20 53 53 (3595520)
I0707 18:30:43.472270 99468 net.cpp:137] Memory required for data: 573612544
I0707 18:30:43.472276 99468 layer_factory.hpp:77] Creating layer loc_ip1
I0707 18:30:43.472304 99468 net.cpp:84] Creating Layer loc_ip1
I0707 18:30:43.472317 99468 net.cpp:406] loc_ip1 <- loc_pool2
I0707 18:30:43.472328 99468 net.cpp:380] loc_ip1 -> loc_ip1
I0707 18:30:43.480590 99468 net.cpp:122] Setting up loc_ip1
I0707 18:30:43.480612 99468 net.cpp:129] Top shape: 64 20 (1280)
I0707 18:30:43.480618 99468 net.cpp:137] Memory required for data: 573617664
I0707 18:30:43.480629 99468 layer_factory.hpp:77] Creating layer loc_relu3
I0707 18:30:43.480639 99468 net.cpp:84] Creating Layer loc_relu3
I0707 18:30:43.480648 99468 net.cpp:406] loc_relu3 <- loc_ip1
I0707 18:30:43.480659 99468 net.cpp:367] loc_relu3 -> loc_ip1 (in-place)
I0707 18:30:43.480867 99468 net.cpp:122] Setting up loc_relu3
I0707 18:30:43.480883 99468 net.cpp:129] Top shape: 64 20 (1280)
I0707 18:30:43.480895 99468 net.cpp:137] Memory required for data: 573622784
I0707 18:30:43.480928 99468 layer_factory.hpp:77] Creating layer loc_reg
I0707 18:30:43.480940 99468 net.cpp:84] Creating Layer loc_reg
I0707 18:30:43.480947 99468 net.cpp:406] loc_reg <- loc_ip1
I0707 18:30:43.480973 99468 net.cpp:380] loc_reg -> theta
I0707 18:30:43.481142 99468 net.cpp:122] Setting up loc_reg
I0707 18:30:43.481158 99468 net.cpp:129] Top shape: 64 6 (384)
I0707 18:30:43.481168 99468 net.cpp:137] Memory required for data: 573624320
I0707 18:30:43.481191 99468 layer_factory.hpp:77] Creating layer st_layer
I0707 18:30:43.481207 99468 net.cpp:84] Creating Layer st_layer
I0707 18:30:43.481217 99468 net.cpp:406] st_layer <- data_data_0_split_1
I0707 18:30:43.481242 99468 net.cpp:406] st_layer <- theta
I0707 18:30:43.481251 99468 net.cpp:380] st_layer -> st_output
I0707 18:30:43.483078 99468 net.cpp:122] Setting up st_layer
I0707 18:30:43.483095 99468 net.cpp:129] Top shape: 64 3 224 224 (9633792)
I0707 18:30:43.483106 99468 net.cpp:137] Memory required for data: 612159488
I0707 18:30:43.483119 99468 layer_factory.hpp:77] Creating layer conv1/7x7_s2
I0707 18:30:43.483134 99468 net.cpp:84] Creating Layer conv1/7x7_s2
I0707 18:30:43.483142 99468 net.cpp:406] conv1/7x7_s2 <- st_output
I0707 18:30:43.483157 99468 net.cpp:380] conv1/7x7_s2 -> conv1/7x7_s2
I0707 18:30:43.487196 99468 net.cpp:122] Setting up conv1/7x7_s2
I0707 18:30:43.487268 99468 net.cpp:129] Top shape: 64 64 112 112 (51380224)
I0707 18:30:43.487287 99468 net.cpp:137] Memory required for data: 817680384
I0707 18:30:43.487327 99468 layer_factory.hpp:77] Creating layer conv1/relu_7x7
I0707 18:30:43.487360 99468 net.cpp:84] Creating Layer conv1/relu_7x7
I0707 18:30:43.487380 99468 net.cpp:406] conv1/relu_7x7 <- conv1/7x7_s2
I0707 18:30:43.487409 99468 net.cpp:367] conv1/relu_7x7 -> conv1/7x7_s2 (in-place)
I0707 18:30:43.489172 99468 net.cpp:122] Setting up conv1/relu_7x7
I0707 18:30:43.489214 99468 net.cpp:129] Top shape: 64 64 112 112 (51380224)
I0707 18:30:43.489229 99468 net.cpp:137] Memory required for data: 1023201280
I0707 18:30:43.489245 99468 layer_factory.hpp:77] Creating layer pool1/3x3_s2
I0707 18:30:43.489303 99468 net.cpp:84] Creating Layer pool1/3x3_s2
I0707 18:30:43.489321 99468 net.cpp:406] pool1/3x3_s2 <- conv1/7x7_s2
I0707 18:30:43.489342 99468 net.cpp:380] pool1/3x3_s2 -> pool1/3x3_s2
I0707 18:30:43.489509 99468 net.cpp:122] Setting up pool1/3x3_s2
I0707 18:30:43.489537 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.489562 99468 net.cpp:137] Memory required for data: 1074581504
I0707 18:30:43.489598 99468 layer_factory.hpp:77] Creating layer pool1/norm1
I0707 18:30:43.489641 99468 net.cpp:84] Creating Layer pool1/norm1
I0707 18:30:43.489660 99468 net.cpp:406] pool1/norm1 <- pool1/3x3_s2
I0707 18:30:43.489686 99468 net.cpp:380] pool1/norm1 -> pool1/norm1
I0707 18:30:43.490202 99468 net.cpp:122] Setting up pool1/norm1
I0707 18:30:43.490233 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.490248 99468 net.cpp:137] Memory required for data: 1125961728
I0707 18:30:43.490262 99468 layer_factory.hpp:77] Creating layer conv2/3x3_reduce
I0707 18:30:43.490300 99468 net.cpp:84] Creating Layer conv2/3x3_reduce
I0707 18:30:43.490319 99468 net.cpp:406] conv2/3x3_reduce <- pool1/norm1
I0707 18:30:43.490408 99468 net.cpp:380] conv2/3x3_reduce -> conv2/3x3_reduce
I0707 18:30:43.494658 99468 net.cpp:122] Setting up conv2/3x3_reduce
I0707 18:30:43.494702 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.494750 99468 net.cpp:137] Memory required for data: 1177341952
I0707 18:30:43.494776 99468 layer_factory.hpp:77] Creating layer conv2/relu_3x3_reduce
I0707 18:30:43.494817 99468 net.cpp:84] Creating Layer conv2/relu_3x3_reduce
I0707 18:30:43.494850 99468 net.cpp:406] conv2/relu_3x3_reduce <- conv2/3x3_reduce
I0707 18:30:43.494873 99468 net.cpp:367] conv2/relu_3x3_reduce -> conv2/3x3_reduce (in-place)
I0707 18:30:43.496358 99468 net.cpp:122] Setting up conv2/relu_3x3_reduce
I0707 18:30:43.496398 99468 net.cpp:129] Top shape: 64 64 56 56 (12845056)
I0707 18:30:43.496413 99468 net.cpp:137] Memory required for data: 1228722176
I0707 18:30:43.496428 99468 layer_factory.hpp:77] Creating layer conv2/3x3
I0707 18:30:43.496493 99468 net.cpp:84] Creating Layer conv2/3x3
I0707 18:30:43.496512 99468 net.cpp:406] conv2/3x3 <- conv2/3x3_reduce
I0707 18:30:43.496567 99468 net.cpp:380] conv2/3x3 -> conv2/3x3
I0707 18:30:43.501161 99468 net.cpp:122] Setting up conv2/3x3
I0707 18:30:43.501209 99468 net.cpp:129] Top shape: 64 192 56 56 (38535168)
I0707 18:30:43.501251 99468 net.cpp:137] Memory required for data: 1382862848
I0707 18:30:43.501289 99468 layer_factory.hpp:77] Creating layer conv2/relu_3x3
I0707 18:30:43.501327 99468 net.cpp:84] Creating Layer conv2/relu_3x3
I0707 18:30:43.501361 99468 net.cpp:406] conv2/relu_3x3 <- conv2/3x3
I0707 18:30:43.501399 99468 net.cpp:367] conv2/relu_3x3 -> conv2/3x3 (in-place)
I0707 18:30:43.502904 99468 net.cpp:122] Setting up conv2/relu_3x3
I0707 18:30:43.502943 99468 net.cpp:129] Top shape: 64 192 56 56 (38535168)
I0707 18:30:43.502959 99468 net.cpp:137] Memory required for data: 1537003520
I0707 18:30:43.502974 99468 layer_factory.hpp:77] Creating layer conv2/norm2
I0707 18:30:43.503028 99468 net.cpp:84] Creating Layer conv2/norm2
I0707 18:30:43.503051 99468 net.cpp:406] conv2/norm2 <- conv2/3x3
I0707 18:30:43.503078 99468 net.cpp:380] conv2/norm2 -> conv2/norm2
I0707 18:30:43.503599 99468 net.cpp:122] Setting up conv2/norm2
I0707 18:30:43.503631 99468 net.cpp:129] Top shape: 64 192 56 56 (38535168)
I0707 18:30:43.503645 99468 net.cpp:137] Memory required for data: 1691144192
I0707 18:30:43.503660 99468 layer_factory.hpp:77] Creating layer pool2/3x3_s2
I0707 18:30:43.503686 99468 net.cpp:84] Creating Layer pool2/3x3_s2
I0707 18:30:43.503702 99468 net.cpp:406] pool2/3x3_s2 <- conv2/norm2
I0707 18:30:43.503727 99468 net.cpp:380] pool2/3x3_s2 -> pool2/3x3_s2
I0707 18:30:43.503852 99468 net.cpp:122] Setting up pool2/3x3_s2
I0707 18:30:43.503877 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.503893 99468 net.cpp:137] Memory required for data: 1729679360
I0707 18:30:43.503911 99468 layer_factory.hpp:77] Creating layer pool2/3x3_s2_pool2/3x3_s2_0_split
I0707 18:30:43.503942 99468 net.cpp:84] Creating Layer pool2/3x3_s2_pool2/3x3_s2_0_split
I0707 18:30:43.503962 99468 net.cpp:406] pool2/3x3_s2_pool2/3x3_s2_0_split <- pool2/3x3_s2
I0707 18:30:43.503984 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_0
I0707 18:30:43.504007 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_1
I0707 18:30:43.504034 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_2
I0707 18:30:43.504060 99468 net.cpp:380] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_3
I0707 18:30:43.504258 99468 net.cpp:122] Setting up pool2/3x3_s2_pool2/3x3_s2_0_split
I0707 18:30:43.504283 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.504300 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.504319 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.504340 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.504357 99468 net.cpp:137] Memory required for data: 1883820032
I0707 18:30:43.504402 99468 layer_factory.hpp:77] Creating layer inception_3a/1x1
I0707 18:30:43.504434 99468 net.cpp:84] Creating Layer inception_3a/1x1
I0707 18:30:43.504456 99468 net.cpp:406] inception_3a/1x1 <- pool2/3x3_s2_pool2/3x3_s2_0_split_0
I0707 18:30:43.504485 99468 net.cpp:380] inception_3a/1x1 -> inception_3a/1x1
I0707 18:30:43.508779 99468 net.cpp:122] Setting up inception_3a/1x1
I0707 18:30:43.508826 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.508869 99468 net.cpp:137] Memory required for data: 1896665088
I0707 18:30:43.508910 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_1x1
I0707 18:30:43.508936 99468 net.cpp:84] Creating Layer inception_3a/relu_1x1
I0707 18:30:43.508955 99468 net.cpp:406] inception_3a/relu_1x1 <- inception_3a/1x1
I0707 18:30:43.508980 99468 net.cpp:367] inception_3a/relu_1x1 -> inception_3a/1x1 (in-place)
I0707 18:30:43.511523 99468 net.cpp:122] Setting up inception_3a/relu_1x1
I0707 18:30:43.511596 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.511618 99468 net.cpp:137] Memory required for data: 1909510144
I0707 18:30:43.511639 99468 layer_factory.hpp:77] Creating layer inception_3a/3x3_reduce
I0707 18:30:43.511672 99468 net.cpp:84] Creating Layer inception_3a/3x3_reduce
I0707 18:30:43.511693 99468 net.cpp:406] inception_3a/3x3_reduce <- pool2/3x3_s2_pool2/3x3_s2_0_split_1
I0707 18:30:43.511719 99468 net.cpp:380] inception_3a/3x3_reduce -> inception_3a/3x3_reduce
I0707 18:30:43.516217 99468 net.cpp:122] Setting up inception_3a/3x3_reduce
I0707 18:30:43.516263 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.516306 99468 net.cpp:137] Memory required for data: 1928777728
I0707 18:30:43.516356 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_3x3_reduce
I0707 18:30:43.516391 99468 net.cpp:84] Creating Layer inception_3a/relu_3x3_reduce
I0707 18:30:43.516424 99468 net.cpp:406] inception_3a/relu_3x3_reduce <- inception_3a/3x3_reduce
I0707 18:30:43.516453 99468 net.cpp:367] inception_3a/relu_3x3_reduce -> inception_3a/3x3_reduce (in-place)
I0707 18:30:43.516892 99468 net.cpp:122] Setting up inception_3a/relu_3x3_reduce
I0707 18:30:43.516924 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.516942 99468 net.cpp:137] Memory required for data: 1948045312
I0707 18:30:43.516961 99468 layer_factory.hpp:77] Creating layer inception_3a/3x3
I0707 18:30:43.517004 99468 net.cpp:84] Creating Layer inception_3a/3x3
I0707 18:30:43.517024 99468 net.cpp:406] inception_3a/3x3 <- inception_3a/3x3_reduce
I0707 18:30:43.517057 99468 net.cpp:380] inception_3a/3x3 -> inception_3a/3x3
I0707 18:30:43.523749 99468 net.cpp:122] Setting up inception_3a/3x3
I0707 18:30:43.523794 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.523839 99468 net.cpp:137] Memory required for data: 1973735424
I0707 18:30:43.523880 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_3x3
I0707 18:30:43.523924 99468 net.cpp:84] Creating Layer inception_3a/relu_3x3
I0707 18:30:43.523943 99468 net.cpp:406] inception_3a/relu_3x3 <- inception_3a/3x3
I0707 18:30:43.523980 99468 net.cpp:367] inception_3a/relu_3x3 -> inception_3a/3x3 (in-place)
I0707 18:30:43.524410 99468 net.cpp:122] Setting up inception_3a/relu_3x3
I0707 18:30:43.524441 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.524457 99468 net.cpp:137] Memory required for data: 1999425536
I0707 18:30:43.524488 99468 layer_factory.hpp:77] Creating layer inception_3a/5x5_reduce
I0707 18:30:43.524523 99468 net.cpp:84] Creating Layer inception_3a/5x5_reduce
I0707 18:30:43.524566 99468 net.cpp:406] inception_3a/5x5_reduce <- pool2/3x3_s2_pool2/3x3_s2_0_split_2
I0707 18:30:43.524593 99468 net.cpp:380] inception_3a/5x5_reduce -> inception_3a/5x5_reduce
I0707 18:30:43.528831 99468 net.cpp:122] Setting up inception_3a/5x5_reduce
I0707 18:30:43.528884 99468 net.cpp:129] Top shape: 64 16 28 28 (802816)
I0707 18:30:43.528934 99468 net.cpp:137] Memory required for data: 2002636800
I0707 18:30:43.528959 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_5x5_reduce
I0707 18:30:43.529012 99468 net.cpp:84] Creating Layer inception_3a/relu_5x5_reduce
I0707 18:30:43.529047 99468 net.cpp:406] inception_3a/relu_5x5_reduce <- inception_3a/5x5_reduce
I0707 18:30:43.529086 99468 net.cpp:367] inception_3a/relu_5x5_reduce -> inception_3a/5x5_reduce (in-place)
I0707 18:30:43.530603 99468 net.cpp:122] Setting up inception_3a/relu_5x5_reduce
I0707 18:30:43.530643 99468 net.cpp:129] Top shape: 64 16 28 28 (802816)
I0707 18:30:43.530658 99468 net.cpp:137] Memory required for data: 2005848064
I0707 18:30:43.530674 99468 layer_factory.hpp:77] Creating layer inception_3a/5x5
I0707 18:30:43.530745 99468 net.cpp:84] Creating Layer inception_3a/5x5
I0707 18:30:43.530763 99468 net.cpp:406] inception_3a/5x5 <- inception_3a/5x5_reduce
I0707 18:30:43.530807 99468 net.cpp:380] inception_3a/5x5 -> inception_3a/5x5
I0707 18:30:43.535147 99468 net.cpp:122] Setting up inception_3a/5x5
I0707 18:30:43.535192 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.535231 99468 net.cpp:137] Memory required for data: 2012270592
I0707 18:30:43.535259 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_5x5
I0707 18:30:43.535300 99468 net.cpp:84] Creating Layer inception_3a/relu_5x5
I0707 18:30:43.535331 99468 net.cpp:406] inception_3a/relu_5x5 <- inception_3a/5x5
I0707 18:30:43.535351 99468 net.cpp:367] inception_3a/relu_5x5 -> inception_3a/5x5 (in-place)
I0707 18:30:43.535814 99468 net.cpp:122] Setting up inception_3a/relu_5x5
I0707 18:30:43.535851 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.535866 99468 net.cpp:137] Memory required for data: 2018693120
I0707 18:30:43.535882 99468 layer_factory.hpp:77] Creating layer inception_3a/pool
I0707 18:30:43.535904 99468 net.cpp:84] Creating Layer inception_3a/pool
I0707 18:30:43.535922 99468 net.cpp:406] inception_3a/pool <- pool2/3x3_s2_pool2/3x3_s2_0_split_3
I0707 18:30:43.535971 99468 net.cpp:380] inception_3a/pool -> inception_3a/pool
I0707 18:30:43.536113 99468 net.cpp:122] Setting up inception_3a/pool
I0707 18:30:43.536139 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.536155 99468 net.cpp:137] Memory required for data: 2057228288
I0707 18:30:43.536170 99468 layer_factory.hpp:77] Creating layer inception_3a/pool_proj
I0707 18:30:43.536206 99468 net.cpp:84] Creating Layer inception_3a/pool_proj
I0707 18:30:43.536229 99468 net.cpp:406] inception_3a/pool_proj <- inception_3a/pool
I0707 18:30:43.536254 99468 net.cpp:380] inception_3a/pool_proj -> inception_3a/pool_proj
I0707 18:30:43.540518 99468 net.cpp:122] Setting up inception_3a/pool_proj
I0707 18:30:43.540568 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.540586 99468 net.cpp:137] Memory required for data: 2063650816
I0707 18:30:43.540637 99468 layer_factory.hpp:77] Creating layer inception_3a/relu_pool_proj
I0707 18:30:43.540679 99468 net.cpp:84] Creating Layer inception_3a/relu_pool_proj
I0707 18:30:43.540714 99468 net.cpp:406] inception_3a/relu_pool_proj <- inception_3a/pool_proj
I0707 18:30:43.540750 99468 net.cpp:367] inception_3a/relu_pool_proj -> inception_3a/pool_proj (in-place)
I0707 18:30:43.541184 99468 net.cpp:122] Setting up inception_3a/relu_pool_proj
I0707 18:30:43.541215 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.541232 99468 net.cpp:137] Memory required for data: 2070073344
I0707 18:30:43.541250 99468 layer_factory.hpp:77] Creating layer inception_3a/output
I0707 18:30:43.541281 99468 net.cpp:84] Creating Layer inception_3a/output
I0707 18:30:43.541303 99468 net.cpp:406] inception_3a/output <- inception_3a/1x1
I0707 18:30:43.541326 99468 net.cpp:406] inception_3a/output <- inception_3a/3x3
I0707 18:30:43.541350 99468 net.cpp:406] inception_3a/output <- inception_3a/5x5
I0707 18:30:43.541371 99468 net.cpp:406] inception_3a/output <- inception_3a/pool_proj
I0707 18:30:43.541393 99468 net.cpp:380] inception_3a/output -> inception_3a/output
I0707 18:30:43.541491 99468 net.cpp:122] Setting up inception_3a/output
I0707 18:30:43.541515 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.541576 99468 net.cpp:137] Memory required for data: 2121453568
I0707 18:30:43.541592 99468 layer_factory.hpp:77] Creating layer inception_3a/output_inception_3a/output_0_split
I0707 18:30:43.541616 99468 net.cpp:84] Creating Layer inception_3a/output_inception_3a/output_0_split
I0707 18:30:43.541637 99468 net.cpp:406] inception_3a/output_inception_3a/output_0_split <- inception_3a/output
I0707 18:30:43.541666 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_0
I0707 18:30:43.541695 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_1
I0707 18:30:43.541723 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_2
I0707 18:30:43.541750 99468 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_3
I0707 18:30:43.541956 99468 net.cpp:122] Setting up inception_3a/output_inception_3a/output_0_split
I0707 18:30:43.541981 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.542003 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.542021 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.542039 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.542057 99468 net.cpp:137] Memory required for data: 2326974464
I0707 18:30:43.542075 99468 layer_factory.hpp:77] Creating layer inception_3b/1x1
I0707 18:30:43.542111 99468 net.cpp:84] Creating Layer inception_3b/1x1
I0707 18:30:43.542131 99468 net.cpp:406] inception_3b/1x1 <- inception_3a/output_inception_3a/output_0_split_0
I0707 18:30:43.542157 99468 net.cpp:380] inception_3b/1x1 -> inception_3b/1x1
I0707 18:30:43.546809 99468 net.cpp:122] Setting up inception_3b/1x1
I0707 18:30:43.546875 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.546893 99468 net.cpp:137] Memory required for data: 2352664576
I0707 18:30:43.546917 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_1x1
I0707 18:30:43.546959 99468 net.cpp:84] Creating Layer inception_3b/relu_1x1
I0707 18:30:43.546979 99468 net.cpp:406] inception_3b/relu_1x1 <- inception_3b/1x1
I0707 18:30:43.547004 99468 net.cpp:367] inception_3b/relu_1x1 -> inception_3b/1x1 (in-place)
I0707 18:30:43.548962 99468 net.cpp:122] Setting up inception_3b/relu_1x1
I0707 18:30:43.549003 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.549018 99468 net.cpp:137] Memory required for data: 2378354688
I0707 18:30:43.549034 99468 layer_factory.hpp:77] Creating layer inception_3b/3x3_reduce
I0707 18:30:43.549067 99468 net.cpp:84] Creating Layer inception_3b/3x3_reduce
I0707 18:30:43.549085 99468 net.cpp:406] inception_3b/3x3_reduce <- inception_3a/output_inception_3a/output_0_split_1
I0707 18:30:43.549140 99468 net.cpp:380] inception_3b/3x3_reduce -> inception_3b/3x3_reduce
I0707 18:30:43.554899 99468 net.cpp:122] Setting up inception_3b/3x3_reduce
I0707 18:30:43.554944 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.554960 99468 net.cpp:137] Memory required for data: 2404044800
I0707 18:30:43.554982 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_3x3_reduce
I0707 18:30:43.555004 99468 net.cpp:84] Creating Layer inception_3b/relu_3x3_reduce
I0707 18:30:43.555022 99468 net.cpp:406] inception_3b/relu_3x3_reduce <- inception_3b/3x3_reduce
I0707 18:30:43.555076 99468 net.cpp:367] inception_3b/relu_3x3_reduce -> inception_3b/3x3_reduce (in-place)
I0707 18:30:43.555529 99468 net.cpp:122] Setting up inception_3b/relu_3x3_reduce
I0707 18:30:43.555568 99468 net.cpp:129] Top shape: 64 128 28 28 (6422528)
I0707 18:30:43.555583 99468 net.cpp:137] Memory required for data: 2429734912
I0707 18:30:43.555598 99468 layer_factory.hpp:77] Creating layer inception_3b/3x3
I0707 18:30:43.555660 99468 net.cpp:84] Creating Layer inception_3b/3x3
I0707 18:30:43.555677 99468 net.cpp:406] inception_3b/3x3 <- inception_3b/3x3_reduce
I0707 18:30:43.555708 99468 net.cpp:380] inception_3b/3x3 -> inception_3b/3x3
I0707 18:30:43.571279 99468 net.cpp:122] Setting up inception_3b/3x3
I0707 18:30:43.571331 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.571346 99468 net.cpp:137] Memory required for data: 2468270080
I0707 18:30:43.571408 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_3x3
I0707 18:30:43.571435 99468 net.cpp:84] Creating Layer inception_3b/relu_3x3
I0707 18:30:43.571455 99468 net.cpp:406] inception_3b/relu_3x3 <- inception_3b/3x3
I0707 18:30:43.571477 99468 net.cpp:367] inception_3b/relu_3x3 -> inception_3b/3x3 (in-place)
I0707 18:30:43.573029 99468 net.cpp:122] Setting up inception_3b/relu_3x3
I0707 18:30:43.573070 99468 net.cpp:129] Top shape: 64 192 28 28 (9633792)
I0707 18:30:43.573084 99468 net.cpp:137] Memory required for data: 2506805248
I0707 18:30:43.573101 99468 layer_factory.hpp:77] Creating layer inception_3b/5x5_reduce
I0707 18:30:43.573166 99468 net.cpp:84] Creating Layer inception_3b/5x5_reduce
I0707 18:30:43.573186 99468 net.cpp:406] inception_3b/5x5_reduce <- inception_3a/output_inception_3a/output_0_split_2
I0707 18:30:43.573226 99468 net.cpp:380] inception_3b/5x5_reduce -> inception_3b/5x5_reduce
I0707 18:30:43.577603 99468 net.cpp:122] Setting up inception_3b/5x5_reduce
I0707 18:30:43.577649 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.577666 99468 net.cpp:137] Memory required for data: 2513227776
I0707 18:30:43.577702 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_5x5_reduce
I0707 18:30:43.577726 99468 net.cpp:84] Creating Layer inception_3b/relu_5x5_reduce
I0707 18:30:43.577746 99468 net.cpp:406] inception_3b/relu_5x5_reduce <- inception_3b/5x5_reduce
I0707 18:30:43.577801 99468 net.cpp:367] inception_3b/relu_5x5_reduce -> inception_3b/5x5_reduce (in-place)
I0707 18:30:43.579321 99468 net.cpp:122] Setting up inception_3b/relu_5x5_reduce
I0707 18:30:43.579362 99468 net.cpp:129] Top shape: 64 32 28 28 (1605632)
I0707 18:30:43.579377 99468 net.cpp:137] Memory required for data: 2519650304
I0707 18:30:43.579393 99468 layer_factory.hpp:77] Creating layer inception_3b/5x5
I0707 18:30:43.579457 99468 net.cpp:84] Creating Layer inception_3b/5x5
I0707 18:30:43.579476 99468 net.cpp:406] inception_3b/5x5 <- inception_3b/5x5_reduce
I0707 18:30:43.579519 99468 net.cpp:380] inception_3b/5x5 -> inception_3b/5x5
I0707 18:30:43.584779 99468 net.cpp:122] Setting up inception_3b/5x5
I0707 18:30:43.584825 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.584842 99468 net.cpp:137] Memory required for data: 2538917888
I0707 18:30:43.584867 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_5x5
I0707 18:30:43.584923 99468 net.cpp:84] Creating Layer inception_3b/relu_5x5
I0707 18:30:43.584941 99468 net.cpp:406] inception_3b/relu_5x5 <- inception_3b/5x5
I0707 18:30:43.584981 99468 net.cpp:367] inception_3b/relu_5x5 -> inception_3b/5x5 (in-place)
I0707 18:30:43.585429 99468 net.cpp:122] Setting up inception_3b/relu_5x5
I0707 18:30:43.585460 99468 net.cpp:129] Top shape: 64 96 28 28 (4816896)
I0707 18:30:43.585494 99468 net.cpp:137] Memory required for data: 2558185472
I0707 18:30:43.585526 99468 layer_factory.hpp:77] Creating layer inception_3b/pool
I0707 18:30:43.585569 99468 net.cpp:84] Creating Layer inception_3b/pool
I0707 18:30:43.585590 99468 net.cpp:406] inception_3b/pool <- inception_3a/output_inception_3a/output_0_split_3
I0707 18:30:43.585615 99468 net.cpp:380] inception_3b/pool -> inception_3b/pool
I0707 18:30:43.585764 99468 net.cpp:122] Setting up inception_3b/pool
I0707 18:30:43.585791 99468 net.cpp:129] Top shape: 64 256 28 28 (12845056)
I0707 18:30:43.585808 99468 net.cpp:137] Memory required for data: 2609565696
I0707 18:30:43.585824 99468 layer_factory.hpp:77] Creating layer inception_3b/pool_proj
I0707 18:30:43.585858 99468 net.cpp:84] Creating Layer inception_3b/pool_proj
I0707 18:30:43.585876 99468 net.cpp:406] inception_3b/pool_proj <- inception_3b/pool
I0707 18:30:43.585908 99468 net.cpp:380] inception_3b/pool_proj -> inception_3b/pool_proj
I0707 18:30:43.590433 99468 net.cpp:122] Setting up inception_3b/pool_proj
I0707 18:30:43.590515 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.590551 99468 net.cpp:137] Memory required for data: 2622410752
I0707 18:30:43.590602 99468 layer_factory.hpp:77] Creating layer inception_3b/relu_pool_proj
I0707 18:30:43.590651 99468 net.cpp:84] Creating Layer inception_3b/relu_pool_proj
I0707 18:30:43.590673 99468 net.cpp:406] inception_3b/relu_pool_proj <- inception_3b/pool_proj
I0707 18:30:43.590699 99468 net.cpp:367] inception_3b/relu_pool_proj -> inception_3b/pool_proj (in-place)
I0707 18:30:43.591145 99468 net.cpp:122] Setting up inception_3b/relu_pool_proj
I0707 18:30:43.591176 99468 net.cpp:129] Top shape: 64 64 28 28 (3211264)
I0707 18:30:43.591192 99468 net.cpp:137] Memory required for data: 2635255808
I0707 18:30:43.591210 99468 layer_factory.hpp:77] Creating layer inception_3b/output
I0707 18:30:43.591241 99468 net.cpp:84] Creating Layer inception_3b/output
I0707 18:30:43.591259 99468 net.cpp:406] inception_3b/output <- inception_3b/1x1
I0707 18:30:43.591282 99468 net.cpp:406] inception_3b/output <- inception_3b/3x3
I0707 18:30:43.591306 99468 net.cpp:406] inception_3b/output <- inception_3b/5x5
I0707 18:30:43.591327 99468 net.cpp:406] inception_3b/output <- inception_3b/pool_proj
I0707 18:30:43.591351 99468 net.cpp:380] inception_3b/output -> inception_3b/output
I0707 18:30:43.591451 99468 net.cpp:122] Setting up inception_3b/output
I0707 18:30:43.591478 99468 net.cpp:129] Top shape: 64 480 28 28 (24084480)
I0707 18:30:43.591498 99468 net.cpp:137] Memory required for data: 2731593728
I0707 18:30:43.591514 99468 layer_factory.hpp:77] Creating layer pool3/3x3_s2
I0707 18:30:43.591540 99468 net.cpp:84] Creating Layer pool3/3x3_s2
I0707 18:30:43.591569 99468 net.cpp:406] pool3/3x3_s2 <- inception_3b/output
I0707 18:30:43.591596 99468 net.cpp:380] pool3/3x3_s2 -> pool3/3x3_s2
I0707 18:30:43.591737 99468 net.cpp:122] Setting up pool3/3x3_s2
I0707 18:30:43.591763 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.591778 99468 net.cpp:137] Memory required for data: 2755678208
I0707 18:30:43.591799 99468 layer_factory.hpp:77] Creating layer pool3/3x3_s2_pool3/3x3_s2_0_split
I0707 18:30:43.591826 99468 net.cpp:84] Creating Layer pool3/3x3_s2_pool3/3x3_s2_0_split
I0707 18:30:43.591850 99468 net.cpp:406] pool3/3x3_s2_pool3/3x3_s2_0_split <- pool3/3x3_s2
I0707 18:30:43.591873 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_0
I0707 18:30:43.591907 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_1
I0707 18:30:43.591934 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_2
I0707 18:30:43.591960 99468 net.cpp:380] pool3/3x3_s2_pool3/3x3_s2_0_split -> pool3/3x3_s2_pool3/3x3_s2_0_split_3
I0707 18:30:43.592160 99468 net.cpp:122] Setting up pool3/3x3_s2_pool3/3x3_s2_0_split
I0707 18:30:43.592186 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.592205 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.592226 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.592245 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.592263 99468 net.cpp:137] Memory required for data: 2852016128
I0707 18:30:43.592280 99468 layer_factory.hpp:77] Creating layer inception_4a/1x1
I0707 18:30:43.592311 99468 net.cpp:84] Creating Layer inception_4a/1x1
I0707 18:30:43.592334 99468 net.cpp:406] inception_4a/1x1 <- pool3/3x3_s2_pool3/3x3_s2_0_split_0
I0707 18:30:43.592365 99468 net.cpp:380] inception_4a/1x1 -> inception_4a/1x1
I0707 18:30:43.597929 99468 net.cpp:122] Setting up inception_4a/1x1
I0707 18:30:43.597973 99468 net.cpp:129] Top shape: 64 192 14 14 (2408448)
I0707 18:30:43.598016 99468 net.cpp:137] Memory required for data: 2861649920
I0707 18:30:43.598055 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_1x1
I0707 18:30:43.598098 99468 net.cpp:84] Creating Layer inception_4a/relu_1x1
I0707 18:30:43.598120 99468 net.cpp:406] inception_4a/relu_1x1 <- inception_4a/1x1
I0707 18:30:43.598173 99468 net.cpp:367] inception_4a/relu_1x1 -> inception_4a/1x1 (in-place)
I0707 18:30:43.599714 99468 net.cpp:122] Setting up inception_4a/relu_1x1
I0707 18:30:43.599755 99468 net.cpp:129] Top shape: 64 192 14 14 (2408448)
I0707 18:30:43.599776 99468 net.cpp:137] Memory required for data: 2871283712
I0707 18:30:43.599795 99468 layer_factory.hpp:77] Creating layer inception_4a/3x3_reduce
I0707 18:30:43.599833 99468 net.cpp:84] Creating Layer inception_4a/3x3_reduce
I0707 18:30:43.599856 99468 net.cpp:406] inception_4a/3x3_reduce <- pool3/3x3_s2_pool3/3x3_s2_0_split_1
I0707 18:30:43.599900 99468 net.cpp:380] inception_4a/3x3_reduce -> inception_4a/3x3_reduce
I0707 18:30:43.604830 99468 net.cpp:122] Setting up inception_4a/3x3_reduce
I0707 18:30:43.604877 99468 net.cpp:129] Top shape: 64 96 14 14 (1204224)
I0707 18:30:43.604919 99468 net.cpp:137] Memory required for data: 2876100608
I0707 18:30:43.604944 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_3x3_reduce
I0707 18:30:43.604984 99468 net.cpp:84] Creating Layer inception_4a/relu_3x3_reduce
I0707 18:30:43.605026 99468 net.cpp:406] inception_4a/relu_3x3_reduce <- inception_4a/3x3_reduce
I0707 18:30:43.605056 99468 net.cpp:367] inception_4a/relu_3x3_reduce -> inception_4a/3x3_reduce (in-place)
I0707 18:30:43.605520 99468 net.cpp:122] Setting up inception_4a/relu_3x3_reduce
I0707 18:30:43.605561 99468 net.cpp:129] Top shape: 64 96 14 14 (1204224)
I0707 18:30:43.605578 99468 net.cpp:137] Memory required for data: 2880917504
I0707 18:30:43.605598 99468 layer_factory.hpp:77] Creating layer inception_4a/3x3
I0707 18:30:43.605634 99468 net.cpp:84] Creating Layer inception_4a/3x3
I0707 18:30:43.605661 99468 net.cpp:406] inception_4a/3x3 <- inception_4a/3x3_reduce
I0707 18:30:43.605687 99468 net.cpp:380] inception_4a/3x3 -> inception_4a/3x3
I0707 18:30:43.613471 99468 net.cpp:122] Setting up inception_4a/3x3
I0707 18:30:43.613518 99468 net.cpp:129] Top shape: 64 208 14 14 (2609152)
I0707 18:30:43.613534 99468 net.cpp:137] Memory required for data: 2891354112
I0707 18:30:43.613600 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_3x3
I0707 18:30:43.613625 99468 net.cpp:84] Creating Layer inception_4a/relu_3x3
I0707 18:30:43.613643 99468 net.cpp:406] inception_4a/relu_3x3 <- inception_4a/3x3
I0707 18:30:43.613700 99468 net.cpp:367] inception_4a/relu_3x3 -> inception_4a/3x3 (in-place)
I0707 18:30:43.614159 99468 net.cpp:122] Setting up inception_4a/relu_3x3
I0707 18:30:43.614192 99468 net.cpp:129] Top shape: 64 208 14 14 (2609152)
I0707 18:30:43.614207 99468 net.cpp:137] Memory required for data: 2901790720
I0707 18:30:43.614222 99468 layer_factory.hpp:77] Creating layer inception_4a/5x5_reduce
I0707 18:30:43.614282 99468 net.cpp:84] Creating Layer inception_4a/5x5_reduce
I0707 18:30:43.614320 99468 net.cpp:406] inception_4a/5x5_reduce <- pool3/3x3_s2_pool3/3x3_s2_0_split_2
I0707 18:30:43.614351 99468 net.cpp:380] inception_4a/5x5_reduce -> inception_4a/5x5_reduce
I0707 18:30:43.618845 99468 net.cpp:122] Setting up inception_4a/5x5_reduce
I0707 18:30:43.618891 99468 net.cpp:129] Top shape: 64 16 14 14 (200704)
I0707 18:30:43.618906 99468 net.cpp:137] Memory required for data: 2902593536
I0707 18:30:43.618963 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_5x5_reduce
I0707 18:30:43.618994 99468 net.cpp:84] Creating Layer inception_4a/relu_5x5_reduce
I0707 18:30:43.619014 99468 net.cpp:406] inception_4a/relu_5x5_reduce <- inception_4a/5x5_reduce
I0707 18:30:43.619051 99468 net.cpp:367] inception_4a/relu_5x5_reduce -> inception_4a/5x5_reduce (in-place)
I0707 18:30:43.620532 99468 net.cpp:122] Setting up inception_4a/relu_5x5_reduce
I0707 18:30:43.620599 99468 net.cpp:129] Top shape: 64 16 14 14 (200704)
I0707 18:30:43.620617 99468 net.cpp:137] Memory required for data: 2903396352
I0707 18:30:43.620667 99468 layer_factory.hpp:77] Creating layer inception_4a/5x5
I0707 18:30:43.620700 99468 net.cpp:84] Creating Layer inception_4a/5x5
I0707 18:30:43.620744 99468 net.cpp:406] inception_4a/5x5 <- inception_4a/5x5_reduce
I0707 18:30:43.620820 99468 net.cpp:380] inception_4a/5x5 -> inception_4a/5x5
I0707 18:30:43.625443 99468 net.cpp:122] Setting up inception_4a/5x5
I0707 18:30:43.625490 99468 net.cpp:129] Top shape: 64 48 14 14 (602112)
I0707 18:30:43.625506 99468 net.cpp:137] Memory required for data: 2905804800
I0707 18:30:43.625529 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_5x5
I0707 18:30:43.625581 99468 net.cpp:84] Creating Layer inception_4a/relu_5x5
I0707 18:30:43.625603 99468 net.cpp:406] inception_4a/relu_5x5 <- inception_4a/5x5
I0707 18:30:43.625669 99468 net.cpp:367] inception_4a/relu_5x5 -> inception_4a/5x5 (in-place)
I0707 18:30:43.627261 99468 net.cpp:122] Setting up inception_4a/relu_5x5
I0707 18:30:43.627302 99468 net.cpp:129] Top shape: 64 48 14 14 (602112)
I0707 18:30:43.627346 99468 net.cpp:137] Memory required for data: 2908213248
I0707 18:30:43.627367 99468 layer_factory.hpp:77] Creating layer inception_4a/pool
I0707 18:30:43.627394 99468 net.cpp:84] Creating Layer inception_4a/pool
I0707 18:30:43.627413 99468 net.cpp:406] inception_4a/pool <- pool3/3x3_s2_pool3/3x3_s2_0_split_3
I0707 18:30:43.627455 99468 net.cpp:380] inception_4a/pool -> inception_4a/pool
I0707 18:30:43.627646 99468 net.cpp:122] Setting up inception_4a/pool
I0707 18:30:43.627677 99468 net.cpp:129] Top shape: 64 480 14 14 (6021120)
I0707 18:30:43.627693 99468 net.cpp:137] Memory required for data: 2932297728
I0707 18:30:43.627732 99468 layer_factory.hpp:77] Creating layer inception_4a/pool_proj
I0707 18:30:43.627768 99468 net.cpp:84] Creating Layer inception_4a/pool_proj
I0707 18:30:43.627790 99468 net.cpp:406] inception_4a/pool_proj <- inception_4a/pool
I0707 18:30:43.627827 99468 net.cpp:380] inception_4a/pool_proj -> inception_4a/pool_proj
I0707 18:30:43.632612 99468 net.cpp:122] Setting up inception_4a/pool_proj
I0707 18:30:43.632660 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.632699 99468 net.cpp:137] Memory required for data: 2935508992
I0707 18:30:43.632738 99468 layer_factory.hpp:77] Creating layer inception_4a/relu_pool_proj
I0707 18:30:43.632784 99468 net.cpp:84] Creating Layer inception_4a/relu_pool_proj
I0707 18:30:43.632823 99468 net.cpp:406] inception_4a/relu_pool_proj <- inception_4a/pool_proj
I0707 18:30:43.632845 99468 net.cpp:367] inception_4a/relu_pool_proj -> inception_4a/pool_proj (in-place)
I0707 18:30:43.633328 99468 net.cpp:122] Setting up inception_4a/relu_pool_proj
I0707 18:30:43.633361 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.633378 99468 net.cpp:137] Memory required for data: 2938720256
I0707 18:30:43.633409 99468 layer_factory.hpp:77] Creating layer inception_4a/output
I0707 18:30:43.633437 99468 net.cpp:84] Creating Layer inception_4a/output
I0707 18:30:43.633455 99468 net.cpp:406] inception_4a/output <- inception_4a/1x1
I0707 18:30:43.633479 99468 net.cpp:406] inception_4a/output <- inception_4a/3x3
I0707 18:30:43.633498 99468 net.cpp:406] inception_4a/output <- inception_4a/5x5
I0707 18:30:43.633522 99468 net.cpp:406] inception_4a/output <- inception_4a/pool_proj
I0707 18:30:43.633545 99468 net.cpp:380] inception_4a/output -> inception_4a/output
I0707 18:30:43.633663 99468 net.cpp:122] Setting up inception_4a/output
I0707 18:30:43.633692 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.633709 99468 net.cpp:137] Memory required for data: 2964410368
I0707 18:30:43.633730 99468 layer_factory.hpp:77] Creating layer inception_4a/output_inception_4a/output_0_split
I0707 18:30:43.633755 99468 net.cpp:84] Creating Layer inception_4a/output_inception_4a/output_0_split
I0707 18:30:43.633776 99468 net.cpp:406] inception_4a/output_inception_4a/output_0_split <- inception_4a/output
I0707 18:30:43.633806 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_0
I0707 18:30:43.633867 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_1
I0707 18:30:43.633896 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_2
I0707 18:30:43.633951 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_3
I0707 18:30:43.633978 99468 net.cpp:380] inception_4a/output_inception_4a/output_0_split -> inception_4a/output_inception_4a/output_0_split_4
I0707 18:30:43.634248 99468 net.cpp:122] Setting up inception_4a/output_inception_4a/output_0_split
I0707 18:30:43.634277 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.634296 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.634318 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.634340 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.634361 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.634379 99468 net.cpp:137] Memory required for data: 3092860928
I0707 18:30:43.634398 99468 layer_factory.hpp:77] Creating layer loss1/ave_pool
I0707 18:30:43.634431 99468 net.cpp:84] Creating Layer loss1/ave_pool
I0707 18:30:43.634451 99468 net.cpp:406] loss1/ave_pool <- inception_4a/output_inception_4a/output_0_split_0
I0707 18:30:43.634475 99468 net.cpp:380] loss1/ave_pool -> loss1/ave_pool
I0707 18:30:43.636065 99468 net.cpp:122] Setting up loss1/ave_pool
I0707 18:30:43.636108 99468 net.cpp:129] Top shape: 64 512 4 4 (524288)
I0707 18:30:43.636133 99468 net.cpp:137] Memory required for data: 3094958080
I0707 18:30:43.636152 99468 layer_factory.hpp:77] Creating layer loss1/conv
I0707 18:30:43.636193 99468 net.cpp:84] Creating Layer loss1/conv
I0707 18:30:43.636216 99468 net.cpp:406] loss1/conv <- loss1/ave_pool
I0707 18:30:43.636245 99468 net.cpp:380] loss1/conv -> loss1/conv
I0707 18:30:43.641532 99468 net.cpp:122] Setting up loss1/conv
I0707 18:30:43.641588 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.641638 99468 net.cpp:137] Memory required for data: 3095482368
I0707 18:30:43.641682 99468 layer_factory.hpp:77] Creating layer loss1/relu_conv
I0707 18:30:43.641732 99468 net.cpp:84] Creating Layer loss1/relu_conv
I0707 18:30:43.641772 99468 net.cpp:406] loss1/relu_conv <- loss1/conv
I0707 18:30:43.641798 99468 net.cpp:367] loss1/relu_conv -> loss1/conv (in-place)
I0707 18:30:43.642266 99468 net.cpp:122] Setting up loss1/relu_conv
I0707 18:30:43.642299 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.642328 99468 net.cpp:137] Memory required for data: 3096006656
I0707 18:30:43.642348 99468 layer_factory.hpp:77] Creating layer loss1/fc
I0707 18:30:43.642379 99468 net.cpp:84] Creating Layer loss1/fc
I0707 18:30:43.642398 99468 net.cpp:406] loss1/fc <- loss1/conv
I0707 18:30:43.642426 99468 net.cpp:380] loss1/fc -> loss1/fc
I0707 18:30:43.676468 99468 net.cpp:122] Setting up loss1/fc
I0707 18:30:43.676517 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.676535 99468 net.cpp:137] Memory required for data: 3096268800
I0707 18:30:43.676601 99468 layer_factory.hpp:77] Creating layer loss1/relu_fc
I0707 18:30:43.676631 99468 net.cpp:84] Creating Layer loss1/relu_fc
I0707 18:30:43.676677 99468 net.cpp:406] loss1/relu_fc <- loss1/fc
I0707 18:30:43.676703 99468 net.cpp:367] loss1/relu_fc -> loss1/fc (in-place)
I0707 18:30:43.678313 99468 net.cpp:122] Setting up loss1/relu_fc
I0707 18:30:43.678356 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.678398 99468 net.cpp:137] Memory required for data: 3096530944
I0707 18:30:43.678438 99468 layer_factory.hpp:77] Creating layer loss1/drop_fc
I0707 18:30:43.678480 99468 net.cpp:84] Creating Layer loss1/drop_fc
I0707 18:30:43.678515 99468 net.cpp:406] loss1/drop_fc <- loss1/fc
I0707 18:30:43.678545 99468 net.cpp:367] loss1/drop_fc -> loss1/fc (in-place)
I0707 18:30:43.678674 99468 net.cpp:122] Setting up loss1/drop_fc
I0707 18:30:43.678704 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.678722 99468 net.cpp:137] Memory required for data: 3096793088
I0707 18:30:43.678743 99468 layer_factory.hpp:77] Creating layer loss1/classifier_my
I0707 18:30:43.678772 99468 net.cpp:84] Creating Layer loss1/classifier_my
I0707 18:30:43.678822 99468 net.cpp:406] loss1/classifier_my <- loss1/fc
I0707 18:30:43.678858 99468 net.cpp:380] loss1/classifier_my -> loss1/classifier
I0707 18:30:43.679822 99468 net.cpp:122] Setting up loss1/classifier_my
I0707 18:30:43.679855 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.679872 99468 net.cpp:137] Memory required for data: 3096803072
I0707 18:30:43.679900 99468 layer_factory.hpp:77] Creating layer loss1/classifier_loss1/classifier_my_0_split
I0707 18:30:43.679929 99468 net.cpp:84] Creating Layer loss1/classifier_loss1/classifier_my_0_split
I0707 18:30:43.679950 99468 net.cpp:406] loss1/classifier_loss1/classifier_my_0_split <- loss1/classifier
I0707 18:30:43.679976 99468 net.cpp:380] loss1/classifier_loss1/classifier_my_0_split -> loss1/classifier_loss1/classifier_my_0_split_0
I0707 18:30:43.680004 99468 net.cpp:380] loss1/classifier_loss1/classifier_my_0_split -> loss1/classifier_loss1/classifier_my_0_split_1
I0707 18:30:43.680032 99468 net.cpp:380] loss1/classifier_loss1/classifier_my_0_split -> loss1/classifier_loss1/classifier_my_0_split_2
I0707 18:30:43.680219 99468 net.cpp:122] Setting up loss1/classifier_loss1/classifier_my_0_split
I0707 18:30:43.680246 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.680268 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.680284 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.680305 99468 net.cpp:137] Memory required for data: 3096833024
I0707 18:30:43.680320 99468 layer_factory.hpp:77] Creating layer loss1/loss
I0707 18:30:43.680346 99468 net.cpp:84] Creating Layer loss1/loss
I0707 18:30:43.680367 99468 net.cpp:406] loss1/loss <- loss1/classifier_loss1/classifier_my_0_split_0
I0707 18:30:43.680393 99468 net.cpp:406] loss1/loss <- label_data_1_split_0
I0707 18:30:43.680423 99468 net.cpp:380] loss1/loss -> loss1/loss1
I0707 18:30:43.680456 99468 layer_factory.hpp:77] Creating layer loss1/loss
I0707 18:30:43.681260 99468 net.cpp:122] Setting up loss1/loss
I0707 18:30:43.681296 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.681313 99468 net.cpp:132]     with loss weight 0.3
I0707 18:30:43.681354 99468 net.cpp:137] Memory required for data: 3096833028
I0707 18:30:43.681371 99468 layer_factory.hpp:77] Creating layer loss1/top-1
I0707 18:30:43.681403 99468 net.cpp:84] Creating Layer loss1/top-1
I0707 18:30:43.681422 99468 net.cpp:406] loss1/top-1 <- loss1/classifier_loss1/classifier_my_0_split_1
I0707 18:30:43.681447 99468 net.cpp:406] loss1/top-1 <- label_data_1_split_1
I0707 18:30:43.681481 99468 net.cpp:380] loss1/top-1 -> loss1/top-1
I0707 18:30:43.681531 99468 net.cpp:122] Setting up loss1/top-1
I0707 18:30:43.681565 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.681586 99468 net.cpp:137] Memory required for data: 3096833032
I0707 18:30:43.681605 99468 layer_factory.hpp:77] Creating layer loss1/top-5
I0707 18:30:43.681628 99468 net.cpp:84] Creating Layer loss1/top-5
I0707 18:30:43.681648 99468 net.cpp:406] loss1/top-5 <- loss1/classifier_loss1/classifier_my_0_split_2
I0707 18:30:43.681668 99468 net.cpp:406] loss1/top-5 <- label_data_1_split_2
I0707 18:30:43.681701 99468 net.cpp:380] loss1/top-5 -> loss1/top-5
I0707 18:30:43.681735 99468 net.cpp:122] Setting up loss1/top-5
I0707 18:30:43.681756 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.681772 99468 net.cpp:137] Memory required for data: 3096833036
I0707 18:30:43.681792 99468 layer_factory.hpp:77] Creating layer inception_4b/1x1
I0707 18:30:43.681829 99468 net.cpp:84] Creating Layer inception_4b/1x1
I0707 18:30:43.681852 99468 net.cpp:406] inception_4b/1x1 <- inception_4a/output_inception_4a/output_0_split_1
I0707 18:30:43.681876 99468 net.cpp:380] inception_4b/1x1 -> inception_4b/1x1
I0707 18:30:43.687458 99468 net.cpp:122] Setting up inception_4b/1x1
I0707 18:30:43.687507 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.687562 99468 net.cpp:137] Memory required for data: 3104861196
I0707 18:30:43.687587 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_1x1
I0707 18:30:43.687633 99468 net.cpp:84] Creating Layer inception_4b/relu_1x1
I0707 18:30:43.687682 99468 net.cpp:406] inception_4b/relu_1x1 <- inception_4b/1x1
I0707 18:30:43.687716 99468 net.cpp:367] inception_4b/relu_1x1 -> inception_4b/1x1 (in-place)
I0707 18:30:43.689272 99468 net.cpp:122] Setting up inception_4b/relu_1x1
I0707 18:30:43.689316 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.689332 99468 net.cpp:137] Memory required for data: 3112889356
I0707 18:30:43.689384 99468 layer_factory.hpp:77] Creating layer inception_4b/3x3_reduce
I0707 18:30:43.689440 99468 net.cpp:84] Creating Layer inception_4b/3x3_reduce
I0707 18:30:43.689461 99468 net.cpp:406] inception_4b/3x3_reduce <- inception_4a/output_inception_4a/output_0_split_2
I0707 18:30:43.689492 99468 net.cpp:380] inception_4b/3x3_reduce -> inception_4b/3x3_reduce
I0707 18:30:43.695977 99468 net.cpp:122] Setting up inception_4b/3x3_reduce
I0707 18:30:43.696025 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.696041 99468 net.cpp:137] Memory required for data: 3118509068
I0707 18:30:43.696064 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_3x3_reduce
I0707 18:30:43.696091 99468 net.cpp:84] Creating Layer inception_4b/relu_3x3_reduce
I0707 18:30:43.696111 99468 net.cpp:406] inception_4b/relu_3x3_reduce <- inception_4b/3x3_reduce
I0707 18:30:43.696131 99468 net.cpp:367] inception_4b/relu_3x3_reduce -> inception_4b/3x3_reduce (in-place)
I0707 18:30:43.696619 99468 net.cpp:122] Setting up inception_4b/relu_3x3_reduce
I0707 18:30:43.696663 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.696677 99468 net.cpp:137] Memory required for data: 3124128780
I0707 18:30:43.696692 99468 layer_factory.hpp:77] Creating layer inception_4b/3x3
I0707 18:30:43.696729 99468 net.cpp:84] Creating Layer inception_4b/3x3
I0707 18:30:43.696748 99468 net.cpp:406] inception_4b/3x3 <- inception_4b/3x3_reduce
I0707 18:30:43.696807 99468 net.cpp:380] inception_4b/3x3 -> inception_4b/3x3
I0707 18:30:43.705325 99468 net.cpp:122] Setting up inception_4b/3x3
I0707 18:30:43.705374 99468 net.cpp:129] Top shape: 64 224 14 14 (2809856)
I0707 18:30:43.705390 99468 net.cpp:137] Memory required for data: 3135368204
I0707 18:30:43.705416 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_3x3
I0707 18:30:43.705479 99468 net.cpp:84] Creating Layer inception_4b/relu_3x3
I0707 18:30:43.705499 99468 net.cpp:406] inception_4b/relu_3x3 <- inception_4b/3x3
I0707 18:30:43.705539 99468 net.cpp:367] inception_4b/relu_3x3 -> inception_4b/3x3 (in-place)
I0707 18:30:43.706053 99468 net.cpp:122] Setting up inception_4b/relu_3x3
I0707 18:30:43.706105 99468 net.cpp:129] Top shape: 64 224 14 14 (2809856)
I0707 18:30:43.706120 99468 net.cpp:137] Memory required for data: 3146607628
I0707 18:30:43.706135 99468 layer_factory.hpp:77] Creating layer inception_4b/5x5_reduce
I0707 18:30:43.706204 99468 net.cpp:84] Creating Layer inception_4b/5x5_reduce
I0707 18:30:43.706225 99468 net.cpp:406] inception_4b/5x5_reduce <- inception_4a/output_inception_4a/output_0_split_3
I0707 18:30:43.706266 99468 net.cpp:380] inception_4b/5x5_reduce -> inception_4b/5x5_reduce
I0707 18:30:43.712106 99468 net.cpp:122] Setting up inception_4b/5x5_reduce
I0707 18:30:43.712153 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.712170 99468 net.cpp:137] Memory required for data: 3147811852
I0707 18:30:43.712196 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_5x5_reduce
I0707 18:30:43.712220 99468 net.cpp:84] Creating Layer inception_4b/relu_5x5_reduce
I0707 18:30:43.712239 99468 net.cpp:406] inception_4b/relu_5x5_reduce <- inception_4b/5x5_reduce
I0707 18:30:43.712301 99468 net.cpp:367] inception_4b/relu_5x5_reduce -> inception_4b/5x5_reduce (in-place)
I0707 18:30:43.713867 99468 net.cpp:122] Setting up inception_4b/relu_5x5_reduce
I0707 18:30:43.713909 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.713924 99468 net.cpp:137] Memory required for data: 3149016076
I0707 18:30:43.713940 99468 layer_factory.hpp:77] Creating layer inception_4b/5x5
I0707 18:30:43.714005 99468 net.cpp:84] Creating Layer inception_4b/5x5
I0707 18:30:43.714066 99468 net.cpp:406] inception_4b/5x5 <- inception_4b/5x5_reduce
I0707 18:30:43.714098 99468 net.cpp:380] inception_4b/5x5 -> inception_4b/5x5
I0707 18:30:43.719091 99468 net.cpp:122] Setting up inception_4b/5x5
I0707 18:30:43.719137 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.719153 99468 net.cpp:137] Memory required for data: 3152227340
I0707 18:30:43.719209 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_5x5
I0707 18:30:43.719270 99468 net.cpp:84] Creating Layer inception_4b/relu_5x5
I0707 18:30:43.719290 99468 net.cpp:406] inception_4b/relu_5x5 <- inception_4b/5x5
I0707 18:30:43.719329 99468 net.cpp:367] inception_4b/relu_5x5 -> inception_4b/5x5 (in-place)
I0707 18:30:43.719877 99468 net.cpp:122] Setting up inception_4b/relu_5x5
I0707 18:30:43.719909 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.719923 99468 net.cpp:137] Memory required for data: 3155438604
I0707 18:30:43.719939 99468 layer_factory.hpp:77] Creating layer inception_4b/pool
I0707 18:30:43.719993 99468 net.cpp:84] Creating Layer inception_4b/pool
I0707 18:30:43.720011 99468 net.cpp:406] inception_4b/pool <- inception_4a/output_inception_4a/output_0_split_4
I0707 18:30:43.720037 99468 net.cpp:380] inception_4b/pool -> inception_4b/pool
I0707 18:30:43.720216 99468 net.cpp:122] Setting up inception_4b/pool
I0707 18:30:43.720247 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.720281 99468 net.cpp:137] Memory required for data: 3181128716
I0707 18:30:43.720302 99468 layer_factory.hpp:77] Creating layer inception_4b/pool_proj
I0707 18:30:43.720329 99468 net.cpp:84] Creating Layer inception_4b/pool_proj
I0707 18:30:43.720351 99468 net.cpp:406] inception_4b/pool_proj <- inception_4b/pool
I0707 18:30:43.720391 99468 net.cpp:380] inception_4b/pool_proj -> inception_4b/pool_proj
I0707 18:30:43.735710 99468 net.cpp:122] Setting up inception_4b/pool_proj
I0707 18:30:43.735764 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.735781 99468 net.cpp:137] Memory required for data: 3184339980
I0707 18:30:43.735839 99468 layer_factory.hpp:77] Creating layer inception_4b/relu_pool_proj
I0707 18:30:43.735868 99468 net.cpp:84] Creating Layer inception_4b/relu_pool_proj
I0707 18:30:43.735888 99468 net.cpp:406] inception_4b/relu_pool_proj <- inception_4b/pool_proj
I0707 18:30:43.735913 99468 net.cpp:367] inception_4b/relu_pool_proj -> inception_4b/pool_proj (in-place)
I0707 18:30:43.736385 99468 net.cpp:122] Setting up inception_4b/relu_pool_proj
I0707 18:30:43.736418 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.736433 99468 net.cpp:137] Memory required for data: 3187551244
I0707 18:30:43.736448 99468 layer_factory.hpp:77] Creating layer inception_4b/output
I0707 18:30:43.736476 99468 net.cpp:84] Creating Layer inception_4b/output
I0707 18:30:43.736495 99468 net.cpp:406] inception_4b/output <- inception_4b/1x1
I0707 18:30:43.736539 99468 net.cpp:406] inception_4b/output <- inception_4b/3x3
I0707 18:30:43.736594 99468 net.cpp:406] inception_4b/output <- inception_4b/5x5
I0707 18:30:43.736615 99468 net.cpp:406] inception_4b/output <- inception_4b/pool_proj
I0707 18:30:43.736637 99468 net.cpp:380] inception_4b/output -> inception_4b/output
I0707 18:30:43.736766 99468 net.cpp:122] Setting up inception_4b/output
I0707 18:30:43.736798 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.736811 99468 net.cpp:137] Memory required for data: 3213241356
I0707 18:30:43.736826 99468 layer_factory.hpp:77] Creating layer inception_4b/output_inception_4b/output_0_split
I0707 18:30:43.736876 99468 net.cpp:84] Creating Layer inception_4b/output_inception_4b/output_0_split
I0707 18:30:43.736893 99468 net.cpp:406] inception_4b/output_inception_4b/output_0_split <- inception_4b/output
I0707 18:30:43.736920 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_0
I0707 18:30:43.736965 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_1
I0707 18:30:43.737021 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_2
I0707 18:30:43.737046 99468 net.cpp:380] inception_4b/output_inception_4b/output_0_split -> inception_4b/output_inception_4b/output_0_split_3
I0707 18:30:43.737298 99468 net.cpp:122] Setting up inception_4b/output_inception_4b/output_0_split
I0707 18:30:43.737325 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.737360 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.737377 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.737398 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.737416 99468 net.cpp:137] Memory required for data: 3316001804
I0707 18:30:43.737437 99468 layer_factory.hpp:77] Creating layer inception_4c/1x1
I0707 18:30:43.737473 99468 net.cpp:84] Creating Layer inception_4c/1x1
I0707 18:30:43.737494 99468 net.cpp:406] inception_4c/1x1 <- inception_4b/output_inception_4b/output_0_split_0
I0707 18:30:43.737520 99468 net.cpp:380] inception_4c/1x1 -> inception_4c/1x1
I0707 18:30:43.742827 99468 net.cpp:122] Setting up inception_4c/1x1
I0707 18:30:43.742879 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.742923 99468 net.cpp:137] Memory required for data: 3322424332
I0707 18:30:43.742966 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_1x1
I0707 18:30:43.743006 99468 net.cpp:84] Creating Layer inception_4c/relu_1x1
I0707 18:30:43.743041 99468 net.cpp:406] inception_4c/relu_1x1 <- inception_4c/1x1
I0707 18:30:43.743084 99468 net.cpp:367] inception_4c/relu_1x1 -> inception_4c/1x1 (in-place)
I0707 18:30:43.744642 99468 net.cpp:122] Setting up inception_4c/relu_1x1
I0707 18:30:43.744683 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.744699 99468 net.cpp:137] Memory required for data: 3328846860
I0707 18:30:43.744746 99468 layer_factory.hpp:77] Creating layer inception_4c/3x3_reduce
I0707 18:30:43.744787 99468 net.cpp:84] Creating Layer inception_4c/3x3_reduce
I0707 18:30:43.744808 99468 net.cpp:406] inception_4c/3x3_reduce <- inception_4b/output_inception_4b/output_0_split_1
I0707 18:30:43.744837 99468 net.cpp:380] inception_4c/3x3_reduce -> inception_4c/3x3_reduce
I0707 18:30:43.750113 99468 net.cpp:122] Setting up inception_4c/3x3_reduce
I0707 18:30:43.750159 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.750175 99468 net.cpp:137] Memory required for data: 3335269388
I0707 18:30:43.750231 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_3x3_reduce
I0707 18:30:43.750254 99468 net.cpp:84] Creating Layer inception_4c/relu_3x3_reduce
I0707 18:30:43.750278 99468 net.cpp:406] inception_4c/relu_3x3_reduce <- inception_4c/3x3_reduce
I0707 18:30:43.750319 99468 net.cpp:367] inception_4c/relu_3x3_reduce -> inception_4c/3x3_reduce (in-place)
I0707 18:30:43.750810 99468 net.cpp:122] Setting up inception_4c/relu_3x3_reduce
I0707 18:30:43.750843 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.750856 99468 net.cpp:137] Memory required for data: 3341691916
I0707 18:30:43.750871 99468 layer_factory.hpp:77] Creating layer inception_4c/3x3
I0707 18:30:43.750934 99468 net.cpp:84] Creating Layer inception_4c/3x3
I0707 18:30:43.750954 99468 net.cpp:406] inception_4c/3x3 <- inception_4c/3x3_reduce
I0707 18:30:43.750979 99468 net.cpp:380] inception_4c/3x3 -> inception_4c/3x3
I0707 18:30:43.760411 99468 net.cpp:122] Setting up inception_4c/3x3
I0707 18:30:43.760458 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.760474 99468 net.cpp:137] Memory required for data: 3354536972
I0707 18:30:43.760498 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_3x3
I0707 18:30:43.760526 99468 net.cpp:84] Creating Layer inception_4c/relu_3x3
I0707 18:30:43.760546 99468 net.cpp:406] inception_4c/relu_3x3 <- inception_4c/3x3
I0707 18:30:43.760576 99468 net.cpp:367] inception_4c/relu_3x3 -> inception_4c/3x3 (in-place)
I0707 18:30:43.761062 99468 net.cpp:122] Setting up inception_4c/relu_3x3
I0707 18:30:43.761123 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.761139 99468 net.cpp:137] Memory required for data: 3367382028
I0707 18:30:43.761185 99468 layer_factory.hpp:77] Creating layer inception_4c/5x5_reduce
I0707 18:30:43.761242 99468 net.cpp:84] Creating Layer inception_4c/5x5_reduce
I0707 18:30:43.761263 99468 net.cpp:406] inception_4c/5x5_reduce <- inception_4b/output_inception_4b/output_0_split_2
I0707 18:30:43.761286 99468 net.cpp:380] inception_4c/5x5_reduce -> inception_4c/5x5_reduce
I0707 18:30:43.765918 99468 net.cpp:122] Setting up inception_4c/5x5_reduce
I0707 18:30:43.765965 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.765981 99468 net.cpp:137] Memory required for data: 3368586252
I0707 18:30:43.766036 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_5x5_reduce
I0707 18:30:43.766064 99468 net.cpp:84] Creating Layer inception_4c/relu_5x5_reduce
I0707 18:30:43.766083 99468 net.cpp:406] inception_4c/relu_5x5_reduce <- inception_4c/5x5_reduce
I0707 18:30:43.766126 99468 net.cpp:367] inception_4c/relu_5x5_reduce -> inception_4c/5x5_reduce (in-place)
I0707 18:30:43.767693 99468 net.cpp:122] Setting up inception_4c/relu_5x5_reduce
I0707 18:30:43.767732 99468 net.cpp:129] Top shape: 64 24 14 14 (301056)
I0707 18:30:43.767747 99468 net.cpp:137] Memory required for data: 3369790476
I0707 18:30:43.767763 99468 layer_factory.hpp:77] Creating layer inception_4c/5x5
I0707 18:30:43.767829 99468 net.cpp:84] Creating Layer inception_4c/5x5
I0707 18:30:43.767849 99468 net.cpp:406] inception_4c/5x5 <- inception_4c/5x5_reduce
I0707 18:30:43.767899 99468 net.cpp:380] inception_4c/5x5 -> inception_4c/5x5
I0707 18:30:43.774171 99468 net.cpp:122] Setting up inception_4c/5x5
I0707 18:30:43.774219 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.774235 99468 net.cpp:137] Memory required for data: 3373001740
I0707 18:30:43.774291 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_5x5
I0707 18:30:43.774317 99468 net.cpp:84] Creating Layer inception_4c/relu_5x5
I0707 18:30:43.774340 99468 net.cpp:406] inception_4c/relu_5x5 <- inception_4c/5x5
I0707 18:30:43.774379 99468 net.cpp:367] inception_4c/relu_5x5 -> inception_4c/5x5 (in-place)
I0707 18:30:43.774878 99468 net.cpp:122] Setting up inception_4c/relu_5x5
I0707 18:30:43.774910 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.774924 99468 net.cpp:137] Memory required for data: 3376213004
I0707 18:30:43.774940 99468 layer_factory.hpp:77] Creating layer inception_4c/pool
I0707 18:30:43.774971 99468 net.cpp:84] Creating Layer inception_4c/pool
I0707 18:30:43.774989 99468 net.cpp:406] inception_4c/pool <- inception_4b/output_inception_4b/output_0_split_3
I0707 18:30:43.775044 99468 net.cpp:380] inception_4c/pool -> inception_4c/pool
I0707 18:30:43.775208 99468 net.cpp:122] Setting up inception_4c/pool
I0707 18:30:43.775235 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.775267 99468 net.cpp:137] Memory required for data: 3401903116
I0707 18:30:43.775283 99468 layer_factory.hpp:77] Creating layer inception_4c/pool_proj
I0707 18:30:43.775321 99468 net.cpp:84] Creating Layer inception_4c/pool_proj
I0707 18:30:43.775344 99468 net.cpp:406] inception_4c/pool_proj <- inception_4c/pool
I0707 18:30:43.775380 99468 net.cpp:380] inception_4c/pool_proj -> inception_4c/pool_proj
I0707 18:30:43.780222 99468 net.cpp:122] Setting up inception_4c/pool_proj
I0707 18:30:43.780268 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.780284 99468 net.cpp:137] Memory required for data: 3405114380
I0707 18:30:43.780341 99468 layer_factory.hpp:77] Creating layer inception_4c/relu_pool_proj
I0707 18:30:43.780367 99468 net.cpp:84] Creating Layer inception_4c/relu_pool_proj
I0707 18:30:43.780386 99468 net.cpp:406] inception_4c/relu_pool_proj <- inception_4c/pool_proj
I0707 18:30:43.780429 99468 net.cpp:367] inception_4c/relu_pool_proj -> inception_4c/pool_proj (in-place)
I0707 18:30:43.780922 99468 net.cpp:122] Setting up inception_4c/relu_pool_proj
I0707 18:30:43.780983 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.780999 99468 net.cpp:137] Memory required for data: 3408325644
I0707 18:30:43.781014 99468 layer_factory.hpp:77] Creating layer inception_4c/output
I0707 18:30:43.781070 99468 net.cpp:84] Creating Layer inception_4c/output
I0707 18:30:43.781087 99468 net.cpp:406] inception_4c/output <- inception_4c/1x1
I0707 18:30:43.781107 99468 net.cpp:406] inception_4c/output <- inception_4c/3x3
I0707 18:30:43.781131 99468 net.cpp:406] inception_4c/output <- inception_4c/5x5
I0707 18:30:43.781147 99468 net.cpp:406] inception_4c/output <- inception_4c/pool_proj
I0707 18:30:43.781178 99468 net.cpp:380] inception_4c/output -> inception_4c/output
I0707 18:30:43.781286 99468 net.cpp:122] Setting up inception_4c/output
I0707 18:30:43.781317 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.781338 99468 net.cpp:137] Memory required for data: 3434015756
I0707 18:30:43.781357 99468 layer_factory.hpp:77] Creating layer inception_4c/output_inception_4c/output_0_split
I0707 18:30:43.781381 99468 net.cpp:84] Creating Layer inception_4c/output_inception_4c/output_0_split
I0707 18:30:43.781399 99468 net.cpp:406] inception_4c/output_inception_4c/output_0_split <- inception_4c/output
I0707 18:30:43.781426 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_0
I0707 18:30:43.781455 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_1
I0707 18:30:43.781478 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_2
I0707 18:30:43.781514 99468 net.cpp:380] inception_4c/output_inception_4c/output_0_split -> inception_4c/output_inception_4c/output_0_split_3
I0707 18:30:43.781774 99468 net.cpp:122] Setting up inception_4c/output_inception_4c/output_0_split
I0707 18:30:43.781802 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.781821 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.781841 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.781862 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.781880 99468 net.cpp:137] Memory required for data: 3536776204
I0707 18:30:43.781896 99468 layer_factory.hpp:77] Creating layer inception_4d/1x1
I0707 18:30:43.781934 99468 net.cpp:84] Creating Layer inception_4d/1x1
I0707 18:30:43.781957 99468 net.cpp:406] inception_4d/1x1 <- inception_4c/output_inception_4c/output_0_split_0
I0707 18:30:43.781987 99468 net.cpp:380] inception_4d/1x1 -> inception_4d/1x1
I0707 18:30:43.792093 99468 net.cpp:122] Setting up inception_4d/1x1
I0707 18:30:43.792165 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.792199 99468 net.cpp:137] Memory required for data: 3542395916
I0707 18:30:43.792223 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_1x1
I0707 18:30:43.792263 99468 net.cpp:84] Creating Layer inception_4d/relu_1x1
I0707 18:30:43.792297 99468 net.cpp:406] inception_4d/relu_1x1 <- inception_4d/1x1
I0707 18:30:43.792342 99468 net.cpp:367] inception_4d/relu_1x1 -> inception_4d/1x1 (in-place)
I0707 18:30:43.793911 99468 net.cpp:122] Setting up inception_4d/relu_1x1
I0707 18:30:43.793956 99468 net.cpp:129] Top shape: 64 112 14 14 (1404928)
I0707 18:30:43.793972 99468 net.cpp:137] Memory required for data: 3548015628
I0707 18:30:43.794019 99468 layer_factory.hpp:77] Creating layer inception_4d/3x3_reduce
I0707 18:30:43.794055 99468 net.cpp:84] Creating Layer inception_4d/3x3_reduce
I0707 18:30:43.794075 99468 net.cpp:406] inception_4d/3x3_reduce <- inception_4c/output_inception_4c/output_0_split_1
I0707 18:30:43.794118 99468 net.cpp:380] inception_4d/3x3_reduce -> inception_4d/3x3_reduce
I0707 18:30:43.801240 99468 net.cpp:122] Setting up inception_4d/3x3_reduce
I0707 18:30:43.801287 99468 net.cpp:129] Top shape: 64 144 14 14 (1806336)
I0707 18:30:43.801303 99468 net.cpp:137] Memory required for data: 3555240972
I0707 18:30:43.801326 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_3x3_reduce
I0707 18:30:43.801383 99468 net.cpp:84] Creating Layer inception_4d/relu_3x3_reduce
I0707 18:30:43.801431 99468 net.cpp:406] inception_4d/relu_3x3_reduce <- inception_4d/3x3_reduce
I0707 18:30:43.801470 99468 net.cpp:367] inception_4d/relu_3x3_reduce -> inception_4d/3x3_reduce (in-place)
I0707 18:30:43.801980 99468 net.cpp:122] Setting up inception_4d/relu_3x3_reduce
I0707 18:30:43.802014 99468 net.cpp:129] Top shape: 64 144 14 14 (1806336)
I0707 18:30:43.802029 99468 net.cpp:137] Memory required for data: 3562466316
I0707 18:30:43.802043 99468 layer_factory.hpp:77] Creating layer inception_4d/3x3
I0707 18:30:43.802109 99468 net.cpp:84] Creating Layer inception_4d/3x3
I0707 18:30:43.802129 99468 net.cpp:406] inception_4d/3x3 <- inception_4d/3x3_reduce
I0707 18:30:43.802153 99468 net.cpp:380] inception_4d/3x3 -> inception_4d/3x3
I0707 18:30:43.812960 99468 net.cpp:122] Setting up inception_4d/3x3
I0707 18:30:43.813009 99468 net.cpp:129] Top shape: 64 288 14 14 (3612672)
I0707 18:30:43.813024 99468 net.cpp:137] Memory required for data: 3576917004
I0707 18:30:43.813079 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_3x3
I0707 18:30:43.813105 99468 net.cpp:84] Creating Layer inception_4d/relu_3x3
I0707 18:30:43.813124 99468 net.cpp:406] inception_4d/relu_3x3 <- inception_4d/3x3
I0707 18:30:43.813171 99468 net.cpp:367] inception_4d/relu_3x3 -> inception_4d/3x3 (in-place)
I0707 18:30:43.813679 99468 net.cpp:122] Setting up inception_4d/relu_3x3
I0707 18:30:43.813712 99468 net.cpp:129] Top shape: 64 288 14 14 (3612672)
I0707 18:30:43.813727 99468 net.cpp:137] Memory required for data: 3591367692
I0707 18:30:43.813742 99468 layer_factory.hpp:77] Creating layer inception_4d/5x5_reduce
I0707 18:30:43.813777 99468 net.cpp:84] Creating Layer inception_4d/5x5_reduce
I0707 18:30:43.813797 99468 net.cpp:406] inception_4d/5x5_reduce <- inception_4c/output_inception_4c/output_0_split_2
I0707 18:30:43.813858 99468 net.cpp:380] inception_4d/5x5_reduce -> inception_4d/5x5_reduce
I0707 18:30:43.819411 99468 net.cpp:122] Setting up inception_4d/5x5_reduce
I0707 18:30:43.819512 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.819532 99468 net.cpp:137] Memory required for data: 3592973324
I0707 18:30:43.819614 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_5x5_reduce
I0707 18:30:43.819694 99468 net.cpp:84] Creating Layer inception_4d/relu_5x5_reduce
I0707 18:30:43.819718 99468 net.cpp:406] inception_4d/relu_5x5_reduce <- inception_4d/5x5_reduce
I0707 18:30:43.819768 99468 net.cpp:367] inception_4d/relu_5x5_reduce -> inception_4d/5x5_reduce (in-place)
I0707 18:30:43.821403 99468 net.cpp:122] Setting up inception_4d/relu_5x5_reduce
I0707 18:30:43.821447 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.821463 99468 net.cpp:137] Memory required for data: 3594578956
I0707 18:30:43.821517 99468 layer_factory.hpp:77] Creating layer inception_4d/5x5
I0707 18:30:43.821585 99468 net.cpp:84] Creating Layer inception_4d/5x5
I0707 18:30:43.821607 99468 net.cpp:406] inception_4d/5x5 <- inception_4d/5x5_reduce
I0707 18:30:43.821656 99468 net.cpp:380] inception_4d/5x5 -> inception_4d/5x5
I0707 18:30:43.827756 99468 net.cpp:122] Setting up inception_4d/5x5
I0707 18:30:43.827805 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.827821 99468 net.cpp:137] Memory required for data: 3597790220
I0707 18:30:43.827843 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_5x5
I0707 18:30:43.827873 99468 net.cpp:84] Creating Layer inception_4d/relu_5x5
I0707 18:30:43.827893 99468 net.cpp:406] inception_4d/relu_5x5 <- inception_4d/5x5
I0707 18:30:43.827945 99468 net.cpp:367] inception_4d/relu_5x5 -> inception_4d/5x5 (in-place)
I0707 18:30:43.828440 99468 net.cpp:122] Setting up inception_4d/relu_5x5
I0707 18:30:43.828474 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.828487 99468 net.cpp:137] Memory required for data: 3601001484
I0707 18:30:43.828502 99468 layer_factory.hpp:77] Creating layer inception_4d/pool
I0707 18:30:43.828567 99468 net.cpp:84] Creating Layer inception_4d/pool
I0707 18:30:43.828625 99468 net.cpp:406] inception_4d/pool <- inception_4c/output_inception_4c/output_0_split_3
I0707 18:30:43.828647 99468 net.cpp:380] inception_4d/pool -> inception_4d/pool
I0707 18:30:43.828773 99468 net.cpp:122] Setting up inception_4d/pool
I0707 18:30:43.828800 99468 net.cpp:129] Top shape: 64 512 14 14 (6422528)
I0707 18:30:43.828833 99468 net.cpp:137] Memory required for data: 3626691596
I0707 18:30:43.828850 99468 layer_factory.hpp:77] Creating layer inception_4d/pool_proj
I0707 18:30:43.828898 99468 net.cpp:84] Creating Layer inception_4d/pool_proj
I0707 18:30:43.828922 99468 net.cpp:406] inception_4d/pool_proj <- inception_4d/pool
I0707 18:30:43.828949 99468 net.cpp:380] inception_4d/pool_proj -> inception_4d/pool_proj
I0707 18:30:43.833534 99468 net.cpp:122] Setting up inception_4d/pool_proj
I0707 18:30:43.833590 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.833636 99468 net.cpp:137] Memory required for data: 3629902860
I0707 18:30:43.833680 99468 layer_factory.hpp:77] Creating layer inception_4d/relu_pool_proj
I0707 18:30:43.833709 99468 net.cpp:84] Creating Layer inception_4d/relu_pool_proj
I0707 18:30:43.833745 99468 net.cpp:406] inception_4d/relu_pool_proj <- inception_4d/pool_proj
I0707 18:30:43.833784 99468 net.cpp:367] inception_4d/relu_pool_proj -> inception_4d/pool_proj (in-place)
I0707 18:30:43.834285 99468 net.cpp:122] Setting up inception_4d/relu_pool_proj
I0707 18:30:43.834317 99468 net.cpp:129] Top shape: 64 64 14 14 (802816)
I0707 18:30:43.834332 99468 net.cpp:137] Memory required for data: 3633114124
I0707 18:30:43.834347 99468 layer_factory.hpp:77] Creating layer inception_4d/output
I0707 18:30:43.834373 99468 net.cpp:84] Creating Layer inception_4d/output
I0707 18:30:43.834398 99468 net.cpp:406] inception_4d/output <- inception_4d/1x1
I0707 18:30:43.834422 99468 net.cpp:406] inception_4d/output <- inception_4d/3x3
I0707 18:30:43.834444 99468 net.cpp:406] inception_4d/output <- inception_4d/5x5
I0707 18:30:43.834466 99468 net.cpp:406] inception_4d/output <- inception_4d/pool_proj
I0707 18:30:43.834491 99468 net.cpp:380] inception_4d/output -> inception_4d/output
I0707 18:30:43.834581 99468 net.cpp:122] Setting up inception_4d/output
I0707 18:30:43.834612 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.834635 99468 net.cpp:137] Memory required for data: 3659607052
I0707 18:30:43.834659 99468 layer_factory.hpp:77] Creating layer inception_4d/output_inception_4d/output_0_split
I0707 18:30:43.834686 99468 net.cpp:84] Creating Layer inception_4d/output_inception_4d/output_0_split
I0707 18:30:43.834707 99468 net.cpp:406] inception_4d/output_inception_4d/output_0_split <- inception_4d/output
I0707 18:30:43.834733 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_0
I0707 18:30:43.834765 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_1
I0707 18:30:43.834792 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_2
I0707 18:30:43.834818 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_3
I0707 18:30:43.834841 99468 net.cpp:380] inception_4d/output_inception_4d/output_0_split -> inception_4d/output_inception_4d/output_0_split_4
I0707 18:30:43.835011 99468 net.cpp:122] Setting up inception_4d/output_inception_4d/output_0_split
I0707 18:30:43.835037 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.835057 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.835078 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.835098 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.835115 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.835136 99468 net.cpp:137] Memory required for data: 3792071692
I0707 18:30:43.835153 99468 layer_factory.hpp:77] Creating layer loss2/ave_pool
I0707 18:30:43.835206 99468 net.cpp:84] Creating Layer loss2/ave_pool
I0707 18:30:43.835232 99468 net.cpp:406] loss2/ave_pool <- inception_4d/output_inception_4d/output_0_split_0
I0707 18:30:43.835275 99468 net.cpp:380] loss2/ave_pool -> loss2/ave_pool
I0707 18:30:43.836910 99468 net.cpp:122] Setting up loss2/ave_pool
I0707 18:30:43.836956 99468 net.cpp:129] Top shape: 64 528 4 4 (540672)
I0707 18:30:43.837007 99468 net.cpp:137] Memory required for data: 3794234380
I0707 18:30:43.837023 99468 layer_factory.hpp:77] Creating layer loss2/conv
I0707 18:30:43.837076 99468 net.cpp:84] Creating Layer loss2/conv
I0707 18:30:43.837116 99468 net.cpp:406] loss2/conv <- loss2/ave_pool
I0707 18:30:43.837163 99468 net.cpp:380] loss2/conv -> loss2/conv
I0707 18:30:43.842356 99468 net.cpp:122] Setting up loss2/conv
I0707 18:30:43.842406 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.842447 99468 net.cpp:137] Memory required for data: 3794758668
I0707 18:30:43.842478 99468 layer_factory.hpp:77] Creating layer loss2/relu_conv
I0707 18:30:43.842571 99468 net.cpp:84] Creating Layer loss2/relu_conv
I0707 18:30:43.842597 99468 net.cpp:406] loss2/relu_conv <- loss2/conv
I0707 18:30:43.842640 99468 net.cpp:367] loss2/relu_conv -> loss2/conv (in-place)
I0707 18:30:43.843134 99468 net.cpp:122] Setting up loss2/relu_conv
I0707 18:30:43.843169 99468 net.cpp:129] Top shape: 64 128 4 4 (131072)
I0707 18:30:43.843186 99468 net.cpp:137] Memory required for data: 3795282956
I0707 18:30:43.843224 99468 layer_factory.hpp:77] Creating layer loss2/fc
I0707 18:30:43.843272 99468 net.cpp:84] Creating Layer loss2/fc
I0707 18:30:43.843297 99468 net.cpp:406] loss2/fc <- loss2/conv
I0707 18:30:43.843322 99468 net.cpp:380] loss2/fc -> loss2/fc
I0707 18:30:43.876996 99468 net.cpp:122] Setting up loss2/fc
I0707 18:30:43.877043 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.877058 99468 net.cpp:137] Memory required for data: 3795545100
I0707 18:30:43.877121 99468 layer_factory.hpp:77] Creating layer loss2/relu_fc
I0707 18:30:43.877151 99468 net.cpp:84] Creating Layer loss2/relu_fc
I0707 18:30:43.877172 99468 net.cpp:406] loss2/relu_fc <- loss2/fc
I0707 18:30:43.877205 99468 net.cpp:367] loss2/relu_fc -> loss2/fc (in-place)
I0707 18:30:43.878969 99468 net.cpp:122] Setting up loss2/relu_fc
I0707 18:30:43.879017 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.879032 99468 net.cpp:137] Memory required for data: 3795807244
I0707 18:30:43.879091 99468 layer_factory.hpp:77] Creating layer loss2/drop_fc
I0707 18:30:43.879120 99468 net.cpp:84] Creating Layer loss2/drop_fc
I0707 18:30:43.879160 99468 net.cpp:406] loss2/drop_fc <- loss2/fc
I0707 18:30:43.879192 99468 net.cpp:367] loss2/drop_fc -> loss2/fc (in-place)
I0707 18:30:43.879266 99468 net.cpp:122] Setting up loss2/drop_fc
I0707 18:30:43.879292 99468 net.cpp:129] Top shape: 64 1024 (65536)
I0707 18:30:43.879334 99468 net.cpp:137] Memory required for data: 3796069388
I0707 18:30:43.879353 99468 layer_factory.hpp:77] Creating layer loss2/classifier_my
I0707 18:30:43.879401 99468 net.cpp:84] Creating Layer loss2/classifier_my
I0707 18:30:43.879420 99468 net.cpp:406] loss2/classifier_my <- loss2/fc
I0707 18:30:43.879469 99468 net.cpp:380] loss2/classifier_my -> loss2/classifier
I0707 18:30:43.880264 99468 net.cpp:122] Setting up loss2/classifier_my
I0707 18:30:43.880296 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.880311 99468 net.cpp:137] Memory required for data: 3796079372
I0707 18:30:43.880333 99468 layer_factory.hpp:77] Creating layer loss2/classifier_loss2/classifier_my_0_split
I0707 18:30:43.880362 99468 net.cpp:84] Creating Layer loss2/classifier_loss2/classifier_my_0_split
I0707 18:30:43.880383 99468 net.cpp:406] loss2/classifier_loss2/classifier_my_0_split <- loss2/classifier
I0707 18:30:43.880403 99468 net.cpp:380] loss2/classifier_loss2/classifier_my_0_split -> loss2/classifier_loss2/classifier_my_0_split_0
I0707 18:30:43.880434 99468 net.cpp:380] loss2/classifier_loss2/classifier_my_0_split -> loss2/classifier_loss2/classifier_my_0_split_1
I0707 18:30:43.880494 99468 net.cpp:380] loss2/classifier_loss2/classifier_my_0_split -> loss2/classifier_loss2/classifier_my_0_split_2
I0707 18:30:43.880630 99468 net.cpp:122] Setting up loss2/classifier_loss2/classifier_my_0_split
I0707 18:30:43.880659 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.880676 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.880703 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:43.880722 99468 net.cpp:137] Memory required for data: 3796109324
I0707 18:30:43.880738 99468 layer_factory.hpp:77] Creating layer loss2/loss
I0707 18:30:43.880769 99468 net.cpp:84] Creating Layer loss2/loss
I0707 18:30:43.880797 99468 net.cpp:406] loss2/loss <- loss2/classifier_loss2/classifier_my_0_split_0
I0707 18:30:43.880825 99468 net.cpp:406] loss2/loss <- label_data_1_split_3
I0707 18:30:43.880847 99468 net.cpp:380] loss2/loss -> loss2/loss2
I0707 18:30:43.880880 99468 layer_factory.hpp:77] Creating layer loss2/loss
I0707 18:30:43.881695 99468 net.cpp:122] Setting up loss2/loss
I0707 18:30:43.881734 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.881757 99468 net.cpp:132]     with loss weight 0.3
I0707 18:30:43.881820 99468 net.cpp:137] Memory required for data: 3796109328
I0707 18:30:43.881846 99468 layer_factory.hpp:77] Creating layer loss2/top-1
I0707 18:30:43.881873 99468 net.cpp:84] Creating Layer loss2/top-1
I0707 18:30:43.881899 99468 net.cpp:406] loss2/top-1 <- loss2/classifier_loss2/classifier_my_0_split_1
I0707 18:30:43.881924 99468 net.cpp:406] loss2/top-1 <- label_data_1_split_4
I0707 18:30:43.881955 99468 net.cpp:380] loss2/top-1 -> loss2/top-1
I0707 18:30:43.881994 99468 net.cpp:122] Setting up loss2/top-1
I0707 18:30:43.882016 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.882040 99468 net.cpp:137] Memory required for data: 3796109332
I0707 18:30:43.882055 99468 layer_factory.hpp:77] Creating layer loss2/top-5
I0707 18:30:43.882083 99468 net.cpp:84] Creating Layer loss2/top-5
I0707 18:30:43.882102 99468 net.cpp:406] loss2/top-5 <- loss2/classifier_loss2/classifier_my_0_split_2
I0707 18:30:43.882127 99468 net.cpp:406] loss2/top-5 <- label_data_1_split_5
I0707 18:30:43.882153 99468 net.cpp:380] loss2/top-5 -> loss2/top-5
I0707 18:30:43.882184 99468 net.cpp:122] Setting up loss2/top-5
I0707 18:30:43.882205 99468 net.cpp:129] Top shape: (1)
I0707 18:30:43.882225 99468 net.cpp:137] Memory required for data: 3796109336
I0707 18:30:43.882246 99468 layer_factory.hpp:77] Creating layer inception_4e/1x1
I0707 18:30:43.882278 99468 net.cpp:84] Creating Layer inception_4e/1x1
I0707 18:30:43.882300 99468 net.cpp:406] inception_4e/1x1 <- inception_4d/output_inception_4d/output_0_split_1
I0707 18:30:43.882328 99468 net.cpp:380] inception_4e/1x1 -> inception_4e/1x1
I0707 18:30:43.889796 99468 net.cpp:122] Setting up inception_4e/1x1
I0707 18:30:43.889850 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.889912 99468 net.cpp:137] Memory required for data: 3808954392
I0707 18:30:43.889961 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_1x1
I0707 18:30:43.890008 99468 net.cpp:84] Creating Layer inception_4e/relu_1x1
I0707 18:30:43.890048 99468 net.cpp:406] inception_4e/relu_1x1 <- inception_4e/1x1
I0707 18:30:43.890099 99468 net.cpp:367] inception_4e/relu_1x1 -> inception_4e/1x1 (in-place)
I0707 18:30:43.891784 99468 net.cpp:122] Setting up inception_4e/relu_1x1
I0707 18:30:43.891832 99468 net.cpp:129] Top shape: 64 256 14 14 (3211264)
I0707 18:30:43.891849 99468 net.cpp:137] Memory required for data: 3821799448
I0707 18:30:43.891906 99468 layer_factory.hpp:77] Creating layer inception_4e/3x3_reduce
I0707 18:30:43.891968 99468 net.cpp:84] Creating Layer inception_4e/3x3_reduce
I0707 18:30:43.891990 99468 net.cpp:406] inception_4e/3x3_reduce <- inception_4d/output_inception_4d/output_0_split_2
I0707 18:30:43.892014 99468 net.cpp:380] inception_4e/3x3_reduce -> inception_4e/3x3_reduce
I0707 18:30:43.897668 99468 net.cpp:122] Setting up inception_4e/3x3_reduce
I0707 18:30:43.897719 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.897811 99468 net.cpp:137] Memory required for data: 3829827608
I0707 18:30:43.897838 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_3x3_reduce
I0707 18:30:43.897866 99468 net.cpp:84] Creating Layer inception_4e/relu_3x3_reduce
I0707 18:30:43.897888 99468 net.cpp:406] inception_4e/relu_3x3_reduce <- inception_4e/3x3_reduce
I0707 18:30:43.897936 99468 net.cpp:367] inception_4e/relu_3x3_reduce -> inception_4e/3x3_reduce (in-place)
I0707 18:30:43.899651 99468 net.cpp:122] Setting up inception_4e/relu_3x3_reduce
I0707 18:30:43.899698 99468 net.cpp:129] Top shape: 64 160 14 14 (2007040)
I0707 18:30:43.899713 99468 net.cpp:137] Memory required for data: 3837855768
I0707 18:30:43.899734 99468 layer_factory.hpp:77] Creating layer inception_4e/3x3
I0707 18:30:43.899777 99468 net.cpp:84] Creating Layer inception_4e/3x3
I0707 18:30:43.899799 99468 net.cpp:406] inception_4e/3x3 <- inception_4e/3x3_reduce
I0707 18:30:43.899864 99468 net.cpp:380] inception_4e/3x3 -> inception_4e/3x3
I0707 18:30:43.912102 99468 net.cpp:122] Setting up inception_4e/3x3
I0707 18:30:43.912163 99468 net.cpp:129] Top shape: 64 320 14 14 (4014080)
I0707 18:30:43.912181 99468 net.cpp:137] Memory required for data: 3853912088
I0707 18:30:43.912206 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_3x3
I0707 18:30:43.912273 99468 net.cpp:84] Creating Layer inception_4e/relu_3x3
I0707 18:30:43.912294 99468 net.cpp:406] inception_4e/relu_3x3 <- inception_4e/3x3
I0707 18:30:43.912339 99468 net.cpp:367] inception_4e/relu_3x3 -> inception_4e/3x3 (in-place)
I0707 18:30:43.912901 99468 net.cpp:122] Setting up inception_4e/relu_3x3
I0707 18:30:43.912940 99468 net.cpp:129] Top shape: 64 320 14 14 (4014080)
I0707 18:30:43.912955 99468 net.cpp:137] Memory required for data: 3869968408
I0707 18:30:43.912971 99468 layer_factory.hpp:77] Creating layer inception_4e/5x5_reduce
I0707 18:30:43.913012 99468 net.cpp:84] Creating Layer inception_4e/5x5_reduce
I0707 18:30:43.913033 99468 net.cpp:406] inception_4e/5x5_reduce <- inception_4d/output_inception_4d/output_0_split_3
I0707 18:30:43.913105 99468 net.cpp:380] inception_4e/5x5_reduce -> inception_4e/5x5_reduce
I0707 18:30:43.917722 99468 net.cpp:122] Setting up inception_4e/5x5_reduce
I0707 18:30:43.917774 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.917791 99468 net.cpp:137] Memory required for data: 3871574040
I0707 18:30:43.917856 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_5x5_reduce
I0707 18:30:43.917886 99468 net.cpp:84] Creating Layer inception_4e/relu_5x5_reduce
I0707 18:30:43.917908 99468 net.cpp:406] inception_4e/relu_5x5_reduce <- inception_4e/5x5_reduce
I0707 18:30:43.917951 99468 net.cpp:367] inception_4e/relu_5x5_reduce -> inception_4e/5x5_reduce (in-place)
I0707 18:30:43.919615 99468 net.cpp:122] Setting up inception_4e/relu_5x5_reduce
I0707 18:30:43.919662 99468 net.cpp:129] Top shape: 64 32 14 14 (401408)
I0707 18:30:43.919678 99468 net.cpp:137] Memory required for data: 3873179672
I0707 18:30:43.919734 99468 layer_factory.hpp:77] Creating layer inception_4e/5x5
I0707 18:30:43.919792 99468 net.cpp:84] Creating Layer inception_4e/5x5
I0707 18:30:43.919814 99468 net.cpp:406] inception_4e/5x5 <- inception_4e/5x5_reduce
I0707 18:30:43.919845 99468 net.cpp:380] inception_4e/5x5 -> inception_4e/5x5
I0707 18:30:43.925164 99468 net.cpp:122] Setting up inception_4e/5x5
I0707 18:30:43.925202 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.925212 99468 net.cpp:137] Memory required for data: 3879602200
I0707 18:30:43.925226 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_5x5
I0707 18:30:43.925242 99468 net.cpp:84] Creating Layer inception_4e/relu_5x5
I0707 18:30:43.925256 99468 net.cpp:406] inception_4e/relu_5x5 <- inception_4e/5x5
I0707 18:30:43.925277 99468 net.cpp:367] inception_4e/relu_5x5 -> inception_4e/5x5 (in-place)
I0707 18:30:43.926376 99468 net.cpp:122] Setting up inception_4e/relu_5x5
I0707 18:30:43.926409 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.926419 99468 net.cpp:137] Memory required for data: 3886024728
I0707 18:30:43.926494 99468 layer_factory.hpp:77] Creating layer inception_4e/pool
I0707 18:30:43.926522 99468 net.cpp:84] Creating Layer inception_4e/pool
I0707 18:30:43.926537 99468 net.cpp:406] inception_4e/pool <- inception_4d/output_inception_4d/output_0_split_4
I0707 18:30:43.926566 99468 net.cpp:380] inception_4e/pool -> inception_4e/pool
I0707 18:30:43.926647 99468 net.cpp:122] Setting up inception_4e/pool
I0707 18:30:43.926671 99468 net.cpp:129] Top shape: 64 528 14 14 (6623232)
I0707 18:30:43.926707 99468 net.cpp:137] Memory required for data: 3912517656
I0707 18:30:43.926720 99468 layer_factory.hpp:77] Creating layer inception_4e/pool_proj
I0707 18:30:43.926764 99468 net.cpp:84] Creating Layer inception_4e/pool_proj
I0707 18:30:43.926798 99468 net.cpp:406] inception_4e/pool_proj <- inception_4e/pool
I0707 18:30:43.926823 99468 net.cpp:380] inception_4e/pool_proj -> inception_4e/pool_proj
I0707 18:30:43.930171 99468 net.cpp:122] Setting up inception_4e/pool_proj
I0707 18:30:43.930209 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.930248 99468 net.cpp:137] Memory required for data: 3918940184
I0707 18:30:43.930263 99468 layer_factory.hpp:77] Creating layer inception_4e/relu_pool_proj
I0707 18:30:43.930302 99468 net.cpp:84] Creating Layer inception_4e/relu_pool_proj
I0707 18:30:43.930316 99468 net.cpp:406] inception_4e/relu_pool_proj <- inception_4e/pool_proj
I0707 18:30:43.930335 99468 net.cpp:367] inception_4e/relu_pool_proj -> inception_4e/pool_proj (in-place)
I0707 18:30:43.930726 99468 net.cpp:122] Setting up inception_4e/relu_pool_proj
I0707 18:30:43.930754 99468 net.cpp:129] Top shape: 64 128 14 14 (1605632)
I0707 18:30:43.930770 99468 net.cpp:137] Memory required for data: 3925362712
I0707 18:30:43.930781 99468 layer_factory.hpp:77] Creating layer inception_4e/output
I0707 18:30:43.930801 99468 net.cpp:84] Creating Layer inception_4e/output
I0707 18:30:43.930816 99468 net.cpp:406] inception_4e/output <- inception_4e/1x1
I0707 18:30:43.930833 99468 net.cpp:406] inception_4e/output <- inception_4e/3x3
I0707 18:30:43.930851 99468 net.cpp:406] inception_4e/output <- inception_4e/5x5
I0707 18:30:43.930863 99468 net.cpp:406] inception_4e/output <- inception_4e/pool_proj
I0707 18:30:43.930886 99468 net.cpp:380] inception_4e/output -> inception_4e/output
I0707 18:30:43.930944 99468 net.cpp:122] Setting up inception_4e/output
I0707 18:30:43.930968 99468 net.cpp:129] Top shape: 64 832 14 14 (10436608)
I0707 18:30:43.930982 99468 net.cpp:137] Memory required for data: 3967109144
I0707 18:30:43.930992 99468 layer_factory.hpp:77] Creating layer pool4/3x3_s2
I0707 18:30:43.931012 99468 net.cpp:84] Creating Layer pool4/3x3_s2
I0707 18:30:43.931025 99468 net.cpp:406] pool4/3x3_s2 <- inception_4e/output
I0707 18:30:43.931044 99468 net.cpp:380] pool4/3x3_s2 -> pool4/3x3_s2
I0707 18:30:43.931114 99468 net.cpp:122] Setting up pool4/3x3_s2
I0707 18:30:43.931135 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.931150 99468 net.cpp:137] Memory required for data: 3977545752
I0707 18:30:43.931161 99468 layer_factory.hpp:77] Creating layer pool4/3x3_s2_pool4/3x3_s2_0_split
I0707 18:30:43.931175 99468 net.cpp:84] Creating Layer pool4/3x3_s2_pool4/3x3_s2_0_split
I0707 18:30:43.931190 99468 net.cpp:406] pool4/3x3_s2_pool4/3x3_s2_0_split <- pool4/3x3_s2
I0707 18:30:43.931210 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_0
I0707 18:30:43.931231 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_1
I0707 18:30:43.931247 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_2
I0707 18:30:43.931269 99468 net.cpp:380] pool4/3x3_s2_pool4/3x3_s2_0_split -> pool4/3x3_s2_pool4/3x3_s2_0_split_3
I0707 18:30:43.931358 99468 net.cpp:122] Setting up pool4/3x3_s2_pool4/3x3_s2_0_split
I0707 18:30:43.931380 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.931396 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.931409 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.931447 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.931463 99468 net.cpp:137] Memory required for data: 4019292184
I0707 18:30:43.931474 99468 layer_factory.hpp:77] Creating layer inception_5a/1x1
I0707 18:30:43.931502 99468 net.cpp:84] Creating Layer inception_5a/1x1
I0707 18:30:43.931527 99468 net.cpp:406] inception_5a/1x1 <- pool4/3x3_s2_pool4/3x3_s2_0_split_0
I0707 18:30:43.931546 99468 net.cpp:380] inception_5a/1x1 -> inception_5a/1x1
I0707 18:30:43.937026 99468 net.cpp:122] Setting up inception_5a/1x1
I0707 18:30:43.937064 99468 net.cpp:129] Top shape: 64 256 7 7 (802816)
I0707 18:30:43.937122 99468 net.cpp:137] Memory required for data: 4022503448
I0707 18:30:43.937144 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_1x1
I0707 18:30:43.937186 99468 net.cpp:84] Creating Layer inception_5a/relu_1x1
I0707 18:30:43.937222 99468 net.cpp:406] inception_5a/relu_1x1 <- inception_5a/1x1
I0707 18:30:43.937242 99468 net.cpp:367] inception_5a/relu_1x1 -> inception_5a/1x1 (in-place)
I0707 18:30:43.938315 99468 net.cpp:122] Setting up inception_5a/relu_1x1
I0707 18:30:43.938349 99468 net.cpp:129] Top shape: 64 256 7 7 (802816)
I0707 18:30:43.938362 99468 net.cpp:137] Memory required for data: 4025714712
I0707 18:30:43.938372 99468 layer_factory.hpp:77] Creating layer inception_5a/3x3_reduce
I0707 18:30:43.938393 99468 net.cpp:84] Creating Layer inception_5a/3x3_reduce
I0707 18:30:43.938446 99468 net.cpp:406] inception_5a/3x3_reduce <- pool4/3x3_s2_pool4/3x3_s2_0_split_1
I0707 18:30:43.938465 99468 net.cpp:380] inception_5a/3x3_reduce -> inception_5a/3x3_reduce
I0707 18:30:43.942659 99468 net.cpp:122] Setting up inception_5a/3x3_reduce
I0707 18:30:43.942695 99468 net.cpp:129] Top shape: 64 160 7 7 (501760)
I0707 18:30:43.942705 99468 net.cpp:137] Memory required for data: 4027721752
I0707 18:30:43.942720 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_3x3_reduce
I0707 18:30:43.942740 99468 net.cpp:84] Creating Layer inception_5a/relu_3x3_reduce
I0707 18:30:43.942759 99468 net.cpp:406] inception_5a/relu_3x3_reduce <- inception_5a/3x3_reduce
I0707 18:30:43.942775 99468 net.cpp:367] inception_5a/relu_3x3_reduce -> inception_5a/3x3_reduce (in-place)
I0707 18:30:43.943831 99468 net.cpp:122] Setting up inception_5a/relu_3x3_reduce
I0707 18:30:43.943864 99468 net.cpp:129] Top shape: 64 160 7 7 (501760)
I0707 18:30:43.943874 99468 net.cpp:137] Memory required for data: 4029728792
I0707 18:30:43.943884 99468 layer_factory.hpp:77] Creating layer inception_5a/3x3
I0707 18:30:43.943908 99468 net.cpp:84] Creating Layer inception_5a/3x3
I0707 18:30:43.943928 99468 net.cpp:406] inception_5a/3x3 <- inception_5a/3x3_reduce
I0707 18:30:43.943944 99468 net.cpp:380] inception_5a/3x3 -> inception_5a/3x3
I0707 18:30:43.951853 99468 net.cpp:122] Setting up inception_5a/3x3
I0707 18:30:43.951889 99468 net.cpp:129] Top shape: 64 320 7 7 (1003520)
I0707 18:30:43.951900 99468 net.cpp:137] Memory required for data: 4033742872
I0707 18:30:43.951913 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_3x3
I0707 18:30:43.951972 99468 net.cpp:84] Creating Layer inception_5a/relu_3x3
I0707 18:30:43.951985 99468 net.cpp:406] inception_5a/relu_3x3 <- inception_5a/3x3
I0707 18:30:43.952000 99468 net.cpp:367] inception_5a/relu_3x3 -> inception_5a/3x3 (in-place)
I0707 18:30:43.953061 99468 net.cpp:122] Setting up inception_5a/relu_3x3
I0707 18:30:43.953094 99468 net.cpp:129] Top shape: 64 320 7 7 (1003520)
I0707 18:30:43.953102 99468 net.cpp:137] Memory required for data: 4037756952
I0707 18:30:43.953112 99468 layer_factory.hpp:77] Creating layer inception_5a/5x5_reduce
I0707 18:30:43.953138 99468 net.cpp:84] Creating Layer inception_5a/5x5_reduce
I0707 18:30:43.953155 99468 net.cpp:406] inception_5a/5x5_reduce <- pool4/3x3_s2_pool4/3x3_s2_0_split_2
I0707 18:30:43.953171 99468 net.cpp:380] inception_5a/5x5_reduce -> inception_5a/5x5_reduce
I0707 18:30:43.957187 99468 net.cpp:122] Setting up inception_5a/5x5_reduce
I0707 18:30:43.957222 99468 net.cpp:129] Top shape: 64 32 7 7 (100352)
I0707 18:30:43.957254 99468 net.cpp:137] Memory required for data: 4038158360
I0707 18:30:43.957273 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_5x5_reduce
I0707 18:30:43.957293 99468 net.cpp:84] Creating Layer inception_5a/relu_5x5_reduce
I0707 18:30:43.957309 99468 net.cpp:406] inception_5a/relu_5x5_reduce <- inception_5a/5x5_reduce
I0707 18:30:43.957320 99468 net.cpp:367] inception_5a/relu_5x5_reduce -> inception_5a/5x5_reduce (in-place)
I0707 18:30:43.958390 99468 net.cpp:122] Setting up inception_5a/relu_5x5_reduce
I0707 18:30:43.958425 99468 net.cpp:129] Top shape: 64 32 7 7 (100352)
I0707 18:30:43.958434 99468 net.cpp:137] Memory required for data: 4038559768
I0707 18:30:43.958443 99468 layer_factory.hpp:77] Creating layer inception_5a/5x5
I0707 18:30:43.958465 99468 net.cpp:84] Creating Layer inception_5a/5x5
I0707 18:30:43.958484 99468 net.cpp:406] inception_5a/5x5 <- inception_5a/5x5_reduce
I0707 18:30:43.958498 99468 net.cpp:380] inception_5a/5x5 -> inception_5a/5x5
I0707 18:30:43.961285 99468 net.cpp:122] Setting up inception_5a/5x5
I0707 18:30:43.961318 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.961328 99468 net.cpp:137] Memory required for data: 4040165400
I0707 18:30:43.961341 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_5x5
I0707 18:30:43.961360 99468 net.cpp:84] Creating Layer inception_5a/relu_5x5
I0707 18:30:43.961374 99468 net.cpp:406] inception_5a/relu_5x5 <- inception_5a/5x5
I0707 18:30:43.961390 99468 net.cpp:367] inception_5a/relu_5x5 -> inception_5a/5x5 (in-place)
I0707 18:30:43.962440 99468 net.cpp:122] Setting up inception_5a/relu_5x5
I0707 18:30:43.962473 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.962482 99468 net.cpp:137] Memory required for data: 4041771032
I0707 18:30:43.962492 99468 layer_factory.hpp:77] Creating layer inception_5a/pool
I0707 18:30:43.962507 99468 net.cpp:84] Creating Layer inception_5a/pool
I0707 18:30:43.962519 99468 net.cpp:406] inception_5a/pool <- pool4/3x3_s2_pool4/3x3_s2_0_split_3
I0707 18:30:43.962535 99468 net.cpp:380] inception_5a/pool -> inception_5a/pool
I0707 18:30:43.962630 99468 net.cpp:122] Setting up inception_5a/pool
I0707 18:30:43.962651 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.962693 99468 net.cpp:137] Memory required for data: 4052207640
I0707 18:30:43.962703 99468 layer_factory.hpp:77] Creating layer inception_5a/pool_proj
I0707 18:30:43.962745 99468 net.cpp:84] Creating Layer inception_5a/pool_proj
I0707 18:30:43.962757 99468 net.cpp:406] inception_5a/pool_proj <- inception_5a/pool
I0707 18:30:43.962780 99468 net.cpp:380] inception_5a/pool_proj -> inception_5a/pool_proj
I0707 18:30:43.967293 99468 net.cpp:122] Setting up inception_5a/pool_proj
I0707 18:30:43.967326 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.967335 99468 net.cpp:137] Memory required for data: 4053813272
I0707 18:30:43.967350 99468 layer_factory.hpp:77] Creating layer inception_5a/relu_pool_proj
I0707 18:30:43.967367 99468 net.cpp:84] Creating Layer inception_5a/relu_pool_proj
I0707 18:30:43.967381 99468 net.cpp:406] inception_5a/relu_pool_proj <- inception_5a/pool_proj
I0707 18:30:43.967428 99468 net.cpp:367] inception_5a/relu_pool_proj -> inception_5a/pool_proj (in-place)
I0707 18:30:43.967763 99468 net.cpp:122] Setting up inception_5a/relu_pool_proj
I0707 18:30:43.967790 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.967806 99468 net.cpp:137] Memory required for data: 4055418904
I0707 18:30:43.967818 99468 layer_factory.hpp:77] Creating layer inception_5a/output
I0707 18:30:43.967857 99468 net.cpp:84] Creating Layer inception_5a/output
I0707 18:30:43.967872 99468 net.cpp:406] inception_5a/output <- inception_5a/1x1
I0707 18:30:43.967901 99468 net.cpp:406] inception_5a/output <- inception_5a/3x3
I0707 18:30:43.967919 99468 net.cpp:406] inception_5a/output <- inception_5a/5x5
I0707 18:30:43.967936 99468 net.cpp:406] inception_5a/output <- inception_5a/pool_proj
I0707 18:30:43.967952 99468 net.cpp:380] inception_5a/output -> inception_5a/output
I0707 18:30:43.968040 99468 net.cpp:122] Setting up inception_5a/output
I0707 18:30:43.968065 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.968077 99468 net.cpp:137] Memory required for data: 4065855512
I0707 18:30:43.968086 99468 layer_factory.hpp:77] Creating layer inception_5a/output_inception_5a/output_0_split
I0707 18:30:43.968111 99468 net.cpp:84] Creating Layer inception_5a/output_inception_5a/output_0_split
I0707 18:30:43.968122 99468 net.cpp:406] inception_5a/output_inception_5a/output_0_split <- inception_5a/output
I0707 18:30:43.968138 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_0
I0707 18:30:43.968158 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_1
I0707 18:30:43.968171 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_2
I0707 18:30:43.968188 99468 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_3
I0707 18:30:43.968282 99468 net.cpp:122] Setting up inception_5a/output_inception_5a/output_0_split
I0707 18:30:43.968302 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.968317 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.968328 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.968339 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:43.968353 99468 net.cpp:137] Memory required for data: 4107601944
I0707 18:30:43.968363 99468 layer_factory.hpp:77] Creating layer inception_5b/1x1
I0707 18:30:43.968382 99468 net.cpp:84] Creating Layer inception_5b/1x1
I0707 18:30:43.968394 99468 net.cpp:406] inception_5b/1x1 <- inception_5a/output_inception_5a/output_0_split_0
I0707 18:30:43.968420 99468 net.cpp:380] inception_5b/1x1 -> inception_5b/1x1
I0707 18:30:43.974709 99468 net.cpp:122] Setting up inception_5b/1x1
I0707 18:30:43.974743 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.974793 99468 net.cpp:137] Memory required for data: 4112418840
I0707 18:30:43.974812 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_1x1
I0707 18:30:43.974846 99468 net.cpp:84] Creating Layer inception_5b/relu_1x1
I0707 18:30:43.974859 99468 net.cpp:406] inception_5b/relu_1x1 <- inception_5b/1x1
I0707 18:30:43.974884 99468 net.cpp:367] inception_5b/relu_1x1 -> inception_5b/1x1 (in-place)
I0707 18:30:43.975929 99468 net.cpp:122] Setting up inception_5b/relu_1x1
I0707 18:30:43.975958 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.975967 99468 net.cpp:137] Memory required for data: 4117235736
I0707 18:30:43.975977 99468 layer_factory.hpp:77] Creating layer inception_5b/3x3_reduce
I0707 18:30:43.975999 99468 net.cpp:84] Creating Layer inception_5b/3x3_reduce
I0707 18:30:43.976018 99468 net.cpp:406] inception_5b/3x3_reduce <- inception_5a/output_inception_5a/output_0_split_1
I0707 18:30:43.976037 99468 net.cpp:380] inception_5b/3x3_reduce -> inception_5b/3x3_reduce
I0707 18:30:43.980250 99468 net.cpp:122] Setting up inception_5b/3x3_reduce
I0707 18:30:43.980283 99468 net.cpp:129] Top shape: 64 192 7 7 (602112)
I0707 18:30:43.980293 99468 net.cpp:137] Memory required for data: 4119644184
I0707 18:30:43.980306 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_3x3_reduce
I0707 18:30:43.980324 99468 net.cpp:84] Creating Layer inception_5b/relu_3x3_reduce
I0707 18:30:43.980372 99468 net.cpp:406] inception_5b/relu_3x3_reduce <- inception_5b/3x3_reduce
I0707 18:30:43.980386 99468 net.cpp:367] inception_5b/relu_3x3_reduce -> inception_5b/3x3_reduce (in-place)
I0707 18:30:43.981412 99468 net.cpp:122] Setting up inception_5b/relu_3x3_reduce
I0707 18:30:43.981442 99468 net.cpp:129] Top shape: 64 192 7 7 (602112)
I0707 18:30:43.981451 99468 net.cpp:137] Memory required for data: 4122052632
I0707 18:30:43.981462 99468 layer_factory.hpp:77] Creating layer inception_5b/3x3
I0707 18:30:43.981483 99468 net.cpp:84] Creating Layer inception_5b/3x3
I0707 18:30:43.981562 99468 net.cpp:406] inception_5b/3x3 <- inception_5b/3x3_reduce
I0707 18:30:43.981585 99468 net.cpp:380] inception_5b/3x3 -> inception_5b/3x3
I0707 18:30:43.990972 99468 net.cpp:122] Setting up inception_5b/3x3
I0707 18:30:43.991004 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.991014 99468 net.cpp:137] Memory required for data: 4126869528
I0707 18:30:43.991029 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_3x3
I0707 18:30:43.991051 99468 net.cpp:84] Creating Layer inception_5b/relu_3x3
I0707 18:30:43.991065 99468 net.cpp:406] inception_5b/relu_3x3 <- inception_5b/3x3
I0707 18:30:43.991086 99468 net.cpp:367] inception_5b/relu_3x3 -> inception_5b/3x3 (in-place)
I0707 18:30:43.991454 99468 net.cpp:122] Setting up inception_5b/relu_3x3
I0707 18:30:43.991477 99468 net.cpp:129] Top shape: 64 384 7 7 (1204224)
I0707 18:30:43.991506 99468 net.cpp:137] Memory required for data: 4131686424
I0707 18:30:43.991519 99468 layer_factory.hpp:77] Creating layer inception_5b/5x5_reduce
I0707 18:30:43.991567 99468 net.cpp:84] Creating Layer inception_5b/5x5_reduce
I0707 18:30:43.991601 99468 net.cpp:406] inception_5b/5x5_reduce <- inception_5a/output_inception_5a/output_0_split_2
I0707 18:30:43.991622 99468 net.cpp:380] inception_5b/5x5_reduce -> inception_5b/5x5_reduce
I0707 18:30:43.994611 99468 net.cpp:122] Setting up inception_5b/5x5_reduce
I0707 18:30:43.994645 99468 net.cpp:129] Top shape: 64 48 7 7 (150528)
I0707 18:30:43.994655 99468 net.cpp:137] Memory required for data: 4132288536
I0707 18:30:43.994704 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_5x5_reduce
I0707 18:30:43.994721 99468 net.cpp:84] Creating Layer inception_5b/relu_5x5_reduce
I0707 18:30:43.994732 99468 net.cpp:406] inception_5b/relu_5x5_reduce <- inception_5b/5x5_reduce
I0707 18:30:43.994786 99468 net.cpp:367] inception_5b/relu_5x5_reduce -> inception_5b/5x5_reduce (in-place)
I0707 18:30:43.995798 99468 net.cpp:122] Setting up inception_5b/relu_5x5_reduce
I0707 18:30:43.995827 99468 net.cpp:129] Top shape: 64 48 7 7 (150528)
I0707 18:30:43.995836 99468 net.cpp:137] Memory required for data: 4132890648
I0707 18:30:43.995844 99468 layer_factory.hpp:77] Creating layer inception_5b/5x5
I0707 18:30:43.995867 99468 net.cpp:84] Creating Layer inception_5b/5x5
I0707 18:30:43.995914 99468 net.cpp:406] inception_5b/5x5 <- inception_5b/5x5_reduce
I0707 18:30:43.995949 99468 net.cpp:380] inception_5b/5x5 -> inception_5b/5x5
I0707 18:30:43.999718 99468 net.cpp:122] Setting up inception_5b/5x5
I0707 18:30:43.999749 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:43.999758 99468 net.cpp:137] Memory required for data: 4134496280
I0707 18:30:43.999773 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_5x5
I0707 18:30:43.999786 99468 net.cpp:84] Creating Layer inception_5b/relu_5x5
I0707 18:30:43.999804 99468 net.cpp:406] inception_5b/relu_5x5 <- inception_5b/5x5
I0707 18:30:43.999827 99468 net.cpp:367] inception_5b/relu_5x5 -> inception_5b/5x5 (in-place)
I0707 18:30:44.000819 99468 net.cpp:122] Setting up inception_5b/relu_5x5
I0707 18:30:44.000847 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:44.000856 99468 net.cpp:137] Memory required for data: 4136101912
I0707 18:30:44.000865 99468 layer_factory.hpp:77] Creating layer inception_5b/pool
I0707 18:30:44.000880 99468 net.cpp:84] Creating Layer inception_5b/pool
I0707 18:30:44.000892 99468 net.cpp:406] inception_5b/pool <- inception_5a/output_inception_5a/output_0_split_3
I0707 18:30:44.000915 99468 net.cpp:380] inception_5b/pool -> inception_5b/pool
I0707 18:30:44.000994 99468 net.cpp:122] Setting up inception_5b/pool
I0707 18:30:44.001015 99468 net.cpp:129] Top shape: 64 832 7 7 (2609152)
I0707 18:30:44.001027 99468 net.cpp:137] Memory required for data: 4146538520
I0707 18:30:44.001065 99468 layer_factory.hpp:77] Creating layer inception_5b/pool_proj
I0707 18:30:44.001088 99468 net.cpp:84] Creating Layer inception_5b/pool_proj
I0707 18:30:44.001106 99468 net.cpp:406] inception_5b/pool_proj <- inception_5b/pool
I0707 18:30:44.001166 99468 net.cpp:380] inception_5b/pool_proj -> inception_5b/pool_proj
I0707 18:30:44.005548 99468 net.cpp:122] Setting up inception_5b/pool_proj
I0707 18:30:44.005587 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:44.005597 99468 net.cpp:137] Memory required for data: 4148144152
I0707 18:30:44.005611 99468 layer_factory.hpp:77] Creating layer inception_5b/relu_pool_proj
I0707 18:30:44.005630 99468 net.cpp:84] Creating Layer inception_5b/relu_pool_proj
I0707 18:30:44.005645 99468 net.cpp:406] inception_5b/relu_pool_proj <- inception_5b/pool_proj
I0707 18:30:44.005656 99468 net.cpp:367] inception_5b/relu_pool_proj -> inception_5b/pool_proj (in-place)
I0707 18:30:44.005995 99468 net.cpp:122] Setting up inception_5b/relu_pool_proj
I0707 18:30:44.006021 99468 net.cpp:129] Top shape: 64 128 7 7 (401408)
I0707 18:30:44.006033 99468 net.cpp:137] Memory required for data: 4149749784
I0707 18:30:44.006047 99468 layer_factory.hpp:77] Creating layer inception_5b/output
I0707 18:30:44.006089 99468 net.cpp:84] Creating Layer inception_5b/output
I0707 18:30:44.006101 99468 net.cpp:406] inception_5b/output <- inception_5b/1x1
I0707 18:30:44.006112 99468 net.cpp:406] inception_5b/output <- inception_5b/3x3
I0707 18:30:44.006124 99468 net.cpp:406] inception_5b/output <- inception_5b/5x5
I0707 18:30:44.006139 99468 net.cpp:406] inception_5b/output <- inception_5b/pool_proj
I0707 18:30:44.006155 99468 net.cpp:380] inception_5b/output -> inception_5b/output
I0707 18:30:44.006227 99468 net.cpp:122] Setting up inception_5b/output
I0707 18:30:44.006244 99468 net.cpp:129] Top shape: 64 1024 7 7 (3211264)
I0707 18:30:44.006271 99468 net.cpp:137] Memory required for data: 4162594840
I0707 18:30:44.006283 99468 layer_factory.hpp:77] Creating layer pool5/7x7_s1
I0707 18:30:44.006302 99468 net.cpp:84] Creating Layer pool5/7x7_s1
I0707 18:30:44.006312 99468 net.cpp:406] pool5/7x7_s1 <- inception_5b/output
I0707 18:30:44.006342 99468 net.cpp:380] pool5/7x7_s1 -> pool5/7x7_s1
I0707 18:30:44.007359 99468 net.cpp:122] Setting up pool5/7x7_s1
I0707 18:30:44.007387 99468 net.cpp:129] Top shape: 64 1024 1 1 (65536)
I0707 18:30:44.007396 99468 net.cpp:137] Memory required for data: 4162856984
I0707 18:30:44.007405 99468 layer_factory.hpp:77] Creating layer pool5/drop_7x7_s1
I0707 18:30:44.007421 99468 net.cpp:84] Creating Layer pool5/drop_7x7_s1
I0707 18:30:44.007433 99468 net.cpp:406] pool5/drop_7x7_s1 <- pool5/7x7_s1
I0707 18:30:44.007450 99468 net.cpp:367] pool5/drop_7x7_s1 -> pool5/7x7_s1 (in-place)
I0707 18:30:44.007493 99468 net.cpp:122] Setting up pool5/drop_7x7_s1
I0707 18:30:44.007508 99468 net.cpp:129] Top shape: 64 1024 1 1 (65536)
I0707 18:30:44.007551 99468 net.cpp:137] Memory required for data: 4163119128
I0707 18:30:44.007568 99468 layer_factory.hpp:77] Creating layer fc8_kevin
I0707 18:30:44.007593 99468 net.cpp:84] Creating Layer fc8_kevin
I0707 18:30:44.007604 99468 net.cpp:406] fc8_kevin <- pool5/7x7_s1
I0707 18:30:44.007625 99468 net.cpp:380] fc8_kevin -> fc8_pascal
I0707 18:30:44.008725 99468 net.cpp:122] Setting up fc8_kevin
I0707 18:30:44.008747 99468 net.cpp:129] Top shape: 64 128 (8192)
I0707 18:30:44.008755 99468 net.cpp:137] Memory required for data: 4163151896
I0707 18:30:44.008767 99468 layer_factory.hpp:77] Creating layer fc8_kevin_encode
I0707 18:30:44.008785 99468 net.cpp:84] Creating Layer fc8_kevin_encode
I0707 18:30:44.008796 99468 net.cpp:406] fc8_kevin_encode <- fc8_pascal
I0707 18:30:44.008810 99468 net.cpp:380] fc8_kevin_encode -> fc8_kevin_encode
I0707 18:30:44.009150 99468 net.cpp:122] Setting up fc8_kevin_encode
I0707 18:30:44.009172 99468 net.cpp:129] Top shape: 64 128 (8192)
I0707 18:30:44.009188 99468 net.cpp:137] Memory required for data: 4163184664
I0707 18:30:44.009201 99468 layer_factory.hpp:77] Creating layer loss3/classifier_my
I0707 18:30:44.009227 99468 net.cpp:84] Creating Layer loss3/classifier_my
I0707 18:30:44.009240 99468 net.cpp:406] loss3/classifier_my <- fc8_kevin_encode
I0707 18:30:44.009255 99468 net.cpp:380] loss3/classifier_my -> loss3/classifier
I0707 18:30:44.009495 99468 net.cpp:122] Setting up loss3/classifier_my
I0707 18:30:44.009516 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:44.009531 99468 net.cpp:137] Memory required for data: 4163194648
I0707 18:30:44.009546 99468 layer_factory.hpp:77] Creating layer loss3/classifier_loss3/classifier_my_0_split
I0707 18:30:44.009569 99468 net.cpp:84] Creating Layer loss3/classifier_loss3/classifier_my_0_split
I0707 18:30:44.009582 99468 net.cpp:406] loss3/classifier_loss3/classifier_my_0_split <- loss3/classifier
I0707 18:30:44.009603 99468 net.cpp:380] loss3/classifier_loss3/classifier_my_0_split -> loss3/classifier_loss3/classifier_my_0_split_0
I0707 18:30:44.009623 99468 net.cpp:380] loss3/classifier_loss3/classifier_my_0_split -> loss3/classifier_loss3/classifier_my_0_split_1
I0707 18:30:44.009636 99468 net.cpp:380] loss3/classifier_loss3/classifier_my_0_split -> loss3/classifier_loss3/classifier_my_0_split_2
I0707 18:30:44.009717 99468 net.cpp:122] Setting up loss3/classifier_loss3/classifier_my_0_split
I0707 18:30:44.009735 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:44.009752 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:44.009760 99468 net.cpp:129] Top shape: 64 39 (2496)
I0707 18:30:44.009773 99468 net.cpp:137] Memory required for data: 4163224600
I0707 18:30:44.009788 99468 layer_factory.hpp:77] Creating layer loss3/loss3
I0707 18:30:44.009804 99468 net.cpp:84] Creating Layer loss3/loss3
I0707 18:30:44.009819 99468 net.cpp:406] loss3/loss3 <- loss3/classifier_loss3/classifier_my_0_split_0
I0707 18:30:44.009834 99468 net.cpp:406] loss3/loss3 <- label_data_1_split_6
I0707 18:30:44.009850 99468 net.cpp:380] loss3/loss3 -> loss3/loss3
I0707 18:30:44.009863 99468 layer_factory.hpp:77] Creating layer loss3/loss3
I0707 18:30:44.011031 99468 net.cpp:122] Setting up loss3/loss3
I0707 18:30:44.011062 99468 net.cpp:129] Top shape: (1)
I0707 18:30:44.011076 99468 net.cpp:132]     with loss weight 1
I0707 18:30:44.011091 99468 net.cpp:137] Memory required for data: 4163224604
I0707 18:30:44.011107 99468 layer_factory.hpp:77] Creating layer loss3/top-1
I0707 18:30:44.011126 99468 net.cpp:84] Creating Layer loss3/top-1
I0707 18:30:44.011137 99468 net.cpp:406] loss3/top-1 <- loss3/classifier_loss3/classifier_my_0_split_1
I0707 18:30:44.011157 99468 net.cpp:406] loss3/top-1 <- label_data_1_split_7
I0707 18:30:44.011169 99468 net.cpp:380] loss3/top-1 -> loss3/top-1
I0707 18:30:44.011188 99468 net.cpp:122] Setting up loss3/top-1
I0707 18:30:44.011200 99468 net.cpp:129] Top shape: (1)
I0707 18:30:44.011211 99468 net.cpp:137] Memory required for data: 4163224608
I0707 18:30:44.011225 99468 layer_factory.hpp:77] Creating layer loss3/top-5
I0707 18:30:44.011247 99468 net.cpp:84] Creating Layer loss3/top-5
I0707 18:30:44.011258 99468 net.cpp:406] loss3/top-5 <- loss3/classifier_loss3/classifier_my_0_split_2
I0707 18:30:44.011274 99468 net.cpp:406] loss3/top-5 <- label_data_1_split_8
I0707 18:30:44.011289 99468 net.cpp:380] loss3/top-5 -> loss3/top-5
I0707 18:30:44.011302 99468 net.cpp:122] Setting up loss3/top-5
I0707 18:30:44.011322 99468 net.cpp:129] Top shape: (1)
I0707 18:30:44.011335 99468 net.cpp:137] Memory required for data: 4163224612
I0707 18:30:44.011344 99468 net.cpp:200] loss3/top-5 does not need backward computation.
I0707 18:30:44.011353 99468 net.cpp:200] loss3/top-1 does not need backward computation.
I0707 18:30:44.011363 99468 net.cpp:198] loss3/loss3 needs backward computation.
I0707 18:30:44.011375 99468 net.cpp:198] loss3/classifier_loss3/classifier_my_0_split needs backward computation.
I0707 18:30:44.011391 99468 net.cpp:198] loss3/classifier_my needs backward computation.
I0707 18:30:44.011401 99468 net.cpp:198] fc8_kevin_encode needs backward computation.
I0707 18:30:44.011410 99468 net.cpp:198] fc8_kevin needs backward computation.
I0707 18:30:44.011423 99468 net.cpp:198] pool5/drop_7x7_s1 needs backward computation.
I0707 18:30:44.011438 99468 net.cpp:198] pool5/7x7_s1 needs backward computation.
I0707 18:30:44.011446 99468 net.cpp:198] inception_5b/output needs backward computation.
I0707 18:30:44.011483 99468 net.cpp:198] inception_5b/relu_pool_proj needs backward computation.
I0707 18:30:44.011497 99468 net.cpp:198] inception_5b/pool_proj needs backward computation.
I0707 18:30:44.011512 99468 net.cpp:198] inception_5b/pool needs backward computation.
I0707 18:30:44.011523 99468 net.cpp:198] inception_5b/relu_5x5 needs backward computation.
I0707 18:30:44.011533 99468 net.cpp:198] inception_5b/5x5 needs backward computation.
I0707 18:30:44.011543 99468 net.cpp:198] inception_5b/relu_5x5_reduce needs backward computation.
I0707 18:30:44.011561 99468 net.cpp:198] inception_5b/5x5_reduce needs backward computation.
I0707 18:30:44.011570 99468 net.cpp:198] inception_5b/relu_3x3 needs backward computation.
I0707 18:30:44.011582 99468 net.cpp:198] inception_5b/3x3 needs backward computation.
I0707 18:30:44.011591 99468 net.cpp:198] inception_5b/relu_3x3_reduce needs backward computation.
I0707 18:30:44.011603 99468 net.cpp:198] inception_5b/3x3_reduce needs backward computation.
I0707 18:30:44.011612 99468 net.cpp:198] inception_5b/relu_1x1 needs backward computation.
I0707 18:30:44.011624 99468 net.cpp:198] inception_5b/1x1 needs backward computation.
I0707 18:30:44.011636 99468 net.cpp:198] inception_5a/output_inception_5a/output_0_split needs backward computation.
I0707 18:30:44.011646 99468 net.cpp:198] inception_5a/output needs backward computation.
I0707 18:30:44.011656 99468 net.cpp:198] inception_5a/relu_pool_proj needs backward computation.
I0707 18:30:44.011664 99468 net.cpp:198] inception_5a/pool_proj needs backward computation.
I0707 18:30:44.011677 99468 net.cpp:198] inception_5a/pool needs backward computation.
I0707 18:30:44.011692 99468 net.cpp:198] inception_5a/relu_5x5 needs backward computation.
I0707 18:30:44.011699 99468 net.cpp:198] inception_5a/5x5 needs backward computation.
I0707 18:30:44.011713 99468 net.cpp:198] inception_5a/relu_5x5_reduce needs backward computation.
I0707 18:30:44.011725 99468 net.cpp:198] inception_5a/5x5_reduce needs backward computation.
I0707 18:30:44.011736 99468 net.cpp:198] inception_5a/relu_3x3 needs backward computation.
I0707 18:30:44.011744 99468 net.cpp:198] inception_5a/3x3 needs backward computation.
I0707 18:30:44.011754 99468 net.cpp:198] inception_5a/relu_3x3_reduce needs backward computation.
I0707 18:30:44.011764 99468 net.cpp:198] inception_5a/3x3_reduce needs backward computation.
I0707 18:30:44.011777 99468 net.cpp:198] inception_5a/relu_1x1 needs backward computation.
I0707 18:30:44.011792 99468 net.cpp:198] inception_5a/1x1 needs backward computation.
I0707 18:30:44.011801 99468 net.cpp:198] pool4/3x3_s2_pool4/3x3_s2_0_split needs backward computation.
I0707 18:30:44.011814 99468 net.cpp:198] pool4/3x3_s2 needs backward computation.
I0707 18:30:44.011823 99468 net.cpp:198] inception_4e/output needs backward computation.
I0707 18:30:44.011838 99468 net.cpp:198] inception_4e/relu_pool_proj needs backward computation.
I0707 18:30:44.011847 99468 net.cpp:198] inception_4e/pool_proj needs backward computation.
I0707 18:30:44.011857 99468 net.cpp:198] inception_4e/pool needs backward computation.
I0707 18:30:44.011868 99468 net.cpp:198] inception_4e/relu_5x5 needs backward computation.
I0707 18:30:44.011880 99468 net.cpp:198] inception_4e/5x5 needs backward computation.
I0707 18:30:44.011890 99468 net.cpp:198] inception_4e/relu_5x5_reduce needs backward computation.
I0707 18:30:44.011900 99468 net.cpp:198] inception_4e/5x5_reduce needs backward computation.
I0707 18:30:44.011912 99468 net.cpp:198] inception_4e/relu_3x3 needs backward computation.
I0707 18:30:44.011926 99468 net.cpp:198] inception_4e/3x3 needs backward computation.
I0707 18:30:44.011935 99468 net.cpp:198] inception_4e/relu_3x3_reduce needs backward computation.
I0707 18:30:44.011945 99468 net.cpp:198] inception_4e/3x3_reduce needs backward computation.
I0707 18:30:44.011957 99468 net.cpp:198] inception_4e/relu_1x1 needs backward computation.
I0707 18:30:44.011970 99468 net.cpp:198] inception_4e/1x1 needs backward computation.
I0707 18:30:44.011981 99468 net.cpp:200] loss2/top-5 does not need backward computation.
I0707 18:30:44.012006 99468 net.cpp:200] loss2/top-1 does not need backward computation.
I0707 18:30:44.012019 99468 net.cpp:198] loss2/loss needs backward computation.
I0707 18:30:44.012030 99468 net.cpp:198] loss2/classifier_loss2/classifier_my_0_split needs backward computation.
I0707 18:30:44.012043 99468 net.cpp:198] loss2/classifier_my needs backward computation.
I0707 18:30:44.012056 99468 net.cpp:198] loss2/drop_fc needs backward computation.
I0707 18:30:44.012069 99468 net.cpp:198] loss2/relu_fc needs backward computation.
I0707 18:30:44.012080 99468 net.cpp:198] loss2/fc needs backward computation.
I0707 18:30:44.012090 99468 net.cpp:198] loss2/relu_conv needs backward computation.
I0707 18:30:44.012104 99468 net.cpp:198] loss2/conv needs backward computation.
I0707 18:30:44.012116 99468 net.cpp:198] loss2/ave_pool needs backward computation.
I0707 18:30:44.012128 99468 net.cpp:198] inception_4d/output_inception_4d/output_0_split needs backward computation.
I0707 18:30:44.012140 99468 net.cpp:198] inception_4d/output needs backward computation.
I0707 18:30:44.012156 99468 net.cpp:198] inception_4d/relu_pool_proj needs backward computation.
I0707 18:30:44.012166 99468 net.cpp:198] inception_4d/pool_proj needs backward computation.
I0707 18:30:44.012179 99468 net.cpp:198] inception_4d/pool needs backward computation.
I0707 18:30:44.012192 99468 net.cpp:198] inception_4d/relu_5x5 needs backward computation.
I0707 18:30:44.012199 99468 net.cpp:198] inception_4d/5x5 needs backward computation.
I0707 18:30:44.012209 99468 net.cpp:198] inception_4d/relu_5x5_reduce needs backward computation.
I0707 18:30:44.012223 99468 net.cpp:198] inception_4d/5x5_reduce needs backward computation.
I0707 18:30:44.012234 99468 net.cpp:198] inception_4d/relu_3x3 needs backward computation.
I0707 18:30:44.012243 99468 net.cpp:198] inception_4d/3x3 needs backward computation.
I0707 18:30:44.012250 99468 net.cpp:198] inception_4d/relu_3x3_reduce needs backward computation.
I0707 18:30:44.012262 99468 net.cpp:198] inception_4d/3x3_reduce needs backward computation.
I0707 18:30:44.012276 99468 net.cpp:198] inception_4d/relu_1x1 needs backward computation.
I0707 18:30:44.012286 99468 net.cpp:198] inception_4d/1x1 needs backward computation.
I0707 18:30:44.012301 99468 net.cpp:198] inception_4c/output_inception_4c/output_0_split needs backward computation.
I0707 18:30:44.012313 99468 net.cpp:198] inception_4c/output needs backward computation.
I0707 18:30:44.012323 99468 net.cpp:198] inception_4c/relu_pool_proj needs backward computation.
I0707 18:30:44.012333 99468 net.cpp:198] inception_4c/pool_proj needs backward computation.
I0707 18:30:44.012344 99468 net.cpp:198] inception_4c/pool needs backward computation.
I0707 18:30:44.012358 99468 net.cpp:198] inception_4c/relu_5x5 needs backward computation.
I0707 18:30:44.012372 99468 net.cpp:198] inception_4c/5x5 needs backward computation.
I0707 18:30:44.012387 99468 net.cpp:198] inception_4c/relu_5x5_reduce needs backward computation.
I0707 18:30:44.012394 99468 net.cpp:198] inception_4c/5x5_reduce needs backward computation.
I0707 18:30:44.012408 99468 net.cpp:198] inception_4c/relu_3x3 needs backward computation.
I0707 18:30:44.012421 99468 net.cpp:198] inception_4c/3x3 needs backward computation.
I0707 18:30:44.012431 99468 net.cpp:198] inception_4c/relu_3x3_reduce needs backward computation.
I0707 18:30:44.012444 99468 net.cpp:198] inception_4c/3x3_reduce needs backward computation.
I0707 18:30:44.012452 99468 net.cpp:198] inception_4c/relu_1x1 needs backward computation.
I0707 18:30:44.012467 99468 net.cpp:198] inception_4c/1x1 needs backward computation.
I0707 18:30:44.012480 99468 net.cpp:198] inception_4b/output_inception_4b/output_0_split needs backward computation.
I0707 18:30:44.012492 99468 net.cpp:198] inception_4b/output needs backward computation.
I0707 18:30:44.012507 99468 net.cpp:198] inception_4b/relu_pool_proj needs backward computation.
I0707 18:30:44.012521 99468 net.cpp:198] inception_4b/pool_proj needs backward computation.
I0707 18:30:44.012540 99468 net.cpp:198] inception_4b/pool needs backward computation.
I0707 18:30:44.012550 99468 net.cpp:198] inception_4b/relu_5x5 needs backward computation.
I0707 18:30:44.012567 99468 net.cpp:198] inception_4b/5x5 needs backward computation.
I0707 18:30:44.012583 99468 net.cpp:198] inception_4b/relu_5x5_reduce needs backward computation.
I0707 18:30:44.012591 99468 net.cpp:198] inception_4b/5x5_reduce needs backward computation.
I0707 18:30:44.012600 99468 net.cpp:198] inception_4b/relu_3x3 needs backward computation.
I0707 18:30:44.012610 99468 net.cpp:198] inception_4b/3x3 needs backward computation.
I0707 18:30:44.012625 99468 net.cpp:198] inception_4b/relu_3x3_reduce needs backward computation.
I0707 18:30:44.012637 99468 net.cpp:198] inception_4b/3x3_reduce needs backward computation.
I0707 18:30:44.012646 99468 net.cpp:198] inception_4b/relu_1x1 needs backward computation.
I0707 18:30:44.012658 99468 net.cpp:198] inception_4b/1x1 needs backward computation.
I0707 18:30:44.012673 99468 net.cpp:200] loss1/top-5 does not need backward computation.
I0707 18:30:44.012683 99468 net.cpp:200] loss1/top-1 does not need backward computation.
I0707 18:30:44.012698 99468 net.cpp:198] loss1/loss needs backward computation.
I0707 18:30:44.012715 99468 net.cpp:198] loss1/classifier_loss1/classifier_my_0_split needs backward computation.
I0707 18:30:44.012730 99468 net.cpp:198] loss1/classifier_my needs backward computation.
I0707 18:30:44.012742 99468 net.cpp:198] loss1/drop_fc needs backward computation.
I0707 18:30:44.012758 99468 net.cpp:198] loss1/relu_fc needs backward computation.
I0707 18:30:44.012766 99468 net.cpp:198] loss1/fc needs backward computation.
I0707 18:30:44.012781 99468 net.cpp:198] loss1/relu_conv needs backward computation.
I0707 18:30:44.012794 99468 net.cpp:198] loss1/conv needs backward computation.
I0707 18:30:44.012804 99468 net.cpp:198] loss1/ave_pool needs backward computation.
I0707 18:30:44.012815 99468 net.cpp:198] inception_4a/output_inception_4a/output_0_split needs backward computation.
I0707 18:30:44.012830 99468 net.cpp:198] inception_4a/output needs backward computation.
I0707 18:30:44.012845 99468 net.cpp:198] inception_4a/relu_pool_proj needs backward computation.
I0707 18:30:44.012853 99468 net.cpp:198] inception_4a/pool_proj needs backward computation.
I0707 18:30:44.012867 99468 net.cpp:198] inception_4a/pool needs backward computation.
I0707 18:30:44.012881 99468 net.cpp:198] inception_4a/relu_5x5 needs backward computation.
I0707 18:30:44.012889 99468 net.cpp:198] inception_4a/5x5 needs backward computation.
I0707 18:30:44.012904 99468 net.cpp:198] inception_4a/relu_5x5_reduce needs backward computation.
I0707 18:30:44.012917 99468 net.cpp:198] inception_4a/5x5_reduce needs backward computation.
I0707 18:30:44.012930 99468 net.cpp:198] inception_4a/relu_3x3 needs backward computation.
I0707 18:30:44.012941 99468 net.cpp:198] inception_4a/3x3 needs backward computation.
I0707 18:30:44.012950 99468 net.cpp:198] inception_4a/relu_3x3_reduce needs backward computation.
I0707 18:30:44.012964 99468 net.cpp:198] inception_4a/3x3_reduce needs backward computation.
I0707 18:30:44.012974 99468 net.cpp:198] inception_4a/relu_1x1 needs backward computation.
I0707 18:30:44.012987 99468 net.cpp:198] inception_4a/1x1 needs backward computation.
I0707 18:30:44.012996 99468 net.cpp:198] pool3/3x3_s2_pool3/3x3_s2_0_split needs backward computation.
I0707 18:30:44.013010 99468 net.cpp:198] pool3/3x3_s2 needs backward computation.
I0707 18:30:44.013023 99468 net.cpp:198] inception_3b/output needs backward computation.
I0707 18:30:44.013033 99468 net.cpp:198] inception_3b/relu_pool_proj needs backward computation.
I0707 18:30:44.013047 99468 net.cpp:198] inception_3b/pool_proj needs backward computation.
I0707 18:30:44.013058 99468 net.cpp:198] inception_3b/pool needs backward computation.
I0707 18:30:44.013070 99468 net.cpp:198] inception_3b/relu_5x5 needs backward computation.
I0707 18:30:44.013082 99468 net.cpp:198] inception_3b/5x5 needs backward computation.
I0707 18:30:44.013092 99468 net.cpp:198] inception_3b/relu_5x5_reduce needs backward computation.
I0707 18:30:44.013111 99468 net.cpp:198] inception_3b/5x5_reduce needs backward computation.
I0707 18:30:44.013125 99468 net.cpp:198] inception_3b/relu_3x3 needs backward computation.
I0707 18:30:44.013137 99468 net.cpp:198] inception_3b/3x3 needs backward computation.
I0707 18:30:44.013146 99468 net.cpp:198] inception_3b/relu_3x3_reduce needs backward computation.
I0707 18:30:44.013162 99468 net.cpp:198] inception_3b/3x3_reduce needs backward computation.
I0707 18:30:44.013175 99468 net.cpp:198] inception_3b/relu_1x1 needs backward computation.
I0707 18:30:44.013183 99468 net.cpp:198] inception_3b/1x1 needs backward computation.
I0707 18:30:44.013193 99468 net.cpp:198] inception_3a/output_inception_3a/output_0_split needs backward computation.
I0707 18:30:44.013206 99468 net.cpp:198] inception_3a/output needs backward computation.
I0707 18:30:44.013218 99468 net.cpp:198] inception_3a/relu_pool_proj needs backward computation.
I0707 18:30:44.013229 99468 net.cpp:198] inception_3a/pool_proj needs backward computation.
I0707 18:30:44.013242 99468 net.cpp:198] inception_3a/pool needs backward computation.
I0707 18:30:44.013253 99468 net.cpp:198] inception_3a/relu_5x5 needs backward computation.
I0707 18:30:44.013267 99468 net.cpp:198] inception_3a/5x5 needs backward computation.
I0707 18:30:44.013276 99468 net.cpp:198] inception_3a/relu_5x5_reduce needs backward computation.
I0707 18:30:44.013288 99468 net.cpp:198] inception_3a/5x5_reduce needs backward computation.
I0707 18:30:44.013298 99468 net.cpp:198] inception_3a/relu_3x3 needs backward computation.
I0707 18:30:44.013314 99468 net.cpp:198] inception_3a/3x3 needs backward computation.
I0707 18:30:44.013324 99468 net.cpp:198] inception_3a/relu_3x3_reduce needs backward computation.
I0707 18:30:44.013336 99468 net.cpp:198] inception_3a/3x3_reduce needs backward computation.
I0707 18:30:44.013345 99468 net.cpp:198] inception_3a/relu_1x1 needs backward computation.
I0707 18:30:44.013358 99468 net.cpp:198] inception_3a/1x1 needs backward computation.
I0707 18:30:44.013372 99468 net.cpp:198] pool2/3x3_s2_pool2/3x3_s2_0_split needs backward computation.
I0707 18:30:44.013388 99468 net.cpp:198] pool2/3x3_s2 needs backward computation.
I0707 18:30:44.013401 99468 net.cpp:198] conv2/norm2 needs backward computation.
I0707 18:30:44.013411 99468 net.cpp:198] conv2/relu_3x3 needs backward computation.
I0707 18:30:44.013425 99468 net.cpp:198] conv2/3x3 needs backward computation.
I0707 18:30:44.013438 99468 net.cpp:198] conv2/relu_3x3_reduce needs backward computation.
I0707 18:30:44.013447 99468 net.cpp:198] conv2/3x3_reduce needs backward computation.
I0707 18:30:44.013463 99468 net.cpp:198] pool1/norm1 needs backward computation.
I0707 18:30:44.013473 99468 net.cpp:198] pool1/3x3_s2 needs backward computation.
I0707 18:30:44.013489 99468 net.cpp:198] conv1/relu_7x7 needs backward computation.
I0707 18:30:44.013497 99468 net.cpp:198] conv1/7x7_s2 needs backward computation.
I0707 18:30:44.013509 99468 net.cpp:198] st_layer needs backward computation.
I0707 18:30:44.013525 99468 net.cpp:198] loc_reg needs backward computation.
I0707 18:30:44.013535 99468 net.cpp:198] loc_relu3 needs backward computation.
I0707 18:30:44.013550 99468 net.cpp:198] loc_ip1 needs backward computation.
I0707 18:30:44.013567 99468 net.cpp:198] loc_relu2 needs backward computation.
I0707 18:30:44.013579 99468 net.cpp:198] loc_pool2 needs backward computation.
I0707 18:30:44.013588 99468 net.cpp:198] loc_conv2 needs backward computation.
I0707 18:30:44.013597 99468 net.cpp:198] loc_relu1 needs backward computation.
I0707 18:30:44.013610 99468 net.cpp:198] loc_pool1 needs backward computation.
I0707 18:30:44.013625 99468 net.cpp:198] loc_conv1 needs backward computation.
I0707 18:30:44.013641 99468 net.cpp:200] label_data_1_split does not need backward computation.
I0707 18:30:44.013655 99468 net.cpp:200] data_data_0_split does not need backward computation.
I0707 18:30:44.013670 99468 net.cpp:200] data does not need backward computation.
I0707 18:30:44.013689 99468 net.cpp:242] This network produces output loss1/loss1
I0707 18:30:44.013703 99468 net.cpp:242] This network produces output loss1/top-1
I0707 18:30:44.013715 99468 net.cpp:242] This network produces output loss1/top-5
I0707 18:30:44.013727 99468 net.cpp:242] This network produces output loss2/loss2
I0707 18:30:44.013737 99468 net.cpp:242] This network produces output loss2/top-1
I0707 18:30:44.013751 99468 net.cpp:242] This network produces output loss2/top-5
I0707 18:30:44.013759 99468 net.cpp:242] This network produces output loss3/loss3
I0707 18:30:44.013772 99468 net.cpp:242] This network produces output loss3/top-1
I0707 18:30:44.013780 99468 net.cpp:242] This network produces output loss3/top-5
I0707 18:30:44.013962 99468 net.cpp:255] Network initialization done.
I0707 18:30:44.015118 99468 solver.cpp:56] Solver scaffolding done.
I0707 18:30:44.021653 99468 caffe.cpp:248] Starting Optimization
I0707 18:30:44.021677 99468 solver.cpp:272] Solving GoogleNet
I0707 18:30:44.021687 99468 solver.cpp:273] Learning Rate Policy: step
I0707 18:30:46.071888 99468 solver.cpp:218] Iteration 0 (-4.06377e-44 iter/s, 2.05007s/40 iters), loss = 7.27887
I0707 18:30:46.071964 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 7.36054 (* 0.3 = 2.20816 loss)
I0707 18:30:46.072027 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 4.76258 (* 0.3 = 1.42877 loss)
I0707 18:30:46.072057 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 3.73564 (* 1 = 3.73564 loss)
I0707 18:30:46.072100 99468 sgd_solver.cpp:105] Iteration 0, lr = 0.001
I0707 18:32:02.186481 99468 solver.cpp:218] Iteration 40 (0.52554 iter/s, 76.1122s/40 iters), loss = 4.13008
I0707 18:32:02.186672 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.63584 (* 0.3 = 0.790753 loss)
I0707 18:32:02.186705 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47435 (* 0.3 = 0.742304 loss)
I0707 18:32:02.186718 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43672 (* 1 = 2.43672 loss)
I0707 18:32:02.186728 99468 sgd_solver.cpp:105] Iteration 40, lr = 0.001
I0707 18:33:18.345166 99468 solver.cpp:218] Iteration 80 (0.525238 iter/s, 76.156s/40 iters), loss = 3.74221
I0707 18:33:18.345504 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55578 (* 0.3 = 0.766735 loss)
I0707 18:33:18.345593 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58034 (* 0.3 = 0.774102 loss)
I0707 18:33:18.345607 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51893 (* 1 = 2.51893 loss)
I0707 18:33:18.345619 99468 sgd_solver.cpp:105] Iteration 80, lr = 0.001
I0707 18:34:34.538532 99468 solver.cpp:218] Iteration 120 (0.525 iter/s, 76.1905s/40 iters), loss = 3.76192
I0707 18:34:34.538713 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54048 (* 0.3 = 0.762145 loss)
I0707 18:34:34.538729 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.60457 (* 0.3 = 0.781372 loss)
I0707 18:34:34.538741 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55948 (* 1 = 2.55948 loss)
I0707 18:34:34.538751 99468 sgd_solver.cpp:105] Iteration 120, lr = 0.001
I0707 18:35:50.759629 99468 solver.cpp:218] Iteration 160 (0.524808 iter/s, 76.2184s/40 iters), loss = 3.72673
I0707 18:35:50.759763 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17991 (* 0.3 = 0.653973 loss)
I0707 18:35:50.759778 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22353 (* 0.3 = 0.667058 loss)
I0707 18:35:50.759788 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17805 (* 1 = 2.17805 loss)
I0707 18:35:50.759799 99468 sgd_solver.cpp:105] Iteration 160, lr = 0.001
I0707 18:37:07.010013 99468 solver.cpp:218] Iteration 200 (0.524606 iter/s, 76.2477s/40 iters), loss = 3.75018
I0707 18:37:07.010171 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46664 (* 0.3 = 0.739993 loss)
I0707 18:37:07.010231 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.54717 (* 0.3 = 0.76415 loss)
I0707 18:37:07.010242 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44776 (* 1 = 2.44776 loss)
I0707 18:37:07.010252 99468 sgd_solver.cpp:105] Iteration 200, lr = 0.001
I0707 18:38:23.243507 99468 solver.cpp:218] Iteration 240 (0.524722 iter/s, 76.2308s/40 iters), loss = 3.74155
I0707 18:38:23.243691 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12196 (* 0.3 = 0.636589 loss)
I0707 18:38:23.243708 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04379 (* 0.3 = 0.613136 loss)
I0707 18:38:23.243719 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99225 (* 1 = 1.99225 loss)
I0707 18:38:23.243733 99468 sgd_solver.cpp:105] Iteration 240, lr = 0.001
I0707 18:39:39.491508 99468 solver.cpp:218] Iteration 280 (0.524622 iter/s, 76.2453s/40 iters), loss = 3.76275
I0707 18:39:39.491664 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28688 (* 0.3 = 0.686064 loss)
I0707 18:39:39.491679 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30729 (* 0.3 = 0.692187 loss)
I0707 18:39:39.491730 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27859 (* 1 = 2.27859 loss)
I0707 18:39:39.491740 99468 sgd_solver.cpp:105] Iteration 280, lr = 0.001
I0707 18:40:55.691506 99468 solver.cpp:218] Iteration 320 (0.524953 iter/s, 76.1973s/40 iters), loss = 3.72673
I0707 18:40:55.691694 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12882 (* 0.3 = 0.638647 loss)
I0707 18:40:55.691716 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07489 (* 0.3 = 0.622467 loss)
I0707 18:40:55.691731 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09412 (* 1 = 2.09412 loss)
I0707 18:40:55.691746 99468 sgd_solver.cpp:105] Iteration 320, lr = 0.001
I0707 18:42:11.897703 99468 solver.cpp:218] Iteration 360 (0.52491 iter/s, 76.2035s/40 iters), loss = 3.70054
I0707 18:42:11.897838 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1562 (* 0.3 = 0.646861 loss)
I0707 18:42:11.897853 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15746 (* 0.3 = 0.647238 loss)
I0707 18:42:11.897866 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13186 (* 1 = 2.13186 loss)
I0707 18:42:11.897879 99468 sgd_solver.cpp:105] Iteration 360, lr = 0.001
I0707 18:43:28.154350 99468 solver.cpp:218] Iteration 400 (0.524563 iter/s, 76.254s/40 iters), loss = 3.74054
I0707 18:43:28.154511 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30725 (* 0.3 = 0.692176 loss)
I0707 18:43:28.154526 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28754 (* 0.3 = 0.686262 loss)
I0707 18:43:28.154583 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27681 (* 1 = 2.27681 loss)
I0707 18:43:28.154592 99468 sgd_solver.cpp:105] Iteration 400, lr = 0.001
I0707 18:44:44.398594 99468 solver.cpp:218] Iteration 440 (0.524648 iter/s, 76.2416s/40 iters), loss = 3.71355
I0707 18:44:44.398746 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5957 (* 0.3 = 0.778711 loss)
I0707 18:44:44.398761 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57986 (* 0.3 = 0.773958 loss)
I0707 18:44:44.398772 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53284 (* 1 = 2.53284 loss)
I0707 18:44:44.398820 99468 sgd_solver.cpp:105] Iteration 440, lr = 0.001
I0707 18:46:00.598119 99468 solver.cpp:218] Iteration 480 (0.524956 iter/s, 76.1969s/40 iters), loss = 3.76304
I0707 18:46:00.598284 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26914 (* 0.3 = 0.680741 loss)
I0707 18:46:00.598299 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28971 (* 0.3 = 0.686914 loss)
I0707 18:46:00.598311 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25783 (* 1 = 2.25783 loss)
I0707 18:46:00.598357 99468 sgd_solver.cpp:105] Iteration 480, lr = 0.001
I0707 18:47:16.834705 99468 solver.cpp:218] Iteration 520 (0.524701 iter/s, 76.2339s/40 iters), loss = 3.73641
I0707 18:47:16.834903 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45419 (* 0.3 = 0.736256 loss)
I0707 18:47:16.834918 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44649 (* 0.3 = 0.733946 loss)
I0707 18:47:16.834930 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43587 (* 1 = 2.43587 loss)
I0707 18:47:16.834941 99468 sgd_solver.cpp:105] Iteration 520, lr = 0.001
I0707 18:48:33.050806 99468 solver.cpp:218] Iteration 560 (0.524842 iter/s, 76.2134s/40 iters), loss = 3.7506
I0707 18:48:33.050948 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3294 (* 0.3 = 0.698821 loss)
I0707 18:48:33.050964 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3407 (* 0.3 = 0.70221 loss)
I0707 18:48:33.051012 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28001 (* 1 = 2.28001 loss)
I0707 18:48:33.051023 99468 sgd_solver.cpp:105] Iteration 560, lr = 0.001
I0707 18:49:49.287760 99468 solver.cpp:218] Iteration 600 (0.524698 iter/s, 76.2343s/40 iters), loss = 3.72288
I0707 18:49:49.287911 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52794 (* 0.3 = 0.758383 loss)
I0707 18:49:49.287927 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61457 (* 0.3 = 0.78437 loss)
I0707 18:49:49.287938 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53634 (* 1 = 2.53634 loss)
I0707 18:49:49.287953 99468 sgd_solver.cpp:105] Iteration 600, lr = 0.001
I0707 18:51:05.446291 99468 solver.cpp:218] Iteration 640 (0.525239 iter/s, 76.1559s/40 iters), loss = 3.74185
I0707 18:51:05.446461 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52161 (* 0.3 = 0.756483 loss)
I0707 18:51:05.446480 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46421 (* 0.3 = 0.739262 loss)
I0707 18:51:05.446535 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46604 (* 1 = 2.46604 loss)
I0707 18:51:05.446547 99468 sgd_solver.cpp:105] Iteration 640, lr = 0.001
I0707 18:52:21.687126 99468 solver.cpp:218] Iteration 680 (0.524672 iter/s, 76.2382s/40 iters), loss = 3.7326
I0707 18:52:21.687299 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31593 (* 0.3 = 0.694778 loss)
I0707 18:52:21.687319 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33716 (* 0.3 = 0.701147 loss)
I0707 18:52:21.687371 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28345 (* 1 = 2.28345 loss)
I0707 18:52:21.687387 99468 sgd_solver.cpp:105] Iteration 680, lr = 0.001
I0707 18:53:37.950438 99468 solver.cpp:218] Iteration 720 (0.524517 iter/s, 76.2606s/40 iters), loss = 3.75331
I0707 18:53:37.950589 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40086 (* 0.3 = 0.720257 loss)
I0707 18:53:37.950606 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37531 (* 0.3 = 0.712594 loss)
I0707 18:53:37.950618 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32188 (* 1 = 2.32188 loss)
I0707 18:53:37.950630 99468 sgd_solver.cpp:105] Iteration 720, lr = 0.001
I0707 18:54:54.080718 99468 solver.cpp:218] Iteration 760 (0.525433 iter/s, 76.1276s/40 iters), loss = 3.73498
I0707 18:54:54.080852 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16776 (* 0.3 = 0.650328 loss)
I0707 18:54:54.080868 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16123 (* 0.3 = 0.64837 loss)
I0707 18:54:54.080880 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14319 (* 1 = 2.14319 loss)
I0707 18:54:54.080893 99468 sgd_solver.cpp:105] Iteration 760, lr = 0.001
I0707 18:56:10.269860 99468 solver.cpp:218] Iteration 800 (0.525027 iter/s, 76.1865s/40 iters), loss = 3.74971
I0707 18:56:10.270007 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02182 (* 0.3 = 0.606546 loss)
I0707 18:56:10.270025 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.02529 (* 0.3 = 0.607587 loss)
I0707 18:56:10.270038 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.00489 (* 1 = 2.00489 loss)
I0707 18:56:10.270051 99468 sgd_solver.cpp:105] Iteration 800, lr = 0.001
I0707 18:57:26.447052 99468 solver.cpp:218] Iteration 840 (0.52511 iter/s, 76.1745s/40 iters), loss = 3.72063
I0707 18:57:26.447227 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25137 (* 0.3 = 0.675411 loss)
I0707 18:57:26.447244 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2955 (* 0.3 = 0.688649 loss)
I0707 18:57:26.447257 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23137 (* 1 = 2.23137 loss)
I0707 18:57:26.447269 99468 sgd_solver.cpp:105] Iteration 840, lr = 0.001
I0707 18:58:42.713805 99468 solver.cpp:218] Iteration 880 (0.524493 iter/s, 76.2641s/40 iters), loss = 3.7689
I0707 18:58:42.713954 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23715 (* 0.3 = 0.671145 loss)
I0707 18:58:42.713970 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29037 (* 0.3 = 0.687111 loss)
I0707 18:58:42.713984 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21283 (* 1 = 2.21283 loss)
I0707 18:58:42.713995 99468 sgd_solver.cpp:105] Iteration 880, lr = 0.001
I0707 18:59:58.914885 99468 solver.cpp:218] Iteration 920 (0.524945 iter/s, 76.1984s/40 iters), loss = 3.75134
I0707 18:59:58.915026 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55863 (* 0.3 = 0.76759 loss)
I0707 18:59:58.915042 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5367 (* 0.3 = 0.76101 loss)
I0707 18:59:58.915055 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52998 (* 1 = 2.52998 loss)
I0707 18:59:58.915066 99468 sgd_solver.cpp:105] Iteration 920, lr = 0.001
I0707 19:01:15.118608 99468 solver.cpp:218] Iteration 960 (0.524927 iter/s, 76.2011s/40 iters), loss = 3.69487
I0707 19:01:15.118774 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16488 (* 0.3 = 0.649464 loss)
I0707 19:01:15.118791 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14931 (* 0.3 = 0.644794 loss)
I0707 19:01:15.118803 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13605 (* 1 = 2.13605 loss)
I0707 19:01:15.118815 99468 sgd_solver.cpp:105] Iteration 960, lr = 0.001
I0707 19:02:31.310796 99468 solver.cpp:218] Iteration 1000 (0.525007 iter/s, 76.1895s/40 iters), loss = 3.69535
I0707 19:02:31.310938 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.89297 (* 0.3 = 0.567891 loss)
I0707 19:02:31.310956 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.9695 (* 0.3 = 0.590849 loss)
I0707 19:02:31.311015 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.88378 (* 1 = 1.88378 loss)
I0707 19:02:31.311028 99468 sgd_solver.cpp:105] Iteration 1000, lr = 0.001
I0707 19:03:47.539717 99468 solver.cpp:218] Iteration 1040 (0.524754 iter/s, 76.2263s/40 iters), loss = 3.68971
I0707 19:03:47.539858 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44414 (* 0.3 = 0.733243 loss)
I0707 19:03:47.539925 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48487 (* 0.3 = 0.74546 loss)
I0707 19:03:47.539937 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45139 (* 1 = 2.45139 loss)
I0707 19:03:47.539948 99468 sgd_solver.cpp:105] Iteration 1040, lr = 0.001
I0707 19:05:03.790293 99468 solver.cpp:218] Iteration 1080 (0.524604 iter/s, 76.2479s/40 iters), loss = 3.68966
I0707 19:05:03.790446 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12909 (* 0.3 = 0.638726 loss)
I0707 19:05:03.790462 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20815 (* 0.3 = 0.662444 loss)
I0707 19:05:03.790477 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14196 (* 1 = 2.14196 loss)
I0707 19:05:03.790531 99468 sgd_solver.cpp:105] Iteration 1080, lr = 0.001
I0707 19:06:20.059208 99468 solver.cpp:218] Iteration 1120 (0.524478 iter/s, 76.2663s/40 iters), loss = 3.70285
I0707 19:06:20.059362 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24537 (* 0.3 = 0.673612 loss)
I0707 19:06:20.059379 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18637 (* 0.3 = 0.655911 loss)
I0707 19:06:20.059392 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16615 (* 1 = 2.16615 loss)
I0707 19:06:20.059406 99468 sgd_solver.cpp:105] Iteration 1120, lr = 0.001
I0707 19:07:36.264591 99468 solver.cpp:218] Iteration 1160 (0.524916 iter/s, 76.2027s/40 iters), loss = 3.67977
I0707 19:07:36.264778 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45298 (* 0.3 = 0.735893 loss)
I0707 19:07:36.264797 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43026 (* 0.3 = 0.729079 loss)
I0707 19:07:36.264856 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42117 (* 1 = 2.42117 loss)
I0707 19:07:36.264868 99468 sgd_solver.cpp:105] Iteration 1160, lr = 0.001
I0707 19:08:52.522286 99468 solver.cpp:218] Iteration 1200 (0.524559 iter/s, 76.2546s/40 iters), loss = 3.76579
I0707 19:08:52.522409 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04532 (* 0.3 = 0.613596 loss)
I0707 19:08:52.522475 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08423 (* 0.3 = 0.62527 loss)
I0707 19:08:52.522490 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.05804 (* 1 = 2.05804 loss)
I0707 19:08:52.522502 99468 sgd_solver.cpp:105] Iteration 1200, lr = 0.001
I0707 19:10:08.730540 99468 solver.cpp:218] Iteration 1240 (0.524896 iter/s, 76.2056s/40 iters), loss = 3.71476
I0707 19:10:08.730693 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29682 (* 0.3 = 0.689047 loss)
I0707 19:10:08.730746 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29674 (* 0.3 = 0.689023 loss)
I0707 19:10:08.730758 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29077 (* 1 = 2.29077 loss)
I0707 19:10:08.730769 99468 sgd_solver.cpp:105] Iteration 1240, lr = 0.001
I0707 19:11:24.915647 99468 solver.cpp:218] Iteration 1280 (0.525055 iter/s, 76.1824s/40 iters), loss = 3.65779
I0707 19:11:24.915789 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.66834 (* 0.3 = 0.800501 loss)
I0707 19:11:24.915807 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.66523 (* 0.3 = 0.799569 loss)
I0707 19:11:24.915819 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59665 (* 1 = 2.59665 loss)
I0707 19:11:24.915834 99468 sgd_solver.cpp:105] Iteration 1280, lr = 0.001
I0707 19:12:41.127915 99468 solver.cpp:218] Iteration 1320 (0.524868 iter/s, 76.2096s/40 iters), loss = 3.72211
I0707 19:12:41.128090 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06934 (* 0.3 = 0.620802 loss)
I0707 19:12:41.128115 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0751 (* 0.3 = 0.622531 loss)
I0707 19:12:41.128129 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.06006 (* 1 = 2.06006 loss)
I0707 19:12:41.128183 99468 sgd_solver.cpp:105] Iteration 1320, lr = 0.001
I0707 19:13:57.328634 99468 solver.cpp:218] Iteration 1360 (0.524948 iter/s, 76.198s/40 iters), loss = 3.69846
I0707 19:13:57.328773 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50892 (* 0.3 = 0.752677 loss)
I0707 19:13:57.328794 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46428 (* 0.3 = 0.739283 loss)
I0707 19:13:57.328811 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44871 (* 1 = 2.44871 loss)
I0707 19:13:57.328824 99468 sgd_solver.cpp:105] Iteration 1360, lr = 0.001
I0707 19:15:13.502545 99468 solver.cpp:218] Iteration 1400 (0.525132 iter/s, 76.1713s/40 iters), loss = 3.73802
I0707 19:15:13.502701 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38362 (* 0.3 = 0.715087 loss)
I0707 19:15:13.502718 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41102 (* 0.3 = 0.723305 loss)
I0707 19:15:13.502769 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37802 (* 1 = 2.37802 loss)
I0707 19:15:13.502782 99468 sgd_solver.cpp:105] Iteration 1400, lr = 0.001
I0707 19:16:29.752207 99468 solver.cpp:218] Iteration 1440 (0.524611 iter/s, 76.247s/40 iters), loss = 3.74128
I0707 19:16:29.752365 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36858 (* 0.3 = 0.710575 loss)
I0707 19:16:29.752418 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39103 (* 0.3 = 0.717308 loss)
I0707 19:16:29.752431 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33496 (* 1 = 2.33496 loss)
I0707 19:16:29.752441 99468 sgd_solver.cpp:105] Iteration 1440, lr = 0.001
I0707 19:17:45.977303 99468 solver.cpp:218] Iteration 1480 (0.52478 iter/s, 76.2224s/40 iters), loss = 3.73043
I0707 19:17:45.977506 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3791 (* 0.3 = 0.71373 loss)
I0707 19:17:45.977527 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37363 (* 0.3 = 0.712088 loss)
I0707 19:17:45.977540 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34407 (* 1 = 2.34407 loss)
I0707 19:17:45.977596 99468 sgd_solver.cpp:105] Iteration 1480, lr = 0.001
I0707 19:19:02.272207 99468 solver.cpp:218] Iteration 1520 (0.5243 iter/s, 76.2922s/40 iters), loss = 3.76215
I0707 19:19:02.272369 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29446 (* 0.3 = 0.688339 loss)
I0707 19:19:02.272388 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25402 (* 0.3 = 0.676207 loss)
I0707 19:19:02.272435 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24116 (* 1 = 2.24116 loss)
I0707 19:19:02.272447 99468 sgd_solver.cpp:105] Iteration 1520, lr = 0.001
I0707 19:20:18.528718 99468 solver.cpp:218] Iteration 1560 (0.524564 iter/s, 76.2538s/40 iters), loss = 3.7472
I0707 19:20:18.528863 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22301 (* 0.3 = 0.666902 loss)
I0707 19:20:18.528880 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21895 (* 0.3 = 0.665684 loss)
I0707 19:20:18.528894 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20329 (* 1 = 2.20329 loss)
I0707 19:20:18.528908 99468 sgd_solver.cpp:105] Iteration 1560, lr = 0.001
I0707 19:21:34.760829 99468 solver.cpp:218] Iteration 1600 (0.524732 iter/s, 76.2295s/40 iters), loss = 3.73357
I0707 19:21:34.760974 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19661 (* 0.3 = 0.658982 loss)
I0707 19:21:34.760993 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19105 (* 0.3 = 0.657315 loss)
I0707 19:21:34.761008 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16169 (* 1 = 2.16169 loss)
I0707 19:21:34.761020 99468 sgd_solver.cpp:105] Iteration 1600, lr = 0.001
I0707 19:22:51.016014 99468 solver.cpp:218] Iteration 1640 (0.524573 iter/s, 76.2525s/40 iters), loss = 3.67826
I0707 19:22:51.016178 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45884 (* 0.3 = 0.737651 loss)
I0707 19:22:51.016202 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43112 (* 0.3 = 0.729336 loss)
I0707 19:22:51.016219 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46293 (* 1 = 2.46293 loss)
I0707 19:22:51.016232 99468 sgd_solver.cpp:105] Iteration 1640, lr = 0.001
I0707 19:24:07.243868 99468 solver.cpp:218] Iteration 1680 (0.524761 iter/s, 76.2252s/40 iters), loss = 3.72471
I0707 19:24:07.244019 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44524 (* 0.3 = 0.733572 loss)
I0707 19:24:07.244040 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47086 (* 0.3 = 0.741259 loss)
I0707 19:24:07.244055 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45039 (* 1 = 2.45039 loss)
I0707 19:24:07.244102 99468 sgd_solver.cpp:105] Iteration 1680, lr = 0.001
I0707 19:25:23.477721 99468 solver.cpp:218] Iteration 1720 (0.52472 iter/s, 76.2312s/40 iters), loss = 3.72943
I0707 19:25:23.477869 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21397 (* 0.3 = 0.664192 loss)
I0707 19:25:23.477887 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22724 (* 0.3 = 0.668172 loss)
I0707 19:25:23.477933 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1989 (* 1 = 2.1989 loss)
I0707 19:25:23.477946 99468 sgd_solver.cpp:105] Iteration 1720, lr = 0.001
I0707 19:26:39.681294 99468 solver.cpp:218] Iteration 1760 (0.524928 iter/s, 76.2009s/40 iters), loss = 3.74177
I0707 19:26:39.681504 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35679 (* 0.3 = 0.707036 loss)
I0707 19:26:39.681531 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40745 (* 0.3 = 0.722235 loss)
I0707 19:26:39.681586 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3607 (* 1 = 2.3607 loss)
I0707 19:26:39.681602 99468 sgd_solver.cpp:105] Iteration 1760, lr = 0.001
I0707 19:27:55.875478 99468 solver.cpp:218] Iteration 1800 (0.524993 iter/s, 76.1915s/40 iters), loss = 3.70354
I0707 19:27:55.875630 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27929 (* 0.3 = 0.683786 loss)
I0707 19:27:55.875648 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2295 (* 0.3 = 0.66885 loss)
I0707 19:27:55.875663 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2329 (* 1 = 2.2329 loss)
I0707 19:27:55.875675 99468 sgd_solver.cpp:105] Iteration 1800, lr = 0.001
I0707 19:29:12.125193 99468 solver.cpp:218] Iteration 1840 (0.52461 iter/s, 76.2471s/40 iters), loss = 3.72029
I0707 19:29:12.125340 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4811 (* 0.3 = 0.744331 loss)
I0707 19:29:12.125358 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50471 (* 0.3 = 0.751413 loss)
I0707 19:29:12.125375 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45702 (* 1 = 2.45702 loss)
I0707 19:29:12.125388 99468 sgd_solver.cpp:105] Iteration 1840, lr = 0.001
I0707 19:30:28.370306 99468 solver.cpp:218] Iteration 1880 (0.524642 iter/s, 76.2425s/40 iters), loss = 3.71607
I0707 19:30:28.370462 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47348 (* 0.3 = 0.742045 loss)
I0707 19:30:28.370518 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50457 (* 0.3 = 0.75137 loss)
I0707 19:30:28.370548 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4616 (* 1 = 2.4616 loss)
I0707 19:30:28.370566 99468 sgd_solver.cpp:105] Iteration 1880, lr = 0.001
I0707 19:31:44.623412 99468 solver.cpp:218] Iteration 1920 (0.524587 iter/s, 76.2504s/40 iters), loss = 3.67429
I0707 19:31:44.623574 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.66116 (* 0.3 = 0.798349 loss)
I0707 19:31:44.623592 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.64857 (* 0.3 = 0.794572 loss)
I0707 19:31:44.623605 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.65165 (* 1 = 2.65165 loss)
I0707 19:31:44.623654 99468 sgd_solver.cpp:105] Iteration 1920, lr = 0.001
I0707 19:33:00.842795 99468 solver.cpp:218] Iteration 1960 (0.524819 iter/s, 76.2167s/40 iters), loss = 3.74008
I0707 19:33:00.842937 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24474 (* 0.3 = 0.673421 loss)
I0707 19:33:00.842954 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2603 (* 0.3 = 0.678089 loss)
I0707 19:33:00.842998 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2358 (* 1 = 2.2358 loss)
I0707 19:33:00.843009 99468 sgd_solver.cpp:105] Iteration 1960, lr = 0.001
I0707 19:34:17.118566 99468 solver.cpp:218] Iteration 2000 (0.524431 iter/s, 76.2731s/40 iters), loss = 3.7709
I0707 19:34:17.118716 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2969 (* 0.3 = 0.689071 loss)
I0707 19:34:17.118736 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33606 (* 0.3 = 0.700817 loss)
I0707 19:34:17.118749 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2687 (* 1 = 2.2687 loss)
I0707 19:34:17.118794 99468 sgd_solver.cpp:105] Iteration 2000, lr = 0.001
I0707 19:35:33.406540 99468 solver.cpp:218] Iteration 2040 (0.524347 iter/s, 76.2853s/40 iters), loss = 3.72319
I0707 19:35:33.406679 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21497 (* 0.3 = 0.664492 loss)
I0707 19:35:33.406697 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16025 (* 0.3 = 0.648076 loss)
I0707 19:35:33.406743 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15555 (* 1 = 2.15555 loss)
I0707 19:35:33.406755 99468 sgd_solver.cpp:105] Iteration 2040, lr = 0.001
I0707 19:36:49.668277 99468 solver.cpp:218] Iteration 2080 (0.524528 iter/s, 76.2591s/40 iters), loss = 3.70242
I0707 19:36:49.668489 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51624 (* 0.3 = 0.754871 loss)
I0707 19:36:49.668519 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.56387 (* 0.3 = 0.76916 loss)
I0707 19:36:49.668537 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48338 (* 1 = 2.48338 loss)
I0707 19:36:49.668560 99468 sgd_solver.cpp:105] Iteration 2080, lr = 0.001
I0707 19:38:05.920764 99468 solver.cpp:218] Iteration 2120 (0.524592 iter/s, 76.2498s/40 iters), loss = 3.72713
I0707 19:38:05.920907 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07494 (* 0.3 = 0.622481 loss)
I0707 19:38:05.920924 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11336 (* 0.3 = 0.634007 loss)
I0707 19:38:05.920939 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07236 (* 1 = 2.07236 loss)
I0707 19:38:05.920953 99468 sgd_solver.cpp:105] Iteration 2120, lr = 0.001
I0707 19:39:22.188143 99468 solver.cpp:218] Iteration 2160 (0.524489 iter/s, 76.2647s/40 iters), loss = 3.75256
I0707 19:39:22.188282 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65311 (* 0.3 = 0.795933 loss)
I0707 19:39:22.188302 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58732 (* 0.3 = 0.776196 loss)
I0707 19:39:22.188354 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.60932 (* 1 = 2.60932 loss)
I0707 19:39:22.188365 99468 sgd_solver.cpp:105] Iteration 2160, lr = 0.001
I0707 19:40:38.469832 99468 solver.cpp:218] Iteration 2200 (0.52439 iter/s, 76.279s/40 iters), loss = 3.69584
I0707 19:40:38.470015 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.62027 (* 0.3 = 0.786081 loss)
I0707 19:40:38.470036 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.67153 (* 0.3 = 0.801458 loss)
I0707 19:40:38.470049 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62095 (* 1 = 2.62095 loss)
I0707 19:40:38.470099 99468 sgd_solver.cpp:105] Iteration 2200, lr = 0.001
I0707 19:41:54.754672 99468 solver.cpp:218] Iteration 2240 (0.524369 iter/s, 76.2822s/40 iters), loss = 3.69053
I0707 19:41:54.754817 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65368 (* 0.3 = 0.796103 loss)
I0707 19:41:54.754839 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.69233 (* 0.3 = 0.8077 loss)
I0707 19:41:54.754851 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.65109 (* 1 = 2.65109 loss)
I0707 19:41:54.754904 99468 sgd_solver.cpp:105] Iteration 2240, lr = 0.001
I0707 19:43:11.032376 99468 solver.cpp:218] Iteration 2280 (0.524418 iter/s, 76.275s/40 iters), loss = 3.68839
I0707 19:43:11.032562 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56836 (* 0.3 = 0.770508 loss)
I0707 19:43:11.032589 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53726 (* 0.3 = 0.761178 loss)
I0707 19:43:11.032606 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52525 (* 1 = 2.52525 loss)
I0707 19:43:11.032621 99468 sgd_solver.cpp:105] Iteration 2280, lr = 0.001
I0707 19:44:27.289726 99468 solver.cpp:218] Iteration 2320 (0.524558 iter/s, 76.2547s/40 iters), loss = 3.65496
I0707 19:44:27.289903 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45624 (* 0.3 = 0.736872 loss)
I0707 19:44:27.289964 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46665 (* 0.3 = 0.739994 loss)
I0707 19:44:27.289981 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46277 (* 1 = 2.46277 loss)
I0707 19:44:27.290001 99468 sgd_solver.cpp:105] Iteration 2320, lr = 0.001
I0707 19:45:43.564355 99468 solver.cpp:218] Iteration 2360 (0.524439 iter/s, 76.2719s/40 iters), loss = 3.74189
I0707 19:45:43.564496 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4535 (* 0.3 = 0.736049 loss)
I0707 19:45:43.564549 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44012 (* 0.3 = 0.732036 loss)
I0707 19:45:43.564570 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43166 (* 1 = 2.43166 loss)
I0707 19:45:43.564581 99468 sgd_solver.cpp:105] Iteration 2360, lr = 0.001
I0707 19:46:59.817919 99468 solver.cpp:218] Iteration 2400 (0.524584 iter/s, 76.2509s/40 iters), loss = 3.69312
I0707 19:46:59.818114 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33104 (* 0.3 = 0.699312 loss)
I0707 19:46:59.818166 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34102 (* 0.3 = 0.702305 loss)
I0707 19:46:59.818183 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35052 (* 1 = 2.35052 loss)
I0707 19:46:59.818197 99468 sgd_solver.cpp:105] Iteration 2400, lr = 0.001
I0707 19:48:16.065919 99468 solver.cpp:218] Iteration 2440 (0.524622 iter/s, 76.2453s/40 iters), loss = 3.68704
I0707 19:48:16.066088 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24675 (* 0.3 = 0.674024 loss)
I0707 19:48:16.066146 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16952 (* 0.3 = 0.650856 loss)
I0707 19:48:16.066159 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19377 (* 1 = 2.19377 loss)
I0707 19:48:16.066190 99468 sgd_solver.cpp:105] Iteration 2440, lr = 0.001
I0707 19:49:32.319895 99468 solver.cpp:218] Iteration 2480 (0.524581 iter/s, 76.2513s/40 iters), loss = 3.69311
I0707 19:49:32.320050 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46744 (* 0.3 = 0.740231 loss)
I0707 19:49:32.320109 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.52858 (* 0.3 = 0.758573 loss)
I0707 19:49:32.320140 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48205 (* 1 = 2.48205 loss)
I0707 19:49:32.320157 99468 sgd_solver.cpp:105] Iteration 2480, lr = 0.001
I0707 19:50:48.539491 99468 solver.cpp:218] Iteration 2520 (0.524818 iter/s, 76.2169s/40 iters), loss = 3.70182
I0707 19:50:48.539664 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12205 (* 0.3 = 0.636616 loss)
I0707 19:50:48.539726 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11862 (* 0.3 = 0.635587 loss)
I0707 19:50:48.539764 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11964 (* 1 = 2.11964 loss)
I0707 19:50:48.539780 99468 sgd_solver.cpp:105] Iteration 2520, lr = 0.001
I0707 19:52:04.816819 99468 solver.cpp:218] Iteration 2560 (0.524421 iter/s, 76.2747s/40 iters), loss = 3.71882
I0707 19:52:04.816975 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50036 (* 0.3 = 0.750109 loss)
I0707 19:52:04.817028 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47974 (* 0.3 = 0.743922 loss)
I0707 19:52:04.817045 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4831 (* 1 = 2.4831 loss)
I0707 19:52:04.817076 99468 sgd_solver.cpp:105] Iteration 2560, lr = 0.001
I0707 19:53:21.081074 99468 solver.cpp:218] Iteration 2600 (0.52451 iter/s, 76.2616s/40 iters), loss = 3.73503
I0707 19:53:21.081238 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28431 (* 0.3 = 0.685293 loss)
I0707 19:53:21.081295 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28469 (* 0.3 = 0.685407 loss)
I0707 19:53:21.081326 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2495 (* 1 = 2.2495 loss)
I0707 19:53:21.081338 99468 sgd_solver.cpp:105] Iteration 2600, lr = 0.001
I0707 19:54:37.353974 99468 solver.cpp:218] Iteration 2640 (0.524451 iter/s, 76.2702s/40 iters), loss = 3.69862
I0707 19:54:37.354135 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.71999 (* 0.3 = 0.815998 loss)
I0707 19:54:37.354161 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.73915 (* 0.3 = 0.821746 loss)
I0707 19:54:37.354177 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.71897 (* 1 = 2.71897 loss)
I0707 19:54:37.354192 99468 sgd_solver.cpp:105] Iteration 2640, lr = 0.001
I0707 19:55:53.631129 99468 solver.cpp:218] Iteration 2680 (0.524422 iter/s, 76.2745s/40 iters), loss = 3.72446
I0707 19:55:53.631286 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4463 (* 0.3 = 0.733889 loss)
I0707 19:55:53.631310 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42943 (* 0.3 = 0.728829 loss)
I0707 19:55:53.631323 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41542 (* 1 = 2.41542 loss)
I0707 19:55:53.631338 99468 sgd_solver.cpp:105] Iteration 2680, lr = 0.001
I0707 19:57:09.901554 99468 solver.cpp:218] Iteration 2720 (0.524468 iter/s, 76.2678s/40 iters), loss = 3.75433
I0707 19:57:09.901726 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22653 (* 0.3 = 0.667959 loss)
I0707 19:57:09.901747 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20999 (* 0.3 = 0.662998 loss)
I0707 19:57:09.901762 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24707 (* 1 = 2.24707 loss)
I0707 19:57:09.901775 99468 sgd_solver.cpp:105] Iteration 2720, lr = 0.001
I0707 19:58:26.135751 99468 solver.cpp:218] Iteration 2760 (0.524717 iter/s, 76.2315s/40 iters), loss = 3.71668
I0707 19:58:26.135915 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21725 (* 0.3 = 0.665176 loss)
I0707 19:58:26.135936 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18402 (* 0.3 = 0.655207 loss)
I0707 19:58:26.135952 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18778 (* 1 = 2.18778 loss)
I0707 19:58:26.136004 99468 sgd_solver.cpp:105] Iteration 2760, lr = 0.001
I0707 19:59:42.396734 99468 solver.cpp:218] Iteration 2800 (0.524533 iter/s, 76.2583s/40 iters), loss = 3.75002
I0707 19:59:42.396886 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37101 (* 0.3 = 0.711304 loss)
I0707 19:59:42.396908 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40645 (* 0.3 = 0.721934 loss)
I0707 19:59:42.396921 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3687 (* 1 = 2.3687 loss)
I0707 19:59:42.396934 99468 sgd_solver.cpp:105] Iteration 2800, lr = 0.001
I0707 20:00:58.673779 99468 solver.cpp:218] Iteration 2840 (0.524422 iter/s, 76.2744s/40 iters), loss = 3.70287
I0707 20:00:58.673961 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.89435 (* 0.3 = 0.568306 loss)
I0707 20:00:58.674000 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.87194 (* 0.3 = 0.561583 loss)
I0707 20:00:58.674026 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.86214 (* 1 = 1.86214 loss)
I0707 20:00:58.674084 99468 sgd_solver.cpp:105] Iteration 2840, lr = 0.001
I0707 20:02:14.923943 99468 solver.cpp:218] Iteration 2880 (0.524608 iter/s, 76.2475s/40 iters), loss = 3.76005
I0707 20:02:14.924104 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16798 (* 0.3 = 0.650393 loss)
I0707 20:02:14.924123 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22615 (* 0.3 = 0.667844 loss)
I0707 20:02:14.924139 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17994 (* 1 = 2.17994 loss)
I0707 20:02:14.924150 99468 sgd_solver.cpp:105] Iteration 2880, lr = 0.001
I0707 20:03:31.157261 99468 solver.cpp:218] Iteration 2920 (0.524723 iter/s, 76.2307s/40 iters), loss = 3.71657
I0707 20:03:31.157423 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26392 (* 0.3 = 0.679177 loss)
I0707 20:03:31.157441 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26155 (* 0.3 = 0.678464 loss)
I0707 20:03:31.157505 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22189 (* 1 = 2.22189 loss)
I0707 20:03:31.157516 99468 sgd_solver.cpp:105] Iteration 2920, lr = 0.001
I0707 20:04:47.345856 99468 solver.cpp:218] Iteration 2960 (0.525031 iter/s, 76.1859s/40 iters), loss = 3.70946
I0707 20:04:47.346009 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18685 (* 0.3 = 0.656056 loss)
I0707 20:04:47.346026 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19316 (* 0.3 = 0.657948 loss)
I0707 20:04:47.346040 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17251 (* 1 = 2.17251 loss)
I0707 20:04:47.346052 99468 sgd_solver.cpp:105] Iteration 2960, lr = 0.001
I0707 20:06:03.614400 99468 solver.cpp:218] Iteration 3000 (0.524481 iter/s, 76.2659s/40 iters), loss = 3.6462
I0707 20:06:03.614544 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5894 (* 0.3 = 0.77682 loss)
I0707 20:06:03.614569 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58786 (* 0.3 = 0.776357 loss)
I0707 20:06:03.614583 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.56686 (* 1 = 2.56686 loss)
I0707 20:06:03.614594 99468 sgd_solver.cpp:105] Iteration 3000, lr = 0.001
I0707 20:07:19.834636 99468 solver.cpp:218] Iteration 3040 (0.524813 iter/s, 76.2176s/40 iters), loss = 3.74414
I0707 20:07:19.834828 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27423 (* 0.3 = 0.682268 loss)
I0707 20:07:19.834890 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25926 (* 0.3 = 0.677778 loss)
I0707 20:07:19.834908 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24425 (* 1 = 2.24425 loss)
I0707 20:07:19.834920 99468 sgd_solver.cpp:105] Iteration 3040, lr = 0.001
I0707 20:08:36.098724 99468 solver.cpp:218] Iteration 3080 (0.524512 iter/s, 76.2614s/40 iters), loss = 3.69896
I0707 20:08:36.098872 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21148 (* 0.3 = 0.663445 loss)
I0707 20:08:36.098929 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19509 (* 0.3 = 0.658527 loss)
I0707 20:08:36.098959 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20387 (* 1 = 2.20387 loss)
I0707 20:08:36.098971 99468 sgd_solver.cpp:105] Iteration 3080, lr = 0.001
I0707 20:09:52.356986 99468 solver.cpp:218] Iteration 3120 (0.524552 iter/s, 76.2556s/40 iters), loss = 3.71618
I0707 20:09:52.357146 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28056 (* 0.3 = 0.684168 loss)
I0707 20:09:52.357162 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29208 (* 0.3 = 0.687625 loss)
I0707 20:09:52.357177 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29528 (* 1 = 2.29528 loss)
I0707 20:09:52.357190 99468 sgd_solver.cpp:105] Iteration 3120, lr = 0.001
I0707 20:11:08.616189 99468 solver.cpp:218] Iteration 3160 (0.524545 iter/s, 76.2565s/40 iters), loss = 3.66803
I0707 20:11:08.616358 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06686 (* 0.3 = 0.620058 loss)
I0707 20:11:08.616379 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03847 (* 0.3 = 0.611542 loss)
I0707 20:11:08.616394 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.05317 (* 1 = 2.05317 loss)
I0707 20:11:08.616410 99468 sgd_solver.cpp:105] Iteration 3160, lr = 0.001
I0707 20:12:24.900966 99468 solver.cpp:218] Iteration 3200 (0.524369 iter/s, 76.2821s/40 iters), loss = 3.75077
I0707 20:12:24.901121 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43851 (* 0.3 = 0.731554 loss)
I0707 20:12:24.901140 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47259 (* 0.3 = 0.741778 loss)
I0707 20:12:24.901157 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43122 (* 1 = 2.43122 loss)
I0707 20:12:24.901168 99468 sgd_solver.cpp:105] Iteration 3200, lr = 0.001
I0707 20:13:41.219650 99468 solver.cpp:218] Iteration 3240 (0.524136 iter/s, 76.316s/40 iters), loss = 3.69592
I0707 20:13:41.219796 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18637 (* 0.3 = 0.655912 loss)
I0707 20:13:41.219849 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19242 (* 0.3 = 0.657725 loss)
I0707 20:13:41.219867 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17608 (* 1 = 2.17608 loss)
I0707 20:13:41.219878 99468 sgd_solver.cpp:105] Iteration 3240, lr = 0.001
I0707 20:14:57.463049 99468 solver.cpp:218] Iteration 3280 (0.524654 iter/s, 76.2408s/40 iters), loss = 3.6695
I0707 20:14:57.463196 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18686 (* 0.3 = 0.656057 loss)
I0707 20:14:57.463245 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1962 (* 0.3 = 0.65886 loss)
I0707 20:14:57.463258 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19441 (* 1 = 2.19441 loss)
I0707 20:14:57.463276 99468 sgd_solver.cpp:105] Iteration 3280, lr = 0.001
I0707 20:16:13.707737 99468 solver.cpp:218] Iteration 3320 (0.524645 iter/s, 76.242s/40 iters), loss = 3.72711
I0707 20:16:13.707933 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54985 (* 0.3 = 0.764954 loss)
I0707 20:16:13.707953 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58211 (* 0.3 = 0.774634 loss)
I0707 20:16:13.707975 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55934 (* 1 = 2.55934 loss)
I0707 20:16:13.707991 99468 sgd_solver.cpp:105] Iteration 3320, lr = 0.001
I0707 20:17:29.950613 99468 solver.cpp:218] Iteration 3360 (0.524658 iter/s, 76.2402s/40 iters), loss = 3.69473
I0707 20:17:29.950798 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11007 (* 0.3 = 0.63302 loss)
I0707 20:17:29.950855 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12579 (* 0.3 = 0.637736 loss)
I0707 20:17:29.950871 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12429 (* 1 = 2.12429 loss)
I0707 20:17:29.950892 99468 sgd_solver.cpp:105] Iteration 3360, lr = 0.001
I0707 20:18:46.223798 99468 solver.cpp:218] Iteration 3400 (0.524449 iter/s, 76.2705s/40 iters), loss = 3.7527
I0707 20:18:46.223951 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.98817 (* 0.3 = 0.59645 loss)
I0707 20:18:46.223970 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00728 (* 0.3 = 0.602184 loss)
I0707 20:18:46.223986 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.00192 (* 1 = 2.00192 loss)
I0707 20:18:46.223997 99468 sgd_solver.cpp:105] Iteration 3400, lr = 0.001
I0707 20:20:02.529129 99468 solver.cpp:218] Iteration 3440 (0.524228 iter/s, 76.3027s/40 iters), loss = 3.68792
I0707 20:20:02.529281 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38297 (* 0.3 = 0.714892 loss)
I0707 20:20:02.529336 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37613 (* 0.3 = 0.712839 loss)
I0707 20:20:02.529351 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36108 (* 1 = 2.36108 loss)
I0707 20:20:02.529363 99468 sgd_solver.cpp:105] Iteration 3440, lr = 0.001
I0707 20:21:18.783432 99468 solver.cpp:218] Iteration 3480 (0.524579 iter/s, 76.2516s/40 iters), loss = 3.67244
I0707 20:21:18.783579 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46261 (* 0.3 = 0.738783 loss)
I0707 20:21:18.783601 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49261 (* 0.3 = 0.747784 loss)
I0707 20:21:18.783613 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44494 (* 1 = 2.44494 loss)
I0707 20:21:18.783634 99468 sgd_solver.cpp:105] Iteration 3480, lr = 0.001
I0707 20:22:35.040215 99468 solver.cpp:218] Iteration 3520 (0.524562 iter/s, 76.2541s/40 iters), loss = 3.7528
I0707 20:22:35.040360 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21082 (* 0.3 = 0.663246 loss)
I0707 20:22:35.040415 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20503 (* 0.3 = 0.661509 loss)
I0707 20:22:35.040426 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2016 (* 1 = 2.2016 loss)
I0707 20:22:35.040457 99468 sgd_solver.cpp:105] Iteration 3520, lr = 0.001
I0707 20:23:51.298619 99468 solver.cpp:218] Iteration 3560 (0.524551 iter/s, 76.2558s/40 iters), loss = 3.72392
I0707 20:23:51.298786 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24845 (* 0.3 = 0.674536 loss)
I0707 20:23:51.298842 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26323 (* 0.3 = 0.678968 loss)
I0707 20:23:51.298861 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25926 (* 1 = 2.25926 loss)
I0707 20:23:51.298892 99468 sgd_solver.cpp:105] Iteration 3560, lr = 0.001
I0707 20:25:07.574909 99468 solver.cpp:218] Iteration 3600 (0.524428 iter/s, 76.2736s/40 iters), loss = 3.70736
I0707 20:25:07.575053 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15419 (* 0.3 = 0.646258 loss)
I0707 20:25:07.575074 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14107 (* 0.3 = 0.64232 loss)
I0707 20:25:07.575089 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13357 (* 1 = 2.13357 loss)
I0707 20:25:07.575134 99468 sgd_solver.cpp:105] Iteration 3600, lr = 0.001
I0707 20:26:23.927536 99468 solver.cpp:218] Iteration 3640 (0.523903 iter/s, 76.35s/40 iters), loss = 3.71369
I0707 20:26:23.927736 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34399 (* 0.3 = 0.703196 loss)
I0707 20:26:23.927758 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35124 (* 0.3 = 0.705372 loss)
I0707 20:26:23.927773 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32194 (* 1 = 2.32194 loss)
I0707 20:26:23.927786 99468 sgd_solver.cpp:105] Iteration 3640, lr = 0.001
I0707 20:27:40.140866 99468 solver.cpp:218] Iteration 3680 (0.524861 iter/s, 76.2106s/40 iters), loss = 3.67987
I0707 20:27:40.141058 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44073 (* 0.3 = 0.732219 loss)
I0707 20:27:40.141125 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45821 (* 0.3 = 0.737464 loss)
I0707 20:27:40.141144 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45703 (* 1 = 2.45703 loss)
I0707 20:27:40.141160 99468 sgd_solver.cpp:105] Iteration 3680, lr = 0.001
I0707 20:28:56.505722 99468 solver.cpp:218] Iteration 3720 (0.52382 iter/s, 76.3622s/40 iters), loss = 3.74301
I0707 20:28:56.505944 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06699 (* 0.3 = 0.620096 loss)
I0707 20:28:56.505967 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07176 (* 0.3 = 0.621529 loss)
I0707 20:28:56.506016 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0716 (* 1 = 2.0716 loss)
I0707 20:28:56.506031 99468 sgd_solver.cpp:105] Iteration 3720, lr = 0.001
I0707 20:30:13.015866 99468 solver.cpp:218] Iteration 3760 (0.522825 iter/s, 76.5074s/40 iters), loss = 3.73059
I0707 20:30:13.016083 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48195 (* 0.3 = 0.744586 loss)
I0707 20:30:13.016106 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45806 (* 0.3 = 0.737418 loss)
I0707 20:30:13.016120 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45443 (* 1 = 2.45443 loss)
I0707 20:30:13.016137 99468 sgd_solver.cpp:105] Iteration 3760, lr = 0.001
I0707 20:31:29.561674 99468 solver.cpp:218] Iteration 3800 (0.522582 iter/s, 76.5431s/40 iters), loss = 3.7297
I0707 20:31:29.561897 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15808 (* 0.3 = 0.647423 loss)
I0707 20:31:29.561918 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16957 (* 0.3 = 0.65087 loss)
I0707 20:31:29.561934 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14218 (* 1 = 2.14218 loss)
I0707 20:31:29.561951 99468 sgd_solver.cpp:105] Iteration 3800, lr = 0.001
I0707 20:32:45.923419 99468 solver.cpp:218] Iteration 3840 (0.523841 iter/s, 76.359s/40 iters), loss = 3.71102
I0707 20:32:45.923650 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41236 (* 0.3 = 0.72371 loss)
I0707 20:32:45.923672 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40051 (* 0.3 = 0.720153 loss)
I0707 20:32:45.923687 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41548 (* 1 = 2.41548 loss)
I0707 20:32:45.923704 99468 sgd_solver.cpp:105] Iteration 3840, lr = 0.001
I0707 20:34:02.457355 99468 solver.cpp:218] Iteration 3880 (0.522663 iter/s, 76.5312s/40 iters), loss = 3.7318
I0707 20:34:02.457584 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31215 (* 0.3 = 0.693646 loss)
I0707 20:34:02.457639 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30581 (* 0.3 = 0.691743 loss)
I0707 20:34:02.457654 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28632 (* 1 = 2.28632 loss)
I0707 20:34:02.457671 99468 sgd_solver.cpp:105] Iteration 3880, lr = 0.001
I0707 20:35:18.991283 99468 solver.cpp:218] Iteration 3920 (0.522663 iter/s, 76.5312s/40 iters), loss = 3.70366
I0707 20:35:18.991505 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3569 (* 0.3 = 0.70707 loss)
I0707 20:35:18.991530 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39033 (* 0.3 = 0.717098 loss)
I0707 20:35:18.991595 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34952 (* 1 = 2.34952 loss)
I0707 20:35:18.991610 99468 sgd_solver.cpp:105] Iteration 3920, lr = 0.001
I0707 20:36:35.507169 99468 solver.cpp:218] Iteration 3960 (0.522786 iter/s, 76.5131s/40 iters), loss = 3.7734
I0707 20:36:35.507436 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41508 (* 0.3 = 0.724523 loss)
I0707 20:36:35.507462 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42004 (* 0.3 = 0.726012 loss)
I0707 20:36:35.507477 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40014 (* 1 = 2.40014 loss)
I0707 20:36:35.507494 99468 sgd_solver.cpp:105] Iteration 3960, lr = 0.001
I0707 20:37:49.540704 99468 solver.cpp:330] Iteration 4000, Testing net (#0)
I0707 20:42:26.019448 99468 blocking_queue.cpp:49] Waiting for data
I0707 20:48:21.436352 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07559 (* 0.3 = 0.622677 loss)
I0707 20:48:21.436846 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.367081
I0707 20:48:21.436878 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794815
I0707 20:48:21.436908 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07456 (* 0.3 = 0.622368 loss)
I0707 20:48:21.436929 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.367081
I0707 20:48:21.436988 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794815
I0707 20:48:21.437052 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.08191 (* 1 = 2.08191 loss)
I0707 20:48:21.437100 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.367081
I0707 20:48:21.437144 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.789656
I0707 20:48:23.338078 99468 solver.cpp:218] Iteration 4000 (0.0565125 iter/s, 707.808s/40 iters), loss = 3.70464
I0707 20:48:23.338152 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13858 (* 0.3 = 0.641575 loss)
I0707 20:48:23.338172 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12576 (* 0.3 = 0.637727 loss)
I0707 20:48:23.338189 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11728 (* 1 = 2.11728 loss)
I0707 20:48:23.338204 99468 sgd_solver.cpp:105] Iteration 4000, lr = 0.001
I0707 20:49:39.515939 99468 solver.cpp:218] Iteration 4040 (0.525105 iter/s, 76.1752s/40 iters), loss = 3.73143
I0707 20:49:39.516218 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02803 (* 0.3 = 0.608408 loss)
I0707 20:49:39.516247 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03582 (* 0.3 = 0.610745 loss)
I0707 20:49:39.516265 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02644 (* 1 = 2.02644 loss)
I0707 20:49:39.516281 99468 sgd_solver.cpp:105] Iteration 4040, lr = 0.001
I0707 20:50:55.802980 99468 solver.cpp:218] Iteration 4080 (0.524355 iter/s, 76.2843s/40 iters), loss = 3.71531
I0707 20:50:55.803145 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22851 (* 0.3 = 0.668552 loss)
I0707 20:50:55.803164 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26331 (* 0.3 = 0.678993 loss)
I0707 20:50:55.803210 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26642 (* 1 = 2.26642 loss)
I0707 20:50:55.803220 99468 sgd_solver.cpp:105] Iteration 4080, lr = 0.001
I0707 20:52:12.088433 99468 solver.cpp:218] Iteration 4120 (0.524365 iter/s, 76.2828s/40 iters), loss = 3.67154
I0707 20:52:12.088631 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26025 (* 0.3 = 0.678075 loss)
I0707 20:52:12.088668 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22782 (* 0.3 = 0.668346 loss)
I0707 20:52:12.088728 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22566 (* 1 = 2.22566 loss)
I0707 20:52:12.088752 99468 sgd_solver.cpp:105] Iteration 4120, lr = 0.001
I0707 20:53:28.402266 99468 solver.cpp:218] Iteration 4160 (0.52417 iter/s, 76.3111s/40 iters), loss = 3.66014
I0707 20:53:28.402442 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2372 (* 0.3 = 0.671159 loss)
I0707 20:53:28.402469 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22935 (* 0.3 = 0.668805 loss)
I0707 20:53:28.402482 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23021 (* 1 = 2.23021 loss)
I0707 20:53:28.402498 99468 sgd_solver.cpp:105] Iteration 4160, lr = 0.001
I0707 20:54:44.765250 99468 solver.cpp:218] Iteration 4200 (0.523833 iter/s, 76.3603s/40 iters), loss = 3.69619
I0707 20:54:44.765437 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1986 (* 0.3 = 0.65958 loss)
I0707 20:54:44.765458 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20338 (* 0.3 = 0.661013 loss)
I0707 20:54:44.765471 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18599 (* 1 = 2.18599 loss)
I0707 20:54:44.765482 99468 sgd_solver.cpp:105] Iteration 4200, lr = 0.001
I0707 20:56:00.997123 99468 solver.cpp:218] Iteration 4240 (0.524733 iter/s, 76.2292s/40 iters), loss = 3.74016
I0707 20:56:00.997283 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55546 (* 0.3 = 0.766638 loss)
I0707 20:56:00.997303 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5483 (* 0.3 = 0.76449 loss)
I0707 20:56:00.997318 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53561 (* 1 = 2.53561 loss)
I0707 20:56:00.997330 99468 sgd_solver.cpp:105] Iteration 4240, lr = 0.001
I0707 20:57:17.283984 99468 solver.cpp:218] Iteration 4280 (0.524355 iter/s, 76.2842s/40 iters), loss = 3.7559
I0707 20:57:17.284159 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59376 (* 0.3 = 0.778129 loss)
I0707 20:57:17.284178 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62649 (* 0.3 = 0.787948 loss)
I0707 20:57:17.284236 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59146 (* 1 = 2.59146 loss)
I0707 20:57:17.284247 99468 sgd_solver.cpp:105] Iteration 4280, lr = 0.001
I0707 20:58:33.525667 99468 solver.cpp:218] Iteration 4320 (0.524666 iter/s, 76.239s/40 iters), loss = 3.66169
I0707 20:58:33.525823 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5092 (* 0.3 = 0.752759 loss)
I0707 20:58:33.525887 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49333 (* 0.3 = 0.747999 loss)
I0707 20:58:33.525902 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48484 (* 1 = 2.48484 loss)
I0707 20:58:33.525913 99468 sgd_solver.cpp:105] Iteration 4320, lr = 0.001
I0707 20:59:49.798375 99468 solver.cpp:218] Iteration 4360 (0.524452 iter/s, 76.27s/40 iters), loss = 3.663
I0707 20:59:49.798537 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26008 (* 0.3 = 0.678023 loss)
I0707 20:59:49.798560 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25622 (* 0.3 = 0.676866 loss)
I0707 20:59:49.798573 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27155 (* 1 = 2.27155 loss)
I0707 20:59:49.798584 99468 sgd_solver.cpp:105] Iteration 4360, lr = 0.001
I0707 21:01:06.092166 99468 solver.cpp:218] Iteration 4400 (0.524308 iter/s, 76.2911s/40 iters), loss = 3.68792
I0707 21:01:06.092310 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.99401 (* 0.3 = 0.598204 loss)
I0707 21:01:06.092330 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00815 (* 0.3 = 0.602444 loss)
I0707 21:01:06.092345 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.98375 (* 1 = 1.98375 loss)
I0707 21:01:06.092356 99468 sgd_solver.cpp:105] Iteration 4400, lr = 0.001
I0707 21:02:22.429513 99468 solver.cpp:218] Iteration 4440 (0.524008 iter/s, 76.3347s/40 iters), loss = 3.7296
I0707 21:02:22.429682 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42923 (* 0.3 = 0.728769 loss)
I0707 21:02:22.429704 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47841 (* 0.3 = 0.743523 loss)
I0707 21:02:22.429723 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44719 (* 1 = 2.44719 loss)
I0707 21:02:22.429739 99468 sgd_solver.cpp:105] Iteration 4440, lr = 0.001
I0707 21:03:38.738916 99468 solver.cpp:218] Iteration 4480 (0.5242 iter/s, 76.3067s/40 iters), loss = 3.72162
I0707 21:03:38.739105 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09313 (* 0.3 = 0.627938 loss)
I0707 21:03:38.739158 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07145 (* 0.3 = 0.621436 loss)
I0707 21:03:38.739189 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07294 (* 1 = 2.07294 loss)
I0707 21:03:38.739202 99468 sgd_solver.cpp:105] Iteration 4480, lr = 0.001
I0707 21:04:55.032383 99468 solver.cpp:218] Iteration 4520 (0.52431 iter/s, 76.2908s/40 iters), loss = 3.76558
I0707 21:04:55.032562 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08628 (* 0.3 = 0.625883 loss)
I0707 21:04:55.032585 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08593 (* 0.3 = 0.62578 loss)
I0707 21:04:55.032600 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08098 (* 1 = 2.08098 loss)
I0707 21:04:55.032615 99468 sgd_solver.cpp:105] Iteration 4520, lr = 0.001
I0707 21:06:11.295029 99468 solver.cpp:218] Iteration 4560 (0.524522 iter/s, 76.26s/40 iters), loss = 3.68187
I0707 21:06:11.295195 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35379 (* 0.3 = 0.706137 loss)
I0707 21:06:11.295218 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3735 (* 0.3 = 0.712049 loss)
I0707 21:06:11.295231 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37388 (* 1 = 2.37388 loss)
I0707 21:06:11.295244 99468 sgd_solver.cpp:105] Iteration 4560, lr = 0.001
I0707 21:07:27.538481 99468 solver.cpp:218] Iteration 4600 (0.524654 iter/s, 76.2408s/40 iters), loss = 3.7277
I0707 21:07:27.538653 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23579 (* 0.3 = 0.670738 loss)
I0707 21:07:27.538676 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25021 (* 0.3 = 0.675063 loss)
I0707 21:07:27.538691 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22492 (* 1 = 2.22492 loss)
I0707 21:07:27.538707 99468 sgd_solver.cpp:105] Iteration 4600, lr = 0.001
I0707 21:08:43.855093 99468 solver.cpp:218] Iteration 4640 (0.524151 iter/s, 76.3139s/40 iters), loss = 3.76935
I0707 21:08:43.855242 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48755 (* 0.3 = 0.746264 loss)
I0707 21:08:43.855260 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46801 (* 0.3 = 0.740404 loss)
I0707 21:08:43.855311 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46848 (* 1 = 2.46848 loss)
I0707 21:08:43.855331 99468 sgd_solver.cpp:105] Iteration 4640, lr = 0.001
I0707 21:10:00.115825 99468 solver.cpp:218] Iteration 4680 (0.524535 iter/s, 76.2581s/40 iters), loss = 3.70675
I0707 21:10:00.115999 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41233 (* 0.3 = 0.723699 loss)
I0707 21:10:00.116055 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39377 (* 0.3 = 0.718131 loss)
I0707 21:10:00.116075 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39268 (* 1 = 2.39268 loss)
I0707 21:10:00.116111 99468 sgd_solver.cpp:105] Iteration 4680, lr = 0.001
I0707 21:11:16.433446 99468 solver.cpp:218] Iteration 4720 (0.524144 iter/s, 76.3149s/40 iters), loss = 3.73378
I0707 21:11:16.434059 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13184 (* 0.3 = 0.639551 loss)
I0707 21:11:16.434111 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1154 (* 0.3 = 0.634621 loss)
I0707 21:11:16.434128 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11353 (* 1 = 2.11353 loss)
I0707 21:11:16.434159 99468 sgd_solver.cpp:105] Iteration 4720, lr = 0.001
I0707 21:12:32.693276 99468 solver.cpp:218] Iteration 4760 (0.524544 iter/s, 76.2567s/40 iters), loss = 3.70967
I0707 21:12:32.693429 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34138 (* 0.3 = 0.702413 loss)
I0707 21:12:32.693449 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3394 (* 0.3 = 0.70182 loss)
I0707 21:12:32.693495 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32351 (* 1 = 2.32351 loss)
I0707 21:12:32.693507 99468 sgd_solver.cpp:105] Iteration 4760, lr = 0.001
I0707 21:13:49.029572 99468 solver.cpp:218] Iteration 4800 (0.524016 iter/s, 76.3336s/40 iters), loss = 3.709
I0707 21:13:49.029742 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38368 (* 0.3 = 0.715104 loss)
I0707 21:13:49.029763 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37045 (* 0.3 = 0.711135 loss)
I0707 21:13:49.029778 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37628 (* 1 = 2.37628 loss)
I0707 21:13:49.029819 99468 sgd_solver.cpp:105] Iteration 4800, lr = 0.001
I0707 21:15:05.319511 99468 solver.cpp:218] Iteration 4840 (0.524334 iter/s, 76.2872s/40 iters), loss = 3.66878
I0707 21:15:05.319670 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24744 (* 0.3 = 0.674231 loss)
I0707 21:15:05.319723 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28982 (* 0.3 = 0.686947 loss)
I0707 21:15:05.319741 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26838 (* 1 = 2.26838 loss)
I0707 21:15:05.319754 99468 sgd_solver.cpp:105] Iteration 4840, lr = 0.001
I0707 21:16:21.596807 99468 solver.cpp:218] Iteration 4880 (0.524421 iter/s, 76.2746s/40 iters), loss = 3.74973
I0707 21:16:21.596948 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.97224 (* 0.3 = 0.591671 loss)
I0707 21:16:21.596968 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.97945 (* 0.3 = 0.593835 loss)
I0707 21:16:21.596985 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.97924 (* 1 = 1.97924 loss)
I0707 21:16:21.597028 99468 sgd_solver.cpp:105] Iteration 4880, lr = 0.001
I0707 21:17:37.903822 99468 solver.cpp:218] Iteration 4920 (0.524216 iter/s, 76.3044s/40 iters), loss = 3.66271
I0707 21:17:37.903978 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65726 (* 0.3 = 0.797177 loss)
I0707 21:17:37.903997 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.66126 (* 0.3 = 0.798378 loss)
I0707 21:17:37.904013 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.66546 (* 1 = 2.66546 loss)
I0707 21:17:37.904026 99468 sgd_solver.cpp:105] Iteration 4920, lr = 0.001
I0707 21:18:54.223850 99468 solver.cpp:218] Iteration 4960 (0.524127 iter/s, 76.3173s/40 iters), loss = 3.71228
I0707 21:18:54.224031 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34442 (* 0.3 = 0.703326 loss)
I0707 21:18:54.224057 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34984 (* 0.3 = 0.704953 loss)
I0707 21:18:54.224074 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36131 (* 1 = 2.36131 loss)
I0707 21:18:54.224089 99468 sgd_solver.cpp:105] Iteration 4960, lr = 0.001
I0707 21:20:10.489737 99468 solver.cpp:218] Iteration 5000 (0.524499 iter/s, 76.2632s/40 iters), loss = 3.72889
I0707 21:20:10.489924 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18891 (* 0.3 = 0.656672 loss)
I0707 21:20:10.489989 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18325 (* 0.3 = 0.654975 loss)
I0707 21:20:10.490008 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.182 (* 1 = 2.182 loss)
I0707 21:20:10.490023 99468 sgd_solver.cpp:105] Iteration 5000, lr = 0.001
I0707 21:21:26.821307 99468 solver.cpp:218] Iteration 5040 (0.524048 iter/s, 76.3289s/40 iters), loss = 3.70818
I0707 21:21:26.821465 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17799 (* 0.3 = 0.653396 loss)
I0707 21:21:26.821482 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16757 (* 0.3 = 0.650271 loss)
I0707 21:21:26.821527 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1684 (* 1 = 2.1684 loss)
I0707 21:21:26.821540 99468 sgd_solver.cpp:105] Iteration 5040, lr = 0.001
I0707 21:22:43.175602 99468 solver.cpp:218] Iteration 5080 (0.523892 iter/s, 76.3516s/40 iters), loss = 3.64575
I0707 21:22:43.175762 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16717 (* 0.3 = 0.65015 loss)
I0707 21:22:43.175822 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16069 (* 0.3 = 0.648206 loss)
I0707 21:22:43.175851 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17302 (* 1 = 2.17302 loss)
I0707 21:22:43.175864 99468 sgd_solver.cpp:105] Iteration 5080, lr = 0.001
I0707 21:23:59.552711 99468 solver.cpp:218] Iteration 5120 (0.523736 iter/s, 76.3744s/40 iters), loss = 3.68836
I0707 21:23:59.552901 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19495 (* 0.3 = 0.658484 loss)
I0707 21:23:59.552953 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21383 (* 0.3 = 0.66415 loss)
I0707 21:23:59.552981 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18398 (* 1 = 2.18398 loss)
I0707 21:23:59.552994 99468 sgd_solver.cpp:105] Iteration 5120, lr = 0.001
I0707 21:25:15.810189 99468 solver.cpp:218] Iteration 5160 (0.524557 iter/s, 76.2548s/40 iters), loss = 3.67334
I0707 21:25:15.810355 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.0972 (* 0.3 = 0.629161 loss)
I0707 21:25:15.810379 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07548 (* 0.3 = 0.622643 loss)
I0707 21:25:15.810396 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09257 (* 1 = 2.09257 loss)
I0707 21:25:15.810410 99468 sgd_solver.cpp:105] Iteration 5160, lr = 0.001
I0707 21:26:32.108631 99468 solver.cpp:218] Iteration 5200 (0.524276 iter/s, 76.2958s/40 iters), loss = 3.74695
I0707 21:26:32.108800 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34725 (* 0.3 = 0.704176 loss)
I0707 21:26:32.108826 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30834 (* 0.3 = 0.692501 loss)
I0707 21:26:32.108877 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33626 (* 1 = 2.33626 loss)
I0707 21:26:32.108891 99468 sgd_solver.cpp:105] Iteration 5200, lr = 0.001
I0707 21:27:48.446221 99468 solver.cpp:218] Iteration 5240 (0.524007 iter/s, 76.3349s/40 iters), loss = 3.66341
I0707 21:27:48.446370 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28875 (* 0.3 = 0.686626 loss)
I0707 21:27:48.446426 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26656 (* 0.3 = 0.679969 loss)
I0707 21:27:48.446444 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24847 (* 1 = 2.24847 loss)
I0707 21:27:48.446455 99468 sgd_solver.cpp:105] Iteration 5240, lr = 0.001
I0707 21:29:04.758615 99468 solver.cpp:218] Iteration 5280 (0.52418 iter/s, 76.3097s/40 iters), loss = 3.69949
I0707 21:29:04.758764 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.61546 (* 0.3 = 0.784638 loss)
I0707 21:29:04.758790 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.63105 (* 0.3 = 0.789315 loss)
I0707 21:29:04.758810 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.63115 (* 1 = 2.63115 loss)
I0707 21:29:04.758822 99468 sgd_solver.cpp:105] Iteration 5280, lr = 0.001
I0707 21:30:21.108698 99468 solver.cpp:218] Iteration 5320 (0.523921 iter/s, 76.3474s/40 iters), loss = 3.75149
I0707 21:30:21.108896 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17931 (* 0.3 = 0.653792 loss)
I0707 21:30:21.108932 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17924 (* 0.3 = 0.653773 loss)
I0707 21:30:21.108960 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16217 (* 1 = 2.16217 loss)
I0707 21:30:21.109019 99468 sgd_solver.cpp:105] Iteration 5320, lr = 0.001
I0707 21:31:37.374788 99468 solver.cpp:218] Iteration 5360 (0.524498 iter/s, 76.2634s/40 iters), loss = 3.72847
I0707 21:31:37.374954 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14492 (* 0.3 = 0.643476 loss)
I0707 21:31:37.374974 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12243 (* 0.3 = 0.636728 loss)
I0707 21:31:37.374991 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13086 (* 1 = 2.13086 loss)
I0707 21:31:37.375036 99468 sgd_solver.cpp:105] Iteration 5360, lr = 0.001
I0707 21:32:53.692770 99468 solver.cpp:218] Iteration 5400 (0.524141 iter/s, 76.3153s/40 iters), loss = 3.67567
I0707 21:32:53.692934 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.96278 (* 0.3 = 0.588834 loss)
I0707 21:32:53.692988 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.97085 (* 0.3 = 0.591254 loss)
I0707 21:32:53.693006 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.9614 (* 1 = 1.9614 loss)
I0707 21:32:53.693037 99468 sgd_solver.cpp:105] Iteration 5400, lr = 0.001
I0707 21:34:10.013815 99468 solver.cpp:218] Iteration 5440 (0.52412 iter/s, 76.3184s/40 iters), loss = 3.74938
I0707 21:34:10.013998 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59659 (* 0.3 = 0.778978 loss)
I0707 21:34:10.014050 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5978 (* 0.3 = 0.779339 loss)
I0707 21:34:10.014080 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.58708 (* 1 = 2.58708 loss)
I0707 21:34:10.014092 99468 sgd_solver.cpp:105] Iteration 5440, lr = 0.001
I0707 21:35:26.324281 99468 solver.cpp:218] Iteration 5480 (0.524193 iter/s, 76.3078s/40 iters), loss = 3.70992
I0707 21:35:26.324446 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46599 (* 0.3 = 0.739797 loss)
I0707 21:35:26.324498 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44764 (* 0.3 = 0.734293 loss)
I0707 21:35:26.324527 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46137 (* 1 = 2.46137 loss)
I0707 21:35:26.324540 99468 sgd_solver.cpp:105] Iteration 5480, lr = 0.001
I0707 21:36:42.645265 99468 solver.cpp:218] Iteration 5520 (0.524121 iter/s, 76.3183s/40 iters), loss = 3.80771
I0707 21:36:42.645426 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35964 (* 0.3 = 0.707893 loss)
I0707 21:36:42.645485 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33603 (* 0.3 = 0.70081 loss)
I0707 21:36:42.645503 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3252 (* 1 = 2.3252 loss)
I0707 21:36:42.645535 99468 sgd_solver.cpp:105] Iteration 5520, lr = 0.001
I0707 21:37:58.948606 99468 solver.cpp:218] Iteration 5560 (0.524242 iter/s, 76.3007s/40 iters), loss = 3.69992
I0707 21:37:58.948765 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56089 (* 0.3 = 0.768266 loss)
I0707 21:37:58.948827 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.54305 (* 0.3 = 0.762915 loss)
I0707 21:37:58.948860 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5319 (* 1 = 2.5319 loss)
I0707 21:37:58.948873 99468 sgd_solver.cpp:105] Iteration 5560, lr = 0.001
I0707 21:39:15.278787 99468 solver.cpp:218] Iteration 5600 (0.524057 iter/s, 76.3275s/40 iters), loss = 3.69394
I0707 21:39:15.278931 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18282 (* 0.3 = 0.654846 loss)
I0707 21:39:15.278950 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18583 (* 0.3 = 0.655749 loss)
I0707 21:39:15.278964 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19588 (* 1 = 2.19588 loss)
I0707 21:39:15.278975 99468 sgd_solver.cpp:105] Iteration 5600, lr = 0.001
I0707 21:40:31.574656 99468 solver.cpp:218] Iteration 5640 (0.524293 iter/s, 76.2932s/40 iters), loss = 3.65882
I0707 21:40:31.574808 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15089 (* 0.3 = 0.645266 loss)
I0707 21:40:31.574827 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19148 (* 0.3 = 0.657443 loss)
I0707 21:40:31.574843 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15957 (* 1 = 2.15957 loss)
I0707 21:40:31.574853 99468 sgd_solver.cpp:105] Iteration 5640, lr = 0.001
I0707 21:41:47.872078 99468 solver.cpp:218] Iteration 5680 (0.524283 iter/s, 76.2947s/40 iters), loss = 3.70023
I0707 21:41:47.872261 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33528 (* 0.3 = 0.700584 loss)
I0707 21:41:47.872288 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39088 (* 0.3 = 0.717264 loss)
I0707 21:41:47.872308 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36014 (* 1 = 2.36014 loss)
I0707 21:41:47.872323 99468 sgd_solver.cpp:105] Iteration 5680, lr = 0.001
I0707 21:43:04.233424 99468 solver.cpp:218] Iteration 5720 (0.523844 iter/s, 76.3586s/40 iters), loss = 3.71659
I0707 21:43:04.233705 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54284 (* 0.3 = 0.762851 loss)
I0707 21:43:04.233777 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.56582 (* 0.3 = 0.769746 loss)
I0707 21:43:04.233800 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52999 (* 1 = 2.52999 loss)
I0707 21:43:04.233821 99468 sgd_solver.cpp:105] Iteration 5720, lr = 0.001
I0707 21:44:20.567111 99468 solver.cpp:218] Iteration 5760 (0.524034 iter/s, 76.3309s/40 iters), loss = 3.71021
I0707 21:44:20.567272 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45762 (* 0.3 = 0.737287 loss)
I0707 21:44:20.567291 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44653 (* 0.3 = 0.733959 loss)
I0707 21:44:20.567339 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48934 (* 1 = 2.48934 loss)
I0707 21:44:20.567351 99468 sgd_solver.cpp:105] Iteration 5760, lr = 0.001
I0707 21:45:36.870909 99468 solver.cpp:218] Iteration 5800 (0.524239 iter/s, 76.3011s/40 iters), loss = 3.71713
I0707 21:45:36.871073 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30362 (* 0.3 = 0.691085 loss)
I0707 21:45:36.871127 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31583 (* 0.3 = 0.69475 loss)
I0707 21:45:36.871156 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3155 (* 1 = 2.3155 loss)
I0707 21:45:36.871168 99468 sgd_solver.cpp:105] Iteration 5800, lr = 0.001
I0707 21:46:53.176224 99468 solver.cpp:218] Iteration 5840 (0.524228 iter/s, 76.3026s/40 iters), loss = 3.71716
I0707 21:46:53.176409 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09627 (* 0.3 = 0.628881 loss)
I0707 21:46:53.176471 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10255 (* 0.3 = 0.630765 loss)
I0707 21:46:53.176488 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07132 (* 1 = 2.07132 loss)
I0707 21:46:53.176507 99468 sgd_solver.cpp:105] Iteration 5840, lr = 0.001
I0707 21:48:09.490599 99468 solver.cpp:218] Iteration 5880 (0.524166 iter/s, 76.3117s/40 iters), loss = 3.66796
I0707 21:48:09.490754 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30479 (* 0.3 = 0.691437 loss)
I0707 21:48:09.490774 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29242 (* 0.3 = 0.687727 loss)
I0707 21:48:09.490793 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30634 (* 1 = 2.30634 loss)
I0707 21:48:09.490806 99468 sgd_solver.cpp:105] Iteration 5880, lr = 0.001
I0707 21:49:25.747355 99468 solver.cpp:218] Iteration 5920 (0.524562 iter/s, 76.2541s/40 iters), loss = 3.67579
I0707 21:49:25.747535 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45617 (* 0.3 = 0.736852 loss)
I0707 21:49:25.747567 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41431 (* 0.3 = 0.724292 loss)
I0707 21:49:25.747586 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43124 (* 1 = 2.43124 loss)
I0707 21:49:25.747607 99468 sgd_solver.cpp:105] Iteration 5920, lr = 0.001
I0707 21:50:42.020617 99468 solver.cpp:218] Iteration 5960 (0.524449 iter/s, 76.2705s/40 iters), loss = 3.73719
I0707 21:50:42.020855 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59027 (* 0.3 = 0.77708 loss)
I0707 21:50:42.020891 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58617 (* 0.3 = 0.77585 loss)
I0707 21:50:42.020921 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.56661 (* 1 = 2.56661 loss)
I0707 21:50:42.020993 99468 sgd_solver.cpp:105] Iteration 5960, lr = 0.001
I0707 21:51:58.354029 99468 solver.cpp:218] Iteration 6000 (0.524036 iter/s, 76.3307s/40 iters), loss = 3.709
I0707 21:51:58.354179 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23941 (* 0.3 = 0.671822 loss)
I0707 21:51:58.354199 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2409 (* 0.3 = 0.672271 loss)
I0707 21:51:58.354213 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24578 (* 1 = 2.24578 loss)
I0707 21:51:58.354223 99468 sgd_solver.cpp:105] Iteration 6000, lr = 0.001
I0707 21:53:14.715867 99468 solver.cpp:218] Iteration 6040 (0.52384 iter/s, 76.3592s/40 iters), loss = 3.76854
I0707 21:53:14.716114 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22554 (* 0.3 = 0.667662 loss)
I0707 21:53:14.716182 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19591 (* 0.3 = 0.658773 loss)
I0707 21:53:14.716199 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20048 (* 1 = 2.20048 loss)
I0707 21:53:14.716235 99468 sgd_solver.cpp:105] Iteration 6040, lr = 0.001
I0707 21:54:31.033932 99468 solver.cpp:218] Iteration 6080 (0.524141 iter/s, 76.3153s/40 iters), loss = 3.67645
I0707 21:54:31.034116 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4939 (* 0.3 = 0.748171 loss)
I0707 21:54:31.034137 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48956 (* 0.3 = 0.746867 loss)
I0707 21:54:31.034184 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47299 (* 1 = 2.47299 loss)
I0707 21:54:31.034198 99468 sgd_solver.cpp:105] Iteration 6080, lr = 0.001
I0707 21:55:47.324220 99468 solver.cpp:218] Iteration 6120 (0.524332 iter/s, 76.2876s/40 iters), loss = 3.73956
I0707 21:55:47.324376 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13472 (* 0.3 = 0.640417 loss)
I0707 21:55:47.324398 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12581 (* 0.3 = 0.637744 loss)
I0707 21:55:47.324448 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1435 (* 1 = 2.1435 loss)
I0707 21:55:47.324461 99468 sgd_solver.cpp:105] Iteration 6120, lr = 0.001
I0707 21:57:03.597522 99468 solver.cpp:218] Iteration 6160 (0.524448 iter/s, 76.2706s/40 iters), loss = 3.71977
I0707 21:57:03.597695 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2473 (* 0.3 = 0.674189 loss)
I0707 21:57:03.597715 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24067 (* 0.3 = 0.672202 loss)
I0707 21:57:03.597730 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2357 (* 1 = 2.2357 loss)
I0707 21:57:03.597741 99468 sgd_solver.cpp:105] Iteration 6160, lr = 0.001
I0707 21:58:19.866091 99468 solver.cpp:218] Iteration 6200 (0.524481 iter/s, 76.2659s/40 iters), loss = 3.74796
I0707 21:58:19.866247 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28844 (* 0.3 = 0.686533 loss)
I0707 21:58:19.866264 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26126 (* 0.3 = 0.678379 loss)
I0707 21:58:19.866308 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26669 (* 1 = 2.26669 loss)
I0707 21:58:19.866322 99468 sgd_solver.cpp:105] Iteration 6200, lr = 0.001
I0707 21:59:36.202081 99468 solver.cpp:218] Iteration 6240 (0.524018 iter/s, 76.3333s/40 iters), loss = 3.74431
I0707 21:59:36.202267 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60573 (* 0.3 = 0.781719 loss)
I0707 21:59:36.202337 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59737 (* 0.3 = 0.779212 loss)
I0707 21:59:36.202353 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.60099 (* 1 = 2.60099 loss)
I0707 21:59:36.202370 99468 sgd_solver.cpp:105] Iteration 6240, lr = 0.001
I0707 22:00:52.446177 99468 solver.cpp:218] Iteration 6280 (0.524649 iter/s, 76.2414s/40 iters), loss = 3.7172
I0707 22:00:52.446353 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50477 (* 0.3 = 0.751432 loss)
I0707 22:00:52.446377 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5147 (* 0.3 = 0.754409 loss)
I0707 22:00:52.446426 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48954 (* 1 = 2.48954 loss)
I0707 22:00:52.446444 99468 sgd_solver.cpp:105] Iteration 6280, lr = 0.001
I0707 22:02:08.696534 99468 solver.cpp:218] Iteration 6320 (0.524606 iter/s, 76.2477s/40 iters), loss = 3.66773
I0707 22:02:08.696715 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38834 (* 0.3 = 0.716503 loss)
I0707 22:02:08.696741 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38938 (* 0.3 = 0.716815 loss)
I0707 22:02:08.696759 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38431 (* 1 = 2.38431 loss)
I0707 22:02:08.696776 99468 sgd_solver.cpp:105] Iteration 6320, lr = 0.001
I0707 22:03:24.943302 99468 solver.cpp:218] Iteration 6360 (0.524631 iter/s, 76.2441s/40 iters), loss = 3.67942
I0707 22:03:24.943500 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10713 (* 0.3 = 0.632138 loss)
I0707 22:03:24.943521 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07973 (* 0.3 = 0.623919 loss)
I0707 22:03:24.943536 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08435 (* 1 = 2.08435 loss)
I0707 22:03:24.943548 99468 sgd_solver.cpp:105] Iteration 6360, lr = 0.001
I0707 22:04:41.189738 99468 solver.cpp:218] Iteration 6400 (0.524633 iter/s, 76.2437s/40 iters), loss = 3.69614
I0707 22:04:41.189893 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35398 (* 0.3 = 0.706194 loss)
I0707 22:04:41.189913 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34936 (* 0.3 = 0.704808 loss)
I0707 22:04:41.189929 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33605 (* 1 = 2.33605 loss)
I0707 22:04:41.189980 99468 sgd_solver.cpp:105] Iteration 6400, lr = 0.001
I0707 22:05:57.536639 99468 solver.cpp:218] Iteration 6440 (0.523943 iter/s, 76.3442s/40 iters), loss = 3.68414
I0707 22:05:57.536854 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30735 (* 0.3 = 0.692204 loss)
I0707 22:05:57.536876 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30614 (* 0.3 = 0.691842 loss)
I0707 22:05:57.536890 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29944 (* 1 = 2.29944 loss)
I0707 22:05:57.536905 99468 sgd_solver.cpp:105] Iteration 6440, lr = 0.001
I0707 22:07:13.857728 99468 solver.cpp:218] Iteration 6480 (0.52412 iter/s, 76.3183s/40 iters), loss = 3.65751
I0707 22:07:13.857899 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04288 (* 0.3 = 0.612863 loss)
I0707 22:07:13.857957 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03672 (* 0.3 = 0.611017 loss)
I0707 22:07:13.857973 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02059 (* 1 = 2.02059 loss)
I0707 22:07:13.857987 99468 sgd_solver.cpp:105] Iteration 6480, lr = 0.001
I0707 22:08:30.212491 99468 solver.cpp:218] Iteration 6520 (0.523889 iter/s, 76.352s/40 iters), loss = 3.71396
I0707 22:08:30.212755 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.97903 (* 0.3 = 0.59371 loss)
I0707 22:08:30.212785 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.99123 (* 0.3 = 0.59737 loss)
I0707 22:08:30.212803 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99306 (* 1 = 1.99306 loss)
I0707 22:08:30.212827 99468 sgd_solver.cpp:105] Iteration 6520, lr = 0.001
I0707 22:09:46.773694 99468 solver.cpp:218] Iteration 6560 (0.522477 iter/s, 76.5584s/40 iters), loss = 3.6646
I0707 22:09:46.773928 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5029 (* 0.3 = 0.75087 loss)
I0707 22:09:46.773952 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53395 (* 0.3 = 0.760186 loss)
I0707 22:09:46.773963 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50196 (* 1 = 2.50196 loss)
I0707 22:09:46.773983 99468 sgd_solver.cpp:105] Iteration 6560, lr = 0.001
I0707 22:11:03.030269 99468 solver.cpp:218] Iteration 6600 (0.524564 iter/s, 76.2538s/40 iters), loss = 3.66289
I0707 22:11:03.030485 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36659 (* 0.3 = 0.709976 loss)
I0707 22:11:03.030506 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37024 (* 0.3 = 0.711073 loss)
I0707 22:11:03.030520 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35244 (* 1 = 2.35244 loss)
I0707 22:11:03.030537 99468 sgd_solver.cpp:105] Iteration 6600, lr = 0.001
I0707 22:12:19.313318 99468 solver.cpp:218] Iteration 6640 (0.524382 iter/s, 76.2803s/40 iters), loss = 3.6951
I0707 22:12:19.313513 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27252 (* 0.3 = 0.681755 loss)
I0707 22:12:19.313544 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26502 (* 0.3 = 0.679507 loss)
I0707 22:12:19.313570 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27279 (* 1 = 2.27279 loss)
I0707 22:12:19.313588 99468 sgd_solver.cpp:105] Iteration 6640, lr = 0.001
I0707 22:13:35.666172 99468 solver.cpp:218] Iteration 6680 (0.523902 iter/s, 76.3501s/40 iters), loss = 3.70573
I0707 22:13:35.666435 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29374 (* 0.3 = 0.688121 loss)
I0707 22:13:35.666460 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28907 (* 0.3 = 0.68672 loss)
I0707 22:13:35.666481 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29746 (* 1 = 2.29746 loss)
I0707 22:13:35.666493 99468 sgd_solver.cpp:105] Iteration 6680, lr = 0.001
I0707 22:14:51.939455 99468 solver.cpp:218] Iteration 6720 (0.524449 iter/s, 76.2705s/40 iters), loss = 3.69389
I0707 22:14:51.939651 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34434 (* 0.3 = 0.703303 loss)
I0707 22:14:51.939672 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36803 (* 0.3 = 0.710408 loss)
I0707 22:14:51.939685 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34252 (* 1 = 2.34252 loss)
I0707 22:14:51.939740 99468 sgd_solver.cpp:105] Iteration 6720, lr = 0.001
I0707 22:16:08.198297 99468 solver.cpp:218] Iteration 6760 (0.524548 iter/s, 76.2561s/40 iters), loss = 3.68155
I0707 22:16:08.198493 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28594 (* 0.3 = 0.685781 loss)
I0707 22:16:08.198514 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31763 (* 0.3 = 0.695289 loss)
I0707 22:16:08.198534 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29201 (* 1 = 2.29201 loss)
I0707 22:16:08.198587 99468 sgd_solver.cpp:105] Iteration 6760, lr = 0.001
I0707 22:17:24.570927 99468 solver.cpp:218] Iteration 6800 (0.523767 iter/s, 76.3699s/40 iters), loss = 3.67306
I0707 22:17:24.571102 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48275 (* 0.3 = 0.744824 loss)
I0707 22:17:24.571163 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49172 (* 0.3 = 0.747516 loss)
I0707 22:17:24.571182 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47066 (* 1 = 2.47066 loss)
I0707 22:17:24.571194 99468 sgd_solver.cpp:105] Iteration 6800, lr = 0.001
I0707 22:18:40.888887 99468 solver.cpp:218] Iteration 6840 (0.524142 iter/s, 76.3153s/40 iters), loss = 3.67298
I0707 22:18:40.889057 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33308 (* 0.3 = 0.699925 loss)
I0707 22:18:40.889080 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33417 (* 0.3 = 0.700251 loss)
I0707 22:18:40.889094 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3202 (* 1 = 2.3202 loss)
I0707 22:18:40.889142 99468 sgd_solver.cpp:105] Iteration 6840, lr = 0.001
I0707 22:19:57.098734 99468 solver.cpp:218] Iteration 6880 (0.524885 iter/s, 76.2072s/40 iters), loss = 3.65265
I0707 22:19:57.098892 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41824 (* 0.3 = 0.725471 loss)
I0707 22:19:57.098954 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40415 (* 0.3 = 0.721246 loss)
I0707 22:19:57.098985 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38566 (* 1 = 2.38566 loss)
I0707 22:19:57.098999 99468 sgd_solver.cpp:105] Iteration 6880, lr = 0.001
I0707 22:21:13.436650 99468 solver.cpp:218] Iteration 6920 (0.524004 iter/s, 76.3352s/40 iters), loss = 3.73676
I0707 22:21:13.436813 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51054 (* 0.3 = 0.753163 loss)
I0707 22:21:13.436833 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5248 (* 0.3 = 0.75744 loss)
I0707 22:21:13.436851 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5078 (* 1 = 2.5078 loss)
I0707 22:21:13.436862 99468 sgd_solver.cpp:105] Iteration 6920, lr = 0.001
I0707 22:22:29.679276 99468 solver.cpp:218] Iteration 6960 (0.524659 iter/s, 76.2399s/40 iters), loss = 3.73629
I0707 22:22:29.679523 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5678 (* 0.3 = 0.77034 loss)
I0707 22:22:29.679560 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57542 (* 0.3 = 0.772627 loss)
I0707 22:22:29.679581 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5742 (* 1 = 2.5742 loss)
I0707 22:22:29.679597 99468 sgd_solver.cpp:105] Iteration 6960, lr = 0.001
I0707 22:23:45.993124 99468 solver.cpp:218] Iteration 7000 (0.52417 iter/s, 76.3111s/40 iters), loss = 3.7246
I0707 22:23:45.993279 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.73225 (* 0.3 = 0.819676 loss)
I0707 22:23:45.993299 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.71352 (* 0.3 = 0.814057 loss)
I0707 22:23:45.993350 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.70286 (* 1 = 2.70286 loss)
I0707 22:23:45.993362 99468 sgd_solver.cpp:105] Iteration 7000, lr = 0.001
I0707 22:25:02.330467 99468 solver.cpp:218] Iteration 7040 (0.524008 iter/s, 76.3347s/40 iters), loss = 3.71491
I0707 22:25:02.330653 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45998 (* 0.3 = 0.737994 loss)
I0707 22:25:02.330680 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4697 (* 0.3 = 0.740909 loss)
I0707 22:25:02.330735 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4386 (* 1 = 2.4386 loss)
I0707 22:25:02.330752 99468 sgd_solver.cpp:105] Iteration 7040, lr = 0.001
I0707 22:26:18.611484 99468 solver.cpp:218] Iteration 7080 (0.524396 iter/s, 76.2783s/40 iters), loss = 3.72608
I0707 22:26:18.611640 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4366 (* 0.3 = 0.730979 loss)
I0707 22:26:18.611696 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45017 (* 0.3 = 0.73505 loss)
I0707 22:26:18.611726 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45153 (* 1 = 2.45153 loss)
I0707 22:26:18.611738 99468 sgd_solver.cpp:105] Iteration 7080, lr = 0.001
I0707 22:27:34.931596 99468 solver.cpp:218] Iteration 7120 (0.524127 iter/s, 76.3174s/40 iters), loss = 3.67691
I0707 22:27:34.931766 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.49197 (* 0.3 = 0.747592 loss)
I0707 22:27:34.931825 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51872 (* 0.3 = 0.755616 loss)
I0707 22:27:34.931843 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49589 (* 1 = 2.49589 loss)
I0707 22:27:34.931857 99468 sgd_solver.cpp:105] Iteration 7120, lr = 0.001
I0707 22:28:51.179461 99468 solver.cpp:218] Iteration 7160 (0.524623 iter/s, 76.2452s/40 iters), loss = 3.71077
I0707 22:28:51.179854 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39458 (* 0.3 = 0.718373 loss)
I0707 22:28:51.179908 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39938 (* 0.3 = 0.719813 loss)
I0707 22:28:51.179925 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38863 (* 1 = 2.38863 loss)
I0707 22:28:51.179955 99468 sgd_solver.cpp:105] Iteration 7160, lr = 0.001
I0707 22:30:07.486743 99468 solver.cpp:218] Iteration 7200 (0.524216 iter/s, 76.3044s/40 iters), loss = 3.75042
I0707 22:30:07.486902 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34926 (* 0.3 = 0.704778 loss)
I0707 22:30:07.486924 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34372 (* 0.3 = 0.703116 loss)
I0707 22:30:07.486938 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34927 (* 1 = 2.34927 loss)
I0707 22:30:07.486955 99468 sgd_solver.cpp:105] Iteration 7200, lr = 0.001
I0707 22:31:23.793831 99468 solver.cpp:218] Iteration 7240 (0.524216 iter/s, 76.3044s/40 iters), loss = 3.69847
I0707 22:31:23.793975 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02523 (* 0.3 = 0.607569 loss)
I0707 22:31:23.793994 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04142 (* 0.3 = 0.612425 loss)
I0707 22:31:23.794013 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.05681 (* 1 = 2.05681 loss)
I0707 22:31:23.794025 99468 sgd_solver.cpp:105] Iteration 7240, lr = 0.001
I0707 22:32:40.089066 99468 solver.cpp:218] Iteration 7280 (0.524298 iter/s, 76.2926s/40 iters), loss = 3.66022
I0707 22:32:40.089272 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32594 (* 0.3 = 0.697783 loss)
I0707 22:32:40.089339 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30132 (* 0.3 = 0.690396 loss)
I0707 22:32:40.089357 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30794 (* 1 = 2.30794 loss)
I0707 22:32:40.089390 99468 sgd_solver.cpp:105] Iteration 7280, lr = 0.001
I0707 22:33:56.323633 99468 solver.cpp:218] Iteration 7320 (0.524715 iter/s, 76.2318s/40 iters), loss = 3.7554
I0707 22:33:56.323802 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14836 (* 0.3 = 0.644509 loss)
I0707 22:33:56.323822 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18555 (* 0.3 = 0.655666 loss)
I0707 22:33:56.323846 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16725 (* 1 = 2.16725 loss)
I0707 22:33:56.323902 99468 sgd_solver.cpp:105] Iteration 7320, lr = 0.001
I0707 22:35:12.597573 99468 solver.cpp:218] Iteration 7360 (0.524444 iter/s, 76.2712s/40 iters), loss = 3.71039
I0707 22:35:12.597728 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31273 (* 0.3 = 0.693819 loss)
I0707 22:35:12.597746 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2959 (* 0.3 = 0.688769 loss)
I0707 22:35:12.597792 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30964 (* 1 = 2.30964 loss)
I0707 22:35:12.597805 99468 sgd_solver.cpp:105] Iteration 7360, lr = 0.001
I0707 22:36:28.893573 99468 solver.cpp:218] Iteration 7400 (0.524292 iter/s, 76.2933s/40 iters), loss = 3.75677
I0707 22:36:28.893743 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43158 (* 0.3 = 0.729475 loss)
I0707 22:36:28.893762 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43173 (* 0.3 = 0.729519 loss)
I0707 22:36:28.893779 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42149 (* 1 = 2.42149 loss)
I0707 22:36:28.893790 99468 sgd_solver.cpp:105] Iteration 7400, lr = 0.001
I0707 22:37:45.185726 99468 solver.cpp:218] Iteration 7440 (0.524319 iter/s, 76.2895s/40 iters), loss = 3.74133
I0707 22:37:45.185890 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37654 (* 0.3 = 0.712962 loss)
I0707 22:37:45.185909 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37928 (* 0.3 = 0.713784 loss)
I0707 22:37:45.185923 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36298 (* 1 = 2.36298 loss)
I0707 22:37:45.185938 99468 sgd_solver.cpp:105] Iteration 7440, lr = 0.001
I0707 22:39:01.491984 99468 solver.cpp:218] Iteration 7480 (0.524222 iter/s, 76.3036s/40 iters), loss = 3.65439
I0707 22:39:01.492151 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12782 (* 0.3 = 0.638345 loss)
I0707 22:39:01.492169 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12993 (* 0.3 = 0.63898 loss)
I0707 22:39:01.492187 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12814 (* 1 = 2.12814 loss)
I0707 22:39:01.492229 99468 sgd_solver.cpp:105] Iteration 7480, lr = 0.001
I0707 22:40:17.728483 99468 solver.cpp:218] Iteration 7520 (0.524702 iter/s, 76.2338s/40 iters), loss = 3.69066
I0707 22:40:17.728652 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24541 (* 0.3 = 0.673623 loss)
I0707 22:40:17.728677 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25078 (* 0.3 = 0.675235 loss)
I0707 22:40:17.728726 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23241 (* 1 = 2.23241 loss)
I0707 22:40:17.728739 99468 sgd_solver.cpp:105] Iteration 7520, lr = 0.001
I0707 22:41:34.004130 99468 solver.cpp:218] Iteration 7560 (0.524432 iter/s, 76.273s/40 iters), loss = 3.69228
I0707 22:41:34.004289 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11314 (* 0.3 = 0.633941 loss)
I0707 22:41:34.004346 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11578 (* 0.3 = 0.634734 loss)
I0707 22:41:34.004377 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1064 (* 1 = 2.1064 loss)
I0707 22:41:34.004391 99468 sgd_solver.cpp:105] Iteration 7560, lr = 0.001
I0707 22:42:50.271394 99468 solver.cpp:218] Iteration 7600 (0.52449 iter/s, 76.2646s/40 iters), loss = 3.71144
I0707 22:42:50.271586 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.95374 (* 0.3 = 0.886122 loss)
I0707 22:42:50.271631 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.96196 (* 0.3 = 0.888589 loss)
I0707 22:42:50.271647 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.94613 (* 1 = 2.94613 loss)
I0707 22:42:50.271659 99468 sgd_solver.cpp:105] Iteration 7600, lr = 0.001
I0707 22:44:06.541479 99468 solver.cpp:218] Iteration 7640 (0.524471 iter/s, 76.2674s/40 iters), loss = 3.72427
I0707 22:44:06.541635 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60576 (* 0.3 = 0.781729 loss)
I0707 22:44:06.541656 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.60108 (* 0.3 = 0.780325 loss)
I0707 22:44:06.541672 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62984 (* 1 = 2.62984 loss)
I0707 22:44:06.541716 99468 sgd_solver.cpp:105] Iteration 7640, lr = 0.001
I0707 22:45:22.901986 99468 solver.cpp:218] Iteration 7680 (0.523849 iter/s, 76.3578s/40 iters), loss = 3.7457
I0707 22:45:22.902149 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40707 (* 0.3 = 0.722121 loss)
I0707 22:45:22.902168 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40306 (* 0.3 = 0.720919 loss)
I0707 22:45:22.902217 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41998 (* 1 = 2.41998 loss)
I0707 22:45:22.902230 99468 sgd_solver.cpp:105] Iteration 7680, lr = 0.001
I0707 22:46:39.227890 99468 solver.cpp:218] Iteration 7720 (0.524087 iter/s, 76.3232s/40 iters), loss = 3.74851
I0707 22:46:39.228041 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.96661 (* 0.3 = 0.589982 loss)
I0707 22:46:39.228060 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.97145 (* 0.3 = 0.591434 loss)
I0707 22:46:39.228104 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.93732 (* 1 = 1.93732 loss)
I0707 22:46:39.228117 99468 sgd_solver.cpp:105] Iteration 7720, lr = 0.001
I0707 22:47:55.520905 99468 solver.cpp:218] Iteration 7760 (0.524313 iter/s, 76.2903s/40 iters), loss = 3.67213
I0707 22:47:55.521059 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31812 (* 0.3 = 0.695437 loss)
I0707 22:47:55.521078 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32236 (* 0.3 = 0.696709 loss)
I0707 22:47:55.521121 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31449 (* 1 = 2.31449 loss)
I0707 22:47:55.521134 99468 sgd_solver.cpp:105] Iteration 7760, lr = 0.001
I0707 22:49:11.815490 99468 solver.cpp:218] Iteration 7800 (0.524302 iter/s, 76.2919s/40 iters), loss = 3.73182
I0707 22:49:11.815672 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59683 (* 0.3 = 0.779048 loss)
I0707 22:49:11.815696 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59812 (* 0.3 = 0.779435 loss)
I0707 22:49:11.815709 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59036 (* 1 = 2.59036 loss)
I0707 22:49:11.815726 99468 sgd_solver.cpp:105] Iteration 7800, lr = 0.001
I0707 22:50:28.101999 99468 solver.cpp:218] Iteration 7840 (0.524358 iter/s, 76.2838s/40 iters), loss = 3.69441
I0707 22:50:28.102166 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14395 (* 0.3 = 0.643185 loss)
I0707 22:50:28.102219 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11083 (* 0.3 = 0.63325 loss)
I0707 22:50:28.102236 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10742 (* 1 = 2.10742 loss)
I0707 22:50:28.102264 99468 sgd_solver.cpp:105] Iteration 7840, lr = 0.001
I0707 22:51:44.368017 99468 solver.cpp:218] Iteration 7880 (0.524498 iter/s, 76.2633s/40 iters), loss = 3.77481
I0707 22:51:44.368180 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41502 (* 0.3 = 0.724505 loss)
I0707 22:51:44.368233 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43566 (* 0.3 = 0.730698 loss)
I0707 22:51:44.368252 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41784 (* 1 = 2.41784 loss)
I0707 22:51:44.368263 99468 sgd_solver.cpp:105] Iteration 7880, lr = 0.001
I0707 22:53:00.623239 99468 solver.cpp:218] Iteration 7920 (0.524574 iter/s, 76.2523s/40 iters), loss = 3.71226
I0707 22:53:00.623407 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04371 (* 0.3 = 0.613112 loss)
I0707 22:53:00.623432 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03526 (* 0.3 = 0.610577 loss)
I0707 22:53:00.623450 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04096 (* 1 = 2.04096 loss)
I0707 22:53:00.623464 99468 sgd_solver.cpp:105] Iteration 7920, lr = 0.001
I0707 22:54:16.883863 99468 solver.cpp:218] Iteration 7960 (0.524536 iter/s, 76.2579s/40 iters), loss = 3.71169
I0707 22:54:16.884032 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55396 (* 0.3 = 0.766189 loss)
I0707 22:54:16.884052 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.54143 (* 0.3 = 0.76243 loss)
I0707 22:54:16.884068 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53425 (* 1 = 2.53425 loss)
I0707 22:54:16.884079 99468 sgd_solver.cpp:105] Iteration 7960, lr = 0.001
I0707 22:55:30.687697 99468 solver.cpp:330] Iteration 8000, Testing net (#0)
I0707 23:05:51.096004 99629 data_layer.cpp:73] Restarting data prefetching from start.
I0707 23:05:59.221549 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07533 (* 0.3 = 0.6226 loss)
I0707 23:05:59.221637 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.367134
I0707 23:05:59.221660 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794115
I0707 23:05:59.221683 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07601 (* 0.3 = 0.622802 loss)
I0707 23:05:59.221748 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.367134
I0707 23:05:59.221777 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794115
I0707 23:05:59.221794 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07558 (* 1 = 2.07558 loss)
I0707 23:05:59.221807 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.326439
I0707 23:05:59.221817 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794115
I0707 23:06:01.112056 99468 solver.cpp:218] Iteration 8000 (0.0568016 iter/s, 704.205s/40 iters), loss = 3.75038
I0707 23:06:01.112115 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55958 (* 0.3 = 0.767873 loss)
I0707 23:06:01.112135 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53582 (* 0.3 = 0.760746 loss)
I0707 23:06:01.112195 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53957 (* 1 = 2.53957 loss)
I0707 23:06:01.112210 99468 sgd_solver.cpp:105] Iteration 8000, lr = 0.001
I0707 23:07:17.488665 99468 solver.cpp:218] Iteration 8040 (0.52374 iter/s, 76.3738s/40 iters), loss = 3.69154
I0707 23:07:17.488842 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32513 (* 0.3 = 0.697539 loss)
I0707 23:07:17.488864 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31923 (* 0.3 = 0.695769 loss)
I0707 23:07:17.488878 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.304 (* 1 = 2.304 loss)
I0707 23:07:17.488894 99468 sgd_solver.cpp:105] Iteration 8040, lr = 0.001
I0707 23:08:33.776409 99468 solver.cpp:218] Iteration 8080 (0.524349 iter/s, 76.2851s/40 iters), loss = 3.70825
I0707 23:08:33.776590 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12267 (* 0.3 = 0.6368 loss)
I0707 23:08:33.776610 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11723 (* 0.3 = 0.635169 loss)
I0707 23:08:33.776628 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0996 (* 1 = 2.0996 loss)
I0707 23:08:33.776638 99468 sgd_solver.cpp:105] Iteration 8080, lr = 0.001
I0707 23:09:50.053689 99468 solver.cpp:218] Iteration 8120 (0.524421 iter/s, 76.2746s/40 iters), loss = 3.7067
I0707 23:09:50.053869 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2218 (* 0.3 = 0.66654 loss)
I0707 23:09:50.053892 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24032 (* 0.3 = 0.672096 loss)
I0707 23:09:50.053905 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2432 (* 1 = 2.2432 loss)
I0707 23:09:50.053917 99468 sgd_solver.cpp:105] Iteration 8120, lr = 0.001
I0707 23:11:06.361258 99468 solver.cpp:218] Iteration 8160 (0.524213 iter/s, 76.3049s/40 iters), loss = 3.68308
I0707 23:11:06.361441 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37604 (* 0.3 = 0.712812 loss)
I0707 23:11:06.361495 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37395 (* 0.3 = 0.712185 loss)
I0707 23:11:06.361511 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35926 (* 1 = 2.35926 loss)
I0707 23:11:06.361522 99468 sgd_solver.cpp:105] Iteration 8160, lr = 0.001
I0707 23:12:22.699211 99468 solver.cpp:218] Iteration 8200 (0.524004 iter/s, 76.3353s/40 iters), loss = 3.73912
I0707 23:12:22.699359 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40188 (* 0.3 = 0.720565 loss)
I0707 23:12:22.699376 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38865 (* 0.3 = 0.716594 loss)
I0707 23:12:22.699424 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41069 (* 1 = 2.41069 loss)
I0707 23:12:22.699440 99468 sgd_solver.cpp:105] Iteration 8200, lr = 0.001
I0707 23:13:38.979229 99468 solver.cpp:218] Iteration 8240 (0.524402 iter/s, 76.2774s/40 iters), loss = 3.67336
I0707 23:13:38.979384 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06259 (* 0.3 = 0.618777 loss)
I0707 23:13:38.979403 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.02247 (* 0.3 = 0.60674 loss)
I0707 23:13:38.979447 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0199 (* 1 = 2.0199 loss)
I0707 23:13:38.979460 99468 sgd_solver.cpp:105] Iteration 8240, lr = 0.001
I0707 23:14:55.283840 99468 solver.cpp:218] Iteration 8280 (0.524233 iter/s, 76.3019s/40 iters), loss = 3.69711
I0707 23:14:55.283980 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01911 (* 0.3 = 0.605734 loss)
I0707 23:14:55.283999 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03317 (* 0.3 = 0.609951 loss)
I0707 23:14:55.284044 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03194 (* 1 = 2.03194 loss)
I0707 23:14:55.284054 99468 sgd_solver.cpp:105] Iteration 8280, lr = 0.001
I0707 23:16:11.569005 99468 solver.cpp:218] Iteration 8320 (0.524367 iter/s, 76.2825s/40 iters), loss = 3.749
I0707 23:16:11.569155 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34025 (* 0.3 = 0.702076 loss)
I0707 23:16:11.569206 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36373 (* 0.3 = 0.70912 loss)
I0707 23:16:11.569236 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33009 (* 1 = 2.33009 loss)
I0707 23:16:11.569247 99468 sgd_solver.cpp:105] Iteration 8320, lr = 0.001
I0707 23:17:27.869655 99468 solver.cpp:218] Iteration 8360 (0.52426 iter/s, 76.298s/40 iters), loss = 3.69409
I0707 23:17:27.869830 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26376 (* 0.3 = 0.679129 loss)
I0707 23:17:27.869849 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26633 (* 0.3 = 0.6799 loss)
I0707 23:17:27.869894 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27484 (* 1 = 2.27484 loss)
I0707 23:17:27.869904 99468 sgd_solver.cpp:105] Iteration 8360, lr = 0.001
I0707 23:18:44.139984 99468 solver.cpp:218] Iteration 8400 (0.524469 iter/s, 76.2676s/40 iters), loss = 3.68187
I0707 23:18:44.140139 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41248 (* 0.3 = 0.723745 loss)
I0707 23:18:44.140159 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41741 (* 0.3 = 0.725223 loss)
I0707 23:18:44.140202 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41995 (* 1 = 2.41995 loss)
I0707 23:18:44.140213 99468 sgd_solver.cpp:105] Iteration 8400, lr = 0.001
I0707 23:20:00.446679 99468 solver.cpp:218] Iteration 8440 (0.524219 iter/s, 76.304s/40 iters), loss = 3.74358
I0707 23:20:00.446882 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.69227 (* 0.3 = 0.807682 loss)
I0707 23:20:00.446931 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.66523 (* 0.3 = 0.79957 loss)
I0707 23:20:00.446946 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.66484 (* 1 = 2.66484 loss)
I0707 23:20:00.446959 99468 sgd_solver.cpp:105] Iteration 8440, lr = 0.001
I0707 23:21:16.740507 99468 solver.cpp:218] Iteration 8480 (0.524307 iter/s, 76.2911s/40 iters), loss = 3.67164
I0707 23:21:16.740676 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17547 (* 0.3 = 0.652642 loss)
I0707 23:21:16.740730 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21247 (* 0.3 = 0.663741 loss)
I0707 23:21:16.740759 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18624 (* 1 = 2.18624 loss)
I0707 23:21:16.740773 99468 sgd_solver.cpp:105] Iteration 8480, lr = 0.001
I0707 23:22:33.032153 99468 solver.cpp:218] Iteration 8520 (0.524322 iter/s, 76.2889s/40 iters), loss = 3.71707
I0707 23:22:33.032344 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15148 (* 0.3 = 0.645445 loss)
I0707 23:22:33.032374 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15117 (* 0.3 = 0.645351 loss)
I0707 23:22:33.032424 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14681 (* 1 = 2.14681 loss)
I0707 23:22:33.032439 99468 sgd_solver.cpp:105] Iteration 8520, lr = 0.001
I0707 23:23:49.292143 99468 solver.cpp:218] Iteration 8560 (0.52454 iter/s, 76.2573s/40 iters), loss = 3.68989
I0707 23:23:49.292357 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34404 (* 0.3 = 0.703213 loss)
I0707 23:23:49.292423 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31346 (* 0.3 = 0.694039 loss)
I0707 23:23:49.292439 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31734 (* 1 = 2.31734 loss)
I0707 23:23:49.292454 99468 sgd_solver.cpp:105] Iteration 8560, lr = 0.001
I0707 23:25:05.548403 99468 solver.cpp:218] Iteration 8600 (0.524566 iter/s, 76.2535s/40 iters), loss = 3.73864
I0707 23:25:05.548549 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43659 (* 0.3 = 0.730978 loss)
I0707 23:25:05.548575 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4418 (* 0.3 = 0.732539 loss)
I0707 23:25:05.548589 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42994 (* 1 = 2.42994 loss)
I0707 23:25:05.548600 99468 sgd_solver.cpp:105] Iteration 8600, lr = 0.001
I0707 23:26:21.806989 99468 solver.cpp:218] Iteration 8640 (0.524549 iter/s, 76.2559s/40 iters), loss = 3.67669
I0707 23:26:21.807150 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31865 (* 0.3 = 0.695596 loss)
I0707 23:26:21.807171 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30962 (* 0.3 = 0.692885 loss)
I0707 23:26:21.807215 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2987 (* 1 = 2.2987 loss)
I0707 23:26:21.807226 99468 sgd_solver.cpp:105] Iteration 8640, lr = 0.001
I0707 23:27:38.002341 99468 solver.cpp:218] Iteration 8680 (0.524985 iter/s, 76.1927s/40 iters), loss = 3.70296
I0707 23:27:38.002502 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48495 (* 0.3 = 0.745484 loss)
I0707 23:27:38.002522 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.52391 (* 0.3 = 0.757173 loss)
I0707 23:27:38.002538 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49866 (* 1 = 2.49866 loss)
I0707 23:27:38.002548 99468 sgd_solver.cpp:105] Iteration 8680, lr = 0.001
I0707 23:28:54.310650 99468 solver.cpp:218] Iteration 8720 (0.524208 iter/s, 76.3056s/40 iters), loss = 3.68932
I0707 23:28:54.310797 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17843 (* 0.3 = 0.653528 loss)
I0707 23:28:54.310817 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18726 (* 0.3 = 0.656178 loss)
I0707 23:28:54.310864 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18587 (* 1 = 2.18587 loss)
I0707 23:28:54.310875 99468 sgd_solver.cpp:105] Iteration 8720, lr = 0.001
I0707 23:30:10.574966 99468 solver.cpp:218] Iteration 8760 (0.52451 iter/s, 76.2617s/40 iters), loss = 3.62761
I0707 23:30:10.575166 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22231 (* 0.3 = 0.666694 loss)
I0707 23:30:10.575186 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23154 (* 0.3 = 0.669463 loss)
I0707 23:30:10.575232 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21699 (* 1 = 2.21699 loss)
I0707 23:30:10.575242 99468 sgd_solver.cpp:105] Iteration 8760, lr = 0.001
I0707 23:31:26.871951 99468 solver.cpp:218] Iteration 8800 (0.524286 iter/s, 76.2943s/40 iters), loss = 3.71985
I0707 23:31:26.872123 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47645 (* 0.3 = 0.742936 loss)
I0707 23:31:26.872176 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50138 (* 0.3 = 0.750415 loss)
I0707 23:31:26.872193 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46784 (* 1 = 2.46784 loss)
I0707 23:31:26.872222 99468 sgd_solver.cpp:105] Iteration 8800, lr = 0.001
I0707 23:32:43.157776 99468 solver.cpp:218] Iteration 8840 (0.524362 iter/s, 76.2831s/40 iters), loss = 3.69143
I0707 23:32:43.157937 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31838 (* 0.3 = 0.695515 loss)
I0707 23:32:43.157959 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29787 (* 0.3 = 0.68936 loss)
I0707 23:32:43.157976 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29769 (* 1 = 2.29769 loss)
I0707 23:32:43.157986 99468 sgd_solver.cpp:105] Iteration 8840, lr = 0.001
I0707 23:33:59.466106 99468 solver.cpp:218] Iteration 8880 (0.524208 iter/s, 76.3056s/40 iters), loss = 3.71979
I0707 23:33:59.466274 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44295 (* 0.3 = 0.732884 loss)
I0707 23:33:59.466295 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41451 (* 0.3 = 0.724353 loss)
I0707 23:33:59.466307 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4196 (* 1 = 2.4196 loss)
I0707 23:33:59.466322 99468 sgd_solver.cpp:105] Iteration 8880, lr = 0.001
I0707 23:35:15.776967 99468 solver.cpp:218] Iteration 8920 (0.52419 iter/s, 76.3082s/40 iters), loss = 3.67443
I0707 23:35:15.777143 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07668 (* 0.3 = 0.623005 loss)
I0707 23:35:15.777204 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.05076 (* 0.3 = 0.615227 loss)
I0707 23:35:15.777221 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.06165 (* 1 = 2.06165 loss)
I0707 23:35:15.777236 99468 sgd_solver.cpp:105] Iteration 8920, lr = 0.001
I0707 23:36:32.071172 99468 solver.cpp:218] Iteration 8960 (0.524305 iter/s, 76.2915s/40 iters), loss = 3.73318
I0707 23:36:32.071336 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15924 (* 0.3 = 0.647772 loss)
I0707 23:36:32.071354 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14739 (* 0.3 = 0.644216 loss)
I0707 23:36:32.071372 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14827 (* 1 = 2.14827 loss)
I0707 23:36:32.071382 99468 sgd_solver.cpp:105] Iteration 8960, lr = 0.001
I0707 23:37:48.321836 99468 solver.cpp:218] Iteration 9000 (0.524604 iter/s, 76.248s/40 iters), loss = 3.7122
I0707 23:37:48.322021 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30952 (* 0.3 = 0.692857 loss)
I0707 23:37:48.322073 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29544 (* 0.3 = 0.688633 loss)
I0707 23:37:48.322090 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30511 (* 1 = 2.30511 loss)
I0707 23:37:48.322116 99468 sgd_solver.cpp:105] Iteration 9000, lr = 0.001
I0707 23:39:04.589318 99468 solver.cpp:218] Iteration 9040 (0.524489 iter/s, 76.2648s/40 iters), loss = 3.724
I0707 23:39:04.589471 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52521 (* 0.3 = 0.757562 loss)
I0707 23:39:04.589524 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51755 (* 0.3 = 0.755266 loss)
I0707 23:39:04.589558 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51056 (* 1 = 2.51056 loss)
I0707 23:39:04.589570 99468 sgd_solver.cpp:105] Iteration 9040, lr = 0.001
I0707 23:40:20.834347 99468 solver.cpp:218] Iteration 9080 (0.524643 iter/s, 76.2424s/40 iters), loss = 3.72281
I0707 23:40:20.834559 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39105 (* 0.3 = 0.717316 loss)
I0707 23:40:20.834580 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36411 (* 0.3 = 0.709233 loss)
I0707 23:40:20.834594 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39833 (* 1 = 2.39833 loss)
I0707 23:40:20.834609 99468 sgd_solver.cpp:105] Iteration 9080, lr = 0.001
I0707 23:41:37.116731 99468 solver.cpp:218] Iteration 9120 (0.524386 iter/s, 76.2796s/40 iters), loss = 3.71771
I0707 23:41:37.116994 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21647 (* 0.3 = 0.664941 loss)
I0707 23:41:37.117055 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21597 (* 0.3 = 0.66479 loss)
I0707 23:41:37.117069 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20298 (* 1 = 2.20298 loss)
I0707 23:41:37.117085 99468 sgd_solver.cpp:105] Iteration 9120, lr = 0.001
I0707 23:41:50.602615 99628 data_layer.cpp:73] Restarting data prefetching from start.
I0707 23:42:53.658073 99468 solver.cpp:218] Iteration 9160 (0.522612 iter/s, 76.5386s/40 iters), loss = 3.73431
I0707 23:42:53.658303 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48087 (* 0.3 = 0.744262 loss)
I0707 23:42:53.658330 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4561 (* 0.3 = 0.736829 loss)
I0707 23:42:53.658347 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45157 (* 1 = 2.45157 loss)
I0707 23:42:53.658363 99468 sgd_solver.cpp:105] Iteration 9160, lr = 0.001
I0707 23:44:10.192821 99468 solver.cpp:218] Iteration 9200 (0.522657 iter/s, 76.532s/40 iters), loss = 3.68596
I0707 23:44:10.193043 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47809 (* 0.3 = 0.743428 loss)
I0707 23:44:10.193106 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44022 (* 0.3 = 0.732066 loss)
I0707 23:44:10.193123 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45864 (* 1 = 2.45864 loss)
I0707 23:44:10.193141 99468 sgd_solver.cpp:105] Iteration 9200, lr = 0.001
I0707 23:45:26.735016 99468 solver.cpp:218] Iteration 9240 (0.522606 iter/s, 76.5394s/40 iters), loss = 3.69822
I0707 23:45:26.735242 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14752 (* 0.3 = 0.644257 loss)
I0707 23:45:26.735301 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12631 (* 0.3 = 0.637892 loss)
I0707 23:45:26.735313 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10593 (* 1 = 2.10593 loss)
I0707 23:45:26.735348 99468 sgd_solver.cpp:105] Iteration 9240, lr = 0.001
I0707 23:46:43.285466 99468 solver.cpp:218] Iteration 9280 (0.52255 iter/s, 76.5477s/40 iters), loss = 3.71858
I0707 23:46:43.285696 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43364 (* 0.3 = 0.730092 loss)
I0707 23:46:43.285718 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41738 (* 0.3 = 0.725214 loss)
I0707 23:46:43.285732 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41033 (* 1 = 2.41033 loss)
I0707 23:46:43.285748 99468 sgd_solver.cpp:105] Iteration 9280, lr = 0.001
I0707 23:47:59.733711 99468 solver.cpp:218] Iteration 9320 (0.523249 iter/s, 76.4455s/40 iters), loss = 3.69807
I0707 23:47:59.733933 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.83945 (* 0.3 = 0.851836 loss)
I0707 23:47:59.733955 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.83463 (* 0.3 = 0.850389 loss)
I0707 23:47:59.733969 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.8528 (* 1 = 2.8528 loss)
I0707 23:47:59.733985 99468 sgd_solver.cpp:105] Iteration 9320, lr = 0.001
I0707 23:49:16.253509 99468 solver.cpp:218] Iteration 9360 (0.522759 iter/s, 76.517s/40 iters), loss = 3.72355
I0707 23:49:16.253809 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44454 (* 0.3 = 0.733363 loss)
I0707 23:49:16.253834 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47117 (* 0.3 = 0.741352 loss)
I0707 23:49:16.253849 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45417 (* 1 = 2.45417 loss)
I0707 23:49:16.253865 99468 sgd_solver.cpp:105] Iteration 9360, lr = 0.001
I0707 23:50:32.761543 99468 solver.cpp:218] Iteration 9400 (0.52284 iter/s, 76.5052s/40 iters), loss = 3.72567
I0707 23:50:32.761780 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16444 (* 0.3 = 0.649333 loss)
I0707 23:50:32.761801 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16752 (* 0.3 = 0.650257 loss)
I0707 23:50:32.761814 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16213 (* 1 = 2.16213 loss)
I0707 23:50:32.761864 99468 sgd_solver.cpp:105] Iteration 9400, lr = 0.001
I0707 23:51:49.263950 99468 solver.cpp:218] Iteration 9440 (0.522878 iter/s, 76.4996s/40 iters), loss = 3.68691
I0707 23:51:49.264204 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9836 (* 0.3 = 0.595081 loss)
I0707 23:51:49.264266 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.99445 (* 0.3 = 0.598335 loss)
I0707 23:51:49.264302 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.97939 (* 1 = 1.97939 loss)
I0707 23:51:49.264322 99468 sgd_solver.cpp:105] Iteration 9440, lr = 0.001
I0707 23:53:05.737920 99468 solver.cpp:218] Iteration 9480 (0.523073 iter/s, 76.4712s/40 iters), loss = 3.71788
I0707 23:53:05.738145 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17532 (* 0.3 = 0.652596 loss)
I0707 23:53:05.738212 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19756 (* 0.3 = 0.659267 loss)
I0707 23:53:05.738226 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17939 (* 1 = 2.17939 loss)
I0707 23:53:05.738261 99468 sgd_solver.cpp:105] Iteration 9480, lr = 0.001
I0707 23:54:22.232594 99468 solver.cpp:218] Iteration 9520 (0.522931 iter/s, 76.4919s/40 iters), loss = 3.68071
I0707 23:54:22.232856 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.49725 (* 0.3 = 0.749175 loss)
I0707 23:54:22.232918 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50864 (* 0.3 = 0.752592 loss)
I0707 23:54:22.232931 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5178 (* 1 = 2.5178 loss)
I0707 23:54:22.232951 99468 sgd_solver.cpp:105] Iteration 9520, lr = 0.001
I0707 23:55:38.691537 99468 solver.cpp:218] Iteration 9560 (0.523176 iter/s, 76.4562s/40 iters), loss = 3.71922
I0707 23:55:38.691767 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.75904 (* 0.3 = 0.827713 loss)
I0707 23:55:38.691833 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.75943 (* 0.3 = 0.827828 loss)
I0707 23:55:38.691850 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.7892 (* 1 = 2.7892 loss)
I0707 23:55:38.691864 99468 sgd_solver.cpp:105] Iteration 9560, lr = 0.001
I0707 23:56:55.220549 99468 solver.cpp:218] Iteration 9600 (0.522696 iter/s, 76.5262s/40 iters), loss = 3.732
I0707 23:56:55.220784 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32397 (* 0.3 = 0.69719 loss)
I0707 23:56:55.220840 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.295 (* 0.3 = 0.6885 loss)
I0707 23:56:55.220870 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29675 (* 1 = 2.29675 loss)
I0707 23:56:55.220886 99468 sgd_solver.cpp:105] Iteration 9600, lr = 0.001
I0707 23:58:11.722831 99468 solver.cpp:218] Iteration 9640 (0.522879 iter/s, 76.4995s/40 iters), loss = 3.72226
I0707 23:58:11.723067 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15019 (* 0.3 = 0.645057 loss)
I0707 23:58:11.723089 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16864 (* 0.3 = 0.650592 loss)
I0707 23:58:11.723104 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15981 (* 1 = 2.15981 loss)
I0707 23:58:11.723121 99468 sgd_solver.cpp:105] Iteration 9640, lr = 0.001
I0707 23:59:28.230355 99468 solver.cpp:218] Iteration 9680 (0.522843 iter/s, 76.5048s/40 iters), loss = 3.70482
I0707 23:59:28.230664 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27653 (* 0.3 = 0.682959 loss)
I0707 23:59:28.230721 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29303 (* 0.3 = 0.68791 loss)
I0707 23:59:28.230736 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27498 (* 1 = 2.27498 loss)
I0707 23:59:28.230752 99468 sgd_solver.cpp:105] Iteration 9680, lr = 0.001
I0708 00:00:44.681900 99468 solver.cpp:218] Iteration 9720 (0.523227 iter/s, 76.4487s/40 iters), loss = 3.73645
I0708 00:00:44.682147 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43933 (* 0.3 = 0.731798 loss)
I0708 00:00:44.682224 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4473 (* 0.3 = 0.73419 loss)
I0708 00:00:44.682238 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43021 (* 1 = 2.43021 loss)
I0708 00:00:44.682256 99468 sgd_solver.cpp:105] Iteration 9720, lr = 0.001
I0708 00:02:01.191761 99468 solver.cpp:218] Iteration 9760 (0.522828 iter/s, 76.5071s/40 iters), loss = 3.6985
I0708 00:02:01.192005 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11884 (* 0.3 = 0.635653 loss)
I0708 00:02:01.192030 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12055 (* 0.3 = 0.636166 loss)
I0708 00:02:01.192042 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09775 (* 1 = 2.09775 loss)
I0708 00:02:01.192100 99468 sgd_solver.cpp:105] Iteration 9760, lr = 0.001
I0708 00:03:17.731032 99468 solver.cpp:218] Iteration 9800 (0.522626 iter/s, 76.5365s/40 iters), loss = 3.71513
I0708 00:03:17.731269 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46399 (* 0.3 = 0.739197 loss)
I0708 00:03:17.731330 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46664 (* 0.3 = 0.739992 loss)
I0708 00:03:17.731345 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47686 (* 1 = 2.47686 loss)
I0708 00:03:17.731362 99468 sgd_solver.cpp:105] Iteration 9800, lr = 0.001
I0708 00:04:34.295692 99468 solver.cpp:218] Iteration 9840 (0.522453 iter/s, 76.5619s/40 iters), loss = 3.72861
I0708 00:04:34.295928 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38519 (* 0.3 = 0.715558 loss)
I0708 00:04:34.295951 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40642 (* 0.3 = 0.721927 loss)
I0708 00:04:34.295965 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38992 (* 1 = 2.38992 loss)
I0708 00:04:34.296018 99468 sgd_solver.cpp:105] Iteration 9840, lr = 0.001
I0708 00:05:50.835566 99468 solver.cpp:218] Iteration 9880 (0.522622 iter/s, 76.5371s/40 iters), loss = 3.73701
I0708 00:05:50.835793 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30249 (* 0.3 = 0.690748 loss)
I0708 00:05:50.835819 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27839 (* 0.3 = 0.683516 loss)
I0708 00:05:50.835834 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28591 (* 1 = 2.28591 loss)
I0708 00:05:50.835852 99468 sgd_solver.cpp:105] Iteration 9880, lr = 0.001
I0708 00:07:07.194942 99468 solver.cpp:218] Iteration 9920 (0.523858 iter/s, 76.3566s/40 iters), loss = 3.73516
I0708 00:07:07.195163 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52235 (* 0.3 = 0.756705 loss)
I0708 00:07:07.195185 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55331 (* 0.3 = 0.765994 loss)
I0708 00:07:07.195200 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53181 (* 1 = 2.53181 loss)
I0708 00:07:07.195257 99468 sgd_solver.cpp:105] Iteration 9920, lr = 0.001
I0708 00:08:23.487777 99468 solver.cpp:218] Iteration 9960 (0.524315 iter/s, 76.2901s/40 iters), loss = 3.70074
I0708 00:08:23.488029 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47171 (* 0.3 = 0.741513 loss)
I0708 00:08:23.488095 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46094 (* 0.3 = 0.738282 loss)
I0708 00:08:23.488131 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44037 (* 1 = 2.44037 loss)
I0708 00:08:23.488155 99468 sgd_solver.cpp:105] Iteration 9960, lr = 0.001
I0708 00:09:39.781047 99468 solver.cpp:218] Iteration 10000 (0.524312 iter/s, 76.2905s/40 iters), loss = 3.74342
I0708 00:09:39.781316 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42127 (* 0.3 = 0.72638 loss)
I0708 00:09:39.781339 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43601 (* 0.3 = 0.730802 loss)
I0708 00:09:39.781389 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42766 (* 1 = 2.42766 loss)
I0708 00:09:39.781406 99468 sgd_solver.cpp:105] Iteration 10000, lr = 0.001
I0708 00:10:56.037685 99468 solver.cpp:218] Iteration 10040 (0.524564 iter/s, 76.2538s/40 iters), loss = 3.73129
I0708 00:10:56.037931 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36747 (* 0.3 = 0.71024 loss)
I0708 00:10:56.037956 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36041 (* 0.3 = 0.708124 loss)
I0708 00:10:56.038002 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37109 (* 1 = 2.37109 loss)
I0708 00:10:56.038020 99468 sgd_solver.cpp:105] Iteration 10040, lr = 0.001
I0708 00:12:12.567538 99468 solver.cpp:218] Iteration 10080 (0.522691 iter/s, 76.5271s/40 iters), loss = 3.7024
I0708 00:12:12.567769 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42717 (* 0.3 = 0.728152 loss)
I0708 00:12:12.567791 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43296 (* 0.3 = 0.729887 loss)
I0708 00:12:12.567806 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4386 (* 1 = 2.4386 loss)
I0708 00:12:12.567821 99468 sgd_solver.cpp:105] Iteration 10080, lr = 0.001
I0708 00:13:28.921962 99468 solver.cpp:218] Iteration 10120 (0.523892 iter/s, 76.3517s/40 iters), loss = 3.669
I0708 00:13:28.922193 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24524 (* 0.3 = 0.673571 loss)
I0708 00:13:28.922219 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23353 (* 0.3 = 0.67006 loss)
I0708 00:13:28.922267 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23055 (* 1 = 2.23055 loss)
I0708 00:13:28.922286 99468 sgd_solver.cpp:105] Iteration 10120, lr = 0.001
I0708 00:14:45.289580 99468 solver.cpp:218] Iteration 10160 (0.523801 iter/s, 76.3649s/40 iters), loss = 3.68849
I0708 00:14:45.289816 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39598 (* 0.3 = 0.718793 loss)
I0708 00:14:45.289882 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36825 (* 0.3 = 0.710474 loss)
I0708 00:14:45.289897 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38234 (* 1 = 2.38234 loss)
I0708 00:14:45.289913 99468 sgd_solver.cpp:105] Iteration 10160, lr = 0.001
I0708 00:16:01.701859 99468 solver.cpp:218] Iteration 10200 (0.523495 iter/s, 76.4095s/40 iters), loss = 3.71809
I0708 00:16:01.702085 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3052 (* 0.3 = 0.691559 loss)
I0708 00:16:01.702136 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31632 (* 0.3 = 0.694896 loss)
I0708 00:16:01.702154 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28883 (* 1 = 2.28883 loss)
I0708 00:16:01.702185 99468 sgd_solver.cpp:105] Iteration 10200, lr = 0.001
I0708 00:17:18.027843 99468 solver.cpp:218] Iteration 10240 (0.524087 iter/s, 76.3232s/40 iters), loss = 3.64667
I0708 00:17:18.028071 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20386 (* 0.3 = 0.661158 loss)
I0708 00:17:18.028091 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21395 (* 0.3 = 0.664184 loss)
I0708 00:17:18.028103 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20092 (* 1 = 2.20092 loss)
I0708 00:17:18.028126 99468 sgd_solver.cpp:105] Iteration 10240, lr = 0.001
I0708 00:18:34.558729 99468 solver.cpp:218] Iteration 10280 (0.522684 iter/s, 76.5281s/40 iters), loss = 3.6592
I0708 00:18:34.558951 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37633 (* 0.3 = 0.7129 loss)
I0708 00:18:34.558974 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37251 (* 0.3 = 0.711753 loss)
I0708 00:18:34.558989 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35991 (* 1 = 2.35991 loss)
I0708 00:18:34.559005 99468 sgd_solver.cpp:105] Iteration 10280, lr = 0.001
I0708 00:19:50.934607 99468 solver.cpp:218] Iteration 10320 (0.523744 iter/s, 76.3731s/40 iters), loss = 3.75651
I0708 00:19:50.934869 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55933 (* 0.3 = 0.767799 loss)
I0708 00:19:50.934895 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5594 (* 0.3 = 0.767819 loss)
I0708 00:19:50.934945 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55978 (* 1 = 2.55978 loss)
I0708 00:19:50.934964 99468 sgd_solver.cpp:105] Iteration 10320, lr = 0.001
I0708 00:21:07.234297 99468 solver.cpp:218] Iteration 10360 (0.524268 iter/s, 76.2969s/40 iters), loss = 3.69661
I0708 00:21:07.234534 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3157 (* 0.3 = 0.694709 loss)
I0708 00:21:07.234596 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30004 (* 0.3 = 0.690012 loss)
I0708 00:21:07.234611 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31337 (* 1 = 2.31337 loss)
I0708 00:21:07.234624 99468 sgd_solver.cpp:105] Iteration 10360, lr = 0.001
I0708 00:22:23.728233 99468 solver.cpp:218] Iteration 10400 (0.522936 iter/s, 76.4912s/40 iters), loss = 3.61643
I0708 00:22:23.728458 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2818 (* 0.3 = 0.684539 loss)
I0708 00:22:23.728482 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27838 (* 0.3 = 0.683514 loss)
I0708 00:22:23.728534 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28294 (* 1 = 2.28294 loss)
I0708 00:22:23.728559 99468 sgd_solver.cpp:105] Iteration 10400, lr = 0.001
I0708 00:23:40.059937 99468 solver.cpp:218] Iteration 10440 (0.524047 iter/s, 76.329s/40 iters), loss = 3.6918
I0708 00:23:40.060161 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3939 (* 0.3 = 0.71817 loss)
I0708 00:23:40.060184 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39362 (* 0.3 = 0.718087 loss)
I0708 00:23:40.060199 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39385 (* 1 = 2.39385 loss)
I0708 00:23:40.060214 99468 sgd_solver.cpp:105] Iteration 10440, lr = 0.001
I0708 00:24:56.482625 99468 solver.cpp:218] Iteration 10480 (0.523424 iter/s, 76.4199s/40 iters), loss = 3.73175
I0708 00:24:56.482852 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24126 (* 0.3 = 0.672378 loss)
I0708 00:24:56.482918 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24822 (* 0.3 = 0.674466 loss)
I0708 00:24:56.482933 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24088 (* 1 = 2.24088 loss)
I0708 00:24:56.482969 99468 sgd_solver.cpp:105] Iteration 10480, lr = 0.001
I0708 00:26:12.804608 99468 solver.cpp:218] Iteration 10520 (0.524114 iter/s, 76.3192s/40 iters), loss = 3.72549
I0708 00:26:12.804823 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23421 (* 0.3 = 0.670262 loss)
I0708 00:26:12.804891 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24159 (* 0.3 = 0.672477 loss)
I0708 00:26:12.804905 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22597 (* 1 = 2.22597 loss)
I0708 00:26:12.804924 99468 sgd_solver.cpp:105] Iteration 10520, lr = 0.001
I0708 00:27:29.259177 99468 solver.cpp:218] Iteration 10560 (0.523205 iter/s, 76.4518s/40 iters), loss = 3.72934
I0708 00:27:29.259429 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.97168 (* 0.3 = 0.891505 loss)
I0708 00:27:29.259455 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.97443 (* 0.3 = 0.892329 loss)
I0708 00:27:29.259472 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.98574 (* 1 = 2.98574 loss)
I0708 00:27:29.259534 99468 sgd_solver.cpp:105] Iteration 10560, lr = 0.001
I0708 00:28:45.593883 99468 solver.cpp:218] Iteration 10600 (0.524027 iter/s, 76.3319s/40 iters), loss = 3.71414
I0708 00:28:45.594167 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3276 (* 0.3 = 0.698281 loss)
I0708 00:28:45.594225 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34743 (* 0.3 = 0.70423 loss)
I0708 00:28:45.594259 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32368 (* 1 = 2.32368 loss)
I0708 00:28:45.594274 99468 sgd_solver.cpp:105] Iteration 10600, lr = 0.001
I0708 00:30:01.994036 99468 solver.cpp:218] Iteration 10640 (0.523578 iter/s, 76.3973s/40 iters), loss = 3.75438
I0708 00:30:01.994272 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31118 (* 0.3 = 0.693356 loss)
I0708 00:30:01.994293 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2883 (* 0.3 = 0.68649 loss)
I0708 00:30:01.994307 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2955 (* 1 = 2.2955 loss)
I0708 00:30:01.994323 99468 sgd_solver.cpp:105] Iteration 10640, lr = 0.001
I0708 00:31:18.423758 99468 solver.cpp:218] Iteration 10680 (0.523376 iter/s, 76.427s/40 iters), loss = 3.71654
I0708 00:31:18.424026 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48412 (* 0.3 = 0.745235 loss)
I0708 00:31:18.424060 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50621 (* 0.3 = 0.751862 loss)
I0708 00:31:18.424079 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49001 (* 1 = 2.49001 loss)
I0708 00:31:18.424096 99468 sgd_solver.cpp:105] Iteration 10680, lr = 0.001
I0708 00:32:34.906816 99468 solver.cpp:218] Iteration 10720 (0.523011 iter/s, 76.4803s/40 iters), loss = 3.74159
I0708 00:32:34.907032 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24608 (* 0.3 = 0.673824 loss)
I0708 00:32:34.907091 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19073 (* 0.3 = 0.65722 loss)
I0708 00:32:34.907107 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22523 (* 1 = 2.22523 loss)
I0708 00:32:34.907121 99468 sgd_solver.cpp:105] Iteration 10720, lr = 0.001
I0708 00:33:51.199543 99468 solver.cpp:218] Iteration 10760 (0.524315 iter/s, 76.29s/40 iters), loss = 3.67441
I0708 00:33:51.199764 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19633 (* 0.3 = 0.658899 loss)
I0708 00:33:51.199786 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18538 (* 0.3 = 0.655614 loss)
I0708 00:33:51.199800 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20106 (* 1 = 2.20106 loss)
I0708 00:33:51.199820 99468 sgd_solver.cpp:105] Iteration 10760, lr = 0.001
I0708 00:35:07.424093 99468 solver.cpp:218] Iteration 10800 (0.524784 iter/s, 76.2218s/40 iters), loss = 3.71706
I0708 00:35:07.424309 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23793 (* 0.3 = 0.67138 loss)
I0708 00:35:07.424363 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25449 (* 0.3 = 0.676347 loss)
I0708 00:35:07.424381 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23236 (* 1 = 2.23236 loss)
I0708 00:35:07.424396 99468 sgd_solver.cpp:105] Iteration 10800, lr = 0.001
I0708 00:36:23.802474 99468 solver.cpp:218] Iteration 10840 (0.523727 iter/s, 76.3756s/40 iters), loss = 3.70165
I0708 00:36:23.802706 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44086 (* 0.3 = 0.732258 loss)
I0708 00:36:23.802734 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42156 (* 0.3 = 0.726468 loss)
I0708 00:36:23.802781 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41316 (* 1 = 2.41316 loss)
I0708 00:36:23.802798 99468 sgd_solver.cpp:105] Iteration 10840, lr = 0.001
I0708 00:37:40.300777 99468 solver.cpp:218] Iteration 10880 (0.522906 iter/s, 76.4955s/40 iters), loss = 3.69255
I0708 00:37:40.301007 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08384 (* 0.3 = 0.625153 loss)
I0708 00:37:40.301029 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11048 (* 0.3 = 0.633144 loss)
I0708 00:37:40.301044 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10284 (* 1 = 2.10284 loss)
I0708 00:37:40.301061 99468 sgd_solver.cpp:105] Iteration 10880, lr = 0.001
I0708 00:38:56.777115 99468 solver.cpp:218] Iteration 10920 (0.523057 iter/s, 76.4736s/40 iters), loss = 3.72181
I0708 00:38:56.777403 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50045 (* 0.3 = 0.750135 loss)
I0708 00:38:56.777429 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50327 (* 0.3 = 0.75098 loss)
I0708 00:38:56.777477 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50803 (* 1 = 2.50803 loss)
I0708 00:38:56.777493 99468 sgd_solver.cpp:105] Iteration 10920, lr = 0.001
I0708 00:40:13.180722 99468 solver.cpp:218] Iteration 10960 (0.523555 iter/s, 76.4008s/40 iters), loss = 3.72688
I0708 00:40:13.180953 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26866 (* 0.3 = 0.680599 loss)
I0708 00:40:13.181016 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2487 (* 0.3 = 0.67461 loss)
I0708 00:40:13.181030 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24777 (* 1 = 2.24777 loss)
I0708 00:40:13.181049 99468 sgd_solver.cpp:105] Iteration 10960, lr = 0.001
I0708 00:41:29.633574 99468 solver.cpp:218] Iteration 11000 (0.523291 iter/s, 76.4392s/40 iters), loss = 3.7308
I0708 00:41:29.634066 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1007 (* 0.3 = 0.630211 loss)
I0708 00:41:29.634133 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0864 (* 0.3 = 0.625919 loss)
I0708 00:41:29.634177 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07863 (* 1 = 2.07863 loss)
I0708 00:41:29.634269 99468 sgd_solver.cpp:105] Iteration 11000, lr = 0.001
I0708 00:42:46.038509 99468 solver.cpp:218] Iteration 11040 (0.523547 iter/s, 76.402s/40 iters), loss = 3.64313
I0708 00:42:46.038733 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.79867 (* 0.3 = 0.839602 loss)
I0708 00:42:46.038782 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.79101 (* 0.3 = 0.837302 loss)
I0708 00:42:46.038811 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.79055 (* 1 = 2.79055 loss)
I0708 00:42:46.038826 99468 sgd_solver.cpp:105] Iteration 11040, lr = 0.001
I0708 00:44:02.523785 99468 solver.cpp:218] Iteration 11080 (0.522995 iter/s, 76.4825s/40 iters), loss = 3.69601
I0708 00:44:02.524003 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23762 (* 0.3 = 0.671286 loss)
I0708 00:44:02.524025 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24281 (* 0.3 = 0.672844 loss)
I0708 00:44:02.524039 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23684 (* 1 = 2.23684 loss)
I0708 00:44:02.524055 99468 sgd_solver.cpp:105] Iteration 11080, lr = 0.001
I0708 00:45:18.992341 99468 solver.cpp:218] Iteration 11120 (0.52311 iter/s, 76.4658s/40 iters), loss = 3.7952
I0708 00:45:18.992576 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43733 (* 0.3 = 0.731198 loss)
I0708 00:45:18.992633 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42958 (* 0.3 = 0.728875 loss)
I0708 00:45:18.992647 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4193 (* 1 = 2.4193 loss)
I0708 00:45:18.992681 99468 sgd_solver.cpp:105] Iteration 11120, lr = 0.001
I0708 00:46:35.405908 99468 solver.cpp:218] Iteration 11160 (0.523486 iter/s, 76.4108s/40 iters), loss = 3.72677
I0708 00:46:35.406131 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40684 (* 0.3 = 0.722052 loss)
I0708 00:46:35.406186 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38646 (* 0.3 = 0.715937 loss)
I0708 00:46:35.406200 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38491 (* 1 = 2.38491 loss)
I0708 00:46:35.406219 99468 sgd_solver.cpp:105] Iteration 11160, lr = 0.001
I0708 00:47:51.859932 99468 solver.cpp:218] Iteration 11200 (0.523209 iter/s, 76.4513s/40 iters), loss = 3.67168
I0708 00:47:51.860183 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.69617 (* 0.3 = 0.80885 loss)
I0708 00:47:51.860203 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.66338 (* 0.3 = 0.799013 loss)
I0708 00:47:51.860216 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.69179 (* 1 = 2.69179 loss)
I0708 00:47:51.860265 99468 sgd_solver.cpp:105] Iteration 11200, lr = 0.001
I0708 00:49:08.412871 99468 solver.cpp:218] Iteration 11240 (0.522533 iter/s, 76.5501s/40 iters), loss = 3.72131
I0708 00:49:08.413175 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3211 (* 0.3 = 0.69633 loss)
I0708 00:49:08.413229 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30084 (* 0.3 = 0.690252 loss)
I0708 00:49:08.413244 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30223 (* 1 = 2.30223 loss)
I0708 00:49:08.413262 99468 sgd_solver.cpp:105] Iteration 11240, lr = 0.001
I0708 00:50:24.858791 99468 solver.cpp:218] Iteration 11280 (0.523265 iter/s, 76.4431s/40 iters), loss = 3.74847
I0708 00:50:24.859015 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.67161 (* 0.3 = 0.501484 loss)
I0708 00:50:24.859035 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.70002 (* 0.3 = 0.510007 loss)
I0708 00:50:24.859048 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.68654 (* 1 = 1.68654 loss)
I0708 00:50:24.859097 99468 sgd_solver.cpp:105] Iteration 11280, lr = 0.001
I0708 00:51:41.273372 99468 solver.cpp:218] Iteration 11320 (0.523479 iter/s, 76.4118s/40 iters), loss = 3.6902
I0708 00:51:41.273615 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.61066 (* 0.3 = 0.783198 loss)
I0708 00:51:41.273672 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62222 (* 0.3 = 0.786666 loss)
I0708 00:51:41.273707 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.61357 (* 1 = 2.61357 loss)
I0708 00:51:41.273723 99468 sgd_solver.cpp:105] Iteration 11320, lr = 0.001
I0708 00:52:57.792127 99468 solver.cpp:218] Iteration 11360 (0.522767 iter/s, 76.516s/40 iters), loss = 3.6776
I0708 00:52:57.792361 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08119 (* 0.3 = 0.624358 loss)
I0708 00:52:57.792384 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08684 (* 0.3 = 0.626053 loss)
I0708 00:52:57.792397 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08618 (* 1 = 2.08618 loss)
I0708 00:52:57.792418 99468 sgd_solver.cpp:105] Iteration 11360, lr = 0.001
I0708 00:54:14.352958 99468 solver.cpp:218] Iteration 11400 (0.522479 iter/s, 76.5581s/40 iters), loss = 3.68096
I0708 00:54:14.353185 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39246 (* 0.3 = 0.717738 loss)
I0708 00:54:14.353206 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39876 (* 0.3 = 0.719627 loss)
I0708 00:54:14.353219 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39406 (* 1 = 2.39406 loss)
I0708 00:54:14.353238 99468 sgd_solver.cpp:105] Iteration 11400, lr = 0.001
I0708 00:55:30.937723 99468 solver.cpp:218] Iteration 11440 (0.522316 iter/s, 76.582s/40 iters), loss = 3.64291
I0708 00:55:30.937952 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40312 (* 0.3 = 0.720937 loss)
I0708 00:55:30.937975 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38668 (* 0.3 = 0.716004 loss)
I0708 00:55:30.937990 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3755 (* 1 = 2.3755 loss)
I0708 00:55:30.938007 99468 sgd_solver.cpp:105] Iteration 11440, lr = 0.001
I0708 00:56:47.527009 99468 solver.cpp:218] Iteration 11480 (0.522285 iter/s, 76.5865s/40 iters), loss = 3.73133
I0708 00:56:47.527235 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44408 (* 0.3 = 0.733223 loss)
I0708 00:56:47.527259 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45373 (* 0.3 = 0.736118 loss)
I0708 00:56:47.527312 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43562 (* 1 = 2.43562 loss)
I0708 00:56:47.527328 99468 sgd_solver.cpp:105] Iteration 11480, lr = 0.001
I0708 00:58:04.083914 99468 solver.cpp:218] Iteration 11520 (0.522506 iter/s, 76.5541s/40 iters), loss = 3.68614
I0708 00:58:04.084141 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17937 (* 0.3 = 0.653812 loss)
I0708 00:58:04.084163 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19344 (* 0.3 = 0.658033 loss)
I0708 00:58:04.084177 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18325 (* 1 = 2.18325 loss)
I0708 00:58:04.084193 99468 sgd_solver.cpp:105] Iteration 11520, lr = 0.001
I0708 00:59:20.627566 99468 solver.cpp:218] Iteration 11560 (0.522596 iter/s, 76.5409s/40 iters), loss = 3.69069
I0708 00:59:20.627884 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28367 (* 0.3 = 0.685101 loss)
I0708 00:59:20.627944 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30228 (* 0.3 = 0.690683 loss)
I0708 00:59:20.627960 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27851 (* 1 = 2.27851 loss)
I0708 00:59:20.627979 99468 sgd_solver.cpp:105] Iteration 11560, lr = 0.001
I0708 01:00:37.241325 99468 solver.cpp:218] Iteration 11600 (0.522119 iter/s, 76.6109s/40 iters), loss = 3.68856
I0708 01:00:37.241578 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32434 (* 0.3 = 0.697303 loss)
I0708 01:00:37.241602 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33952 (* 0.3 = 0.701857 loss)
I0708 01:00:37.241616 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31978 (* 1 = 2.31978 loss)
I0708 01:00:37.241633 99468 sgd_solver.cpp:105] Iteration 11600, lr = 0.001
I0708 01:01:53.810573 99468 solver.cpp:218] Iteration 11640 (0.522422 iter/s, 76.5665s/40 iters), loss = 3.66858
I0708 01:01:53.810825 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42187 (* 0.3 = 0.72656 loss)
I0708 01:01:53.810853 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37144 (* 0.3 = 0.711431 loss)
I0708 01:01:53.810905 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39112 (* 1 = 2.39112 loss)
I0708 01:01:53.810921 99468 sgd_solver.cpp:105] Iteration 11640, lr = 0.001
I0708 01:03:10.336659 99468 solver.cpp:218] Iteration 11680 (0.522717 iter/s, 76.5233s/40 iters), loss = 3.71287
I0708 01:03:10.336882 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22046 (* 0.3 = 0.666139 loss)
I0708 01:03:10.336905 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21023 (* 0.3 = 0.663068 loss)
I0708 01:03:10.336920 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22335 (* 1 = 2.22335 loss)
I0708 01:03:10.336935 99468 sgd_solver.cpp:105] Iteration 11680, lr = 0.001
I0708 01:04:26.661021 99468 solver.cpp:218] Iteration 11720 (0.524098 iter/s, 76.3216s/40 iters), loss = 3.74076
I0708 01:04:26.661236 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34338 (* 0.3 = 0.703013 loss)
I0708 01:04:26.661291 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35415 (* 0.3 = 0.706244 loss)
I0708 01:04:26.661320 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34311 (* 1 = 2.34311 loss)
I0708 01:04:26.661336 99468 sgd_solver.cpp:105] Iteration 11720, lr = 0.001
I0708 01:05:43.182377 99468 solver.cpp:218] Iteration 11760 (0.522749 iter/s, 76.5186s/40 iters), loss = 3.67063
I0708 01:05:43.182607 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21438 (* 0.3 = 0.664315 loss)
I0708 01:05:43.182628 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23064 (* 0.3 = 0.669193 loss)
I0708 01:05:43.182641 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20697 (* 1 = 2.20697 loss)
I0708 01:05:43.182658 99468 sgd_solver.cpp:105] Iteration 11760, lr = 0.001
I0708 01:06:59.536414 99468 solver.cpp:218] Iteration 11800 (0.523894 iter/s, 76.3513s/40 iters), loss = 3.73065
I0708 01:06:59.536656 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1291 (* 0.3 = 0.638729 loss)
I0708 01:06:59.536713 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1085 (* 0.3 = 0.632549 loss)
I0708 01:06:59.536727 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10793 (* 1 = 2.10793 loss)
I0708 01:06:59.536762 99468 sgd_solver.cpp:105] Iteration 11800, lr = 0.001
I0708 01:08:15.800704 99468 solver.cpp:218] Iteration 11840 (0.524511 iter/s, 76.2615s/40 iters), loss = 3.7233
I0708 01:08:15.800984 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55179 (* 0.3 = 0.765536 loss)
I0708 01:08:15.801039 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.52421 (* 0.3 = 0.757264 loss)
I0708 01:08:15.801054 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52374 (* 1 = 2.52374 loss)
I0708 01:08:15.801071 99468 sgd_solver.cpp:105] Iteration 11840, lr = 0.001
I0708 01:09:32.334161 99468 solver.cpp:218] Iteration 11880 (0.522666 iter/s, 76.5307s/40 iters), loss = 3.74142
I0708 01:09:32.334393 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2996 (* 0.3 = 0.689881 loss)
I0708 01:09:32.334415 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3017 (* 0.3 = 0.690511 loss)
I0708 01:09:32.334429 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31693 (* 1 = 2.31693 loss)
I0708 01:09:32.334478 99468 sgd_solver.cpp:105] Iteration 11880, lr = 0.001
I0708 01:10:48.858973 99468 solver.cpp:218] Iteration 11920 (0.522725 iter/s, 76.522s/40 iters), loss = 3.75519
I0708 01:10:48.859216 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13579 (* 0.3 = 0.640738 loss)
I0708 01:10:48.859268 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13048 (* 0.3 = 0.639145 loss)
I0708 01:10:48.859282 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12359 (* 1 = 2.12359 loss)
I0708 01:10:48.859297 99468 sgd_solver.cpp:105] Iteration 11920, lr = 0.001
I0708 01:12:05.408785 99468 solver.cpp:218] Iteration 11960 (0.522554 iter/s, 76.547s/40 iters), loss = 3.6597
I0708 01:12:05.409011 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07993 (* 0.3 = 0.623978 loss)
I0708 01:12:05.409065 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09987 (* 0.3 = 0.629961 loss)
I0708 01:12:05.409082 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08203 (* 1 = 2.08203 loss)
I0708 01:12:05.409116 99468 sgd_solver.cpp:105] Iteration 11960, lr = 0.001
I0708 01:13:19.433451 99468 solver.cpp:330] Iteration 12000, Testing net (#0)
I0708 01:23:50.890135 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.08173 (* 0.3 = 0.62452 loss)
I0708 01:23:50.890420 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.366834
I0708 01:23:50.890452 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.793189
I0708 01:23:50.890483 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.08035 (* 0.3 = 0.624106 loss)
I0708 01:23:50.890503 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.366834
I0708 01:23:50.890518 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.793189
I0708 01:23:50.890602 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07553 (* 1 = 2.07553 loss)
I0708 01:23:50.890619 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.366834
I0708 01:23:50.890635 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.793189
I0708 01:23:52.782140 99468 solver.cpp:218] Iteration 12000 (0.0565491 iter/s, 707.35s/40 iters), loss = 3.7668
I0708 01:23:52.782239 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40325 (* 0.3 = 0.720976 loss)
I0708 01:23:52.782260 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4089 (* 0.3 = 0.722669 loss)
I0708 01:23:52.782279 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4005 (* 1 = 2.4005 loss)
I0708 01:23:52.782323 99468 sgd_solver.cpp:105] Iteration 12000, lr = 0.001
I0708 01:25:09.086694 99468 solver.cpp:218] Iteration 12040 (0.524233 iter/s, 76.3019s/40 iters), loss = 3.71004
I0708 01:25:09.086912 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30449 (* 0.3 = 0.691347 loss)
I0708 01:25:09.086935 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30018 (* 0.3 = 0.690055 loss)
I0708 01:25:09.086947 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30501 (* 1 = 2.30501 loss)
I0708 01:25:09.086967 99468 sgd_solver.cpp:105] Iteration 12040, lr = 0.001
I0708 01:26:25.620985 99468 solver.cpp:218] Iteration 12080 (0.52266 iter/s, 76.5315s/40 iters), loss = 3.71089
I0708 01:26:25.621235 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39862 (* 0.3 = 0.719585 loss)
I0708 01:26:25.621258 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41799 (* 0.3 = 0.725396 loss)
I0708 01:26:25.621273 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41963 (* 1 = 2.41963 loss)
I0708 01:26:25.621289 99468 sgd_solver.cpp:105] Iteration 12080, lr = 0.001
I0708 01:27:42.140313 99468 solver.cpp:218] Iteration 12120 (0.522763 iter/s, 76.5165s/40 iters), loss = 3.66274
I0708 01:27:42.140549 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34115 (* 0.3 = 0.702345 loss)
I0708 01:27:42.140574 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36482 (* 0.3 = 0.709446 loss)
I0708 01:27:42.140586 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34955 (* 1 = 2.34955 loss)
I0708 01:27:42.140602 99468 sgd_solver.cpp:105] Iteration 12120, lr = 0.001
I0708 01:28:58.682826 99468 solver.cpp:218] Iteration 12160 (0.522604 iter/s, 76.5397s/40 iters), loss = 3.67133
I0708 01:28:58.683046 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.72497 (* 0.3 = 0.817492 loss)
I0708 01:28:58.683068 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.69615 (* 0.3 = 0.808846 loss)
I0708 01:28:58.683082 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.70267 (* 1 = 2.70267 loss)
I0708 01:28:58.683128 99468 sgd_solver.cpp:105] Iteration 12160, lr = 0.001
I0708 01:30:15.225868 99468 solver.cpp:218] Iteration 12200 (0.522601 iter/s, 76.5403s/40 iters), loss = 3.73586
I0708 01:30:15.226094 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25391 (* 0.3 = 0.676172 loss)
I0708 01:30:15.226120 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25161 (* 0.3 = 0.675482 loss)
I0708 01:30:15.226133 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24356 (* 1 = 2.24356 loss)
I0708 01:30:15.226150 99468 sgd_solver.cpp:105] Iteration 12200, lr = 0.001
I0708 01:31:31.780758 99468 solver.cpp:218] Iteration 12240 (0.52252 iter/s, 76.5521s/40 iters), loss = 3.68747
I0708 01:31:31.780973 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2551 (* 0.3 = 0.676531 loss)
I0708 01:31:31.781028 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24896 (* 0.3 = 0.674688 loss)
I0708 01:31:31.781045 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24705 (* 1 = 2.24705 loss)
I0708 01:31:31.781077 99468 sgd_solver.cpp:105] Iteration 12240, lr = 0.001
I0708 01:32:48.296877 99468 solver.cpp:218] Iteration 12280 (0.522784 iter/s, 76.5134s/40 iters), loss = 3.67258
I0708 01:32:48.297108 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.57088 (* 0.3 = 0.771265 loss)
I0708 01:32:48.297133 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58 (* 0.3 = 0.774 loss)
I0708 01:32:48.297148 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.54659 (* 1 = 2.54659 loss)
I0708 01:32:48.297163 99468 sgd_solver.cpp:105] Iteration 12280, lr = 0.001
I0708 01:34:04.825518 99468 solver.cpp:218] Iteration 12320 (0.522699 iter/s, 76.5259s/40 iters), loss = 3.73573
I0708 01:34:04.825748 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13259 (* 0.3 = 0.639778 loss)
I0708 01:34:04.825768 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13957 (* 0.3 = 0.641872 loss)
I0708 01:34:04.825783 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13536 (* 1 = 2.13536 loss)
I0708 01:34:04.825803 99468 sgd_solver.cpp:105] Iteration 12320, lr = 0.001
I0708 01:35:21.153275 99468 solver.cpp:218] Iteration 12360 (0.524075 iter/s, 76.325s/40 iters), loss = 3.69685
I0708 01:35:21.153496 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23005 (* 0.3 = 0.669016 loss)
I0708 01:35:21.153518 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24081 (* 0.3 = 0.672244 loss)
I0708 01:35:21.153532 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22202 (* 1 = 2.22202 loss)
I0708 01:35:21.153548 99468 sgd_solver.cpp:105] Iteration 12360, lr = 0.001
I0708 01:36:37.674585 99468 solver.cpp:218] Iteration 12400 (0.522749 iter/s, 76.5186s/40 iters), loss = 3.66962
I0708 01:36:37.674839 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54971 (* 0.3 = 0.764914 loss)
I0708 01:36:37.674865 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57207 (* 0.3 = 0.771621 loss)
I0708 01:36:37.674918 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.54739 (* 1 = 2.54739 loss)
I0708 01:36:37.674935 99468 sgd_solver.cpp:105] Iteration 12400, lr = 0.001
I0708 01:37:54.106042 99468 solver.cpp:218] Iteration 12440 (0.523364 iter/s, 76.4287s/40 iters), loss = 3.72144
I0708 01:37:54.106271 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39295 (* 0.3 = 0.717885 loss)
I0708 01:37:54.106292 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40504 (* 0.3 = 0.721513 loss)
I0708 01:37:54.106305 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38873 (* 1 = 2.38873 loss)
I0708 01:37:54.106320 99468 sgd_solver.cpp:105] Iteration 12440, lr = 0.001
I0708 01:39:10.639786 99468 solver.cpp:218] Iteration 12480 (0.522664 iter/s, 76.531s/40 iters), loss = 3.69921
I0708 01:39:10.640000 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.49378 (* 0.3 = 0.748134 loss)
I0708 01:39:10.640055 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48226 (* 0.3 = 0.744677 loss)
I0708 01:39:10.640074 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48815 (* 1 = 2.48815 loss)
I0708 01:39:10.640092 99468 sgd_solver.cpp:105] Iteration 12480, lr = 0.001
I0708 01:40:27.206125 99468 solver.cpp:218] Iteration 12520 (0.522442 iter/s, 76.5636s/40 iters), loss = 3.74871
I0708 01:40:27.206351 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48508 (* 0.3 = 0.745524 loss)
I0708 01:40:27.206372 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4918 (* 0.3 = 0.747539 loss)
I0708 01:40:27.206385 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45182 (* 1 = 2.45182 loss)
I0708 01:40:27.206401 99468 sgd_solver.cpp:105] Iteration 12520, lr = 0.001
I0708 01:41:43.758122 99468 solver.cpp:218] Iteration 12560 (0.52254 iter/s, 76.5492s/40 iters), loss = 3.64981
I0708 01:41:43.758349 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40209 (* 0.3 = 0.720628 loss)
I0708 01:41:43.758373 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40947 (* 0.3 = 0.722841 loss)
I0708 01:41:43.758386 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39936 (* 1 = 2.39936 loss)
I0708 01:41:43.758402 99468 sgd_solver.cpp:105] Iteration 12560, lr = 0.001
I0708 01:43:00.298375 99468 solver.cpp:218] Iteration 12600 (0.52262 iter/s, 76.5375s/40 iters), loss = 3.68027
I0708 01:43:00.298606 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14723 (* 0.3 = 0.644171 loss)
I0708 01:43:00.298658 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17218 (* 0.3 = 0.651655 loss)
I0708 01:43:00.298671 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1351 (* 1 = 2.1351 loss)
I0708 01:43:00.298704 99468 sgd_solver.cpp:105] Iteration 12600, lr = 0.001
I0708 01:44:16.840991 99468 solver.cpp:218] Iteration 12640 (0.522604 iter/s, 76.5399s/40 iters), loss = 3.7536
I0708 01:44:16.841218 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60815 (* 0.3 = 0.782445 loss)
I0708 01:44:16.841240 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61313 (* 0.3 = 0.78394 loss)
I0708 01:44:16.841255 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.60326 (* 1 = 2.60326 loss)
I0708 01:44:16.841270 99468 sgd_solver.cpp:105] Iteration 12640, lr = 0.001
I0708 01:45:33.366323 99468 solver.cpp:218] Iteration 12680 (0.522722 iter/s, 76.5226s/40 iters), loss = 3.70771
I0708 01:45:33.366545 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32298 (* 0.3 = 0.696893 loss)
I0708 01:45:33.366575 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.331 (* 0.3 = 0.699301 loss)
I0708 01:45:33.366587 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34623 (* 1 = 2.34623 loss)
I0708 01:45:33.366602 99468 sgd_solver.cpp:105] Iteration 12680, lr = 0.001
I0708 01:46:49.866593 99468 solver.cpp:218] Iteration 12720 (0.522893 iter/s, 76.4975s/40 iters), loss = 3.71481
I0708 01:46:49.866842 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34064 (* 0.3 = 0.702193 loss)
I0708 01:46:49.866865 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35472 (* 0.3 = 0.706418 loss)
I0708 01:46:49.866879 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32316 (* 1 = 2.32316 loss)
I0708 01:46:49.866895 99468 sgd_solver.cpp:105] Iteration 12720, lr = 0.001
I0708 01:48:06.241255 99468 solver.cpp:218] Iteration 12760 (0.523753 iter/s, 76.3719s/40 iters), loss = 3.69577
I0708 01:48:06.241477 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28004 (* 0.3 = 0.684013 loss)
I0708 01:48:06.241499 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26518 (* 0.3 = 0.679553 loss)
I0708 01:48:06.241514 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28111 (* 1 = 2.28111 loss)
I0708 01:48:06.241530 99468 sgd_solver.cpp:105] Iteration 12760, lr = 0.001
I0708 01:49:22.720381 99468 solver.cpp:218] Iteration 12800 (0.523037 iter/s, 76.4764s/40 iters), loss = 3.69053
I0708 01:49:22.721122 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.03526 (* 0.3 = 0.610578 loss)
I0708 01:49:22.721195 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03763 (* 0.3 = 0.61129 loss)
I0708 01:49:22.721238 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02502 (* 1 = 2.02502 loss)
I0708 01:49:22.721284 99468 sgd_solver.cpp:105] Iteration 12800, lr = 0.001
I0708 01:50:39.295289 99468 solver.cpp:218] Iteration 12840 (0.522386 iter/s, 76.5717s/40 iters), loss = 3.71494
I0708 01:50:39.295512 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43148 (* 0.3 = 0.729445 loss)
I0708 01:50:39.295536 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38486 (* 0.3 = 0.715458 loss)
I0708 01:50:39.295550 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41113 (* 1 = 2.41113 loss)
I0708 01:50:39.295570 99468 sgd_solver.cpp:105] Iteration 12840, lr = 0.001
I0708 01:51:55.782361 99468 solver.cpp:218] Iteration 12880 (0.522983 iter/s, 76.4843s/40 iters), loss = 3.72983
I0708 01:51:55.782584 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17958 (* 0.3 = 0.653874 loss)
I0708 01:51:55.782634 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19714 (* 0.3 = 0.659141 loss)
I0708 01:51:55.782647 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18007 (* 1 = 2.18007 loss)
I0708 01:51:55.782668 99468 sgd_solver.cpp:105] Iteration 12880, lr = 0.001
I0708 01:53:12.028951 99468 solver.cpp:218] Iteration 12920 (0.524633 iter/s, 76.2438s/40 iters), loss = 3.72443
I0708 01:53:12.029211 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.73817 (* 0.3 = 0.82145 loss)
I0708 01:53:12.029234 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.75297 (* 0.3 = 0.82589 loss)
I0708 01:53:12.029249 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.74661 (* 1 = 2.74661 loss)
I0708 01:53:12.029264 99468 sgd_solver.cpp:105] Iteration 12920, lr = 0.001
I0708 01:54:28.264078 99468 solver.cpp:218] Iteration 12960 (0.524712 iter/s, 76.2324s/40 iters), loss = 3.72159
I0708 01:54:28.264319 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48224 (* 0.3 = 0.744671 loss)
I0708 01:54:28.264341 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46852 (* 0.3 = 0.740556 loss)
I0708 01:54:28.264354 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46946 (* 1 = 2.46946 loss)
I0708 01:54:28.264374 99468 sgd_solver.cpp:105] Iteration 12960, lr = 0.001
I0708 01:55:44.472911 99468 solver.cpp:218] Iteration 13000 (0.524893 iter/s, 76.2061s/40 iters), loss = 3.69731
I0708 01:55:44.473173 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17875 (* 0.3 = 0.653624 loss)
I0708 01:55:44.473196 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19829 (* 0.3 = 0.659486 loss)
I0708 01:55:44.473211 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20018 (* 1 = 2.20018 loss)
I0708 01:55:44.473229 99468 sgd_solver.cpp:105] Iteration 13000, lr = 0.001
I0708 01:57:00.693969 99468 solver.cpp:218] Iteration 13040 (0.524808 iter/s, 76.2183s/40 iters), loss = 3.71283
I0708 01:57:00.694200 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46117 (* 0.3 = 0.738352 loss)
I0708 01:57:00.694219 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48314 (* 0.3 = 0.744943 loss)
I0708 01:57:00.694234 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47162 (* 1 = 2.47162 loss)
I0708 01:57:00.694252 99468 sgd_solver.cpp:105] Iteration 13040, lr = 0.001
I0708 01:58:17.154451 99468 solver.cpp:218] Iteration 13080 (0.523165 iter/s, 76.4577s/40 iters), loss = 3.7778
I0708 01:58:17.154677 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.76442 (* 0.3 = 0.829325 loss)
I0708 01:58:17.154731 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.78894 (* 0.3 = 0.836682 loss)
I0708 01:58:17.154762 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.78336 (* 1 = 2.78336 loss)
I0708 01:58:17.154778 99468 sgd_solver.cpp:105] Iteration 13080, lr = 0.001
I0708 01:59:33.661815 99468 solver.cpp:218] Iteration 13120 (0.522844 iter/s, 76.5046s/40 iters), loss = 3.70251
I0708 01:59:33.662044 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50943 (* 0.3 = 0.75283 loss)
I0708 01:59:33.662065 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53837 (* 0.3 = 0.76151 loss)
I0708 01:59:33.662077 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52246 (* 1 = 2.52246 loss)
I0708 01:59:33.662128 99468 sgd_solver.cpp:105] Iteration 13120, lr = 0.001
I0708 02:00:49.897889 99468 solver.cpp:218] Iteration 13160 (0.524705 iter/s, 76.2333s/40 iters), loss = 3.70941
I0708 02:00:49.898121 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40454 (* 0.3 = 0.721361 loss)
I0708 02:00:49.898142 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40855 (* 0.3 = 0.722564 loss)
I0708 02:00:49.898154 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39814 (* 1 = 2.39814 loss)
I0708 02:00:49.898205 99468 sgd_solver.cpp:105] Iteration 13160, lr = 0.001
I0708 02:02:06.251027 99468 solver.cpp:218] Iteration 13200 (0.5239 iter/s, 76.3504s/40 iters), loss = 3.72122
I0708 02:02:06.251268 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39792 (* 0.3 = 0.719377 loss)
I0708 02:02:06.251291 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41311 (* 0.3 = 0.723932 loss)
I0708 02:02:06.251305 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39606 (* 1 = 2.39606 loss)
I0708 02:02:06.251320 99468 sgd_solver.cpp:105] Iteration 13200, lr = 0.001
I0708 02:03:22.777851 99468 solver.cpp:218] Iteration 13240 (0.522711 iter/s, 76.5241s/40 iters), loss = 3.64778
I0708 02:03:22.778072 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21964 (* 0.3 = 0.665892 loss)
I0708 02:03:22.778095 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22252 (* 0.3 = 0.666755 loss)
I0708 02:03:22.778107 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22116 (* 1 = 2.22116 loss)
I0708 02:03:22.778122 99468 sgd_solver.cpp:105] Iteration 13240, lr = 0.001
I0708 02:04:39.327649 99468 solver.cpp:218] Iteration 13280 (0.522554 iter/s, 76.5471s/40 iters), loss = 3.66844
I0708 02:04:39.327909 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38741 (* 0.3 = 0.716223 loss)
I0708 02:04:39.327930 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38093 (* 0.3 = 0.71428 loss)
I0708 02:04:39.327944 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3737 (* 1 = 2.3737 loss)
I0708 02:04:39.327960 99468 sgd_solver.cpp:105] Iteration 13280, lr = 0.001
I0708 02:05:55.876026 99468 solver.cpp:218] Iteration 13320 (0.522564 iter/s, 76.5456s/40 iters), loss = 3.70523
I0708 02:05:55.876287 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23959 (* 0.3 = 0.671879 loss)
I0708 02:05:55.876310 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19969 (* 0.3 = 0.659908 loss)
I0708 02:05:55.876325 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22023 (* 1 = 2.22023 loss)
I0708 02:05:55.876341 99468 sgd_solver.cpp:105] Iteration 13320, lr = 0.001
I0708 02:07:12.303279 99468 solver.cpp:218] Iteration 13360 (0.523393 iter/s, 76.4245s/40 iters), loss = 3.70837
I0708 02:07:12.303504 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36045 (* 0.3 = 0.708136 loss)
I0708 02:07:12.303525 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33371 (* 0.3 = 0.700114 loss)
I0708 02:07:12.303539 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35806 (* 1 = 2.35806 loss)
I0708 02:07:12.303560 99468 sgd_solver.cpp:105] Iteration 13360, lr = 0.001
I0708 02:08:28.774050 99468 solver.cpp:218] Iteration 13400 (0.523095 iter/s, 76.468s/40 iters), loss = 3.745
I0708 02:08:28.774271 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18094 (* 0.3 = 0.654281 loss)
I0708 02:08:28.774291 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17011 (* 0.3 = 0.651034 loss)
I0708 02:08:28.774304 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18093 (* 1 = 2.18093 loss)
I0708 02:08:28.774323 99468 sgd_solver.cpp:105] Iteration 13400, lr = 0.001
I0708 02:09:45.155021 99468 solver.cpp:218] Iteration 13440 (0.52371 iter/s, 76.3782s/40 iters), loss = 3.69897
I0708 02:09:45.155308 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30119 (* 0.3 = 0.690357 loss)
I0708 02:09:45.155349 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33468 (* 0.3 = 0.700404 loss)
I0708 02:09:45.155418 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3138 (* 1 = 2.3138 loss)
I0708 02:09:45.155447 99468 sgd_solver.cpp:105] Iteration 13440, lr = 0.001
I0708 02:11:01.363524 99468 solver.cpp:218] Iteration 13480 (0.524895 iter/s, 76.2057s/40 iters), loss = 3.66433
I0708 02:11:01.363773 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30067 (* 0.3 = 0.6902 loss)
I0708 02:11:01.363800 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30086 (* 0.3 = 0.690259 loss)
I0708 02:11:01.363819 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29472 (* 1 = 2.29472 loss)
I0708 02:11:01.363836 99468 sgd_solver.cpp:105] Iteration 13480, lr = 0.001
I0708 02:12:17.702270 99468 solver.cpp:218] Iteration 13520 (0.523999 iter/s, 76.336s/40 iters), loss = 3.67169
I0708 02:12:17.702479 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07135 (* 0.3 = 0.621406 loss)
I0708 02:12:17.702502 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0716 (* 0.3 = 0.621479 loss)
I0708 02:12:17.702515 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.072 (* 1 = 2.072 loss)
I0708 02:12:17.702531 99468 sgd_solver.cpp:105] Iteration 13520, lr = 0.001
I0708 02:13:34.226449 99468 solver.cpp:218] Iteration 13560 (0.522729 iter/s, 76.5214s/40 iters), loss = 3.6738
I0708 02:13:34.226662 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2794 (* 0.3 = 0.68382 loss)
I0708 02:13:34.226686 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31748 (* 0.3 = 0.695245 loss)
I0708 02:13:34.226701 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28572 (* 1 = 2.28572 loss)
I0708 02:13:34.226716 99468 sgd_solver.cpp:105] Iteration 13560, lr = 0.001
I0708 02:14:50.562405 99468 solver.cpp:218] Iteration 13600 (0.524018 iter/s, 76.3332s/40 iters), loss = 3.74681
I0708 02:14:50.562629 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14095 (* 0.3 = 0.642285 loss)
I0708 02:14:50.562650 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14806 (* 0.3 = 0.644418 loss)
I0708 02:14:50.562664 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14719 (* 1 = 2.14719 loss)
I0708 02:14:50.562680 99468 sgd_solver.cpp:105] Iteration 13600, lr = 0.001
I0708 02:16:06.855773 99468 solver.cpp:218] Iteration 13640 (0.524311 iter/s, 76.2906s/40 iters), loss = 3.77115
I0708 02:16:06.856036 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31395 (* 0.3 = 0.694186 loss)
I0708 02:16:06.856060 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29925 (* 0.3 = 0.689774 loss)
I0708 02:16:06.856106 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30526 (* 1 = 2.30526 loss)
I0708 02:16:06.856138 99468 sgd_solver.cpp:105] Iteration 13640, lr = 0.001
I0708 02:17:23.413115 99468 solver.cpp:218] Iteration 13680 (0.522503 iter/s, 76.5546s/40 iters), loss = 3.68135
I0708 02:17:23.413345 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5568 (* 0.3 = 0.767039 loss)
I0708 02:17:23.413401 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53905 (* 0.3 = 0.761716 loss)
I0708 02:17:23.413417 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5429 (* 1 = 2.5429 loss)
I0708 02:17:23.413434 99468 sgd_solver.cpp:105] Iteration 13680, lr = 0.001
I0708 02:18:39.960361 99468 solver.cpp:218] Iteration 13720 (0.522572 iter/s, 76.5445s/40 iters), loss = 3.73956
I0708 02:18:39.960608 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25446 (* 0.3 = 0.676337 loss)
I0708 02:18:39.960665 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24655 (* 0.3 = 0.673966 loss)
I0708 02:18:39.960680 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25679 (* 1 = 2.25679 loss)
I0708 02:18:39.960696 99468 sgd_solver.cpp:105] Iteration 13720, lr = 0.001
I0708 02:19:56.495133 99468 solver.cpp:218] Iteration 13760 (0.522657 iter/s, 76.532s/40 iters), loss = 3.72804
I0708 02:19:56.495353 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4144 (* 0.3 = 0.724319 loss)
I0708 02:19:56.495405 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42562 (* 0.3 = 0.727685 loss)
I0708 02:19:56.495424 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42872 (* 1 = 2.42872 loss)
I0708 02:19:56.495455 99468 sgd_solver.cpp:105] Iteration 13760, lr = 0.001
I0708 02:21:13.053921 99468 solver.cpp:218] Iteration 13800 (0.522493 iter/s, 76.556s/40 iters), loss = 3.70254
I0708 02:21:13.054164 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.0665 (* 0.3 = 0.619949 loss)
I0708 02:21:13.054193 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08325 (* 0.3 = 0.624975 loss)
I0708 02:21:13.054211 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08278 (* 1 = 2.08278 loss)
I0708 02:21:13.054229 99468 sgd_solver.cpp:105] Iteration 13800, lr = 0.001
I0708 02:22:29.347337 99468 solver.cpp:218] Iteration 13840 (0.524311 iter/s, 76.2907s/40 iters), loss = 3.73805
I0708 02:22:29.347556 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38365 (* 0.3 = 0.715094 loss)
I0708 02:22:29.347579 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39849 (* 0.3 = 0.719547 loss)
I0708 02:22:29.347591 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39354 (* 1 = 2.39354 loss)
I0708 02:22:29.347610 99468 sgd_solver.cpp:105] Iteration 13840, lr = 0.001
I0708 02:23:45.527039 99468 solver.cpp:218] Iteration 13880 (0.525093 iter/s, 76.177s/40 iters), loss = 3.70795
I0708 02:23:45.527266 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5179 (* 0.3 = 0.755371 loss)
I0708 02:23:45.527287 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49972 (* 0.3 = 0.749915 loss)
I0708 02:23:45.527302 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51076 (* 1 = 2.51076 loss)
I0708 02:23:45.527319 99468 sgd_solver.cpp:105] Iteration 13880, lr = 0.001
I0708 02:25:01.743077 99468 solver.cpp:218] Iteration 13920 (0.524843 iter/s, 76.2133s/40 iters), loss = 3.70812
I0708 02:25:01.743316 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51107 (* 0.3 = 0.753322 loss)
I0708 02:25:01.743371 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49201 (* 0.3 = 0.747602 loss)
I0708 02:25:01.743386 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48854 (* 1 = 2.48854 loss)
I0708 02:25:01.743403 99468 sgd_solver.cpp:105] Iteration 13920, lr = 0.001
I0708 02:26:18.330216 99468 solver.cpp:218] Iteration 13960 (0.5223 iter/s, 76.5844s/40 iters), loss = 3.66249
I0708 02:26:18.330476 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08039 (* 0.3 = 0.624117 loss)
I0708 02:26:18.330499 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09085 (* 0.3 = 0.627255 loss)
I0708 02:26:18.330548 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07385 (* 1 = 2.07385 loss)
I0708 02:26:18.330571 99468 sgd_solver.cpp:105] Iteration 13960, lr = 0.001
I0708 02:27:34.678892 99468 solver.cpp:218] Iteration 14000 (0.523931 iter/s, 76.3459s/40 iters), loss = 3.73894
I0708 02:27:34.679131 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1521 (* 0.3 = 0.645631 loss)
I0708 02:27:34.679152 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15792 (* 0.3 = 0.647376 loss)
I0708 02:27:34.679167 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13938 (* 1 = 2.13938 loss)
I0708 02:27:34.679183 99468 sgd_solver.cpp:105] Iteration 14000, lr = 0.001
I0708 02:28:50.930342 99468 solver.cpp:218] Iteration 14040 (0.524599 iter/s, 76.2487s/40 iters), loss = 3.70375
I0708 02:28:50.930564 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.212 (* 0.3 = 0.663599 loss)
I0708 02:28:50.930629 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20148 (* 0.3 = 0.660443 loss)
I0708 02:28:50.930642 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20725 (* 1 = 2.20725 loss)
I0708 02:28:50.930660 99468 sgd_solver.cpp:105] Iteration 14040, lr = 0.001
I0708 02:30:07.174346 99468 solver.cpp:218] Iteration 14080 (0.52465 iter/s, 76.2413s/40 iters), loss = 3.64896
I0708 02:30:07.174571 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41153 (* 0.3 = 0.723458 loss)
I0708 02:30:07.174631 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41957 (* 0.3 = 0.725872 loss)
I0708 02:30:07.174646 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41813 (* 1 = 2.41813 loss)
I0708 02:30:07.174662 99468 sgd_solver.cpp:105] Iteration 14080, lr = 0.001
I0708 02:31:23.541728 99468 solver.cpp:218] Iteration 14120 (0.523803 iter/s, 76.3646s/40 iters), loss = 3.76335
I0708 02:31:23.541946 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18822 (* 0.3 = 0.656465 loss)
I0708 02:31:23.541968 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18988 (* 0.3 = 0.656965 loss)
I0708 02:31:23.541981 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20073 (* 1 = 2.20073 loss)
I0708 02:31:23.542001 99468 sgd_solver.cpp:105] Iteration 14120, lr = 0.001
I0708 02:32:40.105186 99468 solver.cpp:218] Iteration 14160 (0.522461 iter/s, 76.5607s/40 iters), loss = 3.66715
I0708 02:32:40.105407 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04763 (* 0.3 = 0.614288 loss)
I0708 02:32:40.105428 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07184 (* 0.3 = 0.621552 loss)
I0708 02:32:40.105444 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.05081 (* 1 = 2.05081 loss)
I0708 02:32:40.105460 99468 sgd_solver.cpp:105] Iteration 14160, lr = 0.001
I0708 02:33:56.629371 99468 solver.cpp:218] Iteration 14200 (0.522729 iter/s, 76.5214s/40 iters), loss = 3.66719
I0708 02:33:56.629601 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26991 (* 0.3 = 0.680974 loss)
I0708 02:33:56.629622 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2462 (* 0.3 = 0.67386 loss)
I0708 02:33:56.629637 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26351 (* 1 = 2.26351 loss)
I0708 02:33:56.629652 99468 sgd_solver.cpp:105] Iteration 14200, lr = 0.001
I0708 02:35:13.164057 99468 solver.cpp:218] Iteration 14240 (0.522658 iter/s, 76.5319s/40 iters), loss = 3.72592
I0708 02:35:13.164314 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23607 (* 0.3 = 0.67082 loss)
I0708 02:35:13.164376 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23781 (* 0.3 = 0.671344 loss)
I0708 02:35:13.164391 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24337 (* 1 = 2.24337 loss)
I0708 02:35:13.164410 99468 sgd_solver.cpp:105] Iteration 14240, lr = 0.001
I0708 02:36:29.698063 99468 solver.cpp:218] Iteration 14280 (0.522663 iter/s, 76.5312s/40 iters), loss = 3.63828
I0708 02:36:29.698305 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01513 (* 0.3 = 0.60454 loss)
I0708 02:36:29.698328 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.98248 (* 0.3 = 0.594743 loss)
I0708 02:36:29.698341 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.00416 (* 1 = 2.00416 loss)
I0708 02:36:29.698359 99468 sgd_solver.cpp:105] Iteration 14280, lr = 0.001
I0708 02:37:46.003381 99468 solver.cpp:218] Iteration 14320 (0.524229 iter/s, 76.3025s/40 iters), loss = 3.69942
I0708 02:37:46.003662 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54186 (* 0.3 = 0.762559 loss)
I0708 02:37:46.003705 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55229 (* 0.3 = 0.765686 loss)
I0708 02:37:46.003764 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.54977 (* 1 = 2.54977 loss)
I0708 02:37:46.003810 99468 sgd_solver.cpp:105] Iteration 14320, lr = 0.001
I0708 02:39:02.289803 99468 solver.cpp:218] Iteration 14360 (0.524359 iter/s, 76.2836s/40 iters), loss = 3.72215
I0708 02:39:02.290066 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20922 (* 0.3 = 0.662767 loss)
I0708 02:39:02.290097 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19614 (* 0.3 = 0.658842 loss)
I0708 02:39:02.290115 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21219 (* 1 = 2.21219 loss)
I0708 02:39:02.290169 99468 sgd_solver.cpp:105] Iteration 14360, lr = 0.001
I0708 02:40:18.753464 99468 solver.cpp:218] Iteration 14400 (0.523143 iter/s, 76.4609s/40 iters), loss = 3.64686
I0708 02:40:18.753686 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11623 (* 0.3 = 0.634869 loss)
I0708 02:40:18.753741 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11146 (* 0.3 = 0.633439 loss)
I0708 02:40:18.753758 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11664 (* 1 = 2.11664 loss)
I0708 02:40:18.753775 99468 sgd_solver.cpp:105] Iteration 14400, lr = 0.001
I0708 02:41:35.307826 99468 solver.cpp:218] Iteration 14440 (0.522523 iter/s, 76.5516s/40 iters), loss = 3.77926
I0708 02:41:35.308068 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31315 (* 0.3 = 0.693945 loss)
I0708 02:41:35.308123 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31829 (* 0.3 = 0.695488 loss)
I0708 02:41:35.308136 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31336 (* 1 = 2.31336 loss)
I0708 02:41:35.308169 99468 sgd_solver.cpp:105] Iteration 14440, lr = 0.001
I0708 02:42:51.865666 99468 solver.cpp:218] Iteration 14480 (0.5225 iter/s, 76.5551s/40 iters), loss = 3.68578
I0708 02:42:51.865877 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23798 (* 0.3 = 0.671394 loss)
I0708 02:42:51.865900 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2396 (* 0.3 = 0.671879 loss)
I0708 02:42:51.865914 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24741 (* 1 = 2.24741 loss)
I0708 02:42:51.865931 99468 sgd_solver.cpp:105] Iteration 14480, lr = 0.001
I0708 02:44:08.430086 99468 solver.cpp:218] Iteration 14520 (0.522455 iter/s, 76.5617s/40 iters), loss = 3.67871
I0708 02:44:08.430304 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15975 (* 0.3 = 0.647924 loss)
I0708 02:44:08.430325 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16902 (* 0.3 = 0.650705 loss)
I0708 02:44:08.430338 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17491 (* 1 = 2.17491 loss)
I0708 02:44:08.430354 99468 sgd_solver.cpp:105] Iteration 14520, lr = 0.001
I0708 02:45:24.978567 99468 solver.cpp:218] Iteration 14560 (0.522564 iter/s, 76.5457s/40 iters), loss = 3.73627
I0708 02:45:24.978852 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02708 (* 0.3 = 0.608124 loss)
I0708 02:45:24.978910 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.01901 (* 0.3 = 0.605704 loss)
I0708 02:45:24.978925 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.01615 (* 1 = 2.01615 loss)
I0708 02:45:24.978943 99468 sgd_solver.cpp:105] Iteration 14560, lr = 0.001
I0708 02:46:41.466389 99468 solver.cpp:218] Iteration 14600 (0.522978 iter/s, 76.485s/40 iters), loss = 3.73554
I0708 02:46:41.468107 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15139 (* 0.3 = 0.645416 loss)
I0708 02:46:41.468158 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15542 (* 0.3 = 0.646626 loss)
I0708 02:46:41.468191 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1639 (* 1 = 2.1639 loss)
I0708 02:46:41.468212 99468 sgd_solver.cpp:105] Iteration 14600, lr = 0.001
I0708 02:47:57.826813 99468 solver.cpp:218] Iteration 14640 (0.52386 iter/s, 76.3562s/40 iters), loss = 3.78731
I0708 02:47:57.827056 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33978 (* 0.3 = 0.701935 loss)
I0708 02:47:57.827081 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34389 (* 0.3 = 0.703166 loss)
I0708 02:47:57.827127 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36374 (* 1 = 2.36374 loss)
I0708 02:47:57.827143 99468 sgd_solver.cpp:105] Iteration 14640, lr = 0.001
I0708 02:49:14.327865 99468 solver.cpp:218] Iteration 14680 (0.522888 iter/s, 76.4983s/40 iters), loss = 3.71554
I0708 02:49:14.328088 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25152 (* 0.3 = 0.675455 loss)
I0708 02:49:14.328155 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25707 (* 0.3 = 0.677122 loss)
I0708 02:49:14.328169 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26074 (* 1 = 2.26074 loss)
I0708 02:49:14.328187 99468 sgd_solver.cpp:105] Iteration 14680, lr = 0.001
I0708 02:50:30.812067 99468 solver.cpp:218] Iteration 14720 (0.523003 iter/s, 76.4815s/40 iters), loss = 3.67525
I0708 02:50:30.812288 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29292 (* 0.3 = 0.687875 loss)
I0708 02:50:30.812307 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29152 (* 0.3 = 0.687455 loss)
I0708 02:50:30.812325 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29987 (* 1 = 2.29987 loss)
I0708 02:50:30.812341 99468 sgd_solver.cpp:105] Iteration 14720, lr = 0.001
I0708 02:51:47.296041 99468 solver.cpp:218] Iteration 14760 (0.523004 iter/s, 76.4812s/40 iters), loss = 3.67349
I0708 02:51:47.296272 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11278 (* 0.3 = 0.633833 loss)
I0708 02:51:47.296295 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10692 (* 0.3 = 0.632076 loss)
I0708 02:51:47.296311 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10613 (* 1 = 2.10613 loss)
I0708 02:51:47.296329 99468 sgd_solver.cpp:105] Iteration 14760, lr = 0.001
I0708 02:53:03.526326 99468 solver.cpp:218] Iteration 14800 (0.524745 iter/s, 76.2275s/40 iters), loss = 3.65229
I0708 02:53:03.526556 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33655 (* 0.3 = 0.700965 loss)
I0708 02:53:03.526579 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32328 (* 0.3 = 0.696983 loss)
I0708 02:53:03.526594 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34453 (* 1 = 2.34453 loss)
I0708 02:53:03.526649 99468 sgd_solver.cpp:105] Iteration 14800, lr = 0.001
I0708 02:54:19.690862 99468 solver.cpp:218] Iteration 14840 (0.525198 iter/s, 76.1618s/40 iters), loss = 3.73299
I0708 02:54:19.691144 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24775 (* 0.3 = 0.674325 loss)
I0708 02:54:19.691170 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25757 (* 0.3 = 0.67727 loss)
I0708 02:54:19.691220 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23405 (* 1 = 2.23405 loss)
I0708 02:54:19.691237 99468 sgd_solver.cpp:105] Iteration 14840, lr = 0.001
I0708 02:55:36.016556 99468 solver.cpp:218] Iteration 14880 (0.524089 iter/s, 76.3229s/40 iters), loss = 3.72243
I0708 02:55:36.016852 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25384 (* 0.3 = 0.676151 loss)
I0708 02:55:36.016893 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24142 (* 0.3 = 0.672426 loss)
I0708 02:55:36.016908 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23909 (* 1 = 2.23909 loss)
I0708 02:55:36.016929 99468 sgd_solver.cpp:105] Iteration 14880, lr = 0.001
I0708 02:56:52.460775 99468 solver.cpp:218] Iteration 14920 (0.523277 iter/s, 76.4414s/40 iters), loss = 3.66817
I0708 02:56:52.461007 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22911 (* 0.3 = 0.668734 loss)
I0708 02:56:52.461032 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22115 (* 0.3 = 0.666345 loss)
I0708 02:56:52.461047 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21747 (* 1 = 2.21747 loss)
I0708 02:56:52.461062 99468 sgd_solver.cpp:105] Iteration 14920, lr = 0.001
I0708 02:58:08.704298 99468 solver.cpp:218] Iteration 14960 (0.524654 iter/s, 76.2408s/40 iters), loss = 3.74592
I0708 02:58:08.704515 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16148 (* 0.3 = 0.648444 loss)
I0708 02:58:08.704592 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14903 (* 0.3 = 0.64471 loss)
I0708 02:58:08.704607 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1528 (* 1 = 2.1528 loss)
I0708 02:58:08.704622 99468 sgd_solver.cpp:105] Iteration 14960, lr = 0.001
I0708 02:59:24.948040 99468 solver.cpp:218] Iteration 15000 (0.524652 iter/s, 76.241s/40 iters), loss = 3.6754
I0708 02:59:24.948271 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25098 (* 0.3 = 0.675293 loss)
I0708 02:59:24.948297 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27168 (* 0.3 = 0.681505 loss)
I0708 02:59:24.948315 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2433 (* 1 = 2.2433 loss)
I0708 02:59:24.948330 99468 sgd_solver.cpp:105] Iteration 15000, lr = 0.001
I0708 03:00:41.221909 99468 solver.cpp:218] Iteration 15040 (0.524445 iter/s, 76.2711s/40 iters), loss = 3.63503
I0708 03:00:41.222136 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39534 (* 0.3 = 0.718601 loss)
I0708 03:00:41.222193 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37905 (* 0.3 = 0.713716 loss)
I0708 03:00:41.222208 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37823 (* 1 = 2.37823 loss)
I0708 03:00:41.222226 99468 sgd_solver.cpp:105] Iteration 15040, lr = 0.001
I0708 03:01:57.767036 99468 solver.cpp:218] Iteration 15080 (0.522586 iter/s, 76.5424s/40 iters), loss = 3.74123
I0708 03:01:57.767261 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43027 (* 0.3 = 0.72908 loss)
I0708 03:01:57.767285 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45803 (* 0.3 = 0.73741 loss)
I0708 03:01:57.767300 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43921 (* 1 = 2.43921 loss)
I0708 03:01:57.767315 99468 sgd_solver.cpp:105] Iteration 15080, lr = 0.001
I0708 03:03:14.275424 99468 solver.cpp:218] Iteration 15120 (0.522837 iter/s, 76.5056s/40 iters), loss = 3.70267
I0708 03:03:14.275665 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9646 (* 0.3 = 0.589381 loss)
I0708 03:03:14.275688 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.98604 (* 0.3 = 0.595812 loss)
I0708 03:03:14.275702 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.96943 (* 1 = 1.96943 loss)
I0708 03:03:14.275722 99468 sgd_solver.cpp:105] Iteration 15120, lr = 0.001
I0708 03:04:30.838496 99468 solver.cpp:218] Iteration 15160 (0.522464 iter/s, 76.5603s/40 iters), loss = 3.76414
I0708 03:04:30.838752 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55432 (* 0.3 = 0.766296 loss)
I0708 03:04:30.838824 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55444 (* 0.3 = 0.766333 loss)
I0708 03:04:30.838836 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.57008 (* 1 = 2.57008 loss)
I0708 03:04:30.838856 99468 sgd_solver.cpp:105] Iteration 15160, lr = 0.001
I0708 03:05:47.366863 99468 solver.cpp:218] Iteration 15200 (0.522701 iter/s, 76.5256s/40 iters), loss = 3.67547
I0708 03:05:47.367092 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20947 (* 0.3 = 0.662841 loss)
I0708 03:05:47.367115 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23341 (* 0.3 = 0.670024 loss)
I0708 03:05:47.367130 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22344 (* 1 = 2.22344 loss)
I0708 03:05:47.367182 99468 sgd_solver.cpp:105] Iteration 15200, lr = 0.001
I0708 03:07:03.624310 99468 solver.cpp:218] Iteration 15240 (0.524558 iter/s, 76.2547s/40 iters), loss = 3.75252
I0708 03:07:03.624528 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16681 (* 0.3 = 0.650042 loss)
I0708 03:07:03.624550 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14501 (* 0.3 = 0.643504 loss)
I0708 03:07:03.624570 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16062 (* 1 = 2.16062 loss)
I0708 03:07:03.624586 99468 sgd_solver.cpp:105] Iteration 15240, lr = 0.001
I0708 03:08:19.975572 99468 solver.cpp:218] Iteration 15280 (0.523925 iter/s, 76.3468s/40 iters), loss = 3.72949
I0708 03:08:19.975793 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.61928 (* 0.3 = 0.785783 loss)
I0708 03:08:19.975816 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62261 (* 0.3 = 0.786783 loss)
I0708 03:08:19.975831 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62483 (* 1 = 2.62483 loss)
I0708 03:08:19.975848 99468 sgd_solver.cpp:105] Iteration 15280, lr = 0.001
I0708 03:09:36.551146 99468 solver.cpp:218] Iteration 15320 (0.522379 iter/s, 76.5728s/40 iters), loss = 3.73299
I0708 03:09:36.551365 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32771 (* 0.3 = 0.698314 loss)
I0708 03:09:36.551389 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33453 (* 0.3 = 0.700358 loss)
I0708 03:09:36.551403 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33507 (* 1 = 2.33507 loss)
I0708 03:09:36.551424 99468 sgd_solver.cpp:105] Iteration 15320, lr = 0.001
I0708 03:10:53.077584 99468 solver.cpp:218] Iteration 15360 (0.522714 iter/s, 76.5237s/40 iters), loss = 3.73733
I0708 03:10:53.077818 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40955 (* 0.3 = 0.722864 loss)
I0708 03:10:53.077847 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40715 (* 0.3 = 0.722144 loss)
I0708 03:10:53.077898 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41929 (* 1 = 2.41929 loss)
I0708 03:10:53.077914 99468 sgd_solver.cpp:105] Iteration 15360, lr = 0.001
I0708 03:12:09.636078 99468 solver.cpp:218] Iteration 15400 (0.522495 iter/s, 76.5557s/40 iters), loss = 3.72358
I0708 03:12:09.636313 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24356 (* 0.3 = 0.673069 loss)
I0708 03:12:09.636335 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24287 (* 0.3 = 0.67286 loss)
I0708 03:12:09.636391 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24731 (* 1 = 2.24731 loss)
I0708 03:12:09.636407 99468 sgd_solver.cpp:105] Iteration 15400, lr = 0.001
I0708 03:13:26.146869 99468 solver.cpp:218] Iteration 15440 (0.522821 iter/s, 76.508s/40 iters), loss = 3.63618
I0708 03:13:26.147092 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23343 (* 0.3 = 0.67003 loss)
I0708 03:13:26.147150 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2398 (* 0.3 = 0.671939 loss)
I0708 03:13:26.147169 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23885 (* 1 = 2.23885 loss)
I0708 03:13:26.147184 99468 sgd_solver.cpp:105] Iteration 15440, lr = 0.001
I0708 03:14:42.489344 99468 solver.cpp:218] Iteration 15480 (0.523974 iter/s, 76.3397s/40 iters), loss = 3.6944
I0708 03:14:42.489606 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45509 (* 0.3 = 0.736527 loss)
I0708 03:14:42.489665 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46626 (* 0.3 = 0.739879 loss)
I0708 03:14:42.489678 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45407 (* 1 = 2.45407 loss)
I0708 03:14:42.489703 99468 sgd_solver.cpp:105] Iteration 15480, lr = 0.001
I0708 03:15:58.782008 99468 solver.cpp:218] Iteration 15520 (0.524316 iter/s, 76.2899s/40 iters), loss = 3.70008
I0708 03:15:58.782236 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30209 (* 0.3 = 0.690627 loss)
I0708 03:15:58.782256 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27981 (* 0.3 = 0.683942 loss)
I0708 03:15:58.782274 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29031 (* 1 = 2.29031 loss)
I0708 03:15:58.782290 99468 sgd_solver.cpp:105] Iteration 15520, lr = 0.001
I0708 03:17:15.044977 99468 solver.cpp:218] Iteration 15560 (0.52452 iter/s, 76.2602s/40 iters), loss = 3.66979
I0708 03:17:15.045207 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14213 (* 0.3 = 0.64264 loss)
I0708 03:17:15.045228 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14373 (* 0.3 = 0.643119 loss)
I0708 03:17:15.045244 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12748 (* 1 = 2.12748 loss)
I0708 03:17:15.045261 99468 sgd_solver.cpp:105] Iteration 15560, lr = 0.001
I0708 03:18:31.592542 99468 solver.cpp:218] Iteration 15600 (0.52257 iter/s, 76.5448s/40 iters), loss = 3.64701
I0708 03:18:31.592762 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12937 (* 0.3 = 0.638811 loss)
I0708 03:18:31.592783 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15259 (* 0.3 = 0.645778 loss)
I0708 03:18:31.592797 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13233 (* 1 = 2.13233 loss)
I0708 03:18:31.592818 99468 sgd_solver.cpp:105] Iteration 15600, lr = 0.001
I0708 03:19:48.138952 99468 solver.cpp:218] Iteration 15640 (0.522578 iter/s, 76.5437s/40 iters), loss = 3.71547
I0708 03:19:48.139171 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28058 (* 0.3 = 0.684175 loss)
I0708 03:19:48.139227 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30856 (* 0.3 = 0.692568 loss)
I0708 03:19:48.139258 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30174 (* 1 = 2.30174 loss)
I0708 03:19:48.139276 99468 sgd_solver.cpp:105] Iteration 15640, lr = 0.001
I0708 03:21:04.678055 99468 solver.cpp:218] Iteration 15680 (0.522627 iter/s, 76.5364s/40 iters), loss = 3.65016
I0708 03:21:04.678277 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25691 (* 0.3 = 0.677072 loss)
I0708 03:21:04.678297 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28411 (* 0.3 = 0.685232 loss)
I0708 03:21:04.678313 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27719 (* 1 = 2.27719 loss)
I0708 03:21:04.678329 99468 sgd_solver.cpp:105] Iteration 15680, lr = 0.001
I0708 03:22:21.199558 99468 solver.cpp:218] Iteration 15720 (0.522748 iter/s, 76.5188s/40 iters), loss = 3.68423
I0708 03:22:21.199784 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39765 (* 0.3 = 0.719295 loss)
I0708 03:22:21.199841 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39416 (* 0.3 = 0.718248 loss)
I0708 03:22:21.199856 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38866 (* 1 = 2.38866 loss)
I0708 03:22:21.199872 99468 sgd_solver.cpp:105] Iteration 15720, lr = 0.001
I0708 03:23:37.750113 99468 solver.cpp:218] Iteration 15760 (0.522562 iter/s, 76.546s/40 iters), loss = 3.679
I0708 03:23:37.750335 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34305 (* 0.3 = 0.702916 loss)
I0708 03:23:37.750389 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32727 (* 0.3 = 0.69818 loss)
I0708 03:23:37.750408 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34474 (* 1 = 2.34474 loss)
I0708 03:23:37.750443 99468 sgd_solver.cpp:105] Iteration 15760, lr = 0.001
I0708 03:24:54.025420 99468 solver.cpp:218] Iteration 15800 (0.524435 iter/s, 76.2726s/40 iters), loss = 3.71105
I0708 03:24:54.025707 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38569 (* 0.3 = 0.715708 loss)
I0708 03:24:54.025730 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41608 (* 0.3 = 0.724825 loss)
I0708 03:24:54.025744 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40093 (* 1 = 2.40093 loss)
I0708 03:24:54.025763 99468 sgd_solver.cpp:105] Iteration 15800, lr = 0.001
I0708 03:26:10.278522 99468 solver.cpp:218] Iteration 15840 (0.524588 iter/s, 76.2503s/40 iters), loss = 3.65182
I0708 03:26:10.278749 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06998 (* 0.3 = 0.620994 loss)
I0708 03:26:10.278770 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.06312 (* 0.3 = 0.618935 loss)
I0708 03:26:10.278784 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07631 (* 1 = 2.07631 loss)
I0708 03:26:10.278800 99468 sgd_solver.cpp:105] Iteration 15840, lr = 0.001
I0708 03:27:26.586932 99468 solver.cpp:218] Iteration 15880 (0.524207 iter/s, 76.3057s/40 iters), loss = 3.71934
I0708 03:27:26.587158 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21864 (* 0.3 = 0.665593 loss)
I0708 03:27:26.587185 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.191 (* 0.3 = 0.657299 loss)
I0708 03:27:26.587199 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19436 (* 1 = 2.19436 loss)
I0708 03:27:26.587216 99468 sgd_solver.cpp:105] Iteration 15880, lr = 0.001
I0708 03:28:43.103993 99468 solver.cpp:218] Iteration 15920 (0.522778 iter/s, 76.5143s/40 iters), loss = 3.66238
I0708 03:28:43.104215 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35649 (* 0.3 = 0.706947 loss)
I0708 03:28:43.104234 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35739 (* 0.3 = 0.707218 loss)
I0708 03:28:43.104249 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34826 (* 1 = 2.34826 loss)
I0708 03:28:43.104269 99468 sgd_solver.cpp:105] Iteration 15920, lr = 0.001
I0708 03:29:59.590392 99468 solver.cpp:218] Iteration 15960 (0.522988 iter/s, 76.4837s/40 iters), loss = 3.67433
I0708 03:29:59.590790 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29182 (* 0.3 = 0.687545 loss)
I0708 03:29:59.590812 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30159 (* 0.3 = 0.690478 loss)
I0708 03:29:59.590827 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2986 (* 1 = 2.2986 loss)
I0708 03:29:59.590844 99468 sgd_solver.cpp:105] Iteration 15960, lr = 0.001
I0708 03:31:13.662199 99468 solver.cpp:330] Iteration 16000, Testing net (#0)
I0708 03:41:32.967558 99629 data_layer.cpp:73] Restarting data prefetching from start.
I0708 03:41:48.581465 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07389 (* 0.3 = 0.622168 loss)
I0708 03:41:48.581538 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.367387
I0708 03:41:48.581562 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794255
I0708 03:41:48.581583 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.074 (* 0.3 = 0.622199 loss)
I0708 03:41:48.581598 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.367387
I0708 03:41:48.581609 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794255
I0708 03:41:48.581625 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.072 (* 1 = 2.072 loss)
I0708 03:41:48.581636 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.367387
I0708 03:41:48.581706 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794255
I0708 03:41:50.482024 99468 solver.cpp:218] Iteration 16000 (0.0562692 iter/s, 710.868s/40 iters), loss = 3.68001
I0708 03:41:50.482132 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29994 (* 0.3 = 0.689982 loss)
I0708 03:41:50.482193 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32513 (* 0.3 = 0.69754 loss)
I0708 03:41:50.482228 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31013 (* 1 = 2.31013 loss)
I0708 03:41:50.482244 99468 sgd_solver.cpp:105] Iteration 16000, lr = 0.001
I0708 03:43:07.043298 99468 solver.cpp:218] Iteration 16040 (0.522475 iter/s, 76.5586s/40 iters), loss = 3.7146
I0708 03:43:07.043594 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52988 (* 0.3 = 0.758965 loss)
I0708 03:43:07.043625 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53516 (* 0.3 = 0.760547 loss)
I0708 03:43:07.043642 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52037 (* 1 = 2.52037 loss)
I0708 03:43:07.043663 99468 sgd_solver.cpp:105] Iteration 16040, lr = 0.001
I0708 03:44:23.617813 99468 solver.cpp:218] Iteration 16080 (0.522386 iter/s, 76.5717s/40 iters), loss = 3.72902
I0708 03:44:23.618065 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33011 (* 0.3 = 0.699034 loss)
I0708 03:44:23.618088 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33567 (* 0.3 = 0.700702 loss)
I0708 03:44:23.618103 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32803 (* 1 = 2.32803 loss)
I0708 03:44:23.618119 99468 sgd_solver.cpp:105] Iteration 16080, lr = 0.001
I0708 03:45:40.156621 99468 solver.cpp:218] Iteration 16120 (0.52263 iter/s, 76.536s/40 iters), loss = 3.71507
I0708 03:45:40.156847 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37757 (* 0.3 = 0.713271 loss)
I0708 03:45:40.156868 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37464 (* 0.3 = 0.712391 loss)
I0708 03:45:40.156883 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38109 (* 1 = 2.38109 loss)
I0708 03:45:40.156898 99468 sgd_solver.cpp:105] Iteration 16120, lr = 0.001
I0708 03:46:56.722087 99468 solver.cpp:218] Iteration 16160 (0.522448 iter/s, 76.5627s/40 iters), loss = 3.70425
I0708 03:46:56.722312 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27515 (* 0.3 = 0.682544 loss)
I0708 03:46:56.722334 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28084 (* 0.3 = 0.684251 loss)
I0708 03:46:56.722348 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26805 (* 1 = 2.26805 loss)
I0708 03:46:56.722364 99468 sgd_solver.cpp:105] Iteration 16160, lr = 0.001
I0708 03:48:13.018779 99468 solver.cpp:218] Iteration 16200 (0.524288 iter/s, 76.294s/40 iters), loss = 3.75464
I0708 03:48:13.019001 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4036 (* 0.3 = 0.721081 loss)
I0708 03:48:13.019021 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3907 (* 0.3 = 0.717209 loss)
I0708 03:48:13.019033 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38446 (* 1 = 2.38446 loss)
I0708 03:48:13.019053 99468 sgd_solver.cpp:105] Iteration 16200, lr = 0.001
I0708 03:49:29.581269 99468 solver.cpp:218] Iteration 16240 (0.522468 iter/s, 76.5597s/40 iters), loss = 3.64442
I0708 03:49:29.581493 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33262 (* 0.3 = 0.699787 loss)
I0708 03:49:29.581516 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33693 (* 0.3 = 0.70108 loss)
I0708 03:49:29.581531 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31702 (* 1 = 2.31702 loss)
I0708 03:49:29.581547 99468 sgd_solver.cpp:105] Iteration 16240, lr = 0.001
I0708 03:50:46.133935 99468 solver.cpp:218] Iteration 16280 (0.522535 iter/s, 76.5499s/40 iters), loss = 3.70539
I0708 03:50:46.134171 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.03732 (* 0.3 = 0.611195 loss)
I0708 03:50:46.134198 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00849 (* 0.3 = 0.602546 loss)
I0708 03:50:46.134263 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03039 (* 1 = 2.03039 loss)
I0708 03:50:46.134280 99468 sgd_solver.cpp:105] Iteration 16280, lr = 0.001
I0708 03:52:02.670518 99468 solver.cpp:218] Iteration 16320 (0.522645 iter/s, 76.5338s/40 iters), loss = 3.74057
I0708 03:52:02.670792 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54426 (* 0.3 = 0.763279 loss)
I0708 03:52:02.670857 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55293 (* 0.3 = 0.765879 loss)
I0708 03:52:02.670871 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.54275 (* 1 = 2.54275 loss)
I0708 03:52:02.670891 99468 sgd_solver.cpp:105] Iteration 16320, lr = 0.001
I0708 03:53:18.907210 99468 solver.cpp:218] Iteration 16360 (0.524701 iter/s, 76.2339s/40 iters), loss = 3.68575
I0708 03:53:18.907435 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37808 (* 0.3 = 0.713425 loss)
I0708 03:53:18.907457 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36541 (* 0.3 = 0.709623 loss)
I0708 03:53:18.907474 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36151 (* 1 = 2.36151 loss)
I0708 03:53:18.907488 99468 sgd_solver.cpp:105] Iteration 16360, lr = 0.001
I0708 03:54:35.270506 99468 solver.cpp:218] Iteration 16400 (0.523831 iter/s, 76.3605s/40 iters), loss = 3.69553
I0708 03:54:35.270730 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02796 (* 0.3 = 0.608387 loss)
I0708 03:54:35.270752 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.02914 (* 0.3 = 0.608742 loss)
I0708 03:54:35.270768 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03466 (* 1 = 2.03466 loss)
I0708 03:54:35.270786 99468 sgd_solver.cpp:105] Iteration 16400, lr = 0.001
I0708 03:55:51.850392 99468 solver.cpp:218] Iteration 16440 (0.522349 iter/s, 76.5771s/40 iters), loss = 3.75933
I0708 03:55:51.850738 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36708 (* 0.3 = 0.710124 loss)
I0708 03:55:51.850797 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34496 (* 0.3 = 0.703488 loss)
I0708 03:55:51.850811 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35578 (* 1 = 2.35578 loss)
I0708 03:55:51.850831 99468 sgd_solver.cpp:105] Iteration 16440, lr = 0.001
I0708 03:57:08.403717 99468 solver.cpp:218] Iteration 16480 (0.522531 iter/s, 76.5505s/40 iters), loss = 3.67606
I0708 03:57:08.403939 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44261 (* 0.3 = 0.732784 loss)
I0708 03:57:08.403959 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44321 (* 0.3 = 0.732964 loss)
I0708 03:57:08.403973 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44404 (* 1 = 2.44404 loss)
I0708 03:57:08.404023 99468 sgd_solver.cpp:105] Iteration 16480, lr = 0.001
I0708 03:58:24.968639 99468 solver.cpp:218] Iteration 16520 (0.522451 iter/s, 76.5622s/40 iters), loss = 3.75407
I0708 03:58:24.968852 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29432 (* 0.3 = 0.688295 loss)
I0708 03:58:24.968907 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28964 (* 0.3 = 0.686891 loss)
I0708 03:58:24.968925 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2831 (* 1 = 2.2831 loss)
I0708 03:58:24.968958 99468 sgd_solver.cpp:105] Iteration 16520, lr = 0.001
I0708 03:59:41.449905 99468 solver.cpp:218] Iteration 16560 (0.523023 iter/s, 76.4785s/40 iters), loss = 3.73521
I0708 03:59:41.450136 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38282 (* 0.3 = 0.714846 loss)
I0708 03:59:41.450192 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36392 (* 0.3 = 0.709176 loss)
I0708 03:59:41.450207 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38721 (* 1 = 2.38721 loss)
I0708 03:59:41.450224 99468 sgd_solver.cpp:105] Iteration 16560, lr = 0.001
I0708 04:00:57.863229 99468 solver.cpp:218] Iteration 16600 (0.523488 iter/s, 76.4106s/40 iters), loss = 3.69648
I0708 04:00:57.863466 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41866 (* 0.3 = 0.725597 loss)
I0708 04:00:57.863485 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40798 (* 0.3 = 0.722395 loss)
I0708 04:00:57.863500 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42687 (* 1 = 2.42687 loss)
I0708 04:00:57.863521 99468 sgd_solver.cpp:105] Iteration 16600, lr = 0.001
I0708 04:02:14.429119 99468 solver.cpp:218] Iteration 16640 (0.522445 iter/s, 76.5631s/40 iters), loss = 3.65591
I0708 04:02:14.429388 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1317 (* 0.3 = 0.63951 loss)
I0708 04:02:14.429409 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12952 (* 0.3 = 0.638856 loss)
I0708 04:02:14.429425 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1326 (* 1 = 2.1326 loss)
I0708 04:02:14.429441 99468 sgd_solver.cpp:105] Iteration 16640, lr = 0.001
I0708 04:03:30.959599 99468 solver.cpp:218] Iteration 16680 (0.522687 iter/s, 76.5277s/40 iters), loss = 3.68341
I0708 04:03:30.959825 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59361 (* 0.3 = 0.778082 loss)
I0708 04:03:30.959846 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57616 (* 0.3 = 0.772849 loss)
I0708 04:03:30.959861 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.57706 (* 1 = 2.57706 loss)
I0708 04:03:30.959877 99468 sgd_solver.cpp:105] Iteration 16680, lr = 0.001
I0708 04:04:47.451593 99468 solver.cpp:218] Iteration 16720 (0.522949 iter/s, 76.4892s/40 iters), loss = 3.69839
I0708 04:04:47.451824 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55305 (* 0.3 = 0.765915 loss)
I0708 04:04:47.451848 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5488 (* 0.3 = 0.76464 loss)
I0708 04:04:47.451863 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55196 (* 1 = 2.55196 loss)
I0708 04:04:47.451880 99468 sgd_solver.cpp:105] Iteration 16720, lr = 0.001
I0708 04:06:03.656850 99468 solver.cpp:218] Iteration 16760 (0.524917 iter/s, 76.2025s/40 iters), loss = 3.73685
I0708 04:06:03.657073 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42491 (* 0.3 = 0.727473 loss)
I0708 04:06:03.657133 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43623 (* 0.3 = 0.73087 loss)
I0708 04:06:03.657150 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42959 (* 1 = 2.42959 loss)
I0708 04:06:03.657166 99468 sgd_solver.cpp:105] Iteration 16760, lr = 0.001
I0708 04:07:19.925777 99468 solver.cpp:218] Iteration 16800 (0.524479 iter/s, 76.2662s/40 iters), loss = 3.74294
I0708 04:07:19.926004 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26336 (* 0.3 = 0.679007 loss)
I0708 04:07:19.926025 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23149 (* 0.3 = 0.669446 loss)
I0708 04:07:19.926039 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23897 (* 1 = 2.23897 loss)
I0708 04:07:19.926059 99468 sgd_solver.cpp:105] Iteration 16800, lr = 0.001
I0708 04:08:36.493599 99468 solver.cpp:218] Iteration 16840 (0.522431 iter/s, 76.5651s/40 iters), loss = 3.75281
I0708 04:08:36.493814 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24052 (* 0.3 = 0.672156 loss)
I0708 04:08:36.493836 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25746 (* 0.3 = 0.677239 loss)
I0708 04:08:36.493851 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24702 (* 1 = 2.24702 loss)
I0708 04:08:36.493868 99468 sgd_solver.cpp:105] Iteration 16840, lr = 0.001
I0708 04:09:53.044935 99468 solver.cpp:218] Iteration 16880 (0.522544 iter/s, 76.5486s/40 iters), loss = 3.67328
I0708 04:09:53.045166 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23634 (* 0.3 = 0.670902 loss)
I0708 04:09:53.045191 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2559 (* 0.3 = 0.676769 loss)
I0708 04:09:53.045248 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24117 (* 1 = 2.24117 loss)
I0708 04:09:53.045267 99468 sgd_solver.cpp:105] Iteration 16880, lr = 0.001
I0708 04:11:09.638296 99468 solver.cpp:218] Iteration 16920 (0.522257 iter/s, 76.5906s/40 iters), loss = 3.69218
I0708 04:11:09.638525 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30317 (* 0.3 = 0.690952 loss)
I0708 04:11:09.638545 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29051 (* 0.3 = 0.687152 loss)
I0708 04:11:09.638566 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30006 (* 1 = 2.30006 loss)
I0708 04:11:09.638583 99468 sgd_solver.cpp:105] Iteration 16920, lr = 0.001
I0708 04:12:26.038085 99468 solver.cpp:218] Iteration 16960 (0.52358 iter/s, 76.397s/40 iters), loss = 3.70852
I0708 04:12:26.038348 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48118 (* 0.3 = 0.744355 loss)
I0708 04:12:26.038408 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48129 (* 0.3 = 0.744387 loss)
I0708 04:12:26.038421 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48872 (* 1 = 2.48872 loss)
I0708 04:12:26.038455 99468 sgd_solver.cpp:105] Iteration 16960, lr = 0.001
I0708 04:13:42.373695 99468 solver.cpp:218] Iteration 17000 (0.524021 iter/s, 76.3328s/40 iters), loss = 3.74456
I0708 04:13:42.373920 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24771 (* 0.3 = 0.674314 loss)
I0708 04:13:42.373942 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24375 (* 0.3 = 0.673126 loss)
I0708 04:13:42.373958 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22856 (* 1 = 2.22856 loss)
I0708 04:13:42.373975 99468 sgd_solver.cpp:105] Iteration 17000, lr = 0.001
I0708 04:14:58.915449 99468 solver.cpp:218] Iteration 17040 (0.522609 iter/s, 76.539s/40 iters), loss = 3.75894
I0708 04:14:58.915679 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24418 (* 0.3 = 0.673255 loss)
I0708 04:14:58.915701 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25716 (* 0.3 = 0.677149 loss)
I0708 04:14:58.915716 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25241 (* 1 = 2.25241 loss)
I0708 04:14:58.915733 99468 sgd_solver.cpp:105] Iteration 17040, lr = 0.001
I0708 04:16:15.463763 99468 solver.cpp:218] Iteration 17080 (0.522565 iter/s, 76.5456s/40 iters), loss = 3.69585
I0708 04:16:15.463985 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11551 (* 0.3 = 0.634653 loss)
I0708 04:16:15.464006 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13426 (* 0.3 = 0.640279 loss)
I0708 04:16:15.464020 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11772 (* 1 = 2.11772 loss)
I0708 04:16:15.464071 99468 sgd_solver.cpp:105] Iteration 17080, lr = 0.001
I0708 04:17:32.049207 99468 solver.cpp:218] Iteration 17120 (0.522311 iter/s, 76.5827s/40 iters), loss = 3.74444
I0708 04:17:32.049425 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25299 (* 0.3 = 0.675898 loss)
I0708 04:17:32.049446 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29184 (* 0.3 = 0.687553 loss)
I0708 04:17:32.049460 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26298 (* 1 = 2.26298 loss)
I0708 04:17:32.049476 99468 sgd_solver.cpp:105] Iteration 17120, lr = 0.001
I0708 04:18:48.618680 99468 solver.cpp:218] Iteration 17160 (0.52242 iter/s, 76.5667s/40 iters), loss = 3.69704
I0708 04:18:48.618912 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25381 (* 0.3 = 0.676143 loss)
I0708 04:18:48.618934 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23319 (* 0.3 = 0.669957 loss)
I0708 04:18:48.618949 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24543 (* 1 = 2.24543 loss)
I0708 04:18:48.618966 99468 sgd_solver.cpp:105] Iteration 17160, lr = 0.001
I0708 04:20:05.157752 99468 solver.cpp:218] Iteration 17200 (0.522628 iter/s, 76.5363s/40 iters), loss = 3.70968
I0708 04:20:05.157980 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06185 (* 0.3 = 0.618555 loss)
I0708 04:20:05.158004 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04995 (* 0.3 = 0.614984 loss)
I0708 04:20:05.158017 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04671 (* 1 = 2.04671 loss)
I0708 04:20:05.158032 99468 sgd_solver.cpp:105] Iteration 17200, lr = 0.001
I0708 04:21:21.683820 99468 solver.cpp:218] Iteration 17240 (0.522716 iter/s, 76.5233s/40 iters), loss = 3.71227
I0708 04:21:21.684042 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43241 (* 0.3 = 0.729724 loss)
I0708 04:21:21.684064 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4491 (* 0.3 = 0.734729 loss)
I0708 04:21:21.684078 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43129 (* 1 = 2.43129 loss)
I0708 04:21:21.684096 99468 sgd_solver.cpp:105] Iteration 17240, lr = 0.001
I0708 04:22:38.032014 99468 solver.cpp:218] Iteration 17280 (0.523934 iter/s, 76.3455s/40 iters), loss = 3.67221
I0708 04:22:38.032260 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10019 (* 0.3 = 0.630057 loss)
I0708 04:22:38.032285 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11347 (* 0.3 = 0.634042 loss)
I0708 04:22:38.032299 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10589 (* 1 = 2.10589 loss)
I0708 04:22:38.032346 99468 sgd_solver.cpp:105] Iteration 17280, lr = 0.001
I0708 04:23:54.277207 99468 solver.cpp:218] Iteration 17320 (0.524642 iter/s, 76.2424s/40 iters), loss = 3.67986
I0708 04:23:54.277878 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14213 (* 0.3 = 0.642639 loss)
I0708 04:23:54.277900 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12986 (* 0.3 = 0.638959 loss)
I0708 04:23:54.277954 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14318 (* 1 = 2.14318 loss)
I0708 04:23:54.277981 99468 sgd_solver.cpp:105] Iteration 17320, lr = 0.001
I0708 04:25:10.635346 99468 solver.cpp:218] Iteration 17360 (0.523869 iter/s, 76.3549s/40 iters), loss = 3.719
I0708 04:25:10.635578 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3627 (* 0.3 = 0.708809 loss)
I0708 04:25:10.635630 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35339 (* 0.3 = 0.706016 loss)
I0708 04:25:10.635645 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36178 (* 1 = 2.36178 loss)
I0708 04:25:10.635661 99468 sgd_solver.cpp:105] Iteration 17360, lr = 0.001
I0708 04:26:27.197113 99468 solver.cpp:218] Iteration 17400 (0.522473 iter/s, 76.559s/40 iters), loss = 3.72073
I0708 04:26:27.197336 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27332 (* 0.3 = 0.681996 loss)
I0708 04:26:27.197389 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26585 (* 0.3 = 0.679755 loss)
I0708 04:26:27.197404 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26874 (* 1 = 2.26874 loss)
I0708 04:26:27.197423 99468 sgd_solver.cpp:105] Iteration 17400, lr = 0.001
I0708 04:27:43.796964 99468 solver.cpp:218] Iteration 17440 (0.522224 iter/s, 76.5955s/40 iters), loss = 3.73454
I0708 04:27:43.797183 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15258 (* 0.3 = 0.645774 loss)
I0708 04:27:43.797242 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12027 (* 0.3 = 0.636082 loss)
I0708 04:27:43.797260 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13582 (* 1 = 2.13582 loss)
I0708 04:27:43.797277 99468 sgd_solver.cpp:105] Iteration 17440, lr = 0.001
I0708 04:29:00.337152 99468 solver.cpp:218] Iteration 17480 (0.52262 iter/s, 76.5374s/40 iters), loss = 3.67683
I0708 04:29:00.337378 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59965 (* 0.3 = 0.779894 loss)
I0708 04:29:00.337399 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59945 (* 0.3 = 0.779836 loss)
I0708 04:29:00.337412 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.58137 (* 1 = 2.58137 loss)
I0708 04:29:00.337432 99468 sgd_solver.cpp:105] Iteration 17480, lr = 0.001
I0708 04:30:16.813450 99468 solver.cpp:218] Iteration 17520 (0.523057 iter/s, 76.4735s/40 iters), loss = 3.68201
I0708 04:30:16.813676 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32374 (* 0.3 = 0.697122 loss)
I0708 04:30:16.813699 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30637 (* 0.3 = 0.69191 loss)
I0708 04:30:16.813714 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32141 (* 1 = 2.32141 loss)
I0708 04:30:16.813730 99468 sgd_solver.cpp:105] Iteration 17520, lr = 0.001
I0708 04:31:33.346319 99468 solver.cpp:218] Iteration 17560 (0.52267 iter/s, 76.5301s/40 iters), loss = 3.7177
I0708 04:31:33.346593 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.163 (* 0.3 = 0.648899 loss)
I0708 04:31:33.346621 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14898 (* 0.3 = 0.644694 loss)
I0708 04:31:33.346635 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15091 (* 1 = 2.15091 loss)
I0708 04:31:33.346652 99468 sgd_solver.cpp:105] Iteration 17560, lr = 0.001
I0708 04:32:49.892427 99468 solver.cpp:218] Iteration 17600 (0.52258 iter/s, 76.5433s/40 iters), loss = 3.67585
I0708 04:32:49.892684 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2647 (* 0.3 = 0.679409 loss)
I0708 04:32:49.892705 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28681 (* 0.3 = 0.686043 loss)
I0708 04:32:49.892719 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27655 (* 1 = 2.27655 loss)
I0708 04:32:49.892738 99468 sgd_solver.cpp:105] Iteration 17600, lr = 0.001
I0708 04:34:06.449285 99468 solver.cpp:218] Iteration 17640 (0.522507 iter/s, 76.5541s/40 iters), loss = 3.73789
I0708 04:34:06.449509 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50235 (* 0.3 = 0.750704 loss)
I0708 04:34:06.449530 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51071 (* 0.3 = 0.753214 loss)
I0708 04:34:06.449544 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50983 (* 1 = 2.50983 loss)
I0708 04:34:06.449568 99468 sgd_solver.cpp:105] Iteration 17640, lr = 0.001
I0708 04:35:22.913178 99468 solver.cpp:218] Iteration 17680 (0.523142 iter/s, 76.4612s/40 iters), loss = 3.6723
I0708 04:35:22.913398 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02183 (* 0.3 = 0.606549 loss)
I0708 04:35:22.913419 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.036 (* 0.3 = 0.610799 loss)
I0708 04:35:22.913436 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03839 (* 1 = 2.03839 loss)
I0708 04:35:22.913452 99468 sgd_solver.cpp:105] Iteration 17680, lr = 0.001
I0708 04:36:39.456610 99468 solver.cpp:218] Iteration 17720 (0.522598 iter/s, 76.5407s/40 iters), loss = 3.74007
I0708 04:36:39.456825 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15918 (* 0.3 = 0.647754 loss)
I0708 04:36:39.456848 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15824 (* 0.3 = 0.647471 loss)
I0708 04:36:39.456897 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15707 (* 1 = 2.15707 loss)
I0708 04:36:39.456914 99468 sgd_solver.cpp:105] Iteration 17720, lr = 0.001
I0708 04:37:55.991513 99468 solver.cpp:218] Iteration 17760 (0.522656 iter/s, 76.5322s/40 iters), loss = 3.69701
I0708 04:37:55.991735 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4372 (* 0.3 = 0.731161 loss)
I0708 04:37:55.991791 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41678 (* 0.3 = 0.725035 loss)
I0708 04:37:55.991822 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40718 (* 1 = 2.40718 loss)
I0708 04:37:55.991840 99468 sgd_solver.cpp:105] Iteration 17760, lr = 0.001
I0708 04:39:12.527182 99468 solver.cpp:218] Iteration 17800 (0.522651 iter/s, 76.5329s/40 iters), loss = 3.71395
I0708 04:39:12.527403 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2597 (* 0.3 = 0.677909 loss)
I0708 04:39:12.527425 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26293 (* 0.3 = 0.678878 loss)
I0708 04:39:12.527473 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25546 (* 1 = 2.25546 loss)
I0708 04:39:12.527493 99468 sgd_solver.cpp:105] Iteration 17800, lr = 0.001
I0708 04:40:28.819797 99468 solver.cpp:218] Iteration 17840 (0.524316 iter/s, 76.2899s/40 iters), loss = 3.65272
I0708 04:40:28.820047 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28909 (* 0.3 = 0.686726 loss)
I0708 04:40:28.820075 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31931 (* 0.3 = 0.695794 loss)
I0708 04:40:28.820094 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29505 (* 1 = 2.29505 loss)
I0708 04:40:28.820152 99468 sgd_solver.cpp:105] Iteration 17840, lr = 0.001
I0708 04:41:45.300763 99468 solver.cpp:218] Iteration 17880 (0.523025 iter/s, 76.4782s/40 iters), loss = 3.6221
I0708 04:41:45.301110 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36477 (* 0.3 = 0.70943 loss)
I0708 04:41:45.301132 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38656 (* 0.3 = 0.715969 loss)
I0708 04:41:45.301146 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37502 (* 1 = 2.37502 loss)
I0708 04:41:45.301162 99468 sgd_solver.cpp:105] Iteration 17880, lr = 0.001
I0708 04:43:01.619724 99468 solver.cpp:218] Iteration 17920 (0.524136 iter/s, 76.3161s/40 iters), loss = 3.68867
I0708 04:43:01.619940 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2467 (* 0.3 = 0.67401 loss)
I0708 04:43:01.619957 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25343 (* 0.3 = 0.67603 loss)
I0708 04:43:01.619971 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23138 (* 1 = 2.23138 loss)
I0708 04:43:01.619990 99468 sgd_solver.cpp:105] Iteration 17920, lr = 0.001
I0708 04:44:18.197798 99468 solver.cpp:218] Iteration 17960 (0.522361 iter/s, 76.5753s/40 iters), loss = 3.72177
I0708 04:44:18.198022 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9996 (* 0.3 = 0.599879 loss)
I0708 04:44:18.198086 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.9847 (* 0.3 = 0.59541 loss)
I0708 04:44:18.198101 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99257 (* 1 = 1.99257 loss)
I0708 04:44:18.198117 99468 sgd_solver.cpp:105] Iteration 17960, lr = 0.001
I0708 04:45:34.589701 99468 solver.cpp:218] Iteration 18000 (0.523634 iter/s, 76.3892s/40 iters), loss = 3.69983
I0708 04:45:34.589926 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34738 (* 0.3 = 0.704213 loss)
I0708 04:45:34.589951 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34279 (* 0.3 = 0.702836 loss)
I0708 04:45:34.589969 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34286 (* 1 = 2.34286 loss)
I0708 04:45:34.589984 99468 sgd_solver.cpp:105] Iteration 18000, lr = 0.001
I0708 04:46:51.146178 99468 solver.cpp:218] Iteration 18040 (0.522509 iter/s, 76.5537s/40 iters), loss = 3.66994
I0708 04:46:51.146404 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26805 (* 0.3 = 0.680414 loss)
I0708 04:46:51.146425 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26342 (* 0.3 = 0.679025 loss)
I0708 04:46:51.146442 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25905 (* 1 = 2.25905 loss)
I0708 04:46:51.146457 99468 sgd_solver.cpp:105] Iteration 18040, lr = 0.001
I0708 04:48:07.452177 99468 solver.cpp:218] Iteration 18080 (0.524224 iter/s, 76.3033s/40 iters), loss = 3.75632
I0708 04:48:07.452409 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22616 (* 0.3 = 0.667847 loss)
I0708 04:48:07.452478 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21164 (* 0.3 = 0.663491 loss)
I0708 04:48:07.452492 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20786 (* 1 = 2.20786 loss)
I0708 04:48:07.452524 99468 sgd_solver.cpp:105] Iteration 18080, lr = 0.001
I0708 04:49:23.681176 99468 solver.cpp:218] Iteration 18120 (0.524754 iter/s, 76.2262s/40 iters), loss = 3.69678
I0708 04:49:23.681403 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.93283 (* 0.3 = 0.579849 loss)
I0708 04:49:23.681427 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.91715 (* 0.3 = 0.575144 loss)
I0708 04:49:23.681443 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.95118 (* 1 = 1.95118 loss)
I0708 04:49:23.681460 99468 sgd_solver.cpp:105] Iteration 18120, lr = 0.001
I0708 04:50:39.967020 99468 solver.cpp:218] Iteration 18160 (0.524363 iter/s, 76.2831s/40 iters), loss = 3.72547
I0708 04:50:39.967295 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.92205 (* 0.3 = 0.576614 loss)
I0708 04:50:39.967319 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.91829 (* 0.3 = 0.575486 loss)
I0708 04:50:39.967339 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.91426 (* 1 = 1.91426 loss)
I0708 04:50:39.967353 99468 sgd_solver.cpp:105] Iteration 18160, lr = 0.001
I0708 04:51:56.416352 99468 solver.cpp:218] Iteration 18200 (0.523241 iter/s, 76.4465s/40 iters), loss = 3.71078
I0708 04:51:56.416645 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22659 (* 0.3 = 0.667978 loss)
I0708 04:51:56.416667 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.239 (* 0.3 = 0.671701 loss)
I0708 04:51:56.416682 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22386 (* 1 = 2.22386 loss)
I0708 04:51:56.416738 99468 sgd_solver.cpp:105] Iteration 18200, lr = 0.001
I0708 04:53:12.761548 99468 solver.cpp:218] Iteration 18240 (0.523955 iter/s, 76.3424s/40 iters), loss = 3.72904
I0708 04:53:12.761780 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.77704 (* 0.3 = 0.533112 loss)
I0708 04:53:12.761801 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.79499 (* 0.3 = 0.538498 loss)
I0708 04:53:12.761814 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.78235 (* 1 = 1.78235 loss)
I0708 04:53:12.761868 99468 sgd_solver.cpp:105] Iteration 18240, lr = 0.001
I0708 04:53:44.477233 99628 data_layer.cpp:73] Restarting data prefetching from start.
I0708 04:54:29.306694 99468 solver.cpp:218] Iteration 18280 (0.522586 iter/s, 76.5424s/40 iters), loss = 3.70691
I0708 04:54:29.306924 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65845 (* 0.3 = 0.797534 loss)
I0708 04:54:29.306953 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.68323 (* 0.3 = 0.80497 loss)
I0708 04:54:29.306967 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.67964 (* 1 = 2.67964 loss)
I0708 04:54:29.306984 99468 sgd_solver.cpp:105] Iteration 18280, lr = 0.001
I0708 04:55:45.843318 99468 solver.cpp:218] Iteration 18320 (0.522644 iter/s, 76.5339s/40 iters), loss = 3.69741
I0708 04:55:45.843538 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21231 (* 0.3 = 0.663694 loss)
I0708 04:55:45.843600 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22715 (* 0.3 = 0.668145 loss)
I0708 04:55:45.843613 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21692 (* 1 = 2.21692 loss)
I0708 04:55:45.843629 99468 sgd_solver.cpp:105] Iteration 18320, lr = 0.001
I0708 04:57:02.397047 99468 solver.cpp:218] Iteration 18360 (0.522528 iter/s, 76.551s/40 iters), loss = 3.69982
I0708 04:57:02.397285 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.49214 (* 0.3 = 0.747642 loss)
I0708 04:57:02.397306 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49499 (* 0.3 = 0.748498 loss)
I0708 04:57:02.397320 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49894 (* 1 = 2.49894 loss)
I0708 04:57:02.397337 99468 sgd_solver.cpp:105] Iteration 18360, lr = 0.001
I0708 04:58:18.935560 99468 solver.cpp:218] Iteration 18400 (0.522632 iter/s, 76.5357s/40 iters), loss = 3.71893
I0708 04:58:18.935792 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22541 (* 0.3 = 0.667622 loss)
I0708 04:58:18.935814 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21685 (* 0.3 = 0.665055 loss)
I0708 04:58:18.935829 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21623 (* 1 = 2.21623 loss)
I0708 04:58:18.935845 99468 sgd_solver.cpp:105] Iteration 18400, lr = 0.001
I0708 04:59:35.419881 99468 solver.cpp:218] Iteration 18440 (0.523002 iter/s, 76.4816s/40 iters), loss = 3.71248
I0708 04:59:35.420114 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11946 (* 0.3 = 0.635839 loss)
I0708 04:59:35.420136 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10951 (* 0.3 = 0.632854 loss)
I0708 04:59:35.420150 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1104 (* 1 = 2.1104 loss)
I0708 04:59:35.420202 99468 sgd_solver.cpp:105] Iteration 18440, lr = 0.001
I0708 05:00:51.907447 99468 solver.cpp:218] Iteration 18480 (0.52298 iter/s, 76.4848s/40 iters), loss = 3.69581
I0708 05:00:51.907773 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15991 (* 0.3 = 0.647972 loss)
I0708 05:00:51.907793 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18384 (* 0.3 = 0.655152 loss)
I0708 05:00:51.907809 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17552 (* 1 = 2.17552 loss)
I0708 05:00:51.907824 99468 sgd_solver.cpp:105] Iteration 18480, lr = 0.001
I0708 05:02:08.410185 99468 solver.cpp:218] Iteration 18520 (0.522877 iter/s, 76.4999s/40 iters), loss = 3.70353
I0708 05:02:08.410432 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52329 (* 0.3 = 0.756986 loss)
I0708 05:02:08.410498 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51567 (* 0.3 = 0.7547 loss)
I0708 05:02:08.410516 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51903 (* 1 = 2.51903 loss)
I0708 05:02:08.410531 99468 sgd_solver.cpp:105] Iteration 18520, lr = 0.001
I0708 05:03:24.907889 99468 solver.cpp:218] Iteration 18560 (0.52291 iter/s, 76.4949s/40 iters), loss = 3.72594
I0708 05:03:24.908113 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06473 (* 0.3 = 0.61942 loss)
I0708 05:03:24.908134 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.05455 (* 0.3 = 0.616365 loss)
I0708 05:03:24.908149 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.06717 (* 1 = 2.06717 loss)
I0708 05:03:24.908164 99468 sgd_solver.cpp:105] Iteration 18560, lr = 0.001
I0708 05:04:41.396843 99468 solver.cpp:218] Iteration 18600 (0.52297 iter/s, 76.4862s/40 iters), loss = 3.70966
I0708 05:04:41.397078 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37514 (* 0.3 = 0.712543 loss)
I0708 05:04:41.397101 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38398 (* 0.3 = 0.715195 loss)
I0708 05:04:41.397117 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38079 (* 1 = 2.38079 loss)
I0708 05:04:41.397136 99468 sgd_solver.cpp:105] Iteration 18600, lr = 0.001
I0708 05:05:57.886654 99468 solver.cpp:218] Iteration 18640 (0.522964 iter/s, 76.4871s/40 iters), loss = 3.65093
I0708 05:05:57.886878 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.68278 (* 0.3 = 0.804833 loss)
I0708 05:05:57.886899 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.67553 (* 0.3 = 0.802659 loss)
I0708 05:05:57.886912 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.67696 (* 1 = 2.67696 loss)
I0708 05:05:57.886973 99468 sgd_solver.cpp:105] Iteration 18640, lr = 0.001
I0708 05:07:14.391892 99468 solver.cpp:218] Iteration 18680 (0.522859 iter/s, 76.5025s/40 iters), loss = 3.74437
I0708 05:07:14.392124 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28032 (* 0.3 = 0.684097 loss)
I0708 05:07:14.392144 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26074 (* 0.3 = 0.678223 loss)
I0708 05:07:14.392200 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27276 (* 1 = 2.27276 loss)
I0708 05:07:14.392217 99468 sgd_solver.cpp:105] Iteration 18680, lr = 0.001
I0708 05:08:30.854496 99468 solver.cpp:218] Iteration 18720 (0.52315 iter/s, 76.4598s/40 iters), loss = 3.72219
I0708 05:08:30.854717 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37213 (* 0.3 = 0.71164 loss)
I0708 05:08:30.854771 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36442 (* 0.3 = 0.709327 loss)
I0708 05:08:30.854804 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36543 (* 1 = 2.36543 loss)
I0708 05:08:30.854822 99468 sgd_solver.cpp:105] Iteration 18720, lr = 0.001
I0708 05:09:47.388007 99468 solver.cpp:218] Iteration 18760 (0.522666 iter/s, 76.5308s/40 iters), loss = 3.70495
I0708 05:09:47.388259 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4617 (* 0.3 = 0.73851 loss)
I0708 05:09:47.388280 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49574 (* 0.3 = 0.748721 loss)
I0708 05:09:47.388294 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48184 (* 1 = 2.48184 loss)
I0708 05:09:47.388312 99468 sgd_solver.cpp:105] Iteration 18760, lr = 0.001
I0708 05:11:03.898156 99468 solver.cpp:218] Iteration 18800 (0.522825 iter/s, 76.5074s/40 iters), loss = 3.71483
I0708 05:11:03.898427 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.00814 (* 0.3 = 0.602442 loss)
I0708 05:11:03.898490 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.02489 (* 0.3 = 0.607468 loss)
I0708 05:11:03.898521 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02962 (* 1 = 2.02962 loss)
I0708 05:11:03.898538 99468 sgd_solver.cpp:105] Iteration 18800, lr = 0.001
I0708 05:12:20.319344 99468 solver.cpp:218] Iteration 18840 (0.523434 iter/s, 76.4184s/40 iters), loss = 3.76242
I0708 05:12:20.319584 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22649 (* 0.3 = 0.667947 loss)
I0708 05:12:20.319605 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23217 (* 0.3 = 0.669652 loss)
I0708 05:12:20.319622 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23813 (* 1 = 2.23813 loss)
I0708 05:12:20.319638 99468 sgd_solver.cpp:105] Iteration 18840, lr = 0.001
I0708 05:13:36.795485 99468 solver.cpp:218] Iteration 18880 (0.523058 iter/s, 76.4734s/40 iters), loss = 3.66804
I0708 05:13:36.795711 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17455 (* 0.3 = 0.652365 loss)
I0708 05:13:36.795732 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1623 (* 0.3 = 0.64869 loss)
I0708 05:13:36.795747 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16828 (* 1 = 2.16828 loss)
I0708 05:13:36.795763 99468 sgd_solver.cpp:105] Iteration 18880, lr = 0.001
I0708 05:14:53.315155 99468 solver.cpp:218] Iteration 18920 (0.52276 iter/s, 76.5169s/40 iters), loss = 3.71725
I0708 05:14:53.315367 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.63153 (* 0.3 = 0.78946 loss)
I0708 05:14:53.315388 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62615 (* 0.3 = 0.787846 loss)
I0708 05:14:53.315409 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.63592 (* 1 = 2.63592 loss)
I0708 05:14:53.315423 99468 sgd_solver.cpp:105] Iteration 18920, lr = 0.001
I0708 05:16:09.803198 99468 solver.cpp:218] Iteration 18960 (0.522976 iter/s, 76.4853s/40 iters), loss = 3.72744
I0708 05:16:09.803416 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20246 (* 0.3 = 0.660738 loss)
I0708 05:16:09.803434 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21276 (* 0.3 = 0.663828 loss)
I0708 05:16:09.803448 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2077 (* 1 = 2.2077 loss)
I0708 05:16:09.803500 99468 sgd_solver.cpp:105] Iteration 18960, lr = 0.001
I0708 05:17:26.243963 99468 solver.cpp:218] Iteration 19000 (0.5233 iter/s, 76.438s/40 iters), loss = 3.72772
I0708 05:17:26.244186 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30858 (* 0.3 = 0.692574 loss)
I0708 05:17:26.244207 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29126 (* 0.3 = 0.687379 loss)
I0708 05:17:26.244221 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3009 (* 1 = 2.3009 loss)
I0708 05:17:26.244242 99468 sgd_solver.cpp:105] Iteration 19000, lr = 0.001
I0708 05:18:42.577960 99468 solver.cpp:218] Iteration 19040 (0.524032 iter/s, 76.3313s/40 iters), loss = 3.74443
I0708 05:18:42.578184 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.96515 (* 0.3 = 0.589544 loss)
I0708 05:18:42.578205 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.98318 (* 0.3 = 0.594955 loss)
I0708 05:18:42.578219 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.9661 (* 1 = 1.9661 loss)
I0708 05:18:42.578236 99468 sgd_solver.cpp:105] Iteration 19040, lr = 0.001
I0708 05:19:58.899125 99468 solver.cpp:218] Iteration 19080 (0.52412 iter/s, 76.3184s/40 iters), loss = 3.68958
I0708 05:19:58.899353 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28437 (* 0.3 = 0.685311 loss)
I0708 05:19:58.899376 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2732 (* 0.3 = 0.681959 loss)
I0708 05:19:58.899390 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27974 (* 1 = 2.27974 loss)
I0708 05:19:58.899411 99468 sgd_solver.cpp:105] Iteration 19080, lr = 0.001
I0708 05:21:15.460760 99468 solver.cpp:218] Iteration 19120 (0.522474 iter/s, 76.5589s/40 iters), loss = 3.72172
I0708 05:21:15.461046 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33639 (* 0.3 = 0.700918 loss)
I0708 05:21:15.461068 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34773 (* 0.3 = 0.704318 loss)
I0708 05:21:15.461081 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35418 (* 1 = 2.35418 loss)
I0708 05:21:15.461100 99468 sgd_solver.cpp:105] Iteration 19120, lr = 0.001
I0708 05:22:31.999342 99468 solver.cpp:218] Iteration 19160 (0.522631 iter/s, 76.5358s/40 iters), loss = 3.74819
I0708 05:22:31.999603 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.80501 (* 0.3 = 0.841503 loss)
I0708 05:22:31.999675 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.78447 (* 0.3 = 0.835342 loss)
I0708 05:22:31.999689 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.787 (* 1 = 2.787 loss)
I0708 05:22:31.999706 99468 sgd_solver.cpp:105] Iteration 19160, lr = 0.001
I0708 05:23:48.499671 99468 solver.cpp:218] Iteration 19200 (0.522893 iter/s, 76.4975s/40 iters), loss = 3.69462
I0708 05:23:48.499888 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5678 (* 0.3 = 0.77034 loss)
I0708 05:23:48.499944 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58221 (* 0.3 = 0.774662 loss)
I0708 05:23:48.499959 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.57759 (* 1 = 2.57759 loss)
I0708 05:23:48.499976 99468 sgd_solver.cpp:105] Iteration 19200, lr = 0.001
I0708 05:25:04.942466 99468 solver.cpp:218] Iteration 19240 (0.523286 iter/s, 76.4401s/40 iters), loss = 3.67662
I0708 05:25:04.942698 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08343 (* 0.3 = 0.62503 loss)
I0708 05:25:04.942719 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10394 (* 0.3 = 0.631181 loss)
I0708 05:25:04.942734 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10186 (* 1 = 2.10186 loss)
I0708 05:25:04.942752 99468 sgd_solver.cpp:105] Iteration 19240, lr = 0.001
I0708 05:26:21.390223 99468 solver.cpp:218] Iteration 19280 (0.523252 iter/s, 76.445s/40 iters), loss = 3.69409
I0708 05:26:21.390450 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38904 (* 0.3 = 0.716713 loss)
I0708 05:26:21.390472 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40266 (* 0.3 = 0.720799 loss)
I0708 05:26:21.390486 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39825 (* 1 = 2.39825 loss)
I0708 05:26:21.390538 99468 sgd_solver.cpp:105] Iteration 19280, lr = 0.001
I0708 05:27:37.842638 99468 solver.cpp:218] Iteration 19320 (0.52322 iter/s, 76.4496s/40 iters), loss = 3.73233
I0708 05:27:37.842883 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28091 (* 0.3 = 0.684274 loss)
I0708 05:27:37.842905 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30642 (* 0.3 = 0.691927 loss)
I0708 05:27:37.842922 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2891 (* 1 = 2.2891 loss)
I0708 05:27:37.842939 99468 sgd_solver.cpp:105] Iteration 19320, lr = 0.001
I0708 05:28:54.089287 99468 solver.cpp:218] Iteration 19360 (0.524632 iter/s, 76.2439s/40 iters), loss = 3.63304
I0708 05:28:54.089525 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19333 (* 0.3 = 0.658 loss)
I0708 05:28:54.089587 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17414 (* 0.3 = 0.652242 loss)
I0708 05:28:54.089602 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19041 (* 1 = 2.19041 loss)
I0708 05:28:54.089618 99468 sgd_solver.cpp:105] Iteration 19360, lr = 0.001
I0708 05:30:10.390600 99468 solver.cpp:218] Iteration 19400 (0.524256 iter/s, 76.2985s/40 iters), loss = 3.66361
I0708 05:30:10.390908 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44982 (* 0.3 = 0.734946 loss)
I0708 05:30:10.390947 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43717 (* 0.3 = 0.73115 loss)
I0708 05:30:10.390974 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44835 (* 1 = 2.44835 loss)
I0708 05:30:10.391008 99468 sgd_solver.cpp:105] Iteration 19400, lr = 0.001
I0708 05:31:26.950441 99468 solver.cpp:218] Iteration 19440 (0.522486 iter/s, 76.557s/40 iters), loss = 3.6942
I0708 05:31:26.950707 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18432 (* 0.3 = 0.655296 loss)
I0708 05:31:26.950727 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17168 (* 0.3 = 0.651505 loss)
I0708 05:31:26.950742 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18035 (* 1 = 2.18035 loss)
I0708 05:31:26.950765 99468 sgd_solver.cpp:105] Iteration 19440, lr = 0.001
I0708 05:32:43.475102 99468 solver.cpp:218] Iteration 19480 (0.522726 iter/s, 76.5219s/40 iters), loss = 3.78461
I0708 05:32:43.475328 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.57044 (* 0.3 = 0.771132 loss)
I0708 05:32:43.475352 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55756 (* 0.3 = 0.767267 loss)
I0708 05:32:43.475365 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5658 (* 1 = 2.5658 loss)
I0708 05:32:43.475381 99468 sgd_solver.cpp:105] Iteration 19480, lr = 0.001
I0708 05:33:59.836871 99468 solver.cpp:218] Iteration 19520 (0.523841 iter/s, 76.359s/40 iters), loss = 3.6132
I0708 05:33:59.837110 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24556 (* 0.3 = 0.673669 loss)
I0708 05:33:59.837131 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22669 (* 0.3 = 0.668006 loss)
I0708 05:33:59.837147 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23642 (* 1 = 2.23642 loss)
I0708 05:33:59.837164 99468 sgd_solver.cpp:105] Iteration 19520, lr = 0.001
I0708 05:35:16.396692 99468 solver.cpp:218] Iteration 19560 (0.522486 iter/s, 76.5571s/40 iters), loss = 3.67678
I0708 05:35:16.396925 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1737 (* 0.3 = 0.65211 loss)
I0708 05:35:16.396947 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16397 (* 0.3 = 0.649191 loss)
I0708 05:35:16.396962 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16305 (* 1 = 2.16305 loss)
I0708 05:35:16.396978 99468 sgd_solver.cpp:105] Iteration 19560, lr = 0.001
I0708 05:36:32.933034 99468 solver.cpp:218] Iteration 19600 (0.522646 iter/s, 76.5336s/40 iters), loss = 3.72207
I0708 05:36:32.933265 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01714 (* 0.3 = 0.605143 loss)
I0708 05:36:32.933287 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00139 (* 0.3 = 0.600418 loss)
I0708 05:36:32.933302 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99903 (* 1 = 1.99903 loss)
I0708 05:36:32.933318 99468 sgd_solver.cpp:105] Iteration 19600, lr = 0.001
I0708 05:37:49.369438 99468 solver.cpp:218] Iteration 19640 (0.523335 iter/s, 76.4329s/40 iters), loss = 3.713
I0708 05:37:49.369668 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34708 (* 0.3 = 0.704123 loss)
I0708 05:37:49.369689 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35443 (* 0.3 = 0.706329 loss)
I0708 05:37:49.369704 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35271 (* 1 = 2.35271 loss)
I0708 05:37:49.369721 99468 sgd_solver.cpp:105] Iteration 19640, lr = 0.001
I0708 05:39:05.876339 99468 solver.cpp:218] Iteration 19680 (0.522847 iter/s, 76.5042s/40 iters), loss = 3.67957
I0708 05:39:05.876570 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35121 (* 0.3 = 0.705362 loss)
I0708 05:39:05.876591 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36977 (* 0.3 = 0.710932 loss)
I0708 05:39:05.876606 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35605 (* 1 = 2.35605 loss)
I0708 05:39:05.876623 99468 sgd_solver.cpp:105] Iteration 19680, lr = 0.001
I0708 05:40:22.195225 99468 solver.cpp:218] Iteration 19720 (0.524136 iter/s, 76.3161s/40 iters), loss = 3.75915
I0708 05:40:22.195498 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36471 (* 0.3 = 0.709412 loss)
I0708 05:40:22.195521 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36852 (* 0.3 = 0.710557 loss)
I0708 05:40:22.195534 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35369 (* 1 = 2.35369 loss)
I0708 05:40:22.195551 99468 sgd_solver.cpp:105] Iteration 19720, lr = 0.001
I0708 05:41:38.472383 99468 solver.cpp:218] Iteration 19760 (0.524423 iter/s, 76.2744s/40 iters), loss = 3.73601
I0708 05:41:38.472636 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19284 (* 0.3 = 0.657852 loss)
I0708 05:41:38.472658 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19307 (* 0.3 = 0.65792 loss)
I0708 05:41:38.472673 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18884 (* 1 = 2.18884 loss)
I0708 05:41:38.472689 99468 sgd_solver.cpp:105] Iteration 19760, lr = 0.001
I0708 05:42:54.790963 99468 solver.cpp:218] Iteration 19800 (0.524138 iter/s, 76.3158s/40 iters), loss = 3.71575
I0708 05:42:54.791193 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17237 (* 0.3 = 0.65171 loss)
I0708 05:42:54.791257 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17175 (* 0.3 = 0.651526 loss)
I0708 05:42:54.791270 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15364 (* 1 = 2.15364 loss)
I0708 05:42:54.791288 99468 sgd_solver.cpp:105] Iteration 19800, lr = 0.001
I0708 05:44:11.096557 99468 solver.cpp:218] Iteration 19840 (0.524227 iter/s, 76.3028s/40 iters), loss = 3.76107
I0708 05:44:11.096779 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02561 (* 0.3 = 0.607684 loss)
I0708 05:44:11.096842 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.02507 (* 0.3 = 0.60752 loss)
I0708 05:44:11.096858 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.01901 (* 1 = 2.01901 loss)
I0708 05:44:11.096873 99468 sgd_solver.cpp:105] Iteration 19840, lr = 0.001
I0708 05:45:27.626682 99468 solver.cpp:218] Iteration 19880 (0.522689 iter/s, 76.5274s/40 iters), loss = 3.6446
I0708 05:45:27.626910 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56569 (* 0.3 = 0.769708 loss)
I0708 05:45:27.626933 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58888 (* 0.3 = 0.776665 loss)
I0708 05:45:27.626948 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.57598 (* 1 = 2.57598 loss)
I0708 05:45:27.626965 99468 sgd_solver.cpp:105] Iteration 19880, lr = 0.001
I0708 05:46:44.214658 99468 solver.cpp:218] Iteration 19920 (0.522294 iter/s, 76.5852s/40 iters), loss = 3.74103
I0708 05:46:44.214897 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32153 (* 0.3 = 0.696458 loss)
I0708 05:46:44.214952 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32255 (* 0.3 = 0.696765 loss)
I0708 05:46:44.214967 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30816 (* 1 = 2.30816 loss)
I0708 05:46:44.215003 99468 sgd_solver.cpp:105] Iteration 19920, lr = 0.001
I0708 05:48:00.752878 99468 solver.cpp:218] Iteration 19960 (0.522634 iter/s, 76.5354s/40 iters), loss = 3.66709
I0708 05:48:00.753098 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38269 (* 0.3 = 0.714808 loss)
I0708 05:48:00.753121 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37818 (* 0.3 = 0.713455 loss)
I0708 05:48:00.753135 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38824 (* 1 = 2.38824 loss)
I0708 05:48:00.753152 99468 sgd_solver.cpp:105] Iteration 19960, lr = 0.001
I0708 05:49:14.646710 99468 solver.cpp:330] Iteration 20000, Testing net (#0)
I0708 05:59:52.956167 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07103 (* 0.3 = 0.62131 loss)
I0708 05:59:52.956395 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.366661
I0708 05:59:52.956418 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794569
I0708 05:59:52.956439 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07129 (* 0.3 = 0.621386 loss)
I0708 05:59:52.956454 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.366661
I0708 05:59:52.956470 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794569
I0708 05:59:52.956485 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.06867 (* 1 = 2.06867 loss)
I0708 05:59:52.956504 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.366661
I0708 05:59:52.956565 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794569
I0708 05:59:54.864217 99468 solver.cpp:218] Iteration 20000 (0.0560155 iter/s, 714.088s/40 iters), loss = 3.71702
I0708 05:59:54.864320 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40203 (* 0.3 = 0.720609 loss)
I0708 05:59:54.864339 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40464 (* 0.3 = 0.721391 loss)
I0708 05:59:54.864358 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40412 (* 1 = 2.40412 loss)
I0708 05:59:54.864409 99468 sgd_solver.cpp:105] Iteration 20000, lr = 0.001
I0708 06:01:11.152245 99468 solver.cpp:218] Iteration 20040 (0.524349 iter/s, 76.2851s/40 iters), loss = 3.74068
I0708 06:01:11.152530 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51727 (* 0.3 = 0.755181 loss)
I0708 06:01:11.152565 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51984 (* 0.3 = 0.755951 loss)
I0708 06:01:11.152581 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52056 (* 1 = 2.52056 loss)
I0708 06:01:11.152598 99468 sgd_solver.cpp:105] Iteration 20040, lr = 0.001
I0708 06:02:27.427625 99468 solver.cpp:218] Iteration 20080 (0.524435 iter/s, 76.2726s/40 iters), loss = 3.70039
I0708 06:02:27.427858 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36244 (* 0.3 = 0.708732 loss)
I0708 06:02:27.427878 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34677 (* 0.3 = 0.704031 loss)
I0708 06:02:27.427892 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34774 (* 1 = 2.34774 loss)
I0708 06:02:27.427911 99468 sgd_solver.cpp:105] Iteration 20080, lr = 0.001
I0708 06:03:43.888695 99468 solver.cpp:218] Iteration 20120 (0.523161 iter/s, 76.4583s/40 iters), loss = 3.72312
I0708 06:03:43.888942 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28053 (* 0.3 = 0.68416 loss)
I0708 06:03:43.888975 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27858 (* 0.3 = 0.683573 loss)
I0708 06:03:43.888998 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28452 (* 1 = 2.28452 loss)
I0708 06:03:43.889063 99468 sgd_solver.cpp:105] Iteration 20120, lr = 0.001
I0708 06:05:00.442844 99468 solver.cpp:218] Iteration 20160 (0.522525 iter/s, 76.5514s/40 iters), loss = 3.65284
I0708 06:05:00.443084 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23864 (* 0.3 = 0.671593 loss)
I0708 06:05:00.443140 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22157 (* 0.3 = 0.666472 loss)
I0708 06:05:00.443153 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23059 (* 1 = 2.23059 loss)
I0708 06:05:00.443174 99468 sgd_solver.cpp:105] Iteration 20160, lr = 0.001
I0708 06:06:16.965448 99468 solver.cpp:218] Iteration 20200 (0.52274 iter/s, 76.5198s/40 iters), loss = 3.66973
I0708 06:06:16.965677 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32039 (* 0.3 = 0.696117 loss)
I0708 06:06:16.965728 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30544 (* 0.3 = 0.691632 loss)
I0708 06:06:16.965759 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31407 (* 1 = 2.31407 loss)
I0708 06:06:16.965776 99468 sgd_solver.cpp:105] Iteration 20200, lr = 0.001
I0708 06:07:33.430083 99468 solver.cpp:218] Iteration 20240 (0.523136 iter/s, 76.4619s/40 iters), loss = 3.7692
I0708 06:07:33.430315 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43929 (* 0.3 = 0.731788 loss)
I0708 06:07:33.430368 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45273 (* 0.3 = 0.735821 loss)
I0708 06:07:33.430383 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45103 (* 1 = 2.45103 loss)
I0708 06:07:33.430407 99468 sgd_solver.cpp:105] Iteration 20240, lr = 0.001
I0708 06:08:50.007256 99468 solver.cpp:218] Iteration 20280 (0.522368 iter/s, 76.5744s/40 iters), loss = 3.75341
I0708 06:08:50.007635 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27769 (* 0.3 = 0.683307 loss)
I0708 06:08:50.007664 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26758 (* 0.3 = 0.680274 loss)
I0708 06:08:50.007686 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27263 (* 1 = 2.27263 loss)
I0708 06:08:50.007741 99468 sgd_solver.cpp:105] Iteration 20280, lr = 0.001
I0708 06:10:06.611344 99468 solver.cpp:218] Iteration 20320 (0.522185 iter/s, 76.6012s/40 iters), loss = 3.68615
I0708 06:10:06.611577 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24055 (* 0.3 = 0.672165 loss)
I0708 06:10:06.611600 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25709 (* 0.3 = 0.677127 loss)
I0708 06:10:06.611647 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23968 (* 1 = 2.23968 loss)
I0708 06:10:06.611663 99468 sgd_solver.cpp:105] Iteration 20320, lr = 0.001
I0708 06:11:23.029799 99468 solver.cpp:218] Iteration 20360 (0.523453 iter/s, 76.4157s/40 iters), loss = 3.70748
I0708 06:11:23.030016 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48414 (* 0.3 = 0.745243 loss)
I0708 06:11:23.030037 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48261 (* 0.3 = 0.744782 loss)
I0708 06:11:23.030051 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48255 (* 1 = 2.48255 loss)
I0708 06:11:23.030068 99468 sgd_solver.cpp:105] Iteration 20360, lr = 0.001
I0708 06:12:39.513069 99468 solver.cpp:218] Iteration 20400 (0.523009 iter/s, 76.4805s/40 iters), loss = 3.74827
I0708 06:12:39.513344 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38766 (* 0.3 = 0.716297 loss)
I0708 06:12:39.513370 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38634 (* 0.3 = 0.715902 loss)
I0708 06:12:39.513386 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38404 (* 1 = 2.38404 loss)
I0708 06:12:39.513406 99468 sgd_solver.cpp:105] Iteration 20400, lr = 0.001
I0708 06:13:55.989043 99468 solver.cpp:218] Iteration 20440 (0.523059 iter/s, 76.4732s/40 iters), loss = 3.71534
I0708 06:13:55.989284 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33318 (* 0.3 = 0.699955 loss)
I0708 06:13:55.989310 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34441 (* 0.3 = 0.703324 loss)
I0708 06:13:55.989358 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34771 (* 1 = 2.34771 loss)
I0708 06:13:55.989375 99468 sgd_solver.cpp:105] Iteration 20440, lr = 0.001
I0708 06:15:12.571434 99468 solver.cpp:218] Iteration 20480 (0.522332 iter/s, 76.5796s/40 iters), loss = 3.66229
I0708 06:15:12.571667 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45181 (* 0.3 = 0.735543 loss)
I0708 06:15:12.571688 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45647 (* 0.3 = 0.736941 loss)
I0708 06:15:12.571703 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4579 (* 1 = 2.4579 loss)
I0708 06:15:12.571719 99468 sgd_solver.cpp:105] Iteration 20480, lr = 0.001
I0708 06:16:29.130506 99468 solver.cpp:218] Iteration 20520 (0.522491 iter/s, 76.5563s/40 iters), loss = 3.66684
I0708 06:16:29.130766 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35615 (* 0.3 = 0.706844 loss)
I0708 06:16:29.130798 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33975 (* 0.3 = 0.701924 loss)
I0708 06:16:29.130816 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35129 (* 1 = 2.35129 loss)
I0708 06:16:29.130834 99468 sgd_solver.cpp:105] Iteration 20520, lr = 0.001
I0708 06:17:45.578899 99468 solver.cpp:218] Iteration 20560 (0.523254 iter/s, 76.4447s/40 iters), loss = 3.68052
I0708 06:17:45.579146 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25585 (* 0.3 = 0.676754 loss)
I0708 06:17:45.579169 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25433 (* 0.3 = 0.6763 loss)
I0708 06:17:45.579217 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25516 (* 1 = 2.25516 loss)
I0708 06:17:45.579239 99468 sgd_solver.cpp:105] Iteration 20560, lr = 0.001
I0708 06:19:01.967010 99468 solver.cpp:218] Iteration 20600 (0.523661 iter/s, 76.3853s/40 iters), loss = 3.66998
I0708 06:19:01.967303 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35576 (* 0.3 = 0.706729 loss)
I0708 06:19:01.967362 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36584 (* 0.3 = 0.709753 loss)
I0708 06:19:01.967381 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3626 (* 1 = 2.3626 loss)
I0708 06:19:01.967416 99468 sgd_solver.cpp:105] Iteration 20600, lr = 0.001
I0708 06:20:18.517917 99468 solver.cpp:218] Iteration 20640 (0.522548 iter/s, 76.5481s/40 iters), loss = 3.71537
I0708 06:20:18.518205 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09208 (* 0.3 = 0.627625 loss)
I0708 06:20:18.518240 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08762 (* 0.3 = 0.626286 loss)
I0708 06:20:18.518301 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08352 (* 1 = 2.08352 loss)
I0708 06:20:18.518326 99468 sgd_solver.cpp:105] Iteration 20640, lr = 0.001
I0708 06:21:35.036571 99468 solver.cpp:218] Iteration 20680 (0.522767 iter/s, 76.5159s/40 iters), loss = 3.69963
I0708 06:21:35.036800 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37996 (* 0.3 = 0.713987 loss)
I0708 06:21:35.036821 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38722 (* 0.3 = 0.716168 loss)
I0708 06:21:35.036834 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38299 (* 1 = 2.38299 loss)
I0708 06:21:35.036852 99468 sgd_solver.cpp:105] Iteration 20680, lr = 0.001
I0708 06:22:51.514948 99468 solver.cpp:218] Iteration 20720 (0.523043 iter/s, 76.4756s/40 iters), loss = 3.67721
I0708 06:22:51.515188 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09251 (* 0.3 = 0.627753 loss)
I0708 06:22:51.515213 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10408 (* 0.3 = 0.631224 loss)
I0708 06:22:51.515261 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09927 (* 1 = 2.09927 loss)
I0708 06:22:51.515280 99468 sgd_solver.cpp:105] Iteration 20720, lr = 0.001
I0708 06:24:07.974830 99468 solver.cpp:218] Iteration 20760 (0.523169 iter/s, 76.4571s/40 iters), loss = 3.656
I0708 06:24:07.975064 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07986 (* 0.3 = 0.623959 loss)
I0708 06:24:07.975093 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.06903 (* 0.3 = 0.620709 loss)
I0708 06:24:07.975142 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08428 (* 1 = 2.08428 loss)
I0708 06:24:07.975158 99468 sgd_solver.cpp:105] Iteration 20760, lr = 0.001
I0708 06:25:24.558746 99468 solver.cpp:218] Iteration 20800 (0.522322 iter/s, 76.5812s/40 iters), loss = 3.67601
I0708 06:25:24.558976 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.90162 (* 0.3 = 0.570487 loss)
I0708 06:25:24.558996 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.9106 (* 0.3 = 0.57318 loss)
I0708 06:25:24.559011 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.90278 (* 1 = 1.90278 loss)
I0708 06:25:24.559027 99468 sgd_solver.cpp:105] Iteration 20800, lr = 0.001
I0708 06:26:41.047092 99468 solver.cpp:218] Iteration 20840 (0.522974 iter/s, 76.4856s/40 iters), loss = 3.76926
I0708 06:26:41.047322 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29131 (* 0.3 = 0.687393 loss)
I0708 06:26:41.047344 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27291 (* 0.3 = 0.681873 loss)
I0708 06:26:41.047390 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27093 (* 1 = 2.27093 loss)
I0708 06:26:41.047411 99468 sgd_solver.cpp:105] Iteration 20840, lr = 0.001
I0708 06:27:57.297664 99468 solver.cpp:218] Iteration 20880 (0.524605 iter/s, 76.2478s/40 iters), loss = 3.70664
I0708 06:27:57.297958 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41672 (* 0.3 = 0.725017 loss)
I0708 06:27:57.297983 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37768 (* 0.3 = 0.713305 loss)
I0708 06:27:57.298029 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39113 (* 1 = 2.39113 loss)
I0708 06:27:57.298046 99468 sgd_solver.cpp:105] Iteration 20880, lr = 0.001
I0708 06:29:13.617244 99468 solver.cpp:218] Iteration 20920 (0.524131 iter/s, 76.3168s/40 iters), loss = 3.71646
I0708 06:29:13.617475 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24796 (* 0.3 = 0.674388 loss)
I0708 06:29:13.617498 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23261 (* 0.3 = 0.669784 loss)
I0708 06:29:13.617512 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22779 (* 1 = 2.22779 loss)
I0708 06:29:13.617529 99468 sgd_solver.cpp:105] Iteration 20920, lr = 0.001
I0708 06:30:29.973125 99468 solver.cpp:218] Iteration 20960 (0.523882 iter/s, 76.3531s/40 iters), loss = 3.68172
I0708 06:30:29.973372 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25113 (* 0.3 = 0.67534 loss)
I0708 06:30:29.973433 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26058 (* 0.3 = 0.678174 loss)
I0708 06:30:29.973448 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26232 (* 1 = 2.26232 loss)
I0708 06:30:29.973465 99468 sgd_solver.cpp:105] Iteration 20960, lr = 0.001
I0708 06:31:46.341209 99468 solver.cpp:218] Iteration 21000 (0.523798 iter/s, 76.3653s/40 iters), loss = 3.7548
I0708 06:31:46.341442 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25699 (* 0.3 = 0.677096 loss)
I0708 06:31:46.341464 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25577 (* 0.3 = 0.676731 loss)
I0708 06:31:46.341478 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25816 (* 1 = 2.25816 loss)
I0708 06:31:46.341495 99468 sgd_solver.cpp:105] Iteration 21000, lr = 0.001
I0708 06:33:02.878043 99468 solver.cpp:218] Iteration 21040 (0.522643 iter/s, 76.5341s/40 iters), loss = 3.75398
I0708 06:33:02.878268 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.70686 (* 0.3 = 0.812058 loss)
I0708 06:33:02.878324 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.69869 (* 0.3 = 0.809606 loss)
I0708 06:33:02.878337 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.71269 (* 1 = 2.71269 loss)
I0708 06:33:02.878355 99468 sgd_solver.cpp:105] Iteration 21040, lr = 0.001
I0708 06:34:19.326122 99468 solver.cpp:218] Iteration 21080 (0.52325 iter/s, 76.4453s/40 iters), loss = 3.68739
I0708 06:34:19.326371 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24069 (* 0.3 = 0.672207 loss)
I0708 06:34:19.326395 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23195 (* 0.3 = 0.669586 loss)
I0708 06:34:19.326438 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23878 (* 1 = 2.23878 loss)
I0708 06:34:19.326457 99468 sgd_solver.cpp:105] Iteration 21080, lr = 0.001
I0708 06:35:35.629297 99468 solver.cpp:218] Iteration 21120 (0.524244 iter/s, 76.3004s/40 iters), loss = 3.71991
I0708 06:35:35.629518 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1905 (* 0.3 = 0.65715 loss)
I0708 06:35:35.629576 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21703 (* 0.3 = 0.665109 loss)
I0708 06:35:35.629590 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19566 (* 1 = 2.19566 loss)
I0708 06:35:35.629606 99468 sgd_solver.cpp:105] Iteration 21120, lr = 0.001
I0708 06:36:51.894417 99468 solver.cpp:218] Iteration 21160 (0.524505 iter/s, 76.2624s/40 iters), loss = 3.75265
I0708 06:36:51.894632 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.90442 (* 0.3 = 0.571326 loss)
I0708 06:36:51.894654 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.92439 (* 0.3 = 0.577317 loss)
I0708 06:36:51.894670 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.92198 (* 1 = 1.92198 loss)
I0708 06:36:51.894686 99468 sgd_solver.cpp:105] Iteration 21160, lr = 0.001
I0708 06:38:08.259009 99468 solver.cpp:218] Iteration 21200 (0.523822 iter/s, 76.3619s/40 iters), loss = 3.67266
I0708 06:38:08.259315 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.03091 (* 0.3 = 0.609274 loss)
I0708 06:38:08.259340 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04945 (* 0.3 = 0.614836 loss)
I0708 06:38:08.259387 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03858 (* 1 = 2.03858 loss)
I0708 06:38:08.259404 99468 sgd_solver.cpp:105] Iteration 21200, lr = 0.001
I0708 06:39:24.644203 99468 solver.cpp:218] Iteration 21240 (0.523681 iter/s, 76.3824s/40 iters), loss = 3.6665
I0708 06:39:24.644440 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4488 (* 0.3 = 0.734639 loss)
I0708 06:39:24.644491 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4526 (* 0.3 = 0.73578 loss)
I0708 06:39:24.644505 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46282 (* 1 = 2.46282 loss)
I0708 06:39:24.644538 99468 sgd_solver.cpp:105] Iteration 21240, lr = 0.001
I0708 06:40:41.156430 99468 solver.cpp:218] Iteration 21280 (0.522811 iter/s, 76.5095s/40 iters), loss = 3.6609
I0708 06:40:41.156653 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23829 (* 0.3 = 0.671488 loss)
I0708 06:40:41.156674 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22967 (* 0.3 = 0.668902 loss)
I0708 06:40:41.156689 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23019 (* 1 = 2.23019 loss)
I0708 06:40:41.156708 99468 sgd_solver.cpp:105] Iteration 21280, lr = 0.001
I0708 06:41:57.519687 99468 solver.cpp:218] Iteration 21320 (0.523831 iter/s, 76.3605s/40 iters), loss = 3.75824
I0708 06:41:57.519922 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.00265 (* 0.3 = 0.600794 loss)
I0708 06:41:57.519949 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.99652 (* 0.3 = 0.598956 loss)
I0708 06:41:57.519968 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.98985 (* 1 = 1.98985 loss)
I0708 06:41:57.519985 99468 sgd_solver.cpp:105] Iteration 21320, lr = 0.001
I0708 06:43:13.738082 99468 solver.cpp:218] Iteration 21360 (0.524827 iter/s, 76.2156s/40 iters), loss = 3.67976
I0708 06:43:13.738312 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45151 (* 0.3 = 0.735452 loss)
I0708 06:43:13.738332 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42322 (* 0.3 = 0.726966 loss)
I0708 06:43:13.738348 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44101 (* 1 = 2.44101 loss)
I0708 06:43:13.738365 99468 sgd_solver.cpp:105] Iteration 21360, lr = 0.001
I0708 06:44:30.158676 99468 solver.cpp:218] Iteration 21400 (0.523438 iter/s, 76.4178s/40 iters), loss = 3.68101
I0708 06:44:30.158897 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46903 (* 0.3 = 0.74071 loss)
I0708 06:44:30.158918 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49115 (* 0.3 = 0.747344 loss)
I0708 06:44:30.158931 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48064 (* 1 = 2.48064 loss)
I0708 06:44:30.158952 99468 sgd_solver.cpp:105] Iteration 21400, lr = 0.001
I0708 06:45:46.749948 99468 solver.cpp:218] Iteration 21440 (0.522271 iter/s, 76.5885s/40 iters), loss = 3.72711
I0708 06:45:46.750169 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26526 (* 0.3 = 0.679577 loss)
I0708 06:45:46.750191 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25468 (* 0.3 = 0.676403 loss)
I0708 06:45:46.750206 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26121 (* 1 = 2.26121 loss)
I0708 06:45:46.750222 99468 sgd_solver.cpp:105] Iteration 21440, lr = 0.001
I0708 06:47:03.360958 99468 solver.cpp:218] Iteration 21480 (0.522137 iter/s, 76.6083s/40 iters), loss = 3.6828
I0708 06:47:03.361186 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27614 (* 0.3 = 0.682843 loss)
I0708 06:47:03.361209 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26146 (* 0.3 = 0.678437 loss)
I0708 06:47:03.361258 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26562 (* 1 = 2.26562 loss)
I0708 06:47:03.361279 99468 sgd_solver.cpp:105] Iteration 21480, lr = 0.001
I0708 06:48:19.915911 99468 solver.cpp:218] Iteration 21520 (0.522519 iter/s, 76.5522s/40 iters), loss = 3.67848
I0708 06:48:19.916200 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36814 (* 0.3 = 0.710443 loss)
I0708 06:48:19.916254 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3769 (* 0.3 = 0.713069 loss)
I0708 06:48:19.916270 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36498 (* 1 = 2.36498 loss)
I0708 06:48:19.916287 99468 sgd_solver.cpp:105] Iteration 21520, lr = 0.001
I0708 06:49:36.458417 99468 solver.cpp:218] Iteration 21560 (0.522605 iter/s, 76.5397s/40 iters), loss = 3.68507
I0708 06:49:36.458653 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.88433 (* 0.3 = 0.565298 loss)
I0708 06:49:36.458706 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.8881 (* 0.3 = 0.566431 loss)
I0708 06:49:36.458720 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.88488 (* 1 = 1.88488 loss)
I0708 06:49:36.458741 99468 sgd_solver.cpp:105] Iteration 21560, lr = 0.001
I0708 06:50:53.018652 99468 solver.cpp:218] Iteration 21600 (0.522483 iter/s, 76.5575s/40 iters), loss = 3.6935
I0708 06:50:53.018887 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41145 (* 0.3 = 0.723436 loss)
I0708 06:50:53.018910 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40172 (* 0.3 = 0.720515 loss)
I0708 06:50:53.018957 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4025 (* 1 = 2.4025 loss)
I0708 06:50:53.018978 99468 sgd_solver.cpp:105] Iteration 21600, lr = 0.001
I0708 06:52:09.360270 99468 solver.cpp:218] Iteration 21640 (0.523979 iter/s, 76.3389s/40 iters), loss = 3.73768
I0708 06:52:09.360497 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23893 (* 0.3 = 0.671678 loss)
I0708 06:52:09.360517 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23598 (* 0.3 = 0.670793 loss)
I0708 06:52:09.360530 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23133 (* 1 = 2.23133 loss)
I0708 06:52:09.360584 99468 sgd_solver.cpp:105] Iteration 21640, lr = 0.001
I0708 06:53:25.580869 99468 solver.cpp:218] Iteration 21680 (0.524812 iter/s, 76.2178s/40 iters), loss = 3.71088
I0708 06:53:25.581112 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39381 (* 0.3 = 0.718143 loss)
I0708 06:53:25.581138 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40771 (* 0.3 = 0.722313 loss)
I0708 06:53:25.581156 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40578 (* 1 = 2.40578 loss)
I0708 06:53:25.581171 99468 sgd_solver.cpp:105] Iteration 21680, lr = 0.001
I0708 06:54:42.023303 99468 solver.cpp:218] Iteration 21720 (0.523288 iter/s, 76.4397s/40 iters), loss = 3.6901
I0708 06:54:42.023531 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11773 (* 0.3 = 0.63532 loss)
I0708 06:54:42.023558 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10494 (* 0.3 = 0.631483 loss)
I0708 06:54:42.023574 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10419 (* 1 = 2.10419 loss)
I0708 06:54:42.023588 99468 sgd_solver.cpp:105] Iteration 21720, lr = 0.001
I0708 06:55:58.578779 99468 solver.cpp:218] Iteration 21760 (0.522516 iter/s, 76.5527s/40 iters), loss = 3.71202
I0708 06:55:58.579030 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30632 (* 0.3 = 0.691895 loss)
I0708 06:55:58.579051 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2975 (* 0.3 = 0.689251 loss)
I0708 06:55:58.579069 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30068 (* 1 = 2.30068 loss)
I0708 06:55:58.579084 99468 sgd_solver.cpp:105] Iteration 21760, lr = 0.001
I0708 06:57:14.949079 99468 solver.cpp:218] Iteration 21800 (0.523783 iter/s, 76.3675s/40 iters), loss = 3.73164
I0708 06:57:14.949311 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.89326 (* 0.3 = 0.867978 loss)
I0708 06:57:14.949334 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.9214 (* 0.3 = 0.876422 loss)
I0708 06:57:14.949349 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.90922 (* 1 = 2.90922 loss)
I0708 06:57:14.949368 99468 sgd_solver.cpp:105] Iteration 21800, lr = 0.001
I0708 06:58:31.491174 99468 solver.cpp:218] Iteration 21840 (0.522607 iter/s, 76.5393s/40 iters), loss = 3.69112
I0708 06:58:31.491458 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33046 (* 0.3 = 0.699139 loss)
I0708 06:58:31.491479 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36492 (* 0.3 = 0.709477 loss)
I0708 06:58:31.491493 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34617 (* 1 = 2.34617 loss)
I0708 06:58:31.491513 99468 sgd_solver.cpp:105] Iteration 21840, lr = 0.001
I0708 06:59:47.943385 99468 solver.cpp:218] Iteration 21880 (0.523222 iter/s, 76.4494s/40 iters), loss = 3.69124
I0708 06:59:47.944643 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.598 (* 0.3 = 0.779401 loss)
I0708 06:59:47.944727 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57169 (* 0.3 = 0.771506 loss)
I0708 06:59:47.944783 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5965 (* 1 = 2.5965 loss)
I0708 06:59:47.944839 99468 sgd_solver.cpp:105] Iteration 21880, lr = 0.001
I0708 07:01:04.499924 99468 solver.cpp:218] Iteration 21920 (0.522515 iter/s, 76.5528s/40 iters), loss = 3.69678
I0708 07:01:04.500169 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.94336 (* 0.3 = 0.583008 loss)
I0708 07:01:04.500190 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.94052 (* 0.3 = 0.582155 loss)
I0708 07:01:04.500206 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.94709 (* 1 = 1.94709 loss)
I0708 07:01:04.500222 99468 sgd_solver.cpp:105] Iteration 21920, lr = 0.001
I0708 07:02:21.019469 99468 solver.cpp:218] Iteration 21960 (0.522761 iter/s, 76.5168s/40 iters), loss = 3.6795
I0708 07:02:21.019700 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39277 (* 0.3 = 0.71783 loss)
I0708 07:02:21.019727 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39023 (* 0.3 = 0.717068 loss)
I0708 07:02:21.019776 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38421 (* 1 = 2.38421 loss)
I0708 07:02:21.019793 99468 sgd_solver.cpp:105] Iteration 21960, lr = 0.001
I0708 07:03:37.626854 99468 solver.cpp:218] Iteration 22000 (0.522162 iter/s, 76.6046s/40 iters), loss = 3.76312
I0708 07:03:37.627092 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4995 (* 0.3 = 0.74985 loss)
I0708 07:03:37.627116 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47588 (* 0.3 = 0.742765 loss)
I0708 07:03:37.627166 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49259 (* 1 = 2.49259 loss)
I0708 07:03:37.627182 99468 sgd_solver.cpp:105] Iteration 22000, lr = 0.001
I0708 07:04:53.908509 99468 solver.cpp:218] Iteration 22040 (0.524391 iter/s, 76.2789s/40 iters), loss = 3.72882
I0708 07:04:53.908746 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29954 (* 0.3 = 0.689863 loss)
I0708 07:04:53.908802 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33079 (* 0.3 = 0.699238 loss)
I0708 07:04:53.908819 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32284 (* 1 = 2.32284 loss)
I0708 07:04:53.908852 99468 sgd_solver.cpp:105] Iteration 22040, lr = 0.001
I0708 07:06:10.382727 99468 solver.cpp:218] Iteration 22080 (0.523071 iter/s, 76.4715s/40 iters), loss = 3.7284
I0708 07:06:10.382963 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44604 (* 0.3 = 0.733813 loss)
I0708 07:06:10.382988 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47064 (* 0.3 = 0.741193 loss)
I0708 07:06:10.383039 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45355 (* 1 = 2.45355 loss)
I0708 07:06:10.383056 99468 sgd_solver.cpp:105] Iteration 22080, lr = 0.001
I0708 07:07:26.671394 99468 solver.cpp:218] Iteration 22120 (0.524343 iter/s, 76.2859s/40 iters), loss = 3.65543
I0708 07:07:26.671656 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47418 (* 0.3 = 0.742254 loss)
I0708 07:07:26.671708 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45038 (* 0.3 = 0.735113 loss)
I0708 07:07:26.671721 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.471 (* 1 = 2.471 loss)
I0708 07:07:26.671756 99468 sgd_solver.cpp:105] Iteration 22120, lr = 0.001
I0708 07:08:43.223408 99468 solver.cpp:218] Iteration 22160 (0.52254 iter/s, 76.5492s/40 iters), loss = 3.75718
I0708 07:08:43.223651 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21755 (* 0.3 = 0.665265 loss)
I0708 07:08:43.223675 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22028 (* 0.3 = 0.666084 loss)
I0708 07:08:43.223721 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21225 (* 1 = 2.21225 loss)
I0708 07:08:43.223738 99468 sgd_solver.cpp:105] Iteration 22160, lr = 0.001
I0708 07:09:59.758157 99468 solver.cpp:218] Iteration 22200 (0.522657 iter/s, 76.532s/40 iters), loss = 3.73216
I0708 07:09:59.758391 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30716 (* 0.3 = 0.692147 loss)
I0708 07:09:59.758414 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28685 (* 0.3 = 0.686055 loss)
I0708 07:09:59.758430 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2987 (* 1 = 2.2987 loss)
I0708 07:09:59.758445 99468 sgd_solver.cpp:105] Iteration 22200, lr = 0.001
I0708 07:11:16.313877 99468 solver.cpp:218] Iteration 22240 (0.522514 iter/s, 76.553s/40 iters), loss = 3.70625
I0708 07:11:16.314116 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60421 (* 0.3 = 0.781263 loss)
I0708 07:11:16.314137 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62509 (* 0.3 = 0.787528 loss)
I0708 07:11:16.314152 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.60268 (* 1 = 2.60268 loss)
I0708 07:11:16.314169 99468 sgd_solver.cpp:105] Iteration 22240, lr = 0.001
I0708 07:12:32.855312 99468 solver.cpp:218] Iteration 22280 (0.522612 iter/s, 76.5387s/40 iters), loss = 3.72253
I0708 07:12:32.855543 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04595 (* 0.3 = 0.613784 loss)
I0708 07:12:32.855574 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.05377 (* 0.3 = 0.616132 loss)
I0708 07:12:32.855587 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04737 (* 1 = 2.04737 loss)
I0708 07:12:32.855602 99468 sgd_solver.cpp:105] Iteration 22280, lr = 0.001
I0708 07:13:49.401368 99468 solver.cpp:218] Iteration 22320 (0.52258 iter/s, 76.5433s/40 iters), loss = 3.69957
I0708 07:13:49.401599 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.261 (* 0.3 = 0.6783 loss)
I0708 07:13:49.401655 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26756 (* 0.3 = 0.680269 loss)
I0708 07:13:49.401674 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26847 (* 1 = 2.26847 loss)
I0708 07:13:49.401706 99468 sgd_solver.cpp:105] Iteration 22320, lr = 0.001
I0708 07:15:05.948854 99468 solver.cpp:218] Iteration 22360 (0.52257 iter/s, 76.5447s/40 iters), loss = 3.69673
I0708 07:15:05.949092 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14055 (* 0.3 = 0.642164 loss)
I0708 07:15:05.949115 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13411 (* 0.3 = 0.640233 loss)
I0708 07:15:05.949131 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13896 (* 1 = 2.13896 loss)
I0708 07:15:05.949146 99468 sgd_solver.cpp:105] Iteration 22360, lr = 0.001
I0708 07:16:22.521796 99468 solver.cpp:218] Iteration 22400 (0.522397 iter/s, 76.5702s/40 iters), loss = 3.64316
I0708 07:16:22.522027 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37022 (* 0.3 = 0.711066 loss)
I0708 07:16:22.522048 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34695 (* 0.3 = 0.704085 loss)
I0708 07:16:22.522063 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36664 (* 1 = 2.36664 loss)
I0708 07:16:22.522079 99468 sgd_solver.cpp:105] Iteration 22400, lr = 0.001
I0708 07:17:39.108295 99468 solver.cpp:218] Iteration 22440 (0.522304 iter/s, 76.5837s/40 iters), loss = 3.69218
I0708 07:17:39.108574 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40505 (* 0.3 = 0.721514 loss)
I0708 07:17:39.108631 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38377 (* 0.3 = 0.715131 loss)
I0708 07:17:39.108645 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3819 (* 1 = 2.3819 loss)
I0708 07:17:39.108666 99468 sgd_solver.cpp:105] Iteration 22440, lr = 0.001
I0708 07:18:55.594213 99468 solver.cpp:218] Iteration 22480 (0.522991 iter/s, 76.4831s/40 iters), loss = 3.68863
I0708 07:18:55.594460 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45789 (* 0.3 = 0.737367 loss)
I0708 07:18:55.594516 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4371 (* 0.3 = 0.73113 loss)
I0708 07:18:55.594530 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44385 (* 1 = 2.44385 loss)
I0708 07:18:55.594548 99468 sgd_solver.cpp:105] Iteration 22480, lr = 0.001
I0708 07:20:11.848827 99468 solver.cpp:218] Iteration 22520 (0.524577 iter/s, 76.2518s/40 iters), loss = 3.76948
I0708 07:20:11.849050 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38517 (* 0.3 = 0.715551 loss)
I0708 07:20:11.849073 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39191 (* 0.3 = 0.717572 loss)
I0708 07:20:11.849123 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38087 (* 1 = 2.38087 loss)
I0708 07:20:11.849139 99468 sgd_solver.cpp:105] Iteration 22520, lr = 0.001
I0708 07:21:28.069371 99468 solver.cpp:218] Iteration 22560 (0.524812 iter/s, 76.2178s/40 iters), loss = 3.69051
I0708 07:21:28.069607 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39644 (* 0.3 = 0.718931 loss)
I0708 07:21:28.069629 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40082 (* 0.3 = 0.720246 loss)
I0708 07:21:28.069644 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3996 (* 1 = 2.3996 loss)
I0708 07:21:28.069661 99468 sgd_solver.cpp:105] Iteration 22560, lr = 0.001
I0708 07:22:44.671236 99468 solver.cpp:218] Iteration 22600 (0.522199 iter/s, 76.5991s/40 iters), loss = 3.66581
I0708 07:22:44.671478 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5027 (* 0.3 = 0.75081 loss)
I0708 07:22:44.671500 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49069 (* 0.3 = 0.747208 loss)
I0708 07:22:44.671547 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49966 (* 1 = 2.49966 loss)
I0708 07:22:44.671571 99468 sgd_solver.cpp:105] Iteration 22600, lr = 0.001
I0708 07:24:01.205699 99468 solver.cpp:218] Iteration 22640 (0.522659 iter/s, 76.5317s/40 iters), loss = 3.66691
I0708 07:24:01.205930 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11002 (* 0.3 = 0.633006 loss)
I0708 07:24:01.205953 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13348 (* 0.3 = 0.640044 loss)
I0708 07:24:01.206004 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10648 (* 1 = 2.10648 loss)
I0708 07:24:01.206025 99468 sgd_solver.cpp:105] Iteration 22640, lr = 0.001
I0708 07:25:17.739575 99468 solver.cpp:218] Iteration 22680 (0.522663 iter/s, 76.5311s/40 iters), loss = 3.67893
I0708 07:25:17.739817 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04666 (* 0.3 = 0.613997 loss)
I0708 07:25:17.739867 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03606 (* 0.3 = 0.610817 loss)
I0708 07:25:17.739881 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03253 (* 1 = 2.03253 loss)
I0708 07:25:17.739900 99468 sgd_solver.cpp:105] Iteration 22680, lr = 0.001
I0708 07:26:34.305642 99468 solver.cpp:218] Iteration 22720 (0.522444 iter/s, 76.5633s/40 iters), loss = 3.74943
I0708 07:26:34.305873 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54089 (* 0.3 = 0.762266 loss)
I0708 07:26:34.305894 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53649 (* 0.3 = 0.760948 loss)
I0708 07:26:34.305907 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53565 (* 1 = 2.53565 loss)
I0708 07:26:34.305925 99468 sgd_solver.cpp:105] Iteration 22720, lr = 0.001
I0708 07:27:50.894577 99468 solver.cpp:218] Iteration 22760 (0.522287 iter/s, 76.5862s/40 iters), loss = 3.74026
I0708 07:27:50.894856 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.49778 (* 0.3 = 0.749333 loss)
I0708 07:27:50.894912 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5152 (* 0.3 = 0.754559 loss)
I0708 07:27:50.894927 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51263 (* 1 = 2.51263 loss)
I0708 07:27:50.894944 99468 sgd_solver.cpp:105] Iteration 22760, lr = 0.001
I0708 07:29:07.438637 99468 solver.cpp:218] Iteration 22800 (0.522594 iter/s, 76.5413s/40 iters), loss = 3.72244
I0708 07:29:07.438881 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19904 (* 0.3 = 0.659713 loss)
I0708 07:29:07.438905 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19712 (* 0.3 = 0.659135 loss)
I0708 07:29:07.438920 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19647 (* 1 = 2.19647 loss)
I0708 07:29:07.438971 99468 sgd_solver.cpp:105] Iteration 22800, lr = 0.001
I0708 07:30:24.004876 99468 solver.cpp:218] Iteration 22840 (0.522442 iter/s, 76.5635s/40 iters), loss = 3.71308
I0708 07:30:24.005100 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38095 (* 0.3 = 0.714286 loss)
I0708 07:30:24.005122 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39296 (* 0.3 = 0.717888 loss)
I0708 07:30:24.005136 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3859 (* 1 = 2.3859 loss)
I0708 07:30:24.005152 99468 sgd_solver.cpp:105] Iteration 22840, lr = 0.001
I0708 07:31:40.404062 99468 solver.cpp:218] Iteration 22880 (0.523585 iter/s, 76.3964s/40 iters), loss = 3.73978
I0708 07:31:40.404307 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.86108 (* 0.3 = 0.858323 loss)
I0708 07:31:40.404366 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.83288 (* 0.3 = 0.849863 loss)
I0708 07:31:40.404400 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.83194 (* 1 = 2.83194 loss)
I0708 07:31:40.404419 99468 sgd_solver.cpp:105] Iteration 22880, lr = 0.001
I0708 07:32:56.706640 99468 solver.cpp:218] Iteration 22920 (0.524248 iter/s, 76.2998s/40 iters), loss = 3.71063
I0708 07:32:56.706871 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35538 (* 0.3 = 0.706615 loss)
I0708 07:32:56.706893 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36089 (* 0.3 = 0.708268 loss)
I0708 07:32:56.706907 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36544 (* 1 = 2.36544 loss)
I0708 07:32:56.706924 99468 sgd_solver.cpp:105] Iteration 22920, lr = 0.001
I0708 07:34:13.273524 99468 solver.cpp:218] Iteration 22960 (0.522438 iter/s, 76.5641s/40 iters), loss = 3.73502
I0708 07:34:13.273762 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.61156 (* 0.3 = 0.783468 loss)
I0708 07:34:13.273787 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.64031 (* 0.3 = 0.792094 loss)
I0708 07:34:13.273800 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.61009 (* 1 = 2.61009 loss)
I0708 07:34:13.273818 99468 sgd_solver.cpp:105] Iteration 22960, lr = 0.001
I0708 07:35:29.849561 99468 solver.cpp:218] Iteration 23000 (0.522376 iter/s, 76.5733s/40 iters), loss = 3.70894
I0708 07:35:29.849795 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47812 (* 0.3 = 0.743435 loss)
I0708 07:35:29.849854 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46991 (* 0.3 = 0.740973 loss)
I0708 07:35:29.849887 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47599 (* 1 = 2.47599 loss)
I0708 07:35:29.849905 99468 sgd_solver.cpp:105] Iteration 23000, lr = 0.001
I0708 07:36:46.280787 99468 solver.cpp:218] Iteration 23040 (0.523365 iter/s, 76.4285s/40 iters), loss = 3.68711
I0708 07:36:46.281066 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18764 (* 0.3 = 0.656292 loss)
I0708 07:36:46.281091 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1971 (* 0.3 = 0.65913 loss)
I0708 07:36:46.281110 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18356 (* 1 = 2.18356 loss)
I0708 07:36:46.281127 99468 sgd_solver.cpp:105] Iteration 23040, lr = 0.001
I0708 07:38:02.594647 99468 solver.cpp:218] Iteration 23080 (0.52417 iter/s, 76.3111s/40 iters), loss = 3.68621
I0708 07:38:02.594897 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13171 (* 0.3 = 0.639512 loss)
I0708 07:38:02.594923 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12641 (* 0.3 = 0.637922 loss)
I0708 07:38:02.594938 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11995 (* 1 = 2.11995 loss)
I0708 07:38:02.594956 99468 sgd_solver.cpp:105] Iteration 23080, lr = 0.001
I0708 07:39:18.791780 99468 solver.cpp:218] Iteration 23120 (0.524973 iter/s, 76.1944s/40 iters), loss = 3.69782
I0708 07:39:18.792011 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.64782 (* 0.3 = 0.794345 loss)
I0708 07:39:18.792035 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.66489 (* 0.3 = 0.799468 loss)
I0708 07:39:18.792083 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.65623 (* 1 = 2.65623 loss)
I0708 07:39:18.792106 99468 sgd_solver.cpp:105] Iteration 23120, lr = 0.001
I0708 07:40:35.241117 99468 solver.cpp:218] Iteration 23160 (0.523241 iter/s, 76.4466s/40 iters), loss = 3.68757
I0708 07:40:35.241340 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17279 (* 0.3 = 0.651836 loss)
I0708 07:40:35.241367 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.168 (* 0.3 = 0.6504 loss)
I0708 07:40:35.241420 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17467 (* 1 = 2.17467 loss)
I0708 07:40:35.241436 99468 sgd_solver.cpp:105] Iteration 23160, lr = 0.001
I0708 07:41:51.834282 99468 solver.cpp:218] Iteration 23200 (0.522259 iter/s, 76.5904s/40 iters), loss = 3.69084
I0708 07:41:51.834511 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17728 (* 0.3 = 0.653185 loss)
I0708 07:41:51.834584 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19684 (* 0.3 = 0.659051 loss)
I0708 07:41:51.834599 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18981 (* 1 = 2.18981 loss)
I0708 07:41:51.834616 99468 sgd_solver.cpp:105] Iteration 23200, lr = 0.001
I0708 07:43:08.400010 99468 solver.cpp:218] Iteration 23240 (0.522446 iter/s, 76.563s/40 iters), loss = 3.74441
I0708 07:43:08.400246 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18876 (* 0.3 = 0.656628 loss)
I0708 07:43:08.400272 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19594 (* 0.3 = 0.658782 loss)
I0708 07:43:08.400290 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19511 (* 1 = 2.19511 loss)
I0708 07:43:08.400308 99468 sgd_solver.cpp:105] Iteration 23240, lr = 0.001
I0708 07:44:24.790102 99468 solver.cpp:218] Iteration 23280 (0.523647 iter/s, 76.3873s/40 iters), loss = 3.67545
I0708 07:44:24.790323 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31891 (* 0.3 = 0.695674 loss)
I0708 07:44:24.790374 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32455 (* 0.3 = 0.697366 loss)
I0708 07:44:24.790388 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32124 (* 1 = 2.32124 loss)
I0708 07:44:24.790406 99468 sgd_solver.cpp:105] Iteration 23280, lr = 0.001
I0708 07:45:41.005266 99468 solver.cpp:218] Iteration 23320 (0.524849 iter/s, 76.2124s/40 iters), loss = 3.6748
I0708 07:45:41.005482 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20514 (* 0.3 = 0.661542 loss)
I0708 07:45:41.005506 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18876 (* 0.3 = 0.656629 loss)
I0708 07:45:41.005520 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18117 (* 1 = 2.18117 loss)
I0708 07:45:41.005584 99468 sgd_solver.cpp:105] Iteration 23320, lr = 0.001
I0708 07:46:57.268955 99468 solver.cpp:218] Iteration 23360 (0.524515 iter/s, 76.261s/40 iters), loss = 3.70941
I0708 07:46:57.269260 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65848 (* 0.3 = 0.797543 loss)
I0708 07:46:57.269317 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.64383 (* 0.3 = 0.79315 loss)
I0708 07:46:57.269332 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.66365 (* 1 = 2.66365 loss)
I0708 07:46:57.269367 99468 sgd_solver.cpp:105] Iteration 23360, lr = 0.001
I0708 07:48:13.546349 99468 solver.cpp:218] Iteration 23400 (0.524421 iter/s, 76.2746s/40 iters), loss = 3.67291
I0708 07:48:13.546592 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.0799 (* 0.3 = 0.62397 loss)
I0708 07:48:13.546649 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0727 (* 0.3 = 0.621809 loss)
I0708 07:48:13.546664 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.06818 (* 1 = 2.06818 loss)
I0708 07:48:13.546684 99468 sgd_solver.cpp:105] Iteration 23400, lr = 0.001
I0708 07:49:29.915987 99468 solver.cpp:218] Iteration 23440 (0.523787 iter/s, 76.3669s/40 iters), loss = 3.67955
I0708 07:49:29.916213 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54807 (* 0.3 = 0.764422 loss)
I0708 07:49:29.916234 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5345 (* 0.3 = 0.76035 loss)
I0708 07:49:29.916250 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5443 (* 1 = 2.5443 loss)
I0708 07:49:29.916268 99468 sgd_solver.cpp:105] Iteration 23440, lr = 0.001
I0708 07:50:46.494735 99468 solver.cpp:218] Iteration 23480 (0.522357 iter/s, 76.576s/40 iters), loss = 3.68648
I0708 07:50:46.494977 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13767 (* 0.3 = 0.641301 loss)
I0708 07:50:46.495002 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13444 (* 0.3 = 0.640333 loss)
I0708 07:50:46.495015 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13436 (* 1 = 2.13436 loss)
I0708 07:50:46.495031 99468 sgd_solver.cpp:105] Iteration 23480, lr = 0.001
I0708 07:52:02.827666 99468 solver.cpp:218] Iteration 23520 (0.524039 iter/s, 76.3302s/40 iters), loss = 3.66635
I0708 07:52:02.827898 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.05683 (* 0.3 = 0.617049 loss)
I0708 07:52:02.827955 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.05374 (* 0.3 = 0.616122 loss)
I0708 07:52:02.827968 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.06013 (* 1 = 2.06013 loss)
I0708 07:52:02.828003 99468 sgd_solver.cpp:105] Iteration 23520, lr = 0.001
I0708 07:53:19.187408 99468 solver.cpp:218] Iteration 23560 (0.523855 iter/s, 76.357s/40 iters), loss = 3.75301
I0708 07:53:19.187829 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14619 (* 0.3 = 0.643858 loss)
I0708 07:53:19.187852 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15527 (* 0.3 = 0.64658 loss)
I0708 07:53:19.187870 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15032 (* 1 = 2.15032 loss)
I0708 07:53:19.187885 99468 sgd_solver.cpp:105] Iteration 23560, lr = 0.001
I0708 07:54:35.709261 99468 solver.cpp:218] Iteration 23600 (0.522747 iter/s, 76.5189s/40 iters), loss = 3.70895
I0708 07:54:35.709527 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26749 (* 0.3 = 0.680247 loss)
I0708 07:54:35.709549 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29078 (* 0.3 = 0.687235 loss)
I0708 07:54:35.709573 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26477 (* 1 = 2.26477 loss)
I0708 07:54:35.709590 99468 sgd_solver.cpp:105] Iteration 23600, lr = 0.001
I0708 07:55:52.306612 99468 solver.cpp:218] Iteration 23640 (0.52223 iter/s, 76.5945s/40 iters), loss = 3.70673
I0708 07:55:52.306854 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.74302 (* 0.3 = 0.822908 loss)
I0708 07:55:52.306910 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.74813 (* 0.3 = 0.82444 loss)
I0708 07:55:52.306926 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.74098 (* 1 = 2.74098 loss)
I0708 07:55:52.306944 99468 sgd_solver.cpp:105] Iteration 23640, lr = 0.001
I0708 07:57:08.619866 99468 solver.cpp:218] Iteration 23680 (0.524174 iter/s, 76.3105s/40 iters), loss = 3.6952
I0708 07:57:08.620142 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25533 (* 0.3 = 0.6766 loss)
I0708 07:57:08.620163 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23419 (* 0.3 = 0.670258 loss)
I0708 07:57:08.620177 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23773 (* 1 = 2.23773 loss)
I0708 07:57:08.620193 99468 sgd_solver.cpp:105] Iteration 23680, lr = 0.001
I0708 07:58:25.231564 99468 solver.cpp:218] Iteration 23720 (0.522133 iter/s, 76.6089s/40 iters), loss = 3.74159
I0708 07:58:25.231798 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5552 (* 0.3 = 0.766561 loss)
I0708 07:58:25.231866 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55222 (* 0.3 = 0.765666 loss)
I0708 07:58:25.231881 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.54874 (* 1 = 2.54874 loss)
I0708 07:58:25.231900 99468 sgd_solver.cpp:105] Iteration 23720, lr = 0.001
I0708 07:59:41.479528 99468 solver.cpp:218] Iteration 23760 (0.524623 iter/s, 76.2452s/40 iters), loss = 3.78025
I0708 07:59:41.479779 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.72057 (* 0.3 = 0.816172 loss)
I0708 07:59:41.479799 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.6919 (* 0.3 = 0.807569 loss)
I0708 07:59:41.479813 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.69885 (* 1 = 2.69885 loss)
I0708 07:59:41.479832 99468 sgd_solver.cpp:105] Iteration 23760, lr = 0.001
I0708 08:00:57.706666 99468 solver.cpp:218] Iteration 23800 (0.524767 iter/s, 76.2244s/40 iters), loss = 3.69168
I0708 08:00:57.706887 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25502 (* 0.3 = 0.676505 loss)
I0708 08:00:57.706955 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23237 (* 0.3 = 0.66971 loss)
I0708 08:00:57.706970 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22961 (* 1 = 2.22961 loss)
I0708 08:00:57.706989 99468 sgd_solver.cpp:105] Iteration 23800, lr = 0.001
I0708 08:02:14.224647 99468 solver.cpp:218] Iteration 23840 (0.522772 iter/s, 76.5152s/40 iters), loss = 3.69171
I0708 08:02:14.224889 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39333 (* 0.3 = 0.718 loss)
I0708 08:02:14.224911 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39003 (* 0.3 = 0.717008 loss)
I0708 08:02:14.224932 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38454 (* 1 = 2.38454 loss)
I0708 08:02:14.224947 99468 sgd_solver.cpp:105] Iteration 23840, lr = 0.001
I0708 08:03:30.790284 99468 solver.cpp:218] Iteration 23880 (0.522446 iter/s, 76.5629s/40 iters), loss = 3.70252
I0708 08:03:30.790504 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28279 (* 0.3 = 0.684836 loss)
I0708 08:03:30.790527 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28145 (* 0.3 = 0.684435 loss)
I0708 08:03:30.790541 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29506 (* 1 = 2.29506 loss)
I0708 08:03:30.790561 99468 sgd_solver.cpp:105] Iteration 23880, lr = 0.001
I0708 08:04:47.055783 99468 solver.cpp:218] Iteration 23920 (0.524502 iter/s, 76.2628s/40 iters), loss = 3.66808
I0708 08:04:47.056012 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35508 (* 0.3 = 0.706523 loss)
I0708 08:04:47.056033 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33897 (* 0.3 = 0.701691 loss)
I0708 08:04:47.056048 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3528 (* 1 = 2.3528 loss)
I0708 08:04:47.056067 99468 sgd_solver.cpp:105] Iteration 23920, lr = 0.001
I0708 08:06:03.496729 99468 solver.cpp:218] Iteration 23960 (0.523299 iter/s, 76.4382s/40 iters), loss = 3.68037
I0708 08:06:03.496958 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9275 (* 0.3 = 0.57825 loss)
I0708 08:06:03.496983 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.92416 (* 0.3 = 0.577247 loss)
I0708 08:06:03.496997 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.92132 (* 1 = 1.92132 loss)
I0708 08:06:03.497017 99468 sgd_solver.cpp:105] Iteration 23960, lr = 0.001
I0708 08:07:17.562458 99468 solver.cpp:330] Iteration 24000, Testing net (#0)
I0708 08:17:30.010984 99629 data_layer.cpp:73] Restarting data prefetching from start.
I0708 08:17:53.259160 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07382 (* 0.3 = 0.622145 loss)
I0708 08:17:53.259239 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.367594
I0708 08:17:53.259256 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794435
I0708 08:17:53.259279 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07364 (* 0.3 = 0.622091 loss)
I0708 08:17:53.259299 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.367594
I0708 08:17:53.259312 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794435
I0708 08:17:53.259330 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07122 (* 1 = 2.07122 loss)
I0708 08:17:53.259343 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.367594
I0708 08:17:53.259402 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794435
I0708 08:17:55.151113 99468 solver.cpp:218] Iteration 24000 (0.0562089 iter/s, 711.631s/40 iters), loss = 3.70349
I0708 08:17:55.151217 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.62226 (* 0.3 = 0.786678 loss)
I0708 08:17:55.151275 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.60435 (* 0.3 = 0.781306 loss)
I0708 08:17:55.151293 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62612 (* 1 = 2.62612 loss)
I0708 08:17:55.151311 99468 sgd_solver.cpp:105] Iteration 24000, lr = 0.001
I0708 08:19:11.678015 99468 solver.cpp:218] Iteration 24040 (0.52271 iter/s, 76.5243s/40 iters), loss = 3.71254
I0708 08:19:11.678263 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18344 (* 0.3 = 0.655033 loss)
I0708 08:19:11.678285 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19365 (* 0.3 = 0.658094 loss)
I0708 08:19:11.678303 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19385 (* 1 = 2.19385 loss)
I0708 08:19:11.678320 99468 sgd_solver.cpp:105] Iteration 24040, lr = 0.001
I0708 08:20:28.095268 99468 solver.cpp:218] Iteration 24080 (0.523461 iter/s, 76.4145s/40 iters), loss = 3.7251
I0708 08:20:28.095506 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43388 (* 0.3 = 0.730163 loss)
I0708 08:20:28.095569 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43175 (* 0.3 = 0.729525 loss)
I0708 08:20:28.095587 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42731 (* 1 = 2.42731 loss)
I0708 08:20:28.095604 99468 sgd_solver.cpp:105] Iteration 24080, lr = 0.001
I0708 08:21:44.602453 99468 solver.cpp:218] Iteration 24120 (0.522846 iter/s, 76.5044s/40 iters), loss = 3.6884
I0708 08:21:44.602687 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01754 (* 0.3 = 0.605261 loss)
I0708 08:21:44.602741 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04474 (* 0.3 = 0.613422 loss)
I0708 08:21:44.602761 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04212 (* 1 = 2.04212 loss)
I0708 08:21:44.602779 99468 sgd_solver.cpp:105] Iteration 24120, lr = 0.001
I0708 08:23:01.058941 99468 solver.cpp:218] Iteration 24160 (0.523192 iter/s, 76.4537s/40 iters), loss = 3.65477
I0708 08:23:01.059175 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20576 (* 0.3 = 0.661728 loss)
I0708 08:23:01.059197 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19696 (* 0.3 = 0.659087 loss)
I0708 08:23:01.059212 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19117 (* 1 = 2.19117 loss)
I0708 08:23:01.059228 99468 sgd_solver.cpp:105] Iteration 24160, lr = 0.001
I0708 08:24:17.563247 99468 solver.cpp:218] Iteration 24200 (0.522865 iter/s, 76.5015s/40 iters), loss = 3.70554
I0708 08:24:17.563522 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17932 (* 0.3 = 0.653796 loss)
I0708 08:24:17.563585 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17636 (* 0.3 = 0.652908 loss)
I0708 08:24:17.563598 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1667 (* 1 = 2.1667 loss)
I0708 08:24:17.563616 99468 sgd_solver.cpp:105] Iteration 24200, lr = 0.001
I0708 08:25:33.776724 99468 solver.cpp:218] Iteration 24240 (0.524861 iter/s, 76.2107s/40 iters), loss = 3.71012
I0708 08:25:33.776968 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2677 (* 0.3 = 0.680311 loss)
I0708 08:25:33.776993 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25304 (* 0.3 = 0.675913 loss)
I0708 08:25:33.777040 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25971 (* 1 = 2.25971 loss)
I0708 08:25:33.777057 99468 sgd_solver.cpp:105] Iteration 24240, lr = 0.001
I0708 08:26:50.016510 99468 solver.cpp:218] Iteration 24280 (0.524679 iter/s, 76.237s/40 iters), loss = 3.73958
I0708 08:26:50.016746 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33516 (* 0.3 = 0.700547 loss)
I0708 08:26:50.016772 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33846 (* 0.3 = 0.701537 loss)
I0708 08:26:50.016788 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33555 (* 1 = 2.33555 loss)
I0708 08:26:50.016804 99468 sgd_solver.cpp:105] Iteration 24280, lr = 0.001
I0708 08:28:06.252266 99468 solver.cpp:218] Iteration 24320 (0.524707 iter/s, 76.233s/40 iters), loss = 3.71075
I0708 08:28:06.252498 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.63634 (* 0.3 = 0.790902 loss)
I0708 08:28:06.252562 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.65921 (* 0.3 = 0.797762 loss)
I0708 08:28:06.252575 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.63473 (* 1 = 2.63473 loss)
I0708 08:28:06.252590 99468 sgd_solver.cpp:105] Iteration 24320, lr = 0.001
I0708 08:29:22.542868 99468 solver.cpp:218] Iteration 24360 (0.52433 iter/s, 76.2878s/40 iters), loss = 3.72552
I0708 08:29:22.543110 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10473 (* 0.3 = 0.631418 loss)
I0708 08:29:22.543166 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10861 (* 0.3 = 0.632582 loss)
I0708 08:29:22.543180 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10477 (* 1 = 2.10477 loss)
I0708 08:29:22.543200 99468 sgd_solver.cpp:105] Iteration 24360, lr = 0.001
I0708 08:30:39.101722 99468 solver.cpp:218] Iteration 24400 (0.522493 iter/s, 76.5561s/40 iters), loss = 3.73284
I0708 08:30:39.101958 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38226 (* 0.3 = 0.714677 loss)
I0708 08:30:39.101979 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38924 (* 0.3 = 0.716771 loss)
I0708 08:30:39.101994 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38703 (* 1 = 2.38703 loss)
I0708 08:30:39.102011 99468 sgd_solver.cpp:105] Iteration 24400, lr = 0.001
I0708 08:31:55.570545 99468 solver.cpp:218] Iteration 24440 (0.523118 iter/s, 76.4646s/40 iters), loss = 3.70869
I0708 08:31:55.570786 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10169 (* 0.3 = 0.630506 loss)
I0708 08:31:55.570842 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09856 (* 0.3 = 0.629569 loss)
I0708 08:31:55.570855 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10381 (* 1 = 2.10381 loss)
I0708 08:31:55.570875 99468 sgd_solver.cpp:105] Iteration 24440, lr = 0.001
I0708 08:33:11.828018 99468 solver.cpp:218] Iteration 24480 (0.524558 iter/s, 76.2547s/40 iters), loss = 3.75975
I0708 08:33:11.828248 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39337 (* 0.3 = 0.718012 loss)
I0708 08:33:11.828302 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39857 (* 0.3 = 0.71957 loss)
I0708 08:33:11.828315 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38137 (* 1 = 2.38137 loss)
I0708 08:33:11.828349 99468 sgd_solver.cpp:105] Iteration 24480, lr = 0.001
I0708 08:34:28.415529 99468 solver.cpp:218] Iteration 24520 (0.522297 iter/s, 76.5847s/40 iters), loss = 3.72014
I0708 08:34:28.415787 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38925 (* 0.3 = 0.716776 loss)
I0708 08:34:28.415813 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37692 (* 0.3 = 0.713077 loss)
I0708 08:34:28.415827 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37345 (* 1 = 2.37345 loss)
I0708 08:34:28.415844 99468 sgd_solver.cpp:105] Iteration 24520, lr = 0.001
I0708 08:35:44.946797 99468 solver.cpp:218] Iteration 24560 (0.522681 iter/s, 76.5285s/40 iters), loss = 3.6802
I0708 08:35:44.947046 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37182 (* 0.3 = 0.711547 loss)
I0708 08:35:44.947103 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35979 (* 0.3 = 0.707936 loss)
I0708 08:35:44.947118 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35943 (* 1 = 2.35943 loss)
I0708 08:35:44.947134 99468 sgd_solver.cpp:105] Iteration 24560, lr = 0.001
I0708 08:37:01.400245 99468 solver.cpp:218] Iteration 24600 (0.523213 iter/s, 76.4507s/40 iters), loss = 3.65714
I0708 08:37:01.400480 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.00852 (* 0.3 = 0.602556 loss)
I0708 08:37:01.400499 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.01001 (* 0.3 = 0.603004 loss)
I0708 08:37:01.400513 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99981 (* 1 = 1.99981 loss)
I0708 08:37:01.400568 99468 sgd_solver.cpp:105] Iteration 24600, lr = 0.001
I0708 08:38:17.927701 99468 solver.cpp:218] Iteration 24640 (0.522707 iter/s, 76.5247s/40 iters), loss = 3.7112
I0708 08:38:17.927927 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18337 (* 0.3 = 0.655012 loss)
I0708 08:38:17.927949 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18057 (* 0.3 = 0.654172 loss)
I0708 08:38:17.927963 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1777 (* 1 = 2.1777 loss)
I0708 08:38:17.927983 99468 sgd_solver.cpp:105] Iteration 24640, lr = 0.001
I0708 08:39:34.424644 99468 solver.cpp:218] Iteration 24680 (0.522916 iter/s, 76.4942s/40 iters), loss = 3.66864
I0708 08:39:34.424875 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.88636 (* 0.3 = 0.565909 loss)
I0708 08:39:34.424895 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.89154 (* 0.3 = 0.567461 loss)
I0708 08:39:34.424907 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.88707 (* 1 = 1.88707 loss)
I0708 08:39:34.424928 99468 sgd_solver.cpp:105] Iteration 24680, lr = 0.001
I0708 08:40:50.979691 99468 solver.cpp:218] Iteration 24720 (0.522519 iter/s, 76.5523s/40 iters), loss = 3.64807
I0708 08:40:50.979923 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37084 (* 0.3 = 0.711251 loss)
I0708 08:40:50.979944 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3772 (* 0.3 = 0.713159 loss)
I0708 08:40:50.979959 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37608 (* 1 = 2.37608 loss)
I0708 08:40:50.979975 99468 sgd_solver.cpp:105] Iteration 24720, lr = 0.001
I0708 08:42:07.556797 99468 solver.cpp:218] Iteration 24760 (0.522368 iter/s, 76.5743s/40 iters), loss = 3.72621
I0708 08:42:07.557040 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47515 (* 0.3 = 0.742544 loss)
I0708 08:42:07.557061 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49919 (* 0.3 = 0.749758 loss)
I0708 08:42:07.557076 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4899 (* 1 = 2.4899 loss)
I0708 08:42:07.557093 99468 sgd_solver.cpp:105] Iteration 24760, lr = 0.001
I0708 08:43:24.064074 99468 solver.cpp:218] Iteration 24800 (0.522845 iter/s, 76.5045s/40 iters), loss = 3.63355
I0708 08:43:24.064293 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24941 (* 0.3 = 0.674823 loss)
I0708 08:43:24.064316 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27771 (* 0.3 = 0.683312 loss)
I0708 08:43:24.064330 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26711 (* 1 = 2.26711 loss)
I0708 08:43:24.064347 99468 sgd_solver.cpp:105] Iteration 24800, lr = 0.001
I0708 08:44:40.582820 99468 solver.cpp:218] Iteration 24840 (0.522767 iter/s, 76.516s/40 iters), loss = 3.69228
I0708 08:44:40.583086 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33759 (* 0.3 = 0.701276 loss)
I0708 08:44:40.583142 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35066 (* 0.3 = 0.705198 loss)
I0708 08:44:40.583155 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34574 (* 1 = 2.34574 loss)
I0708 08:44:40.583176 99468 sgd_solver.cpp:105] Iteration 24840, lr = 0.001
I0708 08:45:56.825300 99468 solver.cpp:218] Iteration 24880 (0.524661 iter/s, 76.2397s/40 iters), loss = 3.65748
I0708 08:45:56.825534 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.64142 (* 0.3 = 0.792427 loss)
I0708 08:45:56.825562 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62419 (* 0.3 = 0.787259 loss)
I0708 08:45:56.825578 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.61761 (* 1 = 2.61761 loss)
I0708 08:45:56.825595 99468 sgd_solver.cpp:105] Iteration 24880, lr = 0.001
I0708 08:47:13.052917 99468 solver.cpp:218] Iteration 24920 (0.524763 iter/s, 76.2249s/40 iters), loss = 3.69809
I0708 08:47:13.053153 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27005 (* 0.3 = 0.681015 loss)
I0708 08:47:13.053212 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26263 (* 0.3 = 0.67879 loss)
I0708 08:47:13.053227 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25374 (* 1 = 2.25374 loss)
I0708 08:47:13.053246 99468 sgd_solver.cpp:105] Iteration 24920, lr = 0.001
I0708 08:48:29.554852 99468 solver.cpp:218] Iteration 24960 (0.522882 iter/s, 76.4992s/40 iters), loss = 3.6916
I0708 08:48:29.555085 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40754 (* 0.3 = 0.722261 loss)
I0708 08:48:29.555110 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41152 (* 0.3 = 0.723455 loss)
I0708 08:48:29.555124 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41543 (* 1 = 2.41543 loss)
I0708 08:48:29.555141 99468 sgd_solver.cpp:105] Iteration 24960, lr = 0.001
I0708 08:49:46.042783 99468 solver.cpp:218] Iteration 25000 (0.522977 iter/s, 76.4851s/40 iters), loss = 3.69015
I0708 08:49:46.043058 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41439 (* 0.3 = 0.724316 loss)
I0708 08:49:46.043090 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42028 (* 0.3 = 0.726084 loss)
I0708 08:49:46.043109 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42353 (* 1 = 2.42353 loss)
I0708 08:49:46.043128 99468 sgd_solver.cpp:105] Iteration 25000, lr = 0.001
I0708 08:51:02.678896 99468 solver.cpp:218] Iteration 25040 (0.521966 iter/s, 76.6333s/40 iters), loss = 3.6853
I0708 08:51:02.679172 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35053 (* 0.3 = 0.70516 loss)
I0708 08:51:02.679231 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34446 (* 0.3 = 0.703337 loss)
I0708 08:51:02.679244 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34432 (* 1 = 2.34432 loss)
I0708 08:51:02.679267 99468 sgd_solver.cpp:105] Iteration 25040, lr = 0.001
I0708 08:52:19.151180 99468 solver.cpp:218] Iteration 25080 (0.523085 iter/s, 76.4695s/40 iters), loss = 3.66857
I0708 08:52:19.151408 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27347 (* 0.3 = 0.682042 loss)
I0708 08:52:19.151434 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27849 (* 0.3 = 0.683547 loss)
I0708 08:52:19.151489 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26937 (* 1 = 2.26937 loss)
I0708 08:52:19.151509 99468 sgd_solver.cpp:105] Iteration 25080, lr = 0.001
I0708 08:53:35.433470 99468 solver.cpp:218] Iteration 25120 (0.524387 iter/s, 76.2795s/40 iters), loss = 3.66735
I0708 08:53:35.433691 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.83138 (* 0.3 = 0.549414 loss)
I0708 08:53:35.433712 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.81033 (* 0.3 = 0.543098 loss)
I0708 08:53:35.433725 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.81073 (* 1 = 1.81073 loss)
I0708 08:53:35.433746 99468 sgd_solver.cpp:105] Iteration 25120, lr = 0.001
I0708 08:54:51.724812 99468 solver.cpp:218] Iteration 25160 (0.524325 iter/s, 76.2886s/40 iters), loss = 3.68383
I0708 08:54:51.725091 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22674 (* 0.3 = 0.668021 loss)
I0708 08:54:51.725148 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21887 (* 0.3 = 0.66566 loss)
I0708 08:54:51.725162 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23103 (* 1 = 2.23103 loss)
I0708 08:54:51.725196 99468 sgd_solver.cpp:105] Iteration 25160, lr = 0.001
I0708 08:56:08.323190 99468 solver.cpp:218] Iteration 25200 (0.522223 iter/s, 76.5956s/40 iters), loss = 3.7371
I0708 08:56:08.323415 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60017 (* 0.3 = 0.780051 loss)
I0708 08:56:08.323436 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59445 (* 0.3 = 0.778335 loss)
I0708 08:56:08.323449 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59772 (* 1 = 2.59772 loss)
I0708 08:56:08.323467 99468 sgd_solver.cpp:105] Iteration 25200, lr = 0.001
I0708 08:57:24.901100 99468 solver.cpp:218] Iteration 25240 (0.522363 iter/s, 76.5752s/40 iters), loss = 3.69899
I0708 08:57:24.901325 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10155 (* 0.3 = 0.630466 loss)
I0708 08:57:24.901350 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1123 (* 0.3 = 0.633689 loss)
I0708 08:57:24.901363 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11549 (* 1 = 2.11549 loss)
I0708 08:57:24.901381 99468 sgd_solver.cpp:105] Iteration 25240, lr = 0.001
I0708 08:58:41.446372 99468 solver.cpp:218] Iteration 25280 (0.522585 iter/s, 76.5425s/40 iters), loss = 3.76555
I0708 08:58:41.446617 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56651 (* 0.3 = 0.769952 loss)
I0708 08:58:41.446640 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57177 (* 0.3 = 0.77153 loss)
I0708 08:58:41.446652 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.56633 (* 1 = 2.56633 loss)
I0708 08:58:41.446669 99468 sgd_solver.cpp:105] Iteration 25280, lr = 0.001
I0708 08:59:57.982444 99468 solver.cpp:218] Iteration 25320 (0.522648 iter/s, 76.5333s/40 iters), loss = 3.68967
I0708 08:59:57.982666 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35701 (* 0.3 = 0.707104 loss)
I0708 08:59:57.982687 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36244 (* 0.3 = 0.708732 loss)
I0708 08:59:57.982702 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35008 (* 1 = 2.35008 loss)
I0708 08:59:57.982722 99468 sgd_solver.cpp:105] Iteration 25320, lr = 0.001
I0708 09:01:14.584856 99468 solver.cpp:218] Iteration 25360 (0.522196 iter/s, 76.5997s/40 iters), loss = 3.71831
I0708 09:01:14.585090 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15414 (* 0.3 = 0.646241 loss)
I0708 09:01:14.585111 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15527 (* 0.3 = 0.646581 loss)
I0708 09:01:14.585124 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14823 (* 1 = 2.14823 loss)
I0708 09:01:14.585146 99468 sgd_solver.cpp:105] Iteration 25360, lr = 0.001
I0708 09:02:31.140915 99468 solver.cpp:218] Iteration 25400 (0.522512 iter/s, 76.5533s/40 iters), loss = 3.65525
I0708 09:02:31.141147 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34682 (* 0.3 = 0.704045 loss)
I0708 09:02:31.141211 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.348 (* 0.3 = 0.704401 loss)
I0708 09:02:31.141227 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35137 (* 1 = 2.35137 loss)
I0708 09:02:31.141247 99468 sgd_solver.cpp:105] Iteration 25400, lr = 0.001
I0708 09:03:47.588141 99468 solver.cpp:218] Iteration 25440 (0.523256 iter/s, 76.4445s/40 iters), loss = 3.72915
I0708 09:03:47.588474 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28178 (* 0.3 = 0.684535 loss)
I0708 09:03:47.588497 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28761 (* 0.3 = 0.686284 loss)
I0708 09:03:47.588512 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28904 (* 1 = 2.28904 loss)
I0708 09:03:47.588528 99468 sgd_solver.cpp:105] Iteration 25440, lr = 0.001
I0708 09:05:03.791116 99468 solver.cpp:218] Iteration 25480 (0.524933 iter/s, 76.2001s/40 iters), loss = 3.6961
I0708 09:05:03.791389 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33837 (* 0.3 = 0.701512 loss)
I0708 09:05:03.791451 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34126 (* 0.3 = 0.702377 loss)
I0708 09:05:03.791471 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34517 (* 1 = 2.34517 loss)
I0708 09:05:03.791488 99468 sgd_solver.cpp:105] Iteration 25480, lr = 0.001
I0708 09:06:20.067649 99468 solver.cpp:218] Iteration 25520 (0.524427 iter/s, 76.2737s/40 iters), loss = 3.71146
I0708 09:06:20.067888 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30095 (* 0.3 = 0.690286 loss)
I0708 09:06:20.067942 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30816 (* 0.3 = 0.692447 loss)
I0708 09:06:20.067975 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3044 (* 1 = 2.3044 loss)
I0708 09:06:20.067991 99468 sgd_solver.cpp:105] Iteration 25520, lr = 0.001
I0708 09:07:36.343087 99468 solver.cpp:218] Iteration 25560 (0.524434 iter/s, 76.2727s/40 iters), loss = 3.72994
I0708 09:07:36.343358 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65692 (* 0.3 = 0.797077 loss)
I0708 09:07:36.343384 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.65484 (* 0.3 = 0.796451 loss)
I0708 09:07:36.343399 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.64461 (* 1 = 2.64461 loss)
I0708 09:07:36.343412 99468 sgd_solver.cpp:105] Iteration 25560, lr = 0.001
I0708 09:08:52.550979 99468 solver.cpp:218] Iteration 25600 (0.524899 iter/s, 76.2051s/40 iters), loss = 3.69562
I0708 09:08:52.551241 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34929 (* 0.3 = 0.704786 loss)
I0708 09:08:52.551265 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35586 (* 0.3 = 0.706757 loss)
I0708 09:08:52.551280 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35398 (* 1 = 2.35398 loss)
I0708 09:08:52.551295 99468 sgd_solver.cpp:105] Iteration 25600, lr = 0.001
I0708 09:10:08.784752 99468 solver.cpp:218] Iteration 25640 (0.524721 iter/s, 76.231s/40 iters), loss = 3.70847
I0708 09:10:08.785013 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60069 (* 0.3 = 0.780206 loss)
I0708 09:10:08.785038 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61112 (* 0.3 = 0.783336 loss)
I0708 09:10:08.785056 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.61149 (* 1 = 2.61149 loss)
I0708 09:10:08.785070 99468 sgd_solver.cpp:105] Iteration 25640, lr = 0.001
I0708 09:11:25.046288 99468 solver.cpp:218] Iteration 25680 (0.52453 iter/s, 76.2588s/40 iters), loss = 3.75298
I0708 09:11:25.046577 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10127 (* 0.3 = 0.63038 loss)
I0708 09:11:25.046633 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08995 (* 0.3 = 0.626984 loss)
I0708 09:11:25.046648 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09025 (* 1 = 2.09025 loss)
I0708 09:11:25.046664 99468 sgd_solver.cpp:105] Iteration 25680, lr = 0.001
I0708 09:12:41.199923 99468 solver.cpp:218] Iteration 25720 (0.525273 iter/s, 76.1508s/40 iters), loss = 3.71812
I0708 09:12:41.200172 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20627 (* 0.3 = 0.661881 loss)
I0708 09:12:41.200192 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24114 (* 0.3 = 0.672343 loss)
I0708 09:12:41.200208 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2332 (* 1 = 2.2332 loss)
I0708 09:12:41.200223 99468 sgd_solver.cpp:105] Iteration 25720, lr = 0.001
I0708 09:13:57.458786 99468 solver.cpp:218] Iteration 25760 (0.524548 iter/s, 76.2561s/40 iters), loss = 3.64076
I0708 09:13:57.459116 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27826 (* 0.3 = 0.683479 loss)
I0708 09:13:57.459141 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28114 (* 0.3 = 0.684341 loss)
I0708 09:13:57.459188 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.245 (* 1 = 2.245 loss)
I0708 09:13:57.459602 99468 sgd_solver.cpp:105] Iteration 25760, lr = 0.001
I0708 09:15:13.722306 99468 solver.cpp:218] Iteration 25800 (0.524517 iter/s, 76.2607s/40 iters), loss = 3.69063
I0708 09:15:13.722565 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28287 (* 0.3 = 0.68486 loss)
I0708 09:15:13.722620 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28646 (* 0.3 = 0.685937 loss)
I0708 09:15:13.722635 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28135 (* 1 = 2.28135 loss)
I0708 09:15:13.722651 99468 sgd_solver.cpp:105] Iteration 25800, lr = 0.001
I0708 09:16:29.965400 99468 solver.cpp:218] Iteration 25840 (0.524657 iter/s, 76.2403s/40 iters), loss = 3.68777
I0708 09:16:29.965656 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45537 (* 0.3 = 0.736611 loss)
I0708 09:16:29.965677 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43287 (* 0.3 = 0.729862 loss)
I0708 09:16:29.965726 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44026 (* 1 = 2.44026 loss)
I0708 09:16:29.965741 99468 sgd_solver.cpp:105] Iteration 25840, lr = 0.001
I0708 09:17:46.198563 99468 solver.cpp:218] Iteration 25880 (0.524725 iter/s, 76.2304s/40 iters), loss = 3.73493
I0708 09:17:46.198822 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35942 (* 0.3 = 0.707826 loss)
I0708 09:17:46.198844 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35646 (* 0.3 = 0.706938 loss)
I0708 09:17:46.198859 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34589 (* 1 = 2.34589 loss)
I0708 09:17:46.198874 99468 sgd_solver.cpp:105] Iteration 25880, lr = 0.001
I0708 09:19:02.425269 99468 solver.cpp:218] Iteration 25920 (0.52477 iter/s, 76.2239s/40 iters), loss = 3.72888
I0708 09:19:02.425520 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10602 (* 0.3 = 0.631807 loss)
I0708 09:19:02.425542 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12397 (* 0.3 = 0.63719 loss)
I0708 09:19:02.425564 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13513 (* 1 = 2.13513 loss)
I0708 09:19:02.425578 99468 sgd_solver.cpp:105] Iteration 25920, lr = 0.001
I0708 09:20:18.739734 99468 solver.cpp:218] Iteration 25960 (0.524166 iter/s, 76.3117s/40 iters), loss = 3.74712
I0708 09:20:18.740001 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.95727 (* 0.3 = 0.587182 loss)
I0708 09:20:18.740072 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.95309 (* 0.3 = 0.585928 loss)
I0708 09:20:18.740087 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.95679 (* 1 = 1.95679 loss)
I0708 09:20:18.740103 99468 sgd_solver.cpp:105] Iteration 25960, lr = 0.001
I0708 09:21:35.009153 99468 solver.cpp:218] Iteration 26000 (0.524476 iter/s, 76.2666s/40 iters), loss = 3.7144
I0708 09:21:35.009588 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08911 (* 0.3 = 0.626734 loss)
I0708 09:21:35.009634 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0927 (* 0.3 = 0.62781 loss)
I0708 09:21:35.009663 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10221 (* 1 = 2.10221 loss)
I0708 09:21:35.009742 99468 sgd_solver.cpp:105] Iteration 26000, lr = 0.001
I0708 09:22:51.300930 99468 solver.cpp:218] Iteration 26040 (0.524323 iter/s, 76.2888s/40 iters), loss = 3.66948
I0708 09:22:51.301192 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41337 (* 0.3 = 0.724011 loss)
I0708 09:22:51.301218 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41455 (* 0.3 = 0.724364 loss)
I0708 09:22:51.301268 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41195 (* 1 = 2.41195 loss)
I0708 09:22:51.301283 99468 sgd_solver.cpp:105] Iteration 26040, lr = 0.001
I0708 09:24:07.540165 99468 solver.cpp:218] Iteration 26080 (0.524683 iter/s, 76.2365s/40 iters), loss = 3.72971
I0708 09:24:07.540472 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32546 (* 0.3 = 0.697637 loss)
I0708 09:24:07.540495 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31698 (* 0.3 = 0.695093 loss)
I0708 09:24:07.540510 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31226 (* 1 = 2.31226 loss)
I0708 09:24:07.540527 99468 sgd_solver.cpp:105] Iteration 26080, lr = 0.001
I0708 09:25:23.750844 99468 solver.cpp:218] Iteration 26120 (0.52488 iter/s, 76.2079s/40 iters), loss = 3.71246
I0708 09:25:23.751096 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34541 (* 0.3 = 0.703624 loss)
I0708 09:25:23.751117 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36473 (* 0.3 = 0.709418 loss)
I0708 09:25:23.751132 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34973 (* 1 = 2.34973 loss)
I0708 09:25:23.751152 99468 sgd_solver.cpp:105] Iteration 26120, lr = 0.001
I0708 09:26:40.030659 99468 solver.cpp:218] Iteration 26160 (0.524404 iter/s, 76.277s/40 iters), loss = 3.78023
I0708 09:26:40.030930 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14824 (* 0.3 = 0.644473 loss)
I0708 09:26:40.030951 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1596 (* 0.3 = 0.647879 loss)
I0708 09:26:40.030966 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1449 (* 1 = 2.1449 loss)
I0708 09:26:40.030985 99468 sgd_solver.cpp:105] Iteration 26160, lr = 0.001
I0708 09:27:56.270777 99468 solver.cpp:218] Iteration 26200 (0.524677 iter/s, 76.2373s/40 iters), loss = 3.70051
I0708 09:27:56.271054 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36529 (* 0.3 = 0.709587 loss)
I0708 09:27:56.271085 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35684 (* 0.3 = 0.707053 loss)
I0708 09:27:56.271106 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35741 (* 1 = 2.35741 loss)
I0708 09:27:56.271122 99468 sgd_solver.cpp:105] Iteration 26200, lr = 0.001
I0708 09:29:12.524828 99468 solver.cpp:218] Iteration 26240 (0.524581 iter/s, 76.2513s/40 iters), loss = 3.72228
I0708 09:29:12.525074 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17761 (* 0.3 = 0.653283 loss)
I0708 09:29:12.525096 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17311 (* 0.3 = 0.651932 loss)
I0708 09:29:12.525111 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17295 (* 1 = 2.17295 loss)
I0708 09:29:12.525126 99468 sgd_solver.cpp:105] Iteration 26240, lr = 0.001
I0708 09:30:28.726306 99468 solver.cpp:218] Iteration 26280 (0.524943 iter/s, 76.1987s/40 iters), loss = 3.70928
I0708 09:30:28.726564 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54456 (* 0.3 = 0.763368 loss)
I0708 09:30:28.726591 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.54708 (* 0.3 = 0.764123 loss)
I0708 09:30:28.726605 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.56659 (* 1 = 2.56659 loss)
I0708 09:30:28.726620 99468 sgd_solver.cpp:105] Iteration 26280, lr = 0.001
I0708 09:31:44.976024 99468 solver.cpp:218] Iteration 26320 (0.524611 iter/s, 76.2469s/40 iters), loss = 3.71134
I0708 09:31:44.976286 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35755 (* 0.3 = 0.707264 loss)
I0708 09:31:44.976308 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33483 (* 0.3 = 0.700449 loss)
I0708 09:31:44.976323 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34132 (* 1 = 2.34132 loss)
I0708 09:31:44.976344 99468 sgd_solver.cpp:105] Iteration 26320, lr = 0.001
I0708 09:33:01.244065 99468 solver.cpp:218] Iteration 26360 (0.524485 iter/s, 76.2653s/40 iters), loss = 3.6969
I0708 09:33:01.244423 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.58295 (* 0.3 = 0.774885 loss)
I0708 09:33:01.244489 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58082 (* 0.3 = 0.774247 loss)
I0708 09:33:01.244504 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.58877 (* 1 = 2.58877 loss)
I0708 09:33:01.244539 99468 sgd_solver.cpp:105] Iteration 26360, lr = 0.001
I0708 09:34:17.518571 99468 solver.cpp:218] Iteration 26400 (0.524441 iter/s, 76.2716s/40 iters), loss = 3.67288
I0708 09:34:17.518829 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2611 (* 0.3 = 0.678329 loss)
I0708 09:34:17.518852 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26245 (* 0.3 = 0.678735 loss)
I0708 09:34:17.518867 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25446 (* 1 = 2.25446 loss)
I0708 09:34:17.518916 99468 sgd_solver.cpp:105] Iteration 26400, lr = 0.001
I0708 09:35:33.795595 99468 solver.cpp:218] Iteration 26440 (0.524424 iter/s, 76.2742s/40 iters), loss = 3.69955
I0708 09:35:33.795852 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38768 (* 0.3 = 0.716305 loss)
I0708 09:35:33.795876 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4091 (* 0.3 = 0.72273 loss)
I0708 09:35:33.795892 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39172 (* 1 = 2.39172 loss)
I0708 09:35:33.795907 99468 sgd_solver.cpp:105] Iteration 26440, lr = 0.001
I0708 09:36:50.070859 99468 solver.cpp:218] Iteration 26480 (0.524436 iter/s, 76.2725s/40 iters), loss = 3.68357
I0708 09:36:50.071099 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38976 (* 0.3 = 0.716927 loss)
I0708 09:36:50.071161 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38001 (* 0.3 = 0.714002 loss)
I0708 09:36:50.071175 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37931 (* 1 = 2.37931 loss)
I0708 09:36:50.071192 99468 sgd_solver.cpp:105] Iteration 26480, lr = 0.001
I0708 09:38:06.582610 99468 solver.cpp:218] Iteration 26520 (0.522814 iter/s, 76.509s/40 iters), loss = 3.71173
I0708 09:38:06.582854 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40964 (* 0.3 = 0.722892 loss)
I0708 09:38:06.582875 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40505 (* 0.3 = 0.721515 loss)
I0708 09:38:06.582891 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39505 (* 1 = 2.39505 loss)
I0708 09:38:06.582948 99468 sgd_solver.cpp:105] Iteration 26520, lr = 0.001
I0708 09:39:23.035962 99468 solver.cpp:218] Iteration 26560 (0.523214 iter/s, 76.4506s/40 iters), loss = 3.73874
I0708 09:39:23.036191 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44458 (* 0.3 = 0.733373 loss)
I0708 09:39:23.036217 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44172 (* 0.3 = 0.732516 loss)
I0708 09:39:23.036233 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4444 (* 1 = 2.4444 loss)
I0708 09:39:23.036249 99468 sgd_solver.cpp:105] Iteration 26560, lr = 0.001
I0708 09:40:39.280131 99468 solver.cpp:218] Iteration 26600 (0.524649 iter/s, 76.2414s/40 iters), loss = 3.67248
I0708 09:40:39.280367 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13992 (* 0.3 = 0.641975 loss)
I0708 09:40:39.280388 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12982 (* 0.3 = 0.638945 loss)
I0708 09:40:39.280401 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12026 (* 1 = 2.12026 loss)
I0708 09:40:39.280423 99468 sgd_solver.cpp:105] Iteration 26600, lr = 0.001
I0708 09:41:55.663661 99468 solver.cpp:218] Iteration 26640 (0.523692 iter/s, 76.3808s/40 iters), loss = 3.72739
I0708 09:41:55.663892 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25066 (* 0.3 = 0.675199 loss)
I0708 09:41:55.663916 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25498 (* 0.3 = 0.676494 loss)
I0708 09:41:55.663931 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24671 (* 1 = 2.24671 loss)
I0708 09:41:55.663949 99468 sgd_solver.cpp:105] Iteration 26640, lr = 0.001
I0708 09:43:12.262380 99468 solver.cpp:218] Iteration 26680 (0.522221 iter/s, 76.596s/40 iters), loss = 3.6524
I0708 09:43:12.262671 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.87497 (* 0.3 = 0.562491 loss)
I0708 09:43:12.262696 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.85744 (* 0.3 = 0.557231 loss)
I0708 09:43:12.262714 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.86498 (* 1 = 1.86498 loss)
I0708 09:43:12.262730 99468 sgd_solver.cpp:105] Iteration 26680, lr = 0.001
I0708 09:44:28.713004 99468 solver.cpp:218] Iteration 26720 (0.523233 iter/s, 76.4478s/40 iters), loss = 3.75062
I0708 09:44:28.713238 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48003 (* 0.3 = 0.744009 loss)
I0708 09:44:28.713260 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48223 (* 0.3 = 0.744669 loss)
I0708 09:44:28.713274 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48372 (* 1 = 2.48372 loss)
I0708 09:44:28.713294 99468 sgd_solver.cpp:105] Iteration 26720, lr = 0.001
I0708 09:45:44.931543 99468 solver.cpp:218] Iteration 26760 (0.524826 iter/s, 76.2158s/40 iters), loss = 3.6713
I0708 09:45:44.931784 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5365 (* 0.3 = 0.760949 loss)
I0708 09:45:44.931835 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.52397 (* 0.3 = 0.757192 loss)
I0708 09:45:44.931849 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5234 (* 1 = 2.5234 loss)
I0708 09:45:44.931874 99468 sgd_solver.cpp:105] Iteration 26760, lr = 0.001
I0708 09:47:01.340382 99468 solver.cpp:218] Iteration 26800 (0.523519 iter/s, 76.4061s/40 iters), loss = 3.67274
I0708 09:47:01.340638 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2994 (* 0.3 = 0.689821 loss)
I0708 09:47:01.340664 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30001 (* 0.3 = 0.690004 loss)
I0708 09:47:01.340682 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29077 (* 1 = 2.29077 loss)
I0708 09:47:01.340699 99468 sgd_solver.cpp:105] Iteration 26800, lr = 0.001
I0708 09:48:17.880772 99468 solver.cpp:218] Iteration 26840 (0.522619 iter/s, 76.5376s/40 iters), loss = 3.73945
I0708 09:48:17.880996 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43782 (* 0.3 = 0.731345 loss)
I0708 09:48:17.881016 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44603 (* 0.3 = 0.733809 loss)
I0708 09:48:17.881031 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43389 (* 1 = 2.43389 loss)
I0708 09:48:17.881053 99468 sgd_solver.cpp:105] Iteration 26840, lr = 0.001
I0708 09:49:34.438503 99468 solver.cpp:218] Iteration 26880 (0.5225 iter/s, 76.555s/40 iters), loss = 3.73131
I0708 09:49:34.438735 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.64719 (* 0.3 = 0.794158 loss)
I0708 09:49:34.438792 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.64352 (* 0.3 = 0.793056 loss)
I0708 09:49:34.438807 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.64392 (* 1 = 2.64392 loss)
I0708 09:49:34.438827 99468 sgd_solver.cpp:105] Iteration 26880, lr = 0.001
I0708 09:50:51.005249 99468 solver.cpp:218] Iteration 26920 (0.522439 iter/s, 76.564s/40 iters), loss = 3.69073
I0708 09:50:51.005481 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50767 (* 0.3 = 0.7523 loss)
I0708 09:50:51.005506 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51828 (* 0.3 = 0.755485 loss)
I0708 09:50:51.005548 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51668 (* 1 = 2.51668 loss)
I0708 09:50:51.005571 99468 sgd_solver.cpp:105] Iteration 26920, lr = 0.001
I0708 09:52:07.392501 99468 solver.cpp:218] Iteration 26960 (0.523666 iter/s, 76.3845s/40 iters), loss = 3.66562
I0708 09:52:07.392743 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33668 (* 0.3 = 0.701004 loss)
I0708 09:52:07.392798 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33451 (* 0.3 = 0.700354 loss)
I0708 09:52:07.392813 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32565 (* 1 = 2.32565 loss)
I0708 09:52:07.392832 99468 sgd_solver.cpp:105] Iteration 26960, lr = 0.001
I0708 09:53:23.826151 99468 solver.cpp:218] Iteration 27000 (0.523349 iter/s, 76.4309s/40 iters), loss = 3.66689
I0708 09:53:23.826489 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23772 (* 0.3 = 0.671316 loss)
I0708 09:53:23.826535 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25731 (* 0.3 = 0.677194 loss)
I0708 09:53:23.826550 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24681 (* 1 = 2.24681 loss)
I0708 09:53:23.826575 99468 sgd_solver.cpp:105] Iteration 27000, lr = 0.001
I0708 09:54:40.366250 99468 solver.cpp:218] Iteration 27040 (0.522622 iter/s, 76.5372s/40 iters), loss = 3.67104
I0708 09:54:40.366500 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27728 (* 0.3 = 0.683183 loss)
I0708 09:54:40.366561 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28375 (* 0.3 = 0.685126 loss)
I0708 09:54:40.366577 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27712 (* 1 = 2.27712 loss)
I0708 09:54:40.366598 99468 sgd_solver.cpp:105] Iteration 27040, lr = 0.001
I0708 09:55:56.840679 99468 solver.cpp:218] Iteration 27080 (0.52307 iter/s, 76.4717s/40 iters), loss = 3.70307
I0708 09:55:56.840899 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1131 (* 0.3 = 0.633931 loss)
I0708 09:55:56.840924 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08747 (* 0.3 = 0.626241 loss)
I0708 09:55:56.840968 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09739 (* 1 = 2.09739 loss)
I0708 09:55:56.840986 99468 sgd_solver.cpp:105] Iteration 27080, lr = 0.001
I0708 09:57:13.400833 99468 solver.cpp:218] Iteration 27120 (0.522484 iter/s, 76.5574s/40 iters), loss = 3.68946
I0708 09:57:13.401062 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16114 (* 0.3 = 0.648341 loss)
I0708 09:57:13.401113 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14747 (* 0.3 = 0.644241 loss)
I0708 09:57:13.401126 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14798 (* 1 = 2.14798 loss)
I0708 09:57:13.401147 99468 sgd_solver.cpp:105] Iteration 27120, lr = 0.001
I0708 09:58:29.960767 99468 solver.cpp:218] Iteration 27160 (0.522485 iter/s, 76.5572s/40 iters), loss = 3.68223
I0708 09:58:29.961024 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.57687 (* 0.3 = 0.77306 loss)
I0708 09:58:29.961048 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.60686 (* 0.3 = 0.782058 loss)
I0708 09:58:29.961061 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59699 (* 1 = 2.59699 loss)
I0708 09:58:29.961079 99468 sgd_solver.cpp:105] Iteration 27160, lr = 0.001
I0708 09:59:46.318080 99468 solver.cpp:218] Iteration 27200 (0.523872 iter/s, 76.3545s/40 iters), loss = 3.72564
I0708 09:59:46.318310 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17167 (* 0.3 = 0.651501 loss)
I0708 09:59:46.318332 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17136 (* 0.3 = 0.651407 loss)
I0708 09:59:46.318346 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17039 (* 1 = 2.17039 loss)
I0708 09:59:46.318361 99468 sgd_solver.cpp:105] Iteration 27200, lr = 0.001
I0708 10:01:02.877372 99468 solver.cpp:218] Iteration 27240 (0.52249 iter/s, 76.5565s/40 iters), loss = 3.73009
I0708 10:01:02.877609 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39744 (* 0.3 = 0.719232 loss)
I0708 10:01:02.877631 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41484 (* 0.3 = 0.724453 loss)
I0708 10:01:02.877646 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38682 (* 1 = 2.38682 loss)
I0708 10:01:02.877704 99468 sgd_solver.cpp:105] Iteration 27240, lr = 0.001
I0708 10:02:19.420343 99468 solver.cpp:218] Iteration 27280 (0.522601 iter/s, 76.5402s/40 iters), loss = 3.70523
I0708 10:02:19.420608 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14601 (* 0.3 = 0.643802 loss)
I0708 10:02:19.420636 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13926 (* 0.3 = 0.641778 loss)
I0708 10:02:19.420655 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14284 (* 1 = 2.14284 loss)
I0708 10:02:19.420675 99468 sgd_solver.cpp:105] Iteration 27280, lr = 0.001
I0708 10:03:35.906569 99468 solver.cpp:218] Iteration 27320 (0.522989 iter/s, 76.4834s/40 iters), loss = 3.71287
I0708 10:03:35.906846 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15784 (* 0.3 = 0.647352 loss)
I0708 10:03:35.906904 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.135 (* 0.3 = 0.640499 loss)
I0708 10:03:35.906920 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14591 (* 1 = 2.14591 loss)
I0708 10:03:35.906939 99468 sgd_solver.cpp:105] Iteration 27320, lr = 0.001
I0708 10:04:52.371683 99468 solver.cpp:218] Iteration 27360 (0.523134 iter/s, 76.4623s/40 iters), loss = 3.73448
I0708 10:04:52.371919 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32199 (* 0.3 = 0.696597 loss)
I0708 10:04:52.371944 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32816 (* 0.3 = 0.698447 loss)
I0708 10:04:52.371958 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33388 (* 1 = 2.33388 loss)
I0708 10:04:52.372009 99468 sgd_solver.cpp:105] Iteration 27360, lr = 0.001
I0708 10:05:43.181521 99628 data_layer.cpp:73] Restarting data prefetching from start.
I0708 10:06:08.849828 99468 solver.cpp:218] Iteration 27400 (0.523044 iter/s, 76.4754s/40 iters), loss = 3.68996
I0708 10:06:08.849936 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26627 (* 0.3 = 0.679881 loss)
I0708 10:06:08.849958 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2634 (* 0.3 = 0.679019 loss)
I0708 10:06:08.850008 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26253 (* 1 = 2.26253 loss)
I0708 10:06:08.850028 99468 sgd_solver.cpp:105] Iteration 27400, lr = 0.001
I0708 10:07:25.249866 99468 solver.cpp:218] Iteration 27440 (0.523578 iter/s, 76.3974s/40 iters), loss = 3.72549
I0708 10:07:25.250092 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36049 (* 0.3 = 0.708146 loss)
I0708 10:07:25.250114 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36284 (* 0.3 = 0.708853 loss)
I0708 10:07:25.250130 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35258 (* 1 = 2.35258 loss)
I0708 10:07:25.250146 99468 sgd_solver.cpp:105] Iteration 27440, lr = 0.001
I0708 10:08:41.830545 99468 solver.cpp:218] Iteration 27480 (0.522344 iter/s, 76.5779s/40 iters), loss = 3.68873
I0708 10:08:41.830808 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09514 (* 0.3 = 0.628543 loss)
I0708 10:08:41.830837 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09536 (* 0.3 = 0.628608 loss)
I0708 10:08:41.830857 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08961 (* 1 = 2.08961 loss)
I0708 10:08:41.830875 99468 sgd_solver.cpp:105] Iteration 27480, lr = 0.001
I0708 10:09:58.357542 99468 solver.cpp:218] Iteration 27520 (0.52271 iter/s, 76.5242s/40 iters), loss = 3.70946
I0708 10:09:58.357774 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15176 (* 0.3 = 0.645528 loss)
I0708 10:09:58.357794 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16174 (* 0.3 = 0.648521 loss)
I0708 10:09:58.357808 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15401 (* 1 = 2.15401 loss)
I0708 10:09:58.357826 99468 sgd_solver.cpp:105] Iteration 27520, lr = 0.001
I0708 10:11:14.886525 99468 solver.cpp:218] Iteration 27560 (0.522697 iter/s, 76.5262s/40 iters), loss = 3.69642
I0708 10:11:14.886775 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25129 (* 0.3 = 0.675387 loss)
I0708 10:11:14.886795 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24935 (* 0.3 = 0.674804 loss)
I0708 10:11:14.886809 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25281 (* 1 = 2.25281 loss)
I0708 10:11:14.886826 99468 sgd_solver.cpp:105] Iteration 27560, lr = 0.001
I0708 10:12:31.386265 99468 solver.cpp:218] Iteration 27600 (0.522897 iter/s, 76.4969s/40 iters), loss = 3.70899
I0708 10:12:31.386601 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36237 (* 0.3 = 0.708712 loss)
I0708 10:12:31.386626 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35883 (* 0.3 = 0.707649 loss)
I0708 10:12:31.386642 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34764 (* 1 = 2.34764 loss)
I0708 10:12:31.386658 99468 sgd_solver.cpp:105] Iteration 27600, lr = 0.001
I0708 10:13:47.975843 99468 solver.cpp:218] Iteration 27640 (0.522284 iter/s, 76.5867s/40 iters), loss = 3.69192
I0708 10:13:47.976119 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09361 (* 0.3 = 0.628082 loss)
I0708 10:13:47.976146 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09577 (* 0.3 = 0.628731 loss)
I0708 10:13:47.976166 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09229 (* 1 = 2.09229 loss)
I0708 10:13:47.976186 99468 sgd_solver.cpp:105] Iteration 27640, lr = 0.001
I0708 10:15:04.595258 99468 solver.cpp:218] Iteration 27680 (0.52208 iter/s, 76.6166s/40 iters), loss = 3.75004
I0708 10:15:04.595492 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29861 (* 0.3 = 0.689582 loss)
I0708 10:15:04.595515 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28176 (* 0.3 = 0.684529 loss)
I0708 10:15:04.595526 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28927 (* 1 = 2.28927 loss)
I0708 10:15:04.595543 99468 sgd_solver.cpp:105] Iteration 27680, lr = 0.001
I0708 10:16:21.097398 99468 solver.cpp:218] Iteration 27720 (0.52288 iter/s, 76.4994s/40 iters), loss = 3.70928
I0708 10:16:21.098800 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30757 (* 0.3 = 0.69227 loss)
I0708 10:16:21.098826 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2888 (* 0.3 = 0.68664 loss)
I0708 10:16:21.098841 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.314 (* 1 = 2.314 loss)
I0708 10:16:21.098856 99468 sgd_solver.cpp:105] Iteration 27720, lr = 0.001
I0708 10:17:37.629585 99468 solver.cpp:218] Iteration 27760 (0.522683 iter/s, 76.5283s/40 iters), loss = 3.65135
I0708 10:17:37.629843 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.203 (* 0.3 = 0.660901 loss)
I0708 10:17:37.629866 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20013 (* 0.3 = 0.66004 loss)
I0708 10:17:37.629881 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20479 (* 1 = 2.20479 loss)
I0708 10:17:37.629896 99468 sgd_solver.cpp:105] Iteration 27760, lr = 0.001
I0708 10:18:54.066543 99468 solver.cpp:218] Iteration 27800 (0.523326 iter/s, 76.4342s/40 iters), loss = 3.72737
I0708 10:18:54.066792 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08594 (* 0.3 = 0.625782 loss)
I0708 10:18:54.066843 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.06887 (* 0.3 = 0.62066 loss)
I0708 10:18:54.066857 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07834 (* 1 = 2.07834 loss)
I0708 10:18:54.066879 99468 sgd_solver.cpp:105] Iteration 27800, lr = 0.001
I0708 10:20:10.566148 99468 solver.cpp:218] Iteration 27840 (0.522897 iter/s, 76.4968s/40 iters), loss = 3.70047
I0708 10:20:10.566390 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47924 (* 0.3 = 0.743771 loss)
I0708 10:20:10.566411 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47211 (* 0.3 = 0.741632 loss)
I0708 10:20:10.566426 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46221 (* 1 = 2.46221 loss)
I0708 10:20:10.566443 99468 sgd_solver.cpp:105] Iteration 27840, lr = 0.001
I0708 10:21:27.082767 99468 solver.cpp:218] Iteration 27880 (0.522781 iter/s, 76.5138s/40 iters), loss = 3.72144
I0708 10:21:27.083019 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48478 (* 0.3 = 0.745435 loss)
I0708 10:21:27.083045 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47851 (* 0.3 = 0.743552 loss)
I0708 10:21:27.083062 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48285 (* 1 = 2.48285 loss)
I0708 10:21:27.083078 99468 sgd_solver.cpp:105] Iteration 27880, lr = 0.001
I0708 10:22:43.575135 99468 solver.cpp:218] Iteration 27920 (0.522947 iter/s, 76.4896s/40 iters), loss = 3.7228
I0708 10:22:43.575505 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27036 (* 0.3 = 0.681107 loss)
I0708 10:22:43.575531 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27648 (* 0.3 = 0.682945 loss)
I0708 10:22:43.575548 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27546 (* 1 = 2.27546 loss)
I0708 10:22:43.575578 99468 sgd_solver.cpp:105] Iteration 27920, lr = 0.001
I0708 10:24:00.009928 99468 solver.cpp:218] Iteration 27960 (0.523342 iter/s, 76.4319s/40 iters), loss = 3.73936
I0708 10:24:00.010160 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34485 (* 0.3 = 0.703456 loss)
I0708 10:24:00.010182 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36043 (* 0.3 = 0.708128 loss)
I0708 10:24:00.010197 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36098 (* 1 = 2.36098 loss)
I0708 10:24:00.010215 99468 sgd_solver.cpp:105] Iteration 27960, lr = 0.001
I0708 10:25:14.027935 99468 solver.cpp:330] Iteration 28000, Testing net (#0)
I0708 10:35:45.315973 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07408 (* 0.3 = 0.622223 loss)
I0708 10:35:45.316249 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.366614
I0708 10:35:45.316323 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794409
I0708 10:35:45.316342 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.0739 (* 0.3 = 0.62217 loss)
I0708 10:35:45.316359 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.366614
I0708 10:35:45.316370 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794409
I0708 10:35:45.316385 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07732 (* 1 = 2.07732 loss)
I0708 10:35:45.316400 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.366614
I0708 10:35:45.316411 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794409
I0708 10:35:47.219460 99468 solver.cpp:218] Iteration 28000 (0.0565622 iter/s, 707.186s/40 iters), loss = 3.69569
I0708 10:35:47.219600 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38863 (* 0.3 = 0.716588 loss)
I0708 10:35:47.219672 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38025 (* 0.3 = 0.714074 loss)
I0708 10:35:47.219692 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38549 (* 1 = 2.38549 loss)
I0708 10:35:47.219735 99468 sgd_solver.cpp:105] Iteration 28000, lr = 0.001
I0708 10:37:03.726074 99468 solver.cpp:218] Iteration 28040 (0.522849 iter/s, 76.5039s/40 iters), loss = 3.71287
I0708 10:37:03.726310 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35949 (* 0.3 = 0.707848 loss)
I0708 10:37:03.726332 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36973 (* 0.3 = 0.71092 loss)
I0708 10:37:03.726347 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35856 (* 1 = 2.35856 loss)
I0708 10:37:03.726362 99468 sgd_solver.cpp:105] Iteration 28040, lr = 0.001
I0708 10:38:20.109469 99468 solver.cpp:218] Iteration 28080 (0.523693 iter/s, 76.3806s/40 iters), loss = 3.70383
I0708 10:38:20.109737 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59062 (* 0.3 = 0.777185 loss)
I0708 10:38:20.109805 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61563 (* 0.3 = 0.78469 loss)
I0708 10:38:20.109823 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59214 (* 1 = 2.59214 loss)
I0708 10:38:20.109844 99468 sgd_solver.cpp:105] Iteration 28080, lr = 0.001
I0708 10:39:36.609953 99468 solver.cpp:218] Iteration 28120 (0.522892 iter/s, 76.4977s/40 iters), loss = 3.75914
I0708 10:39:36.610177 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.64673 (* 0.3 = 0.79402 loss)
I0708 10:39:36.610199 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.65606 (* 0.3 = 0.796818 loss)
I0708 10:39:36.610214 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.64839 (* 1 = 2.64839 loss)
I0708 10:39:36.610266 99468 sgd_solver.cpp:105] Iteration 28120, lr = 0.001
I0708 10:40:53.136605 99468 solver.cpp:218] Iteration 28160 (0.522713 iter/s, 76.5239s/40 iters), loss = 3.70578
I0708 10:40:53.136955 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60284 (* 0.3 = 0.780852 loss)
I0708 10:40:53.137017 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62466 (* 0.3 = 0.787397 loss)
I0708 10:40:53.137032 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.61068 (* 1 = 2.61068 loss)
I0708 10:40:53.137068 99468 sgd_solver.cpp:105] Iteration 28160, lr = 0.001
I0708 10:42:09.488271 99468 solver.cpp:218] Iteration 28200 (0.523911 iter/s, 76.3488s/40 iters), loss = 3.7246
I0708 10:42:09.488505 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04162 (* 0.3 = 0.612486 loss)
I0708 10:42:09.488528 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04496 (* 0.3 = 0.613487 loss)
I0708 10:42:09.488543 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02469 (* 1 = 2.02469 loss)
I0708 10:42:09.488564 99468 sgd_solver.cpp:105] Iteration 28200, lr = 0.001
I0708 10:43:25.994092 99468 solver.cpp:218] Iteration 28240 (0.522855 iter/s, 76.5031s/40 iters), loss = 3.7003
I0708 10:43:25.994333 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27517 (* 0.3 = 0.682552 loss)
I0708 10:43:25.994356 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28189 (* 0.3 = 0.684566 loss)
I0708 10:43:25.994372 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28061 (* 1 = 2.28061 loss)
I0708 10:43:25.994390 99468 sgd_solver.cpp:105] Iteration 28240, lr = 0.001
I0708 10:44:42.493434 99468 solver.cpp:218] Iteration 28280 (0.522899 iter/s, 76.4966s/40 iters), loss = 3.71871
I0708 10:44:42.493679 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38399 (* 0.3 = 0.715197 loss)
I0708 10:44:42.493734 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37635 (* 0.3 = 0.712906 loss)
I0708 10:44:42.493748 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.376 (* 1 = 2.376 loss)
I0708 10:44:42.493764 99468 sgd_solver.cpp:105] Iteration 28280, lr = 0.001
I0708 10:45:58.975102 99468 solver.cpp:218] Iteration 28320 (0.52302 iter/s, 76.4789s/40 iters), loss = 3.73041
I0708 10:45:58.975327 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.79927 (* 0.3 = 0.53978 loss)
I0708 10:45:58.975347 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.80761 (* 0.3 = 0.542282 loss)
I0708 10:45:58.975363 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.78893 (* 1 = 1.78893 loss)
I0708 10:45:58.975378 99468 sgd_solver.cpp:105] Iteration 28320, lr = 0.001
I0708 10:47:15.510944 99468 solver.cpp:218] Iteration 28360 (0.52265 iter/s, 76.5331s/40 iters), loss = 3.69803
I0708 10:47:15.511171 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.63799 (* 0.3 = 0.791397 loss)
I0708 10:47:15.511194 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61262 (* 0.3 = 0.783787 loss)
I0708 10:47:15.511209 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62737 (* 1 = 2.62737 loss)
I0708 10:47:15.511225 99468 sgd_solver.cpp:105] Iteration 28360, lr = 0.001
I0708 10:48:31.925660 99468 solver.cpp:218] Iteration 28400 (0.523478 iter/s, 76.412s/40 iters), loss = 3.66937
I0708 10:48:31.925899 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24249 (* 0.3 = 0.672747 loss)
I0708 10:48:31.925954 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23729 (* 0.3 = 0.671187 loss)
I0708 10:48:31.925969 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23332 (* 1 = 2.23332 loss)
I0708 10:48:31.925989 99468 sgd_solver.cpp:105] Iteration 28400, lr = 0.001
I0708 10:49:48.240583 99468 solver.cpp:218] Iteration 28440 (0.524163 iter/s, 76.3122s/40 iters), loss = 3.70516
I0708 10:49:48.240815 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39136 (* 0.3 = 0.717408 loss)
I0708 10:49:48.240870 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3956 (* 0.3 = 0.718679 loss)
I0708 10:49:48.240885 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38691 (* 1 = 2.38691 loss)
I0708 10:49:48.240906 99468 sgd_solver.cpp:105] Iteration 28440, lr = 0.001
I0708 10:51:04.520120 99468 solver.cpp:218] Iteration 28480 (0.524406 iter/s, 76.2768s/40 iters), loss = 3.65412
I0708 10:51:04.520427 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33823 (* 0.3 = 0.701469 loss)
I0708 10:51:04.520452 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32948 (* 0.3 = 0.698845 loss)
I0708 10:51:04.520503 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33014 (* 1 = 2.33014 loss)
I0708 10:51:04.520524 99468 sgd_solver.cpp:105] Iteration 28480, lr = 0.001
I0708 10:52:20.809775 99468 solver.cpp:218] Iteration 28520 (0.524337 iter/s, 76.2868s/40 iters), loss = 3.6938
I0708 10:52:20.810012 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46256 (* 0.3 = 0.738768 loss)
I0708 10:52:20.810035 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48725 (* 0.3 = 0.746175 loss)
I0708 10:52:20.810051 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47518 (* 1 = 2.47518 loss)
I0708 10:52:20.810068 99468 sgd_solver.cpp:105] Iteration 28520, lr = 0.001
I0708 10:53:37.077735 99468 solver.cpp:218] Iteration 28560 (0.524486 iter/s, 76.2652s/40 iters), loss = 3.64786
I0708 10:53:37.078003 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36181 (* 0.3 = 0.708543 loss)
I0708 10:53:37.078032 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35753 (* 0.3 = 0.707258 loss)
I0708 10:53:37.078049 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3523 (* 1 = 2.3523 loss)
I0708 10:53:37.078073 99468 sgd_solver.cpp:105] Iteration 28560, lr = 0.001
I0708 10:54:53.560503 99468 solver.cpp:218] Iteration 28600 (0.523013 iter/s, 76.48s/40 iters), loss = 3.78306
I0708 10:54:53.560750 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.6206 (* 0.3 = 0.786179 loss)
I0708 10:54:53.560802 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62602 (* 0.3 = 0.787806 loss)
I0708 10:54:53.560816 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.63334 (* 1 = 2.63334 loss)
I0708 10:54:53.560833 99468 sgd_solver.cpp:105] Iteration 28600, lr = 0.001
I0708 10:56:10.025154 99468 solver.cpp:218] Iteration 28640 (0.523137 iter/s, 76.4619s/40 iters), loss = 3.66985
I0708 10:56:10.025390 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.80873 (* 0.3 = 0.842618 loss)
I0708 10:56:10.025446 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.80662 (* 0.3 = 0.841987 loss)
I0708 10:56:10.025461 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.80835 (* 1 = 2.80835 loss)
I0708 10:56:10.025478 99468 sgd_solver.cpp:105] Iteration 28640, lr = 0.001
I0708 10:57:26.248608 99468 solver.cpp:218] Iteration 28680 (0.524792 iter/s, 76.2207s/40 iters), loss = 3.65552
I0708 10:57:26.248847 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48599 (* 0.3 = 0.745798 loss)
I0708 10:57:26.248872 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48708 (* 0.3 = 0.746124 loss)
I0708 10:57:26.248884 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47916 (* 1 = 2.47916 loss)
I0708 10:57:26.248905 99468 sgd_solver.cpp:105] Iteration 28680, lr = 0.001
I0708 10:58:42.676900 99468 solver.cpp:218] Iteration 28720 (0.523385 iter/s, 76.4255s/40 iters), loss = 3.69134
I0708 10:58:42.677141 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.97378 (* 0.3 = 0.592133 loss)
I0708 10:58:42.677166 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.97909 (* 0.3 = 0.593728 loss)
I0708 10:58:42.677183 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99162 (* 1 = 1.99162 loss)
I0708 10:58:42.677199 99468 sgd_solver.cpp:105] Iteration 28720, lr = 0.001
I0708 10:59:59.125210 99468 solver.cpp:218] Iteration 28760 (0.523248 iter/s, 76.4455s/40 iters), loss = 3.71973
I0708 10:59:59.125522 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55995 (* 0.3 = 0.767984 loss)
I0708 10:59:59.125543 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.56002 (* 0.3 = 0.768007 loss)
I0708 10:59:59.125564 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55233 (* 1 = 2.55233 loss)
I0708 10:59:59.125581 99468 sgd_solver.cpp:105] Iteration 28760, lr = 0.001
I0708 11:01:15.490506 99468 solver.cpp:218] Iteration 28800 (0.523817 iter/s, 76.3625s/40 iters), loss = 3.68777
I0708 11:01:15.490762 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60711 (* 0.3 = 0.782133 loss)
I0708 11:01:15.490787 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59775 (* 0.3 = 0.779326 loss)
I0708 11:01:15.490803 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.6077 (* 1 = 2.6077 loss)
I0708 11:01:15.490819 99468 sgd_solver.cpp:105] Iteration 28800, lr = 0.001
I0708 11:02:31.816989 99468 solver.cpp:218] Iteration 28840 (0.524084 iter/s, 76.3237s/40 iters), loss = 3.72458
I0708 11:02:31.817242 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02679 (* 0.3 = 0.608036 loss)
I0708 11:02:31.817268 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04096 (* 0.3 = 0.612287 loss)
I0708 11:02:31.817288 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02142 (* 1 = 2.02142 loss)
I0708 11:02:31.817306 99468 sgd_solver.cpp:105] Iteration 28840, lr = 0.001
I0708 11:03:48.109927 99468 solver.cpp:218] Iteration 28880 (0.524314 iter/s, 76.2902s/40 iters), loss = 3.71049
I0708 11:03:48.110152 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08859 (* 0.3 = 0.626577 loss)
I0708 11:03:48.110174 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08955 (* 0.3 = 0.626866 loss)
I0708 11:03:48.110189 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08137 (* 1 = 2.08137 loss)
I0708 11:03:48.110206 99468 sgd_solver.cpp:105] Iteration 28880, lr = 0.001
I0708 11:05:04.586097 99468 solver.cpp:218] Iteration 28920 (0.523058 iter/s, 76.4734s/40 iters), loss = 3.78781
I0708 11:05:04.586328 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.03762 (* 0.3 = 0.611286 loss)
I0708 11:05:04.586381 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.05244 (* 0.3 = 0.615733 loss)
I0708 11:05:04.586396 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04151 (* 1 = 2.04151 loss)
I0708 11:05:04.586416 99468 sgd_solver.cpp:105] Iteration 28920, lr = 0.001
I0708 11:06:21.168560 99468 solver.cpp:218] Iteration 28960 (0.522332 iter/s, 76.5797s/40 iters), loss = 3.73015
I0708 11:06:21.168802 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54223 (* 0.3 = 0.762669 loss)
I0708 11:06:21.168825 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5381 (* 0.3 = 0.761431 loss)
I0708 11:06:21.168839 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51804 (* 1 = 2.51804 loss)
I0708 11:06:21.168855 99468 sgd_solver.cpp:105] Iteration 28960, lr = 0.001
I0708 11:07:37.720957 99468 solver.cpp:218] Iteration 29000 (0.522537 iter/s, 76.5496s/40 iters), loss = 3.68412
I0708 11:07:37.721190 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07634 (* 0.3 = 0.622903 loss)
I0708 11:07:37.721212 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08266 (* 0.3 = 0.624799 loss)
I0708 11:07:37.721227 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.075 (* 1 = 2.075 loss)
I0708 11:07:37.721247 99468 sgd_solver.cpp:105] Iteration 29000, lr = 0.001
I0708 11:08:54.318033 99468 solver.cpp:218] Iteration 29040 (0.522232 iter/s, 76.5943s/40 iters), loss = 3.69669
I0708 11:08:54.318260 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27338 (* 0.3 = 0.682013 loss)
I0708 11:08:54.318282 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2775 (* 0.3 = 0.68325 loss)
I0708 11:08:54.318296 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26428 (* 1 = 2.26428 loss)
I0708 11:08:54.318312 99468 sgd_solver.cpp:105] Iteration 29040, lr = 0.001
I0708 11:10:10.838163 99468 solver.cpp:218] Iteration 29080 (0.522757 iter/s, 76.5174s/40 iters), loss = 3.69322
I0708 11:10:10.838524 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60958 (* 0.3 = 0.782875 loss)
I0708 11:10:10.838558 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62222 (* 0.3 = 0.786667 loss)
I0708 11:10:10.838580 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62322 (* 1 = 2.62322 loss)
I0708 11:10:10.838603 99468 sgd_solver.cpp:105] Iteration 29080, lr = 0.001
I0708 11:11:27.271538 99468 solver.cpp:218] Iteration 29120 (0.523351 iter/s, 76.4305s/40 iters), loss = 3.68894
I0708 11:11:27.271776 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32665 (* 0.3 = 0.697996 loss)
I0708 11:11:27.271839 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33924 (* 0.3 = 0.701773 loss)
I0708 11:11:27.271852 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33211 (* 1 = 2.33211 loss)
I0708 11:11:27.271872 99468 sgd_solver.cpp:105] Iteration 29120, lr = 0.001
I0708 11:12:43.866956 99468 solver.cpp:218] Iteration 29160 (0.522243 iter/s, 76.5927s/40 iters), loss = 3.76204
I0708 11:12:43.867168 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1866 (* 0.3 = 0.65598 loss)
I0708 11:12:43.867195 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17209 (* 0.3 = 0.651628 loss)
I0708 11:12:43.867210 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17881 (* 1 = 2.17881 loss)
I0708 11:12:43.867225 99468 sgd_solver.cpp:105] Iteration 29160, lr = 0.001
I0708 11:14:00.441745 99468 solver.cpp:218] Iteration 29200 (0.522384 iter/s, 76.5721s/40 iters), loss = 3.70259
I0708 11:14:00.441965 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34648 (* 0.3 = 0.703943 loss)
I0708 11:14:00.442024 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34777 (* 0.3 = 0.704331 loss)
I0708 11:14:00.442056 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35146 (* 1 = 2.35146 loss)
I0708 11:14:00.442075 99468 sgd_solver.cpp:105] Iteration 29200, lr = 0.001
I0708 11:15:17.007334 99468 solver.cpp:218] Iteration 29240 (0.522447 iter/s, 76.5628s/40 iters), loss = 3.69001
I0708 11:15:17.007568 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31368 (* 0.3 = 0.694104 loss)
I0708 11:15:17.007594 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3293 (* 0.3 = 0.698791 loss)
I0708 11:15:17.007642 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31167 (* 1 = 2.31167 loss)
I0708 11:15:17.007661 99468 sgd_solver.cpp:105] Iteration 29240, lr = 0.001
I0708 11:16:33.580282 99468 solver.cpp:218] Iteration 29280 (0.522397 iter/s, 76.5702s/40 iters), loss = 3.67639
I0708 11:16:33.580540 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4489 (* 0.3 = 0.734671 loss)
I0708 11:16:33.580579 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46668 (* 0.3 = 0.740003 loss)
I0708 11:16:33.580597 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43288 (* 1 = 2.43288 loss)
I0708 11:16:33.580617 99468 sgd_solver.cpp:105] Iteration 29280, lr = 0.001
I0708 11:17:50.204421 99468 solver.cpp:218] Iteration 29320 (0.522048 iter/s, 76.6213s/40 iters), loss = 3.67407
I0708 11:17:50.204700 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2396 (* 0.3 = 0.67188 loss)
I0708 11:17:50.204730 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2404 (* 0.3 = 0.672119 loss)
I0708 11:17:50.204749 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2299 (* 1 = 2.2299 loss)
I0708 11:17:50.204807 99468 sgd_solver.cpp:105] Iteration 29320, lr = 0.001
I0708 11:19:06.825168 99468 solver.cpp:218] Iteration 29360 (0.522071 iter/s, 76.6179s/40 iters), loss = 3.75243
I0708 11:19:06.825387 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50867 (* 0.3 = 0.752602 loss)
I0708 11:19:06.825408 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51366 (* 0.3 = 0.754098 loss)
I0708 11:19:06.825423 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50443 (* 1 = 2.50443 loss)
I0708 11:19:06.825439 99468 sgd_solver.cpp:105] Iteration 29360, lr = 0.001
I0708 11:20:23.365005 99468 solver.cpp:218] Iteration 29400 (0.522623 iter/s, 76.5371s/40 iters), loss = 3.76193
I0708 11:20:23.365324 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60792 (* 0.3 = 0.782375 loss)
I0708 11:20:23.365350 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59037 (* 0.3 = 0.777113 loss)
I0708 11:20:23.365365 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62814 (* 1 = 2.62814 loss)
I0708 11:20:23.365381 99468 sgd_solver.cpp:105] Iteration 29400, lr = 0.001
I0708 11:21:39.811513 99468 solver.cpp:218] Iteration 29440 (0.523266 iter/s, 76.443s/40 iters), loss = 3.67086
I0708 11:21:39.811746 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15972 (* 0.3 = 0.647915 loss)
I0708 11:21:39.811776 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16934 (* 0.3 = 0.650801 loss)
I0708 11:21:39.811794 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16211 (* 1 = 2.16211 loss)
I0708 11:21:39.811810 99468 sgd_solver.cpp:105] Iteration 29440, lr = 0.001
I0708 11:22:56.223536 99468 solver.cpp:218] Iteration 29480 (0.523497 iter/s, 76.4093s/40 iters), loss = 3.7213
I0708 11:22:56.223763 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34523 (* 0.3 = 0.703568 loss)
I0708 11:22:56.223789 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34385 (* 0.3 = 0.703154 loss)
I0708 11:22:56.223803 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34844 (* 1 = 2.34844 loss)
I0708 11:22:56.223819 99468 sgd_solver.cpp:105] Iteration 29480, lr = 0.001
I0708 11:24:12.677392 99468 solver.cpp:218] Iteration 29520 (0.52321 iter/s, 76.4511s/40 iters), loss = 3.6927
I0708 11:24:12.677649 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36117 (* 0.3 = 0.70835 loss)
I0708 11:24:12.677680 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37466 (* 0.3 = 0.712397 loss)
I0708 11:24:12.677698 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35694 (* 1 = 2.35694 loss)
I0708 11:24:12.677717 99468 sgd_solver.cpp:105] Iteration 29520, lr = 0.001
I0708 11:25:29.204831 99468 solver.cpp:218] Iteration 29560 (0.522707 iter/s, 76.5247s/40 iters), loss = 3.75379
I0708 11:25:29.205070 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36626 (* 0.3 = 0.709878 loss)
I0708 11:25:29.205092 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37332 (* 0.3 = 0.711996 loss)
I0708 11:25:29.205107 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34424 (* 1 = 2.34424 loss)
I0708 11:25:29.205126 99468 sgd_solver.cpp:105] Iteration 29560, lr = 0.001
I0708 11:26:45.788758 99468 solver.cpp:218] Iteration 29600 (0.522322 iter/s, 76.5811s/40 iters), loss = 3.66738
I0708 11:26:45.788995 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09424 (* 0.3 = 0.628271 loss)
I0708 11:26:45.789049 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09021 (* 0.3 = 0.627065 loss)
I0708 11:26:45.789064 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08782 (* 1 = 2.08782 loss)
I0708 11:26:45.789082 99468 sgd_solver.cpp:105] Iteration 29600, lr = 0.001
I0708 11:28:02.355768 99468 solver.cpp:218] Iteration 29640 (0.522437 iter/s, 76.5642s/40 iters), loss = 3.68225
I0708 11:28:02.356011 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10689 (* 0.3 = 0.632067 loss)
I0708 11:28:02.356063 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12235 (* 0.3 = 0.636705 loss)
I0708 11:28:02.356076 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09756 (* 1 = 2.09756 loss)
I0708 11:28:02.356111 99468 sgd_solver.cpp:105] Iteration 29640, lr = 0.001
I0708 11:29:18.838719 99468 solver.cpp:218] Iteration 29680 (0.523011 iter/s, 76.4802s/40 iters), loss = 3.66786
I0708 11:29:18.838946 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18998 (* 0.3 = 0.656994 loss)
I0708 11:29:18.838968 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19437 (* 0.3 = 0.658311 loss)
I0708 11:29:18.838984 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19008 (* 1 = 2.19008 loss)
I0708 11:29:18.839000 99468 sgd_solver.cpp:105] Iteration 29680, lr = 0.001
I0708 11:30:35.217342 99468 solver.cpp:218] Iteration 29720 (0.523726 iter/s, 76.3759s/40 iters), loss = 3.66825
I0708 11:30:35.218999 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65157 (* 0.3 = 0.795472 loss)
I0708 11:30:35.219069 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.67579 (* 0.3 = 0.802737 loss)
I0708 11:30:35.219117 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.65439 (* 1 = 2.65439 loss)
I0708 11:30:35.219163 99468 sgd_solver.cpp:105] Iteration 29720, lr = 0.001
I0708 11:31:51.664639 99468 solver.cpp:218] Iteration 29760 (0.523265 iter/s, 76.4431s/40 iters), loss = 3.71989
I0708 11:31:51.664909 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55664 (* 0.3 = 0.766992 loss)
I0708 11:31:51.664937 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.56058 (* 0.3 = 0.768174 loss)
I0708 11:31:51.664957 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55356 (* 1 = 2.55356 loss)
I0708 11:31:51.665009 99468 sgd_solver.cpp:105] Iteration 29760, lr = 0.001
I0708 11:33:08.183008 99468 solver.cpp:218] Iteration 29800 (0.522769 iter/s, 76.5156s/40 iters), loss = 3.6731
I0708 11:33:08.183271 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31508 (* 0.3 = 0.694523 loss)
I0708 11:33:08.183297 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33805 (* 0.3 = 0.701416 loss)
I0708 11:33:08.183313 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31637 (* 1 = 2.31637 loss)
I0708 11:33:08.183331 99468 sgd_solver.cpp:105] Iteration 29800, lr = 0.001
I0708 11:34:24.771778 99468 solver.cpp:218] Iteration 29840 (0.522289 iter/s, 76.586s/40 iters), loss = 3.68551
I0708 11:34:24.772042 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33348 (* 0.3 = 0.700043 loss)
I0708 11:34:24.772073 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32681 (* 0.3 = 0.698044 loss)
I0708 11:34:24.772090 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32614 (* 1 = 2.32614 loss)
I0708 11:34:24.772110 99468 sgd_solver.cpp:105] Iteration 29840, lr = 0.001
I0708 11:35:41.314374 99468 solver.cpp:218] Iteration 29880 (0.522604 iter/s, 76.5398s/40 iters), loss = 3.67421
I0708 11:35:41.314602 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2163 (* 0.3 = 0.664891 loss)
I0708 11:35:41.314625 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20456 (* 0.3 = 0.661368 loss)
I0708 11:35:41.314677 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20934 (* 1 = 2.20934 loss)
I0708 11:35:41.314695 99468 sgd_solver.cpp:105] Iteration 29880, lr = 0.001
I0708 11:36:57.765652 99468 solver.cpp:218] Iteration 29920 (0.523228 iter/s, 76.4485s/40 iters), loss = 3.68556
I0708 11:36:57.765879 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24724 (* 0.3 = 0.674172 loss)
I0708 11:36:57.765928 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24677 (* 0.3 = 0.674032 loss)
I0708 11:36:57.765959 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24116 (* 1 = 2.24116 loss)
I0708 11:36:57.765976 99468 sgd_solver.cpp:105] Iteration 29920, lr = 0.001
I0708 11:38:14.225898 99468 solver.cpp:218] Iteration 29960 (0.523167 iter/s, 76.4575s/40 iters), loss = 3.75464
I0708 11:38:14.226125 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45961 (* 0.3 = 0.737882 loss)
I0708 11:38:14.226152 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45293 (* 0.3 = 0.735878 loss)
I0708 11:38:14.226166 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46111 (* 1 = 2.46111 loss)
I0708 11:38:14.226182 99468 sgd_solver.cpp:105] Iteration 29960, lr = 0.001
I0708 11:39:30.500859 99468 solver.cpp:218] Iteration 30000 (0.524438 iter/s, 76.2722s/40 iters), loss = 3.68329
I0708 11:39:30.501132 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32665 (* 0.3 = 0.697995 loss)
I0708 11:39:30.501188 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31765 (* 0.3 = 0.695296 loss)
I0708 11:39:30.501204 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32261 (* 1 = 2.32261 loss)
I0708 11:39:30.501221 99468 sgd_solver.cpp:105] Iteration 30000, lr = 0.001
I0708 11:40:46.767123 99468 solver.cpp:218] Iteration 30040 (0.524498 iter/s, 76.2635s/40 iters), loss = 3.72835
I0708 11:40:46.767400 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37778 (* 0.3 = 0.713333 loss)
I0708 11:40:46.767421 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38255 (* 0.3 = 0.714766 loss)
I0708 11:40:46.767436 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3714 (* 1 = 2.3714 loss)
I0708 11:40:46.767453 99468 sgd_solver.cpp:105] Iteration 30040, lr = 0.001
I0708 11:42:03.130436 99468 solver.cpp:218] Iteration 30080 (0.523831 iter/s, 76.3605s/40 iters), loss = 3.70329
I0708 11:42:03.130678 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45337 (* 0.3 = 0.73601 loss)
I0708 11:42:03.130700 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46087 (* 0.3 = 0.738261 loss)
I0708 11:42:03.130750 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46865 (* 1 = 2.46865 loss)
I0708 11:42:03.130769 99468 sgd_solver.cpp:105] Iteration 30080, lr = 0.001
I0708 11:43:19.672298 99468 solver.cpp:218] Iteration 30120 (0.522609 iter/s, 76.5391s/40 iters), loss = 3.75587
I0708 11:43:19.672528 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20149 (* 0.3 = 0.660448 loss)
I0708 11:43:19.672547 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20037 (* 0.3 = 0.660111 loss)
I0708 11:43:19.672567 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20194 (* 1 = 2.20194 loss)
I0708 11:43:19.672585 99468 sgd_solver.cpp:105] Iteration 30120, lr = 0.001
I0708 11:44:36.244635 99468 solver.cpp:218] Iteration 30160 (0.522401 iter/s, 76.5696s/40 iters), loss = 3.71523
I0708 11:44:36.244863 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07141 (* 0.3 = 0.621424 loss)
I0708 11:44:36.244885 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08004 (* 0.3 = 0.624012 loss)
I0708 11:44:36.244899 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07995 (* 1 = 2.07995 loss)
I0708 11:44:36.244916 99468 sgd_solver.cpp:105] Iteration 30160, lr = 0.001
I0708 11:45:52.797741 99468 solver.cpp:218] Iteration 30200 (0.522532 iter/s, 76.5503s/40 iters), loss = 3.71773
I0708 11:45:52.798090 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34191 (* 0.3 = 0.702572 loss)
I0708 11:45:52.798151 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33083 (* 0.3 = 0.699249 loss)
I0708 11:45:52.798187 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33726 (* 1 = 2.33726 loss)
I0708 11:45:52.798225 99468 sgd_solver.cpp:105] Iteration 30200, lr = 0.001
I0708 11:47:09.184568 99468 solver.cpp:218] Iteration 30240 (0.52367 iter/s, 76.384s/40 iters), loss = 3.71341
I0708 11:47:09.184813 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37332 (* 0.3 = 0.711996 loss)
I0708 11:47:09.184839 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37579 (* 0.3 = 0.712737 loss)
I0708 11:47:09.184890 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36847 (* 1 = 2.36847 loss)
I0708 11:47:09.184908 99468 sgd_solver.cpp:105] Iteration 30240, lr = 0.001
I0708 11:48:25.749543 99468 solver.cpp:218] Iteration 30280 (0.522451 iter/s, 76.5622s/40 iters), loss = 3.7676
I0708 11:48:25.749800 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33098 (* 0.3 = 0.699295 loss)
I0708 11:48:25.749826 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34182 (* 0.3 = 0.702547 loss)
I0708 11:48:25.749842 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34431 (* 1 = 2.34431 loss)
I0708 11:48:25.749861 99468 sgd_solver.cpp:105] Iteration 30280, lr = 0.001
I0708 11:49:42.308925 99468 solver.cpp:218] Iteration 30320 (0.522489 iter/s, 76.5566s/40 iters), loss = 3.62997
I0708 11:49:42.309211 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39939 (* 0.3 = 0.719818 loss)
I0708 11:49:42.309265 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40653 (* 0.3 = 0.72196 loss)
I0708 11:49:42.309279 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40091 (* 1 = 2.40091 loss)
I0708 11:49:42.309295 99468 sgd_solver.cpp:105] Iteration 30320, lr = 0.001
I0708 11:50:58.806047 99468 solver.cpp:218] Iteration 30360 (0.522915 iter/s, 76.4943s/40 iters), loss = 3.71062
I0708 11:50:58.806280 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27558 (* 0.3 = 0.682674 loss)
I0708 11:50:58.806301 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29622 (* 0.3 = 0.688867 loss)
I0708 11:50:58.806318 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27515 (* 1 = 2.27515 loss)
I0708 11:50:58.806334 99468 sgd_solver.cpp:105] Iteration 30360, lr = 0.001
I0708 11:52:15.308653 99468 solver.cpp:218] Iteration 30400 (0.522877 iter/s, 76.4999s/40 iters), loss = 3.62999
I0708 11:52:15.308881 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17532 (* 0.3 = 0.652595 loss)
I0708 11:52:15.308902 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21573 (* 0.3 = 0.664718 loss)
I0708 11:52:15.308917 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18894 (* 1 = 2.18894 loss)
I0708 11:52:15.308935 99468 sgd_solver.cpp:105] Iteration 30400, lr = 0.001
I0708 11:53:31.871170 99468 solver.cpp:218] Iteration 30440 (0.522468 iter/s, 76.5598s/40 iters), loss = 3.74586
I0708 11:53:31.871407 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28523 (* 0.3 = 0.68557 loss)
I0708 11:53:31.871464 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28474 (* 0.3 = 0.685423 loss)
I0708 11:53:31.871477 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2895 (* 1 = 2.2895 loss)
I0708 11:53:31.871512 99468 sgd_solver.cpp:105] Iteration 30440, lr = 0.001
I0708 11:54:48.433413 99468 solver.cpp:218] Iteration 30480 (0.52247 iter/s, 76.5595s/40 iters), loss = 3.66003
I0708 11:54:48.433651 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28583 (* 0.3 = 0.685749 loss)
I0708 11:54:48.433676 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28521 (* 0.3 = 0.685564 loss)
I0708 11:54:48.433691 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29231 (* 1 = 2.29231 loss)
I0708 11:54:48.433708 99468 sgd_solver.cpp:105] Iteration 30480, lr = 0.001
I0708 11:56:04.994014 99468 solver.cpp:218] Iteration 30520 (0.522481 iter/s, 76.5578s/40 iters), loss = 3.75117
I0708 11:56:04.994256 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26979 (* 0.3 = 0.680936 loss)
I0708 11:56:04.994310 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28519 (* 0.3 = 0.685557 loss)
I0708 11:56:04.994325 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27107 (* 1 = 2.27107 loss)
I0708 11:56:04.994341 99468 sgd_solver.cpp:105] Iteration 30520, lr = 0.001
I0708 11:57:21.560036 99468 solver.cpp:218] Iteration 30560 (0.522444 iter/s, 76.5632s/40 iters), loss = 3.67727
I0708 11:57:21.560281 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38542 (* 0.3 = 0.715625 loss)
I0708 11:57:21.560305 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37258 (* 0.3 = 0.711774 loss)
I0708 11:57:21.560355 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37819 (* 1 = 2.37819 loss)
I0708 11:57:21.560374 99468 sgd_solver.cpp:105] Iteration 30560, lr = 0.001
I0708 11:58:38.138705 99468 solver.cpp:218] Iteration 30600 (0.522358 iter/s, 76.5759s/40 iters), loss = 3.69813
I0708 11:58:38.138942 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55049 (* 0.3 = 0.765147 loss)
I0708 11:58:38.138965 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53432 (* 0.3 = 0.760297 loss)
I0708 11:58:38.139014 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53708 (* 1 = 2.53708 loss)
I0708 11:58:38.139034 99468 sgd_solver.cpp:105] Iteration 30600, lr = 0.001
I0708 11:59:54.703807 99468 solver.cpp:218] Iteration 30640 (0.52245 iter/s, 76.5623s/40 iters), loss = 3.67962
I0708 11:59:54.704108 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.79741 (* 0.3 = 0.539223 loss)
I0708 11:59:54.704165 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.79578 (* 0.3 = 0.538735 loss)
I0708 11:59:54.704180 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.7855 (* 1 = 1.7855 loss)
I0708 11:59:54.704200 99468 sgd_solver.cpp:105] Iteration 30640, lr = 0.001
I0708 12:01:11.132719 99468 solver.cpp:218] Iteration 30680 (0.523382 iter/s, 76.4261s/40 iters), loss = 3.67923
I0708 12:01:11.132952 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21518 (* 0.3 = 0.664553 loss)
I0708 12:01:11.133011 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20351 (* 0.3 = 0.661054 loss)
I0708 12:01:11.133030 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20843 (* 1 = 2.20843 loss)
I0708 12:01:11.133049 99468 sgd_solver.cpp:105] Iteration 30680, lr = 0.001
I0708 12:02:27.650090 99468 solver.cpp:218] Iteration 30720 (0.522779 iter/s, 76.5141s/40 iters), loss = 3.68631
I0708 12:02:27.650328 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22421 (* 0.3 = 0.667262 loss)
I0708 12:02:27.650382 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23311 (* 0.3 = 0.669933 loss)
I0708 12:02:27.650396 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23015 (* 1 = 2.23015 loss)
I0708 12:02:27.650431 99468 sgd_solver.cpp:105] Iteration 30720, lr = 0.001
I0708 12:03:44.139541 99468 solver.cpp:218] Iteration 30760 (0.522967 iter/s, 76.4867s/40 iters), loss = 3.74695
I0708 12:03:44.139780 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28526 (* 0.3 = 0.685579 loss)
I0708 12:03:44.139807 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2848 (* 0.3 = 0.685439 loss)
I0708 12:03:44.139825 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28831 (* 1 = 2.28831 loss)
I0708 12:03:44.139840 99468 sgd_solver.cpp:105] Iteration 30760, lr = 0.001
I0708 12:05:00.682895 99468 solver.cpp:218] Iteration 30800 (0.522599 iter/s, 76.5406s/40 iters), loss = 3.70327
I0708 12:05:00.683116 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44998 (* 0.3 = 0.734995 loss)
I0708 12:05:00.683137 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42562 (* 0.3 = 0.727686 loss)
I0708 12:05:00.683151 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42935 (* 1 = 2.42935 loss)
I0708 12:05:00.683168 99468 sgd_solver.cpp:105] Iteration 30800, lr = 0.001
I0708 12:06:17.253990 99468 solver.cpp:218] Iteration 30840 (0.522409 iter/s, 76.5683s/40 iters), loss = 3.69735
I0708 12:06:17.254235 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56948 (* 0.3 = 0.770844 loss)
I0708 12:06:17.254292 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57305 (* 0.3 = 0.771914 loss)
I0708 12:06:17.254305 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.57429 (* 1 = 2.57429 loss)
I0708 12:06:17.254323 99468 sgd_solver.cpp:105] Iteration 30840, lr = 0.001
I0708 12:07:33.831343 99468 solver.cpp:218] Iteration 30880 (0.522367 iter/s, 76.5746s/40 iters), loss = 3.67337
I0708 12:07:33.831575 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51508 (* 0.3 = 0.754525 loss)
I0708 12:07:33.831595 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49083 (* 0.3 = 0.747249 loss)
I0708 12:07:33.831609 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49637 (* 1 = 2.49637 loss)
I0708 12:07:33.831627 99468 sgd_solver.cpp:105] Iteration 30880, lr = 0.001
I0708 12:08:50.412415 99468 solver.cpp:218] Iteration 30920 (0.522341 iter/s, 76.5783s/40 iters), loss = 3.71478
I0708 12:08:50.412704 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20015 (* 0.3 = 0.660046 loss)
I0708 12:08:50.412729 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19196 (* 0.3 = 0.657588 loss)
I0708 12:08:50.412744 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18403 (* 1 = 2.18403 loss)
I0708 12:08:50.412762 99468 sgd_solver.cpp:105] Iteration 30920, lr = 0.001
I0708 12:10:06.991886 99468 solver.cpp:218] Iteration 30960 (0.522352 iter/s, 76.5766s/40 iters), loss = 3.76133
I0708 12:10:06.992132 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55956 (* 0.3 = 0.767868 loss)
I0708 12:10:06.992152 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55521 (* 0.3 = 0.766563 loss)
I0708 12:10:06.992168 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55172 (* 1 = 2.55172 loss)
I0708 12:10:06.992187 99468 sgd_solver.cpp:105] Iteration 30960, lr = 0.001
I0708 12:11:23.591487 99468 solver.cpp:218] Iteration 31000 (0.522215 iter/s, 76.5968s/40 iters), loss = 3.67868
I0708 12:11:23.591728 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46231 (* 0.3 = 0.738694 loss)
I0708 12:11:23.591753 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46862 (* 0.3 = 0.740587 loss)
I0708 12:11:23.591768 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45774 (* 1 = 2.45774 loss)
I0708 12:11:23.591784 99468 sgd_solver.cpp:105] Iteration 31000, lr = 0.001
I0708 12:12:40.178350 99468 solver.cpp:218] Iteration 31040 (0.522302 iter/s, 76.5841s/40 iters), loss = 3.67889
I0708 12:12:40.178580 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23408 (* 0.3 = 0.670223 loss)
I0708 12:12:40.178637 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21864 (* 0.3 = 0.665593 loss)
I0708 12:12:40.178650 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21049 (* 1 = 2.21049 loss)
I0708 12:12:40.178666 99468 sgd_solver.cpp:105] Iteration 31040, lr = 0.001
I0708 12:13:56.497833 99468 solver.cpp:218] Iteration 31080 (0.524131 iter/s, 76.3167s/40 iters), loss = 3.68997
I0708 12:13:56.498076 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1669 (* 0.3 = 0.650071 loss)
I0708 12:13:56.498137 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15743 (* 0.3 = 0.647229 loss)
I0708 12:13:56.498152 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15596 (* 1 = 2.15596 loss)
I0708 12:13:56.498170 99468 sgd_solver.cpp:105] Iteration 31080, lr = 0.001
I0708 12:15:12.873139 99468 solver.cpp:218] Iteration 31120 (0.523749 iter/s, 76.3725s/40 iters), loss = 3.75054
I0708 12:15:12.873404 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08005 (* 0.3 = 0.624016 loss)
I0708 12:15:12.873431 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07578 (* 0.3 = 0.622733 loss)
I0708 12:15:12.873450 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09032 (* 1 = 2.09032 loss)
I0708 12:15:12.873469 99468 sgd_solver.cpp:105] Iteration 31120, lr = 0.001
I0708 12:16:29.423218 99468 solver.cpp:218] Iteration 31160 (0.522553 iter/s, 76.5473s/40 iters), loss = 3.72615
I0708 12:16:29.423475 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.71504 (* 0.3 = 0.814513 loss)
I0708 12:16:29.423497 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.70168 (* 0.3 = 0.810503 loss)
I0708 12:16:29.423511 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.70528 (* 1 = 2.70528 loss)
I0708 12:16:29.423527 99468 sgd_solver.cpp:105] Iteration 31160, lr = 0.001
I0708 12:17:45.980660 99468 solver.cpp:218] Iteration 31200 (0.522502 iter/s, 76.5547s/40 iters), loss = 3.70732
I0708 12:17:45.980924 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18123 (* 0.3 = 0.65437 loss)
I0708 12:17:45.980952 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18819 (* 0.3 = 0.656456 loss)
I0708 12:17:45.981012 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1863 (* 1 = 2.1863 loss)
I0708 12:17:45.981029 99468 sgd_solver.cpp:105] Iteration 31200, lr = 0.001
I0708 12:19:02.339944 99468 solver.cpp:218] Iteration 31240 (0.523858 iter/s, 76.3565s/40 iters), loss = 3.69522
I0708 12:19:02.340216 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34779 (* 0.3 = 0.704336 loss)
I0708 12:19:02.340239 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35635 (* 0.3 = 0.706905 loss)
I0708 12:19:02.340253 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35033 (* 1 = 2.35033 loss)
I0708 12:19:02.340272 99468 sgd_solver.cpp:105] Iteration 31240, lr = 0.001
I0708 12:20:18.597357 99468 solver.cpp:218] Iteration 31280 (0.524558 iter/s, 76.2546s/40 iters), loss = 3.75386
I0708 12:20:18.597611 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33772 (* 0.3 = 0.701317 loss)
I0708 12:20:18.597635 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33635 (* 0.3 = 0.700905 loss)
I0708 12:20:18.597652 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33462 (* 1 = 2.33462 loss)
I0708 12:20:18.597669 99468 sgd_solver.cpp:105] Iteration 31280, lr = 0.001
I0708 12:21:35.031878 99468 solver.cpp:218] Iteration 31320 (0.523343 iter/s, 76.4317s/40 iters), loss = 3.68942
I0708 12:21:35.032121 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08042 (* 0.3 = 0.624127 loss)
I0708 12:21:35.032142 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08247 (* 0.3 = 0.624741 loss)
I0708 12:21:35.032155 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0813 (* 1 = 2.0813 loss)
I0708 12:21:35.032173 99468 sgd_solver.cpp:105] Iteration 31320, lr = 0.001
I0708 12:22:51.568117 99468 solver.cpp:218] Iteration 31360 (0.522647 iter/s, 76.5335s/40 iters), loss = 3.73587
I0708 12:22:51.568353 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06435 (* 0.3 = 0.619306 loss)
I0708 12:22:51.568373 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.05187 (* 0.3 = 0.61556 loss)
I0708 12:22:51.568392 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03468 (* 1 = 2.03468 loss)
I0708 12:22:51.568408 99468 sgd_solver.cpp:105] Iteration 31360, lr = 0.001
I0708 12:24:08.108201 99468 solver.cpp:218] Iteration 31400 (0.522621 iter/s, 76.5373s/40 iters), loss = 3.73489
I0708 12:24:08.108429 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28492 (* 0.3 = 0.685477 loss)
I0708 12:24:08.108453 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30027 (* 0.3 = 0.69008 loss)
I0708 12:24:08.108467 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28615 (* 1 = 2.28615 loss)
I0708 12:24:08.108484 99468 sgd_solver.cpp:105] Iteration 31400, lr = 0.001
I0708 12:25:24.700278 99468 solver.cpp:218] Iteration 31440 (0.522266 iter/s, 76.5893s/40 iters), loss = 3.70996
I0708 12:25:24.700518 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23865 (* 0.3 = 0.671596 loss)
I0708 12:25:24.700537 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23347 (* 0.3 = 0.670042 loss)
I0708 12:25:24.700551 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23496 (* 1 = 2.23496 loss)
I0708 12:25:24.700577 99468 sgd_solver.cpp:105] Iteration 31440, lr = 0.001
I0708 12:26:41.281752 99468 solver.cpp:218] Iteration 31480 (0.522338 iter/s, 76.5787s/40 iters), loss = 3.70571
I0708 12:26:41.281981 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22625 (* 0.3 = 0.667876 loss)
I0708 12:26:41.282003 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23316 (* 0.3 = 0.669947 loss)
I0708 12:26:41.282018 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2315 (* 1 = 2.2315 loss)
I0708 12:26:41.282069 99468 sgd_solver.cpp:105] Iteration 31480, lr = 0.001
I0708 12:27:57.867918 99468 solver.cpp:218] Iteration 31520 (0.522306 iter/s, 76.5834s/40 iters), loss = 3.63353
I0708 12:27:57.868149 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17915 (* 0.3 = 0.653745 loss)
I0708 12:27:57.868170 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17123 (* 0.3 = 0.65137 loss)
I0708 12:27:57.868185 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18747 (* 1 = 2.18747 loss)
I0708 12:27:57.868234 99468 sgd_solver.cpp:105] Iteration 31520, lr = 0.001
I0708 12:29:14.446751 99468 solver.cpp:218] Iteration 31560 (0.522356 iter/s, 76.5761s/40 iters), loss = 3.66086
I0708 12:29:14.447036 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22356 (* 0.3 = 0.667067 loss)
I0708 12:29:14.447059 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21384 (* 0.3 = 0.664152 loss)
I0708 12:29:14.447077 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22136 (* 1 = 2.22136 loss)
I0708 12:29:14.447093 99468 sgd_solver.cpp:105] Iteration 31560, lr = 0.001
I0708 12:30:31.002934 99468 solver.cpp:218] Iteration 31600 (0.522511 iter/s, 76.5534s/40 iters), loss = 3.67781
I0708 12:30:31.003190 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37727 (* 0.3 = 0.71318 loss)
I0708 12:30:31.003212 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36742 (* 0.3 = 0.710225 loss)
I0708 12:30:31.003227 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35808 (* 1 = 2.35808 loss)
I0708 12:30:31.003247 99468 sgd_solver.cpp:105] Iteration 31600, lr = 0.001
I0708 12:31:47.549919 99468 solver.cpp:218] Iteration 31640 (0.522574 iter/s, 76.5442s/40 iters), loss = 3.76346
I0708 12:31:47.550158 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5624 (* 0.3 = 0.768721 loss)
I0708 12:31:47.550179 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57021 (* 0.3 = 0.771062 loss)
I0708 12:31:47.550194 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55731 (* 1 = 2.55731 loss)
I0708 12:31:47.550248 99468 sgd_solver.cpp:105] Iteration 31640, lr = 0.001
I0708 12:33:04.125159 99468 solver.cpp:218] Iteration 31680 (0.522381 iter/s, 76.5725s/40 iters), loss = 3.72902
I0708 12:33:04.125389 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.6669 (* 0.3 = 0.800069 loss)
I0708 12:33:04.125411 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.67782 (* 0.3 = 0.803347 loss)
I0708 12:33:04.125425 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.66672 (* 1 = 2.66672 loss)
I0708 12:33:04.125445 99468 sgd_solver.cpp:105] Iteration 31680, lr = 0.001
I0708 12:34:20.434592 99468 solver.cpp:218] Iteration 31720 (0.5242 iter/s, 76.3067s/40 iters), loss = 3.67621
I0708 12:34:20.434839 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34349 (* 0.3 = 0.703046 loss)
I0708 12:34:20.434896 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33815 (* 0.3 = 0.701445 loss)
I0708 12:34:20.434911 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34624 (* 1 = 2.34624 loss)
I0708 12:34:20.434928 99468 sgd_solver.cpp:105] Iteration 31720, lr = 0.001
I0708 12:35:36.998157 99468 solver.cpp:218] Iteration 31760 (0.522461 iter/s, 76.5608s/40 iters), loss = 3.658
I0708 12:35:36.998395 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06657 (* 0.3 = 0.619971 loss)
I0708 12:35:36.998416 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07537 (* 0.3 = 0.622611 loss)
I0708 12:35:36.998430 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.06663 (* 1 = 2.06663 loss)
I0708 12:35:36.998448 99468 sgd_solver.cpp:105] Iteration 31760, lr = 0.001
I0708 12:36:53.559026 99468 solver.cpp:218] Iteration 31800 (0.522479 iter/s, 76.5581s/40 iters), loss = 3.65087
I0708 12:36:53.559269 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5743 (* 0.3 = 0.772291 loss)
I0708 12:36:53.559291 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5603 (* 0.3 = 0.768091 loss)
I0708 12:36:53.559306 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.58299 (* 1 = 2.58299 loss)
I0708 12:36:53.559324 99468 sgd_solver.cpp:105] Iteration 31800, lr = 0.001
I0708 12:38:10.074053 99468 solver.cpp:218] Iteration 31840 (0.522792 iter/s, 76.5123s/40 iters), loss = 3.75556
I0708 12:38:10.074296 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54713 (* 0.3 = 0.764138 loss)
I0708 12:38:10.074348 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.52635 (* 0.3 = 0.757905 loss)
I0708 12:38:10.074362 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53553 (* 1 = 2.53553 loss)
I0708 12:38:10.074379 99468 sgd_solver.cpp:105] Iteration 31840, lr = 0.001
I0708 12:39:26.318150 99468 solver.cpp:218] Iteration 31880 (0.52465 iter/s, 76.2413s/40 iters), loss = 3.7403
I0708 12:39:26.318464 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30173 (* 0.3 = 0.690518 loss)
I0708 12:39:26.318490 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31144 (* 0.3 = 0.693431 loss)
I0708 12:39:26.318506 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30582 (* 1 = 2.30582 loss)
I0708 12:39:26.318523 99468 sgd_solver.cpp:105] Iteration 31880, lr = 0.001
I0708 12:40:42.543020 99468 solver.cpp:218] Iteration 31920 (0.524783 iter/s, 76.222s/40 iters), loss = 3.73549
I0708 12:40:42.543284 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23672 (* 0.3 = 0.671016 loss)
I0708 12:40:42.543308 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22725 (* 0.3 = 0.668175 loss)
I0708 12:40:42.543326 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23021 (* 1 = 2.23021 loss)
I0708 12:40:42.543342 99468 sgd_solver.cpp:105] Iteration 31920, lr = 0.001
I0708 12:41:59.012357 99468 solver.cpp:218] Iteration 31960 (0.523105 iter/s, 76.4666s/40 iters), loss = 3.68595
I0708 12:41:59.012611 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42693 (* 0.3 = 0.72808 loss)
I0708 12:41:59.012635 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43721 (* 0.3 = 0.731162 loss)
I0708 12:41:59.012651 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43144 (* 1 = 2.43144 loss)
I0708 12:41:59.012667 99468 sgd_solver.cpp:105] Iteration 31960, lr = 0.001
I0708 12:43:13.015939 99468 solver.cpp:330] Iteration 32000, Testing net (#0)
I0708 12:53:09.714535 99629 data_layer.cpp:73] Restarting data prefetching from start.
I0708 12:53:39.857003 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07692 (* 0.3 = 0.623076 loss)
I0708 12:53:39.857379 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.367661
I0708 12:53:39.857466 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794589
I0708 12:53:39.857497 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07714 (* 0.3 = 0.623142 loss)
I0708 12:53:39.857522 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.367661
I0708 12:53:39.857570 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794589
I0708 12:53:39.857591 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07638 (* 1 = 2.07638 loss)
I0708 12:53:39.857635 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.367661
I0708 12:53:39.857676 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794589
I0708 12:53:41.758949 99468 solver.cpp:218] Iteration 32000 (0.0569214 iter/s, 702.723s/40 iters), loss = 3.72297
I0708 12:53:41.759057 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07052 (* 0.3 = 0.621156 loss)
I0708 12:53:41.759115 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07508 (* 0.3 = 0.622525 loss)
I0708 12:53:41.759135 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07971 (* 1 = 2.07971 loss)
I0708 12:53:41.759167 99468 sgd_solver.cpp:105] Iteration 32000, lr = 0.001
I0708 12:54:58.323529 99468 solver.cpp:218] Iteration 32040 (0.522453 iter/s, 76.5619s/40 iters), loss = 3.74342
I0708 12:54:58.323761 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5141 (* 0.3 = 0.75423 loss)
I0708 12:54:58.323786 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.52961 (* 0.3 = 0.758883 loss)
I0708 12:54:58.323806 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52038 (* 1 = 2.52038 loss)
I0708 12:54:58.323823 99468 sgd_solver.cpp:105] Iteration 32040, lr = 0.001
I0708 12:56:14.816051 99468 solver.cpp:218] Iteration 32080 (0.522946 iter/s, 76.4898s/40 iters), loss = 3.70515
I0708 12:56:14.816313 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36798 (* 0.3 = 0.710393 loss)
I0708 12:56:14.816375 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36847 (* 0.3 = 0.71054 loss)
I0708 12:56:14.816388 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36226 (* 1 = 2.36226 loss)
I0708 12:56:14.816406 99468 sgd_solver.cpp:105] Iteration 32080, lr = 0.001
I0708 12:57:31.042943 99468 solver.cpp:218] Iteration 32120 (0.524768 iter/s, 76.2241s/40 iters), loss = 3.73258
I0708 12:57:31.043196 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1991 (* 0.3 = 0.65973 loss)
I0708 12:57:31.043251 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18891 (* 0.3 = 0.656674 loss)
I0708 12:57:31.043267 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20134 (* 1 = 2.20134 loss)
I0708 12:57:31.043284 99468 sgd_solver.cpp:105] Iteration 32120, lr = 0.001
I0708 12:58:47.554855 99468 solver.cpp:218] Iteration 32160 (0.522813 iter/s, 76.5091s/40 iters), loss = 3.66714
I0708 12:58:47.555083 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26478 (* 0.3 = 0.679435 loss)
I0708 12:58:47.555140 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25024 (* 0.3 = 0.675073 loss)
I0708 12:58:47.555155 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26278 (* 1 = 2.26278 loss)
I0708 12:58:47.555171 99468 sgd_solver.cpp:105] Iteration 32160, lr = 0.001
I0708 13:00:04.072010 99468 solver.cpp:218] Iteration 32200 (0.522777 iter/s, 76.5144s/40 iters), loss = 3.70783
I0708 13:00:04.072242 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11847 (* 0.3 = 0.635541 loss)
I0708 13:00:04.072269 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11089 (* 0.3 = 0.633266 loss)
I0708 13:00:04.072285 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11206 (* 1 = 2.11206 loss)
I0708 13:00:04.072302 99468 sgd_solver.cpp:105] Iteration 32200, lr = 0.001
I0708 13:01:20.573284 99468 solver.cpp:218] Iteration 32240 (0.522886 iter/s, 76.4985s/40 iters), loss = 3.67052
I0708 13:01:20.573511 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28596 (* 0.3 = 0.685788 loss)
I0708 13:01:20.573535 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28652 (* 0.3 = 0.685956 loss)
I0708 13:01:20.573549 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28292 (* 1 = 2.28292 loss)
I0708 13:01:20.573573 99468 sgd_solver.cpp:105] Iteration 32240, lr = 0.001
I0708 13:02:36.816205 99468 solver.cpp:218] Iteration 32280 (0.524658 iter/s, 76.2402s/40 iters), loss = 3.73968
I0708 13:02:36.816433 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46424 (* 0.3 = 0.739271 loss)
I0708 13:02:36.816457 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.457 (* 0.3 = 0.737101 loss)
I0708 13:02:36.816474 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45976 (* 1 = 2.45976 loss)
I0708 13:02:36.816493 99468 sgd_solver.cpp:105] Iteration 32280, lr = 0.001
I0708 13:03:53.106621 99468 solver.cpp:218] Iteration 32320 (0.524331 iter/s, 76.2877s/40 iters), loss = 3.65514
I0708 13:03:53.106845 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07813 (* 0.3 = 0.62344 loss)
I0708 13:03:53.106868 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07508 (* 0.3 = 0.622525 loss)
I0708 13:03:53.106883 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07273 (* 1 = 2.07273 loss)
I0708 13:03:53.106899 99468 sgd_solver.cpp:105] Iteration 32320, lr = 0.001
I0708 13:05:09.398262 99468 solver.cpp:218] Iteration 32360 (0.524323 iter/s, 76.2889s/40 iters), loss = 3.72485
I0708 13:05:09.398478 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3561 (* 0.3 = 0.70683 loss)
I0708 13:05:09.398502 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36162 (* 0.3 = 0.708485 loss)
I0708 13:05:09.398550 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36071 (* 1 = 2.36071 loss)
I0708 13:05:09.398573 99468 sgd_solver.cpp:105] Iteration 32360, lr = 0.001
I0708 13:06:25.638816 99468 solver.cpp:218] Iteration 32400 (0.524693 iter/s, 76.2351s/40 iters), loss = 3.69339
I0708 13:06:25.639075 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41873 (* 0.3 = 0.72562 loss)
I0708 13:06:25.639137 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41686 (* 0.3 = 0.725057 loss)
I0708 13:06:25.639169 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41396 (* 1 = 2.41396 loss)
I0708 13:06:25.639188 99468 sgd_solver.cpp:105] Iteration 32400, lr = 0.001
I0708 13:07:41.857422 99468 solver.cpp:218] Iteration 32440 (0.524825 iter/s, 76.2158s/40 iters), loss = 3.71789
I0708 13:07:41.857651 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23074 (* 0.3 = 0.669222 loss)
I0708 13:07:41.857677 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20765 (* 0.3 = 0.662295 loss)
I0708 13:07:41.857727 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22184 (* 1 = 2.22184 loss)
I0708 13:07:41.857744 99468 sgd_solver.cpp:105] Iteration 32440, lr = 0.001
I0708 13:08:58.373004 99468 solver.cpp:218] Iteration 32480 (0.522788 iter/s, 76.5128s/40 iters), loss = 3.66379
I0708 13:08:58.373246 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.63994 (* 0.3 = 0.791981 loss)
I0708 13:08:58.373303 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.6331 (* 0.3 = 0.789931 loss)
I0708 13:08:58.373319 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.62906 (* 1 = 2.62906 loss)
I0708 13:08:58.373337 99468 sgd_solver.cpp:105] Iteration 32480, lr = 0.001
I0708 13:10:14.934540 99468 solver.cpp:218] Iteration 32520 (0.522474 iter/s, 76.5588s/40 iters), loss = 3.66833
I0708 13:10:14.934788 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9767 (* 0.3 = 0.593009 loss)
I0708 13:10:14.934813 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.98871 (* 0.3 = 0.596612 loss)
I0708 13:10:14.934862 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.98229 (* 1 = 1.98229 loss)
I0708 13:10:14.934880 99468 sgd_solver.cpp:105] Iteration 32520, lr = 0.001
I0708 13:11:31.473666 99468 solver.cpp:218] Iteration 32560 (0.522627 iter/s, 76.5364s/40 iters), loss = 3.68719
I0708 13:11:31.473898 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.94401 (* 0.3 = 0.583204 loss)
I0708 13:11:31.473925 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.95071 (* 0.3 = 0.585212 loss)
I0708 13:11:31.473940 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.93956 (* 1 = 1.93956 loss)
I0708 13:11:31.473958 99468 sgd_solver.cpp:105] Iteration 32560, lr = 0.001
I0708 13:12:48.064322 99468 solver.cpp:218] Iteration 32600 (0.522276 iter/s, 76.5879s/40 iters), loss = 3.71827
I0708 13:12:48.064561 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31772 (* 0.3 = 0.695317 loss)
I0708 13:12:48.064586 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32269 (* 0.3 = 0.696806 loss)
I0708 13:12:48.064600 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32214 (* 1 = 2.32214 loss)
I0708 13:12:48.064615 99468 sgd_solver.cpp:105] Iteration 32600, lr = 0.001
I0708 13:14:04.612562 99468 solver.cpp:218] Iteration 32640 (0.522565 iter/s, 76.5455s/40 iters), loss = 3.64603
I0708 13:14:04.612798 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27622 (* 0.3 = 0.682867 loss)
I0708 13:14:04.612824 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27672 (* 0.3 = 0.683016 loss)
I0708 13:14:04.612871 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2682 (* 1 = 2.2682 loss)
I0708 13:14:04.612888 99468 sgd_solver.cpp:105] Iteration 32640, lr = 0.001
I0708 13:15:21.144052 99468 solver.cpp:218] Iteration 32680 (0.52268 iter/s, 76.5287s/40 iters), loss = 3.73846
I0708 13:15:21.144287 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33498 (* 0.3 = 0.700495 loss)
I0708 13:15:21.144309 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3184 (* 0.3 = 0.695521 loss)
I0708 13:15:21.144325 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31785 (* 1 = 2.31785 loss)
I0708 13:15:21.144342 99468 sgd_solver.cpp:105] Iteration 32680, lr = 0.001
I0708 13:16:37.722846 99468 solver.cpp:218] Iteration 32720 (0.522357 iter/s, 76.576s/40 iters), loss = 3.72081
I0708 13:16:37.723114 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.81032 (* 0.3 = 0.843095 loss)
I0708 13:16:37.723136 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.79092 (* 0.3 = 0.837276 loss)
I0708 13:16:37.723151 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.81409 (* 1 = 2.81409 loss)
I0708 13:16:37.723168 99468 sgd_solver.cpp:105] Iteration 32720, lr = 0.001
I0708 13:17:54.298231 99468 solver.cpp:218] Iteration 32760 (0.52238 iter/s, 76.5726s/40 iters), loss = 3.70832
I0708 13:17:54.298456 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2565 (* 0.3 = 0.676949 loss)
I0708 13:17:54.298478 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25812 (* 0.3 = 0.677435 loss)
I0708 13:17:54.298493 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27234 (* 1 = 2.27234 loss)
I0708 13:17:54.298511 99468 sgd_solver.cpp:105] Iteration 32760, lr = 0.001
I0708 13:19:10.755717 99468 solver.cpp:218] Iteration 32800 (0.523185 iter/s, 76.4547s/40 iters), loss = 3.67759
I0708 13:19:10.755933 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26615 (* 0.3 = 0.679844 loss)
I0708 13:19:10.755959 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27745 (* 0.3 = 0.683234 loss)
I0708 13:19:10.755973 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28319 (* 1 = 2.28319 loss)
I0708 13:19:10.755990 99468 sgd_solver.cpp:105] Iteration 32800, lr = 0.001
I0708 13:20:27.335739 99468 solver.cpp:218] Iteration 32840 (0.522348 iter/s, 76.5773s/40 iters), loss = 3.70604
I0708 13:20:27.335978 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47542 (* 0.3 = 0.742627 loss)
I0708 13:20:27.336002 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47167 (* 0.3 = 0.7415 loss)
I0708 13:20:27.336051 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4747 (* 1 = 2.4747 loss)
I0708 13:20:27.336072 99468 sgd_solver.cpp:105] Iteration 32840, lr = 0.001
I0708 13:21:43.877719 99468 solver.cpp:218] Iteration 32880 (0.522608 iter/s, 76.5392s/40 iters), loss = 3.80907
I0708 13:21:43.877954 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.58953 (* 0.3 = 0.776859 loss)
I0708 13:21:43.877976 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58317 (* 0.3 = 0.774951 loss)
I0708 13:21:43.877991 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.58147 (* 1 = 2.58147 loss)
I0708 13:21:43.878010 99468 sgd_solver.cpp:105] Iteration 32880, lr = 0.001
I0708 13:23:00.409637 99468 solver.cpp:218] Iteration 32920 (0.522677 iter/s, 76.5292s/40 iters), loss = 3.71681
I0708 13:23:00.409873 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41331 (* 0.3 = 0.723993 loss)
I0708 13:23:00.409898 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40721 (* 0.3 = 0.722163 loss)
I0708 13:23:00.409914 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40611 (* 1 = 2.40611 loss)
I0708 13:23:00.409929 99468 sgd_solver.cpp:105] Iteration 32920, lr = 0.001
I0708 13:24:16.744354 99468 solver.cpp:218] Iteration 32960 (0.524027 iter/s, 76.332s/40 iters), loss = 3.69165
I0708 13:24:16.744590 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4801 (* 0.3 = 0.744031 loss)
I0708 13:24:16.744617 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48426 (* 0.3 = 0.745279 loss)
I0708 13:24:16.744663 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48374 (* 1 = 2.48374 loss)
I0708 13:24:16.744680 99468 sgd_solver.cpp:105] Iteration 32960, lr = 0.001
I0708 13:25:33.315912 99468 solver.cpp:218] Iteration 33000 (0.522406 iter/s, 76.5688s/40 iters), loss = 3.68223
I0708 13:25:33.316134 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.99553 (* 0.3 = 0.598659 loss)
I0708 13:25:33.316184 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.98576 (* 0.3 = 0.595728 loss)
I0708 13:25:33.316215 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99105 (* 1 = 1.99105 loss)
I0708 13:25:33.316232 99468 sgd_solver.cpp:105] Iteration 33000, lr = 0.001
I0708 13:26:49.603837 99468 solver.cpp:218] Iteration 33040 (0.524348 iter/s, 76.2852s/40 iters), loss = 3.67897
I0708 13:26:49.604145 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26827 (* 0.3 = 0.680482 loss)
I0708 13:26:49.604179 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26628 (* 0.3 = 0.679885 loss)
I0708 13:26:49.604198 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27241 (* 1 = 2.27241 loss)
I0708 13:26:49.604220 99468 sgd_solver.cpp:105] Iteration 33040, lr = 0.001
I0708 13:28:05.866631 99468 solver.cpp:218] Iteration 33080 (0.524521 iter/s, 76.26s/40 iters), loss = 3.6906
I0708 13:28:05.866864 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46854 (* 0.3 = 0.740563 loss)
I0708 13:28:05.866885 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48467 (* 0.3 = 0.745402 loss)
I0708 13:28:05.866900 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4896 (* 1 = 2.4896 loss)
I0708 13:28:05.866919 99468 sgd_solver.cpp:105] Iteration 33080, lr = 0.001
I0708 13:29:22.114400 99468 solver.cpp:218] Iteration 33120 (0.524624 iter/s, 76.245s/40 iters), loss = 3.69194
I0708 13:29:22.114694 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.98396 (* 0.3 = 0.595189 loss)
I0708 13:29:22.114717 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.97423 (* 0.3 = 0.59227 loss)
I0708 13:29:22.114735 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.9899 (* 1 = 1.9899 loss)
I0708 13:29:22.114753 99468 sgd_solver.cpp:105] Iteration 33120, lr = 0.001
I0708 13:30:38.594488 99468 solver.cpp:218] Iteration 33160 (0.523031 iter/s, 76.4773s/40 iters), loss = 3.69943
I0708 13:30:38.594732 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51112 (* 0.3 = 0.753337 loss)
I0708 13:30:38.594753 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51023 (* 0.3 = 0.75307 loss)
I0708 13:30:38.594772 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50781 (* 1 = 2.50781 loss)
I0708 13:30:38.594789 99468 sgd_solver.cpp:105] Iteration 33160, lr = 0.001
I0708 13:31:55.166738 99468 solver.cpp:218] Iteration 33200 (0.522401 iter/s, 76.5695s/40 iters), loss = 3.71068
I0708 13:31:55.166977 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52648 (* 0.3 = 0.757944 loss)
I0708 13:31:55.166996 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51323 (* 0.3 = 0.753969 loss)
I0708 13:31:55.167011 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51895 (* 1 = 2.51895 loss)
I0708 13:31:55.167026 99468 sgd_solver.cpp:105] Iteration 33200, lr = 0.001
I0708 13:33:11.740839 99468 solver.cpp:218] Iteration 33240 (0.522389 iter/s, 76.5713s/40 iters), loss = 3.70831
I0708 13:33:11.741065 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4862 (* 0.3 = 0.745861 loss)
I0708 13:33:11.741086 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46774 (* 0.3 = 0.740322 loss)
I0708 13:33:11.741102 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48072 (* 1 = 2.48072 loss)
I0708 13:33:11.741160 99468 sgd_solver.cpp:105] Iteration 33240, lr = 0.001
I0708 13:34:28.099653 99468 solver.cpp:218] Iteration 33280 (0.523861 iter/s, 76.3561s/40 iters), loss = 3.68421
I0708 13:34:28.099882 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34707 (* 0.3 = 0.704121 loss)
I0708 13:34:28.099905 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34688 (* 0.3 = 0.704064 loss)
I0708 13:34:28.099920 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34585 (* 1 = 2.34585 loss)
I0708 13:34:28.099937 99468 sgd_solver.cpp:105] Iteration 33280, lr = 0.001
I0708 13:35:44.652559 99468 solver.cpp:218] Iteration 33320 (0.522533 iter/s, 76.5501s/40 iters), loss = 3.67585
I0708 13:35:44.652829 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48213 (* 0.3 = 0.744639 loss)
I0708 13:35:44.652887 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47992 (* 0.3 = 0.743977 loss)
I0708 13:35:44.652902 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47168 (* 1 = 2.47168 loss)
I0708 13:35:44.652920 99468 sgd_solver.cpp:105] Iteration 33320, lr = 0.001
I0708 13:37:01.138547 99468 solver.cpp:218] Iteration 33360 (0.522991 iter/s, 76.4832s/40 iters), loss = 3.73183
I0708 13:37:01.141480 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9444 (* 0.3 = 0.583319 loss)
I0708 13:37:01.141541 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.933 (* 0.3 = 0.579899 loss)
I0708 13:37:01.141559 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.93422 (* 1 = 1.93422 loss)
I0708 13:37:01.141578 99468 sgd_solver.cpp:105] Iteration 33360, lr = 0.001
I0708 13:38:17.714077 99468 solver.cpp:218] Iteration 33400 (0.522397 iter/s, 76.5701s/40 iters), loss = 3.70595
I0708 13:38:17.714304 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.87305 (* 0.3 = 0.561916 loss)
I0708 13:38:17.714325 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.88225 (* 0.3 = 0.564675 loss)
I0708 13:38:17.714340 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.88937 (* 1 = 1.88937 loss)
I0708 13:38:17.714359 99468 sgd_solver.cpp:105] Iteration 33400, lr = 0.001
I0708 13:39:34.260697 99468 solver.cpp:218] Iteration 33440 (0.522576 iter/s, 76.5439s/40 iters), loss = 3.71517
I0708 13:39:34.260934 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01823 (* 0.3 = 0.605469 loss)
I0708 13:39:34.260998 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04453 (* 0.3 = 0.613359 loss)
I0708 13:39:34.261011 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03061 (* 1 = 2.03061 loss)
I0708 13:39:34.261030 99468 sgd_solver.cpp:105] Iteration 33440, lr = 0.001
I0708 13:40:50.621315 99468 solver.cpp:218] Iteration 33480 (0.523849 iter/s, 76.3579s/40 iters), loss = 3.69876
I0708 13:40:50.621537 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34477 (* 0.3 = 0.703432 loss)
I0708 13:40:50.621565 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31717 (* 0.3 = 0.695151 loss)
I0708 13:40:50.621580 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32178 (* 1 = 2.32178 loss)
I0708 13:40:50.621598 99468 sgd_solver.cpp:105] Iteration 33480, lr = 0.001
I0708 13:42:07.018987 99468 solver.cpp:218] Iteration 33520 (0.523595 iter/s, 76.3949s/40 iters), loss = 3.72663
I0708 13:42:07.019217 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46912 (* 0.3 = 0.740735 loss)
I0708 13:42:07.019276 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45918 (* 0.3 = 0.737755 loss)
I0708 13:42:07.019291 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4642 (* 1 = 2.4642 loss)
I0708 13:42:07.019307 99468 sgd_solver.cpp:105] Iteration 33520, lr = 0.001
I0708 13:43:23.559182 99468 solver.cpp:218] Iteration 33560 (0.52262 iter/s, 76.5374s/40 iters), loss = 3.76018
I0708 13:43:23.559413 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42349 (* 0.3 = 0.727048 loss)
I0708 13:43:23.559440 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41346 (* 0.3 = 0.724037 loss)
I0708 13:43:23.559494 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42564 (* 1 = 2.42564 loss)
I0708 13:43:23.559510 99468 sgd_solver.cpp:105] Iteration 33560, lr = 0.001
I0708 13:44:39.821749 99468 solver.cpp:218] Iteration 33600 (0.524523 iter/s, 76.2598s/40 iters), loss = 3.72131
I0708 13:44:39.821969 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.91978 (* 0.3 = 0.875934 loss)
I0708 13:44:39.821993 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.89402 (* 0.3 = 0.868206 loss)
I0708 13:44:39.822042 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.91616 (* 1 = 2.91616 loss)
I0708 13:44:39.822062 99468 sgd_solver.cpp:105] Iteration 33600, lr = 0.001
I0708 13:45:56.149986 99468 solver.cpp:218] Iteration 33640 (0.524071 iter/s, 76.3255s/40 iters), loss = 3.73001
I0708 13:45:56.150260 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08364 (* 0.3 = 0.625092 loss)
I0708 13:45:56.150321 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09175 (* 0.3 = 0.627526 loss)
I0708 13:45:56.150336 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09274 (* 1 = 2.09274 loss)
I0708 13:45:56.150357 99468 sgd_solver.cpp:105] Iteration 33640, lr = 0.001
I0708 13:47:12.719432 99468 solver.cpp:218] Iteration 33680 (0.522421 iter/s, 76.5666s/40 iters), loss = 3.69542
I0708 13:47:12.719672 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.73854 (* 0.3 = 0.821562 loss)
I0708 13:47:12.719698 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.7577 (* 0.3 = 0.827309 loss)
I0708 13:47:12.719717 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.73161 (* 1 = 2.73161 loss)
I0708 13:47:12.719733 99468 sgd_solver.cpp:105] Iteration 33680, lr = 0.001
I0708 13:48:29.266253 99468 solver.cpp:218] Iteration 33720 (0.522575 iter/s, 76.544s/40 iters), loss = 3.65202
I0708 13:48:29.266492 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26535 (* 0.3 = 0.679605 loss)
I0708 13:48:29.266551 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26284 (* 0.3 = 0.678852 loss)
I0708 13:48:29.266573 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24984 (* 1 = 2.24984 loss)
I0708 13:48:29.266589 99468 sgd_solver.cpp:105] Iteration 33720, lr = 0.001
I0708 13:49:45.550061 99468 solver.cpp:218] Iteration 33760 (0.524377 iter/s, 76.281s/40 iters), loss = 3.70546
I0708 13:49:45.550283 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25286 (* 0.3 = 0.675857 loss)
I0708 13:49:45.550338 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2515 (* 0.3 = 0.67545 loss)
I0708 13:49:45.550354 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2498 (* 1 = 2.2498 loss)
I0708 13:49:45.550374 99468 sgd_solver.cpp:105] Iteration 33760, lr = 0.001
I0708 13:51:02.133445 99468 solver.cpp:218] Iteration 33800 (0.522325 iter/s, 76.5806s/40 iters), loss = 3.70113
I0708 13:51:02.133703 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27677 (* 0.3 = 0.68303 loss)
I0708 13:51:02.133766 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27554 (* 0.3 = 0.682664 loss)
I0708 13:51:02.133800 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.274 (* 1 = 2.274 loss)
I0708 13:51:02.133818 99468 sgd_solver.cpp:105] Iteration 33800, lr = 0.001
I0708 13:52:18.698355 99468 solver.cpp:218] Iteration 33840 (0.522451 iter/s, 76.5621s/40 iters), loss = 3.63818
I0708 13:52:18.698599 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29949 (* 0.3 = 0.689847 loss)
I0708 13:52:18.698622 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29314 (* 0.3 = 0.687942 loss)
I0708 13:52:18.698637 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29738 (* 1 = 2.29738 loss)
I0708 13:52:18.698657 99468 sgd_solver.cpp:105] Iteration 33840, lr = 0.001
I0708 13:53:35.220510 99468 solver.cpp:218] Iteration 33880 (0.522743 iter/s, 76.5194s/40 iters), loss = 3.6981
I0708 13:53:35.220749 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48101 (* 0.3 = 0.744304 loss)
I0708 13:53:35.220774 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48314 (* 0.3 = 0.744942 loss)
I0708 13:53:35.220827 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47877 (* 1 = 2.47877 loss)
I0708 13:53:35.220844 99468 sgd_solver.cpp:105] Iteration 33880, lr = 0.001
I0708 13:54:51.475055 99468 solver.cpp:218] Iteration 33920 (0.524578 iter/s, 76.2518s/40 iters), loss = 3.65713
I0708 13:54:51.475278 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50264 (* 0.3 = 0.750793 loss)
I0708 13:54:51.475301 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49248 (* 0.3 = 0.747745 loss)
I0708 13:54:51.475349 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49493 (* 1 = 2.49493 loss)
I0708 13:54:51.475369 99468 sgd_solver.cpp:105] Iteration 33920, lr = 0.001
I0708 13:56:07.763659 99468 solver.cpp:218] Iteration 33960 (0.524344 iter/s, 76.2859s/40 iters), loss = 3.705
I0708 13:56:07.763931 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17228 (* 0.3 = 0.651685 loss)
I0708 13:56:07.763957 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1744 (* 0.3 = 0.652319 loss)
I0708 13:56:07.763977 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17399 (* 1 = 2.17399 loss)
I0708 13:56:07.763993 99468 sgd_solver.cpp:105] Iteration 33960, lr = 0.001
I0708 13:57:24.096781 99468 solver.cpp:218] Iteration 34000 (0.524038 iter/s, 76.3303s/40 iters), loss = 3.63486
I0708 13:57:24.097050 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28755 (* 0.3 = 0.686265 loss)
I0708 13:57:24.097079 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28099 (* 0.3 = 0.684296 loss)
I0708 13:57:24.097095 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28509 (* 1 = 2.28509 loss)
I0708 13:57:24.097111 99468 sgd_solver.cpp:105] Iteration 34000, lr = 0.001
I0708 13:58:40.380492 99468 solver.cpp:218] Iteration 34040 (0.524377 iter/s, 76.2809s/40 iters), loss = 3.69043
I0708 13:58:40.380717 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56343 (* 0.3 = 0.76903 loss)
I0708 13:58:40.380741 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.56003 (* 0.3 = 0.768009 loss)
I0708 13:58:40.380791 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.56345 (* 1 = 2.56345 loss)
I0708 13:58:40.380810 99468 sgd_solver.cpp:105] Iteration 34040, lr = 0.001
I0708 13:59:56.899963 99468 solver.cpp:218] Iteration 34080 (0.522762 iter/s, 76.5167s/40 iters), loss = 3.67429
I0708 13:59:56.900194 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04056 (* 0.3 = 0.612167 loss)
I0708 13:59:56.900250 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03246 (* 0.3 = 0.609737 loss)
I0708 13:59:56.900264 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02436 (* 1 = 2.02436 loss)
I0708 13:59:56.900285 99468 sgd_solver.cpp:105] Iteration 34080, lr = 0.001
I0708 14:01:13.435932 99468 solver.cpp:218] Iteration 34120 (0.522649 iter/s, 76.5332s/40 iters), loss = 3.70178
I0708 14:01:13.436187 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30187 (* 0.3 = 0.69056 loss)
I0708 14:01:13.436249 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31867 (* 0.3 = 0.695601 loss)
I0708 14:01:13.436281 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30927 (* 1 = 2.30927 loss)
I0708 14:01:13.436312 99468 sgd_solver.cpp:105] Iteration 34120, lr = 0.001
I0708 14:02:29.935781 99468 solver.cpp:218] Iteration 34160 (0.522896 iter/s, 76.4971s/40 iters), loss = 3.68544
I0708 14:02:29.936009 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33221 (* 0.3 = 0.699662 loss)
I0708 14:02:29.936036 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35215 (* 0.3 = 0.705645 loss)
I0708 14:02:29.936080 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33853 (* 1 = 2.33853 loss)
I0708 14:02:29.936098 99468 sgd_solver.cpp:105] Iteration 34160, lr = 0.001
I0708 14:03:46.455274 99468 solver.cpp:218] Iteration 34200 (0.522761 iter/s, 76.5167s/40 iters), loss = 3.66896
I0708 14:03:46.455493 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38117 (* 0.3 = 0.71435 loss)
I0708 14:03:46.455515 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38669 (* 0.3 = 0.716007 loss)
I0708 14:03:46.455530 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39175 (* 1 = 2.39175 loss)
I0708 14:03:46.455548 99468 sgd_solver.cpp:105] Iteration 34200, lr = 0.001
I0708 14:05:03.047639 99468 solver.cpp:218] Iteration 34240 (0.522264 iter/s, 76.5896s/40 iters), loss = 3.67149
I0708 14:05:03.047895 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11005 (* 0.3 = 0.633014 loss)
I0708 14:05:03.047952 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.10553 (* 0.3 = 0.631658 loss)
I0708 14:05:03.047984 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09645 (* 1 = 2.09645 loss)
I0708 14:05:03.048002 99468 sgd_solver.cpp:105] Iteration 34240, lr = 0.001
I0708 14:06:19.410851 99468 solver.cpp:218] Iteration 34280 (0.523832 iter/s, 76.3604s/40 iters), loss = 3.67956
I0708 14:06:19.411079 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29251 (* 0.3 = 0.687753 loss)
I0708 14:06:19.411137 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27846 (* 0.3 = 0.683537 loss)
I0708 14:06:19.411152 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27403 (* 1 = 2.27403 loss)
I0708 14:06:19.411170 99468 sgd_solver.cpp:105] Iteration 34280, lr = 0.001
I0708 14:07:35.980721 99468 solver.cpp:218] Iteration 34320 (0.522417 iter/s, 76.5671s/40 iters), loss = 3.71134
I0708 14:07:35.980943 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.75224 (* 0.3 = 0.825671 loss)
I0708 14:07:35.980973 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.74949 (* 0.3 = 0.824847 loss)
I0708 14:07:35.981019 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.76444 (* 1 = 2.76444 loss)
I0708 14:07:35.981040 99468 sgd_solver.cpp:105] Iteration 34320, lr = 0.001
I0708 14:08:52.405336 99468 solver.cpp:218] Iteration 34360 (0.52341 iter/s, 76.4219s/40 iters), loss = 3.72439
I0708 14:08:52.405581 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44164 (* 0.3 = 0.732491 loss)
I0708 14:08:52.405604 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43146 (* 0.3 = 0.729438 loss)
I0708 14:08:52.405619 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44588 (* 1 = 2.44588 loss)
I0708 14:08:52.405635 99468 sgd_solver.cpp:105] Iteration 34360, lr = 0.001
I0708 14:10:08.925922 99468 solver.cpp:218] Iteration 34400 (0.522754 iter/s, 76.5178s/40 iters), loss = 3.74354
I0708 14:10:08.926165 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56002 (* 0.3 = 0.768006 loss)
I0708 14:10:08.926228 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55679 (* 0.3 = 0.767038 loss)
I0708 14:10:08.926242 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55743 (* 1 = 2.55743 loss)
I0708 14:10:08.926259 99468 sgd_solver.cpp:105] Iteration 34400, lr = 0.001
I0708 14:11:25.415680 99468 solver.cpp:218] Iteration 34440 (0.522965 iter/s, 76.487s/40 iters), loss = 3.69535
I0708 14:11:25.415918 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12216 (* 0.3 = 0.636649 loss)
I0708 14:11:25.415940 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12086 (* 0.3 = 0.636258 loss)
I0708 14:11:25.415956 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11743 (* 1 = 2.11743 loss)
I0708 14:11:25.415972 99468 sgd_solver.cpp:105] Iteration 34440, lr = 0.001
I0708 14:12:41.974159 99468 solver.cpp:218] Iteration 34480 (0.522495 iter/s, 76.5557s/40 iters), loss = 3.70729
I0708 14:12:41.974378 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14721 (* 0.3 = 0.644164 loss)
I0708 14:12:41.974448 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13907 (* 0.3 = 0.641722 loss)
I0708 14:12:41.974462 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13583 (* 1 = 2.13583 loss)
I0708 14:12:41.974483 99468 sgd_solver.cpp:105] Iteration 34480, lr = 0.001
I0708 14:13:58.356748 99468 solver.cpp:218] Iteration 34520 (0.523698 iter/s, 76.3798s/40 iters), loss = 3.67674
I0708 14:13:58.356976 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39943 (* 0.3 = 0.719828 loss)
I0708 14:13:58.356998 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3997 (* 0.3 = 0.719909 loss)
I0708 14:13:58.357013 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39705 (* 1 = 2.39705 loss)
I0708 14:13:58.357030 99468 sgd_solver.cpp:105] Iteration 34520, lr = 0.001
I0708 14:15:14.855129 99468 solver.cpp:218] Iteration 34560 (0.522906 iter/s, 76.4956s/40 iters), loss = 3.71809
I0708 14:15:14.855417 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26176 (* 0.3 = 0.678528 loss)
I0708 14:15:14.855444 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2625 (* 0.3 = 0.678749 loss)
I0708 14:15:14.855461 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25927 (* 1 = 2.25927 loss)
I0708 14:15:14.855478 99468 sgd_solver.cpp:105] Iteration 34560, lr = 0.001
I0708 14:16:31.278627 99468 solver.cpp:218] Iteration 34600 (0.523419 iter/s, 76.4207s/40 iters), loss = 3.70121
I0708 14:16:31.278879 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.7452 (* 0.3 = 0.823559 loss)
I0708 14:16:31.278901 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.71811 (* 0.3 = 0.815433 loss)
I0708 14:16:31.278919 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.73324 (* 1 = 2.73324 loss)
I0708 14:16:31.278936 99468 sgd_solver.cpp:105] Iteration 34600, lr = 0.001
I0708 14:17:47.802157 99468 solver.cpp:218] Iteration 34640 (0.522734 iter/s, 76.5207s/40 iters), loss = 3.70406
I0708 14:17:47.802400 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24556 (* 0.3 = 0.673668 loss)
I0708 14:17:47.802425 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24123 (* 0.3 = 0.672368 loss)
I0708 14:17:47.802443 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2529 (* 1 = 2.2529 loss)
I0708 14:17:47.802459 99468 sgd_solver.cpp:105] Iteration 34640, lr = 0.001
I0708 14:19:04.383779 99468 solver.cpp:218] Iteration 34680 (0.522337 iter/s, 76.5788s/40 iters), loss = 3.71056
I0708 14:19:04.384008 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.69097 (* 0.3 = 0.80729 loss)
I0708 14:19:04.384032 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.69392 (* 0.3 = 0.808176 loss)
I0708 14:19:04.384048 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.69305 (* 1 = 2.69305 loss)
I0708 14:19:04.384064 99468 sgd_solver.cpp:105] Iteration 34680, lr = 0.001
I0708 14:20:20.968312 99468 solver.cpp:218] Iteration 34720 (0.522318 iter/s, 76.5818s/40 iters), loss = 3.72879
I0708 14:20:20.968547 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38466 (* 0.3 = 0.715399 loss)
I0708 14:20:20.968575 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37838 (* 0.3 = 0.713513 loss)
I0708 14:20:20.968590 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38155 (* 1 = 2.38155 loss)
I0708 14:20:20.968605 99468 sgd_solver.cpp:105] Iteration 34720, lr = 0.001
I0708 14:21:37.541450 99468 solver.cpp:218] Iteration 34760 (0.522395 iter/s, 76.5704s/40 iters), loss = 3.70264
I0708 14:21:37.541681 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56655 (* 0.3 = 0.769964 loss)
I0708 14:21:37.541702 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.56656 (* 0.3 = 0.769967 loss)
I0708 14:21:37.541718 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.56715 (* 1 = 2.56715 loss)
I0708 14:21:37.541734 99468 sgd_solver.cpp:105] Iteration 34760, lr = 0.001
I0708 14:22:54.124608 99468 solver.cpp:218] Iteration 34800 (0.522327 iter/s, 76.5804s/40 iters), loss = 3.74541
I0708 14:22:54.124835 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26652 (* 0.3 = 0.679956 loss)
I0708 14:22:54.124861 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29023 (* 0.3 = 0.687068 loss)
I0708 14:22:54.124876 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27621 (* 1 = 2.27621 loss)
I0708 14:22:54.124892 99468 sgd_solver.cpp:105] Iteration 34800, lr = 0.001
I0708 14:24:10.536963 99468 solver.cpp:218] Iteration 34840 (0.523494 iter/s, 76.4096s/40 iters), loss = 3.72897
I0708 14:24:10.537205 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.05847 (* 0.3 = 0.61754 loss)
I0708 14:24:10.537225 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.05396 (* 0.3 = 0.616188 loss)
I0708 14:24:10.537237 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.05579 (* 1 = 2.05579 loss)
I0708 14:24:10.537256 99468 sgd_solver.cpp:105] Iteration 34840, lr = 0.001
I0708 14:25:26.824453 99468 solver.cpp:218] Iteration 34880 (0.524351 iter/s, 76.2847s/40 iters), loss = 3.63358
I0708 14:25:26.824759 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28268 (* 0.3 = 0.684805 loss)
I0708 14:25:26.824785 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28576 (* 0.3 = 0.685727 loss)
I0708 14:25:26.824800 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28191 (* 1 = 2.28191 loss)
I0708 14:25:26.824865 99468 sgd_solver.cpp:105] Iteration 34880, lr = 0.001
I0708 14:26:43.399958 99468 solver.cpp:218] Iteration 34920 (0.52238 iter/s, 76.5727s/40 iters), loss = 3.68722
I0708 14:26:43.400194 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10939 (* 0.3 = 0.632818 loss)
I0708 14:26:43.400216 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12638 (* 0.3 = 0.637914 loss)
I0708 14:26:43.400231 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1059 (* 1 = 2.1059 loss)
I0708 14:26:43.400248 99468 sgd_solver.cpp:105] Iteration 34920, lr = 0.001
I0708 14:27:59.989965 99468 solver.cpp:218] Iteration 34960 (0.52228 iter/s, 76.5872s/40 iters), loss = 3.69852
I0708 14:27:59.990202 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43965 (* 0.3 = 0.731894 loss)
I0708 14:27:59.990227 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43631 (* 0.3 = 0.730894 loss)
I0708 14:27:59.990242 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43501 (* 1 = 2.43501 loss)
I0708 14:27:59.990262 99468 sgd_solver.cpp:105] Iteration 34960, lr = 0.001
I0708 14:29:16.581315 99468 solver.cpp:218] Iteration 35000 (0.522271 iter/s, 76.5886s/40 iters), loss = 3.72126
I0708 14:29:16.581540 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45889 (* 0.3 = 0.737668 loss)
I0708 14:29:16.581567 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45779 (* 0.3 = 0.737338 loss)
I0708 14:29:16.581580 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44675 (* 1 = 2.44675 loss)
I0708 14:29:16.581598 99468 sgd_solver.cpp:105] Iteration 35000, lr = 0.001
I0708 14:30:33.185813 99468 solver.cpp:218] Iteration 35040 (0.522182 iter/s, 76.6017s/40 iters), loss = 3.71258
I0708 14:30:33.186106 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02595 (* 0.3 = 0.607785 loss)
I0708 14:30:33.186190 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04585 (* 0.3 = 0.613755 loss)
I0708 14:30:33.186236 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03726 (* 1 = 2.03726 loss)
I0708 14:30:33.186257 99468 sgd_solver.cpp:105] Iteration 35040, lr = 0.001
I0708 14:31:49.523356 99468 solver.cpp:218] Iteration 35080 (0.524008 iter/s, 76.3347s/40 iters), loss = 3.74735
I0708 14:31:49.523594 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29983 (* 0.3 = 0.689949 loss)
I0708 14:31:49.523615 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30035 (* 0.3 = 0.690105 loss)
I0708 14:31:49.523633 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3069 (* 1 = 2.3069 loss)
I0708 14:31:49.523649 99468 sgd_solver.cpp:105] Iteration 35080, lr = 0.001
I0708 14:33:05.795387 99468 solver.cpp:218] Iteration 35120 (0.524458 iter/s, 76.2693s/40 iters), loss = 3.7557
I0708 14:33:05.795653 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56378 (* 0.3 = 0.769134 loss)
I0708 14:33:05.795677 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57218 (* 0.3 = 0.771653 loss)
I0708 14:33:05.795693 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.57801 (* 1 = 2.57801 loss)
I0708 14:33:05.795711 99468 sgd_solver.cpp:105] Iteration 35120, lr = 0.001
I0708 14:34:22.122669 99468 solver.cpp:218] Iteration 35160 (0.524078 iter/s, 76.3245s/40 iters), loss = 3.63959
I0708 14:34:22.122920 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17439 (* 0.3 = 0.652318 loss)
I0708 14:34:22.122942 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15277 (* 0.3 = 0.64583 loss)
I0708 14:34:22.122993 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16436 (* 1 = 2.16436 loss)
I0708 14:34:22.123011 99468 sgd_solver.cpp:105] Iteration 35160, lr = 0.001
I0708 14:35:38.397451 99468 solver.cpp:218] Iteration 35200 (0.524439 iter/s, 76.272s/40 iters), loss = 3.71571
I0708 14:35:38.397745 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35348 (* 0.3 = 0.706043 loss)
I0708 14:35:38.397800 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.383 (* 0.3 = 0.7149 loss)
I0708 14:35:38.397815 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37916 (* 1 = 2.37916 loss)
I0708 14:35:38.397833 99468 sgd_solver.cpp:105] Iteration 35200, lr = 0.001
I0708 14:36:54.974709 99468 solver.cpp:218] Iteration 35240 (0.522368 iter/s, 76.5744s/40 iters), loss = 3.72188
I0708 14:36:54.974941 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28712 (* 0.3 = 0.686135 loss)
I0708 14:36:54.974966 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29135 (* 0.3 = 0.687406 loss)
I0708 14:36:54.974978 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28014 (* 1 = 2.28014 loss)
I0708 14:36:54.974998 99468 sgd_solver.cpp:105] Iteration 35240, lr = 0.001
I0708 14:38:11.567472 99468 solver.cpp:218] Iteration 35280 (0.522261 iter/s, 76.59s/40 iters), loss = 3.75718
I0708 14:38:11.567706 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12746 (* 0.3 = 0.638238 loss)
I0708 14:38:11.567731 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12865 (* 0.3 = 0.638594 loss)
I0708 14:38:11.567746 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13924 (* 1 = 2.13924 loss)
I0708 14:38:11.567762 99468 sgd_solver.cpp:105] Iteration 35280, lr = 0.001
I0708 14:39:28.132405 99468 solver.cpp:218] Iteration 35320 (0.522451 iter/s, 76.5622s/40 iters), loss = 3.71926
I0708 14:39:28.132638 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47163 (* 0.3 = 0.741488 loss)
I0708 14:39:28.132661 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47512 (* 0.3 = 0.742535 loss)
I0708 14:39:28.132676 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47939 (* 1 = 2.47939 loss)
I0708 14:39:28.132699 99468 sgd_solver.cpp:105] Iteration 35320, lr = 0.001
I0708 14:40:44.707250 99468 solver.cpp:218] Iteration 35360 (0.522384 iter/s, 76.5721s/40 iters), loss = 3.70946
I0708 14:40:44.707479 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52285 (* 0.3 = 0.756854 loss)
I0708 14:40:44.707546 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50633 (* 0.3 = 0.7519 loss)
I0708 14:40:44.707568 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50845 (* 1 = 2.50845 loss)
I0708 14:40:44.707583 99468 sgd_solver.cpp:105] Iteration 35360, lr = 0.001
I0708 14:42:01.282263 99468 solver.cpp:218] Iteration 35400 (0.522382 iter/s, 76.5723s/40 iters), loss = 3.7268
I0708 14:42:01.282497 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20554 (* 0.3 = 0.661662 loss)
I0708 14:42:01.282519 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18807 (* 0.3 = 0.656421 loss)
I0708 14:42:01.282533 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20095 (* 1 = 2.20095 loss)
I0708 14:42:01.282552 99468 sgd_solver.cpp:105] Iteration 35400, lr = 0.001
I0708 14:43:17.830165 99468 solver.cpp:218] Iteration 35440 (0.522567 iter/s, 76.5451s/40 iters), loss = 3.69066
I0708 14:43:17.830402 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19459 (* 0.3 = 0.658378 loss)
I0708 14:43:17.830425 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20772 (* 0.3 = 0.662315 loss)
I0708 14:43:17.830440 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19684 (* 1 = 2.19684 loss)
I0708 14:43:17.830459 99468 sgd_solver.cpp:105] Iteration 35440, lr = 0.001
I0708 14:44:34.027146 99468 solver.cpp:218] Iteration 35480 (0.524974 iter/s, 76.1942s/40 iters), loss = 3.7034
I0708 14:44:34.027472 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20719 (* 0.3 = 0.662158 loss)
I0708 14:44:34.027536 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18068 (* 0.3 = 0.654205 loss)
I0708 14:44:34.027551 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1942 (* 1 = 2.1942 loss)
I0708 14:44:34.027576 99468 sgd_solver.cpp:105] Iteration 35480, lr = 0.001
I0708 14:45:50.266497 99468 solver.cpp:218] Iteration 35520 (0.524683 iter/s, 76.2365s/40 iters), loss = 3.70249
I0708 14:45:50.266793 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44996 (* 0.3 = 0.734988 loss)
I0708 14:45:50.266822 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43111 (* 0.3 = 0.729334 loss)
I0708 14:45:50.266842 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43282 (* 1 = 2.43282 loss)
I0708 14:45:50.266903 99468 sgd_solver.cpp:105] Iteration 35520, lr = 0.001
I0708 14:47:06.479871 99468 solver.cpp:218] Iteration 35560 (0.524862 iter/s, 76.2106s/40 iters), loss = 3.68618
I0708 14:47:06.480131 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14088 (* 0.3 = 0.642263 loss)
I0708 14:47:06.480155 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13101 (* 0.3 = 0.639303 loss)
I0708 14:47:06.480207 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14147 (* 1 = 2.14147 loss)
I0708 14:47:06.480224 99468 sgd_solver.cpp:105] Iteration 35560, lr = 0.001
I0708 14:48:22.757781 99468 solver.cpp:218] Iteration 35600 (0.524417 iter/s, 76.2751s/40 iters), loss = 3.68445
I0708 14:48:22.758040 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.95982 (* 0.3 = 0.587946 loss)
I0708 14:48:22.758062 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.94867 (* 0.3 = 0.584601 loss)
I0708 14:48:22.758077 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.95024 (* 1 = 1.95024 loss)
I0708 14:48:22.758095 99468 sgd_solver.cpp:105] Iteration 35600, lr = 0.001
I0708 14:49:38.986887 99468 solver.cpp:218] Iteration 35640 (0.524753 iter/s, 76.2263s/40 iters), loss = 3.68894
I0708 14:49:38.987145 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.372 (* 0.3 = 0.711601 loss)
I0708 14:49:38.987169 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39232 (* 0.3 = 0.717696 loss)
I0708 14:49:38.987185 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38236 (* 1 = 2.38236 loss)
I0708 14:49:38.987200 99468 sgd_solver.cpp:105] Iteration 35640, lr = 0.001
I0708 14:50:55.214814 99468 solver.cpp:218] Iteration 35680 (0.524761 iter/s, 76.2252s/40 iters), loss = 3.74617
I0708 14:50:55.215068 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33945 (* 0.3 = 0.701835 loss)
I0708 14:50:55.215090 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34228 (* 0.3 = 0.702683 loss)
I0708 14:50:55.215104 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3435 (* 1 = 2.3435 loss)
I0708 14:50:55.215121 99468 sgd_solver.cpp:105] Iteration 35680, lr = 0.001
I0708 14:52:11.517947 99468 solver.cpp:218] Iteration 35720 (0.524244 iter/s, 76.3004s/40 iters), loss = 3.68499
I0708 14:52:11.518208 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34353 (* 0.3 = 0.70306 loss)
I0708 14:52:11.518271 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34567 (* 0.3 = 0.703702 loss)
I0708 14:52:11.518287 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33063 (* 1 = 2.33063 loss)
I0708 14:52:11.518306 99468 sgd_solver.cpp:105] Iteration 35720, lr = 0.001
I0708 14:53:27.728633 99468 solver.cpp:218] Iteration 35760 (0.52488 iter/s, 76.2079s/40 iters), loss = 3.73212
I0708 14:53:27.728974 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42133 (* 0.3 = 0.7264 loss)
I0708 14:53:27.729055 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42304 (* 0.3 = 0.726911 loss)
I0708 14:53:27.729084 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42064 (* 1 = 2.42064 loss)
I0708 14:53:27.729115 99468 sgd_solver.cpp:105] Iteration 35760, lr = 0.001
I0708 14:54:43.980228 99468 solver.cpp:218] Iteration 35800 (0.524599 iter/s, 76.2487s/40 iters), loss = 3.6499
I0708 14:54:43.980547 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.81285 (* 0.3 = 0.843856 loss)
I0708 14:54:43.980576 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.81018 (* 0.3 = 0.843055 loss)
I0708 14:54:43.980588 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.80233 (* 1 = 2.80233 loss)
I0708 14:54:43.980603 99468 sgd_solver.cpp:105] Iteration 35800, lr = 0.001
I0708 14:56:00.209372 99468 solver.cpp:218] Iteration 35840 (0.524753 iter/s, 76.2263s/40 iters), loss = 3.74356
I0708 14:56:00.209700 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4493 (* 0.3 = 0.734791 loss)
I0708 14:56:00.209724 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44071 (* 0.3 = 0.732214 loss)
I0708 14:56:00.209739 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43238 (* 1 = 2.43238 loss)
I0708 14:56:00.209758 99468 sgd_solver.cpp:105] Iteration 35840, lr = 0.001
I0708 14:57:16.412863 99468 solver.cpp:218] Iteration 35880 (0.52493 iter/s, 76.2006s/40 iters), loss = 3.66895
I0708 14:57:16.413117 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.73432 (* 0.3 = 0.820297 loss)
I0708 14:57:16.413138 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.73679 (* 0.3 = 0.821037 loss)
I0708 14:57:16.413153 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.72977 (* 1 = 2.72977 loss)
I0708 14:57:16.413172 99468 sgd_solver.cpp:105] Iteration 35880, lr = 0.001
I0708 14:58:32.657397 99468 solver.cpp:218] Iteration 35920 (0.524647 iter/s, 76.2418s/40 iters), loss = 3.70941
I0708 14:58:32.657965 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45222 (* 0.3 = 0.735665 loss)
I0708 14:58:32.658026 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4426 (* 0.3 = 0.732779 loss)
I0708 14:58:32.658041 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44791 (* 1 = 2.44791 loss)
I0708 14:58:32.658058 99468 sgd_solver.cpp:105] Iteration 35920, lr = 0.001
I0708 14:59:49.166381 99468 solver.cpp:218] Iteration 35960 (0.522835 iter/s, 76.5059s/40 iters), loss = 3.69514
I0708 14:59:49.167287 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43097 (* 0.3 = 0.72929 loss)
I0708 14:59:49.167361 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43164 (* 0.3 = 0.729492 loss)
I0708 14:59:49.167379 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43054 (* 1 = 2.43054 loss)
I0708 14:59:49.167399 99468 sgd_solver.cpp:105] Iteration 35960, lr = 0.001
I0708 15:01:03.243562 99468 solver.cpp:330] Iteration 36000, Testing net (#0)
I0708 15:11:30.798090 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07352 (* 0.3 = 0.622055 loss)
I0708 15:11:30.798374 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.366621
I0708 15:11:30.798398 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794242
I0708 15:11:30.798421 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07334 (* 0.3 = 0.622001 loss)
I0708 15:11:30.798437 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.366621
I0708 15:11:30.798487 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794242
I0708 15:11:30.798508 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07167 (* 1 = 2.07167 loss)
I0708 15:11:30.798522 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.366621
I0708 15:11:30.798535 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794242
I0708 15:11:32.699168 99468 solver.cpp:218] Iteration 36000 (0.0568578 iter/s, 703.509s/40 iters), loss = 3.71923
I0708 15:11:32.699265 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12248 (* 0.3 = 0.636743 loss)
I0708 15:11:32.699285 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14757 (* 0.3 = 0.644272 loss)
I0708 15:11:32.699337 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13715 (* 1 = 2.13715 loss)
I0708 15:11:32.699355 99468 sgd_solver.cpp:105] Iteration 36000, lr = 0.001
I0708 15:12:49.006559 99468 solver.cpp:218] Iteration 36040 (0.524214 iter/s, 76.3048s/40 iters), loss = 3.7109
I0708 15:12:49.006834 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.6236 (* 0.3 = 0.787079 loss)
I0708 15:12:49.006863 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.63004 (* 0.3 = 0.789011 loss)
I0708 15:12:49.006878 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.64259 (* 1 = 2.64259 loss)
I0708 15:12:49.006894 99468 sgd_solver.cpp:105] Iteration 36040, lr = 0.001
I0708 15:14:05.484532 99468 solver.cpp:218] Iteration 36080 (0.523046 iter/s, 76.4752s/40 iters), loss = 3.64729
I0708 15:14:05.484786 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18312 (* 0.3 = 0.654937 loss)
I0708 15:14:05.484812 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17316 (* 0.3 = 0.651947 loss)
I0708 15:14:05.484872 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18039 (* 1 = 2.18039 loss)
I0708 15:14:05.484891 99468 sgd_solver.cpp:105] Iteration 36080, lr = 0.001
I0708 15:15:21.874130 99468 solver.cpp:218] Iteration 36120 (0.523651 iter/s, 76.3868s/40 iters), loss = 3.6886
I0708 15:15:21.874366 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.355 (* 0.3 = 0.706499 loss)
I0708 15:15:21.874393 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34359 (* 0.3 = 0.703078 loss)
I0708 15:15:21.874410 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35135 (* 1 = 2.35135 loss)
I0708 15:15:21.874428 99468 sgd_solver.cpp:105] Iteration 36120, lr = 0.001
I0708 15:16:38.432338 99468 solver.cpp:218] Iteration 36160 (0.522497 iter/s, 76.5554s/40 iters), loss = 3.6566
I0708 15:16:38.432564 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42378 (* 0.3 = 0.727133 loss)
I0708 15:16:38.432621 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42698 (* 0.3 = 0.728093 loss)
I0708 15:16:38.432656 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41973 (* 1 = 2.41973 loss)
I0708 15:16:38.432672 99468 sgd_solver.cpp:105] Iteration 36160, lr = 0.001
I0708 15:17:54.710263 99468 solver.cpp:218] Iteration 36200 (0.524417 iter/s, 76.2752s/40 iters), loss = 3.72484
I0708 15:17:54.710505 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3734 (* 0.3 = 0.712021 loss)
I0708 15:17:54.710567 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34799 (* 0.3 = 0.704398 loss)
I0708 15:17:54.710584 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34718 (* 1 = 2.34718 loss)
I0708 15:17:54.710624 99468 sgd_solver.cpp:105] Iteration 36200, lr = 0.001
I0708 15:19:11.069710 99468 solver.cpp:218] Iteration 36240 (0.523857 iter/s, 76.3567s/40 iters), loss = 3.65136
I0708 15:19:11.069927 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50964 (* 0.3 = 0.752893 loss)
I0708 15:19:11.069950 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.52374 (* 0.3 = 0.757123 loss)
I0708 15:19:11.069965 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5262 (* 1 = 2.5262 loss)
I0708 15:19:11.069983 99468 sgd_solver.cpp:105] Iteration 36240, lr = 0.001
I0708 15:20:27.663349 99468 solver.cpp:218] Iteration 36280 (0.522255 iter/s, 76.5909s/40 iters), loss = 3.70836
I0708 15:20:27.663592 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46687 (* 0.3 = 0.740062 loss)
I0708 15:20:27.663617 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46653 (* 0.3 = 0.73996 loss)
I0708 15:20:27.663633 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48652 (* 1 = 2.48652 loss)
I0708 15:20:27.663650 99468 sgd_solver.cpp:105] Iteration 36280, lr = 0.001
I0708 15:21:44.061230 99468 solver.cpp:218] Iteration 36320 (0.523594 iter/s, 76.3951s/40 iters), loss = 3.699
I0708 15:21:44.061472 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26311 (* 0.3 = 0.678934 loss)
I0708 15:21:44.061496 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2722 (* 0.3 = 0.681661 loss)
I0708 15:21:44.061511 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25766 (* 1 = 2.25766 loss)
I0708 15:21:44.061528 99468 sgd_solver.cpp:105] Iteration 36320, lr = 0.001
I0708 15:23:00.431339 99468 solver.cpp:218] Iteration 36360 (0.523784 iter/s, 76.3673s/40 iters), loss = 3.73839
I0708 15:23:00.431638 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35854 (* 0.3 = 0.707562 loss)
I0708 15:23:00.431694 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35845 (* 0.3 = 0.707535 loss)
I0708 15:23:00.431710 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35605 (* 1 = 2.35605 loss)
I0708 15:23:00.431727 99468 sgd_solver.cpp:105] Iteration 36360, lr = 0.001
I0708 15:24:16.718111 99468 solver.cpp:218] Iteration 36400 (0.524363 iter/s, 76.283s/40 iters), loss = 3.71409
I0708 15:24:16.718374 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36291 (* 0.3 = 0.708873 loss)
I0708 15:24:16.718402 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3635 (* 0.3 = 0.709051 loss)
I0708 15:24:16.718422 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36144 (* 1 = 2.36144 loss)
I0708 15:24:16.718437 99468 sgd_solver.cpp:105] Iteration 36400, lr = 0.001
I0708 15:25:33.108785 99468 solver.cpp:218] Iteration 36440 (0.523643 iter/s, 76.3879s/40 iters), loss = 3.72145
I0708 15:25:33.109031 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48468 (* 0.3 = 0.745405 loss)
I0708 15:25:33.109094 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49482 (* 0.3 = 0.748447 loss)
I0708 15:25:33.109108 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50978 (* 1 = 2.50978 loss)
I0708 15:25:33.109127 99468 sgd_solver.cpp:105] Iteration 36440, lr = 0.001
I0708 15:26:49.580345 99468 solver.cpp:218] Iteration 36480 (0.523089 iter/s, 76.4688s/40 iters), loss = 3.72017
I0708 15:26:49.580648 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.54529 (* 0.3 = 0.763587 loss)
I0708 15:26:49.580720 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55653 (* 0.3 = 0.76696 loss)
I0708 15:26:49.580740 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.54985 (* 1 = 2.54985 loss)
I0708 15:26:49.580765 99468 sgd_solver.cpp:105] Iteration 36480, lr = 0.001
I0708 15:27:58.421988 99628 data_layer.cpp:73] Restarting data prefetching from start.
I0708 15:28:05.875591 99468 solver.cpp:218] Iteration 36520 (0.524299 iter/s, 76.2924s/40 iters), loss = 3.71075
I0708 15:28:05.875710 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27503 (* 0.3 = 0.68251 loss)
I0708 15:28:05.875771 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28657 (* 0.3 = 0.685972 loss)
I0708 15:28:05.875790 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2761 (* 1 = 2.2761 loss)
I0708 15:28:05.875811 99468 sgd_solver.cpp:105] Iteration 36520, lr = 0.001
I0708 15:29:22.209938 99468 solver.cpp:218] Iteration 36560 (0.524029 iter/s, 76.3317s/40 iters), loss = 3.7168
I0708 15:29:22.210172 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42359 (* 0.3 = 0.727076 loss)
I0708 15:29:22.210197 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41748 (* 0.3 = 0.725243 loss)
I0708 15:29:22.210245 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41043 (* 1 = 2.41043 loss)
I0708 15:29:22.210263 99468 sgd_solver.cpp:105] Iteration 36560, lr = 0.001
I0708 15:30:38.817404 99468 solver.cpp:218] Iteration 36600 (0.522161 iter/s, 76.6047s/40 iters), loss = 3.67671
I0708 15:30:38.817665 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32625 (* 0.3 = 0.697876 loss)
I0708 15:30:38.817724 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33514 (* 0.3 = 0.700541 loss)
I0708 15:30:38.817740 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33095 (* 1 = 2.33095 loss)
I0708 15:30:38.817759 99468 sgd_solver.cpp:105] Iteration 36600, lr = 0.001
I0708 15:31:55.359367 99468 solver.cpp:218] Iteration 36640 (0.522608 iter/s, 76.5392s/40 iters), loss = 3.71436
I0708 15:31:55.359678 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.6488 (* 0.3 = 0.79464 loss)
I0708 15:31:55.359699 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.65696 (* 0.3 = 0.797089 loss)
I0708 15:31:55.359714 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.65797 (* 1 = 2.65797 loss)
I0708 15:31:55.359730 99468 sgd_solver.cpp:105] Iteration 36640, lr = 0.001
I0708 15:33:11.754616 99468 solver.cpp:218] Iteration 36680 (0.523612 iter/s, 76.3924s/40 iters), loss = 3.67984
I0708 15:33:11.754886 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44281 (* 0.3 = 0.732844 loss)
I0708 15:33:11.754945 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46041 (* 0.3 = 0.738123 loss)
I0708 15:33:11.754963 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44366 (* 1 = 2.44366 loss)
I0708 15:33:11.754986 99468 sgd_solver.cpp:105] Iteration 36680, lr = 0.001
I0708 15:34:28.294028 99468 solver.cpp:218] Iteration 36720 (0.522626 iter/s, 76.5366s/40 iters), loss = 3.70941
I0708 15:34:28.294270 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60335 (* 0.3 = 0.781006 loss)
I0708 15:34:28.294328 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61483 (* 0.3 = 0.784449 loss)
I0708 15:34:28.294363 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.60826 (* 1 = 2.60826 loss)
I0708 15:34:28.294381 99468 sgd_solver.cpp:105] Iteration 36720, lr = 0.001
I0708 15:35:44.845882 99468 solver.cpp:218] Iteration 36760 (0.522541 iter/s, 76.5491s/40 iters), loss = 3.71442
I0708 15:35:44.846101 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17851 (* 0.3 = 0.653554 loss)
I0708 15:35:44.846158 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17794 (* 0.3 = 0.653382 loss)
I0708 15:35:44.846173 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1814 (* 1 = 2.1814 loss)
I0708 15:35:44.846189 99468 sgd_solver.cpp:105] Iteration 36760, lr = 0.001
I0708 15:37:01.368167 99468 solver.cpp:218] Iteration 36800 (0.522742 iter/s, 76.5195s/40 iters), loss = 3.72781
I0708 15:37:01.368460 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.12581 (* 0.3 = 0.637743 loss)
I0708 15:37:01.368526 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12763 (* 0.3 = 0.63829 loss)
I0708 15:37:01.368547 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11697 (* 1 = 2.11697 loss)
I0708 15:37:01.368584 99468 sgd_solver.cpp:105] Iteration 36800, lr = 0.001
I0708 15:38:17.901188 99468 solver.cpp:218] Iteration 36840 (0.522669 iter/s, 76.5302s/40 iters), loss = 3.70143
I0708 15:38:17.901455 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21832 (* 0.3 = 0.665497 loss)
I0708 15:38:17.901516 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2084 (* 0.3 = 0.662519 loss)
I0708 15:38:17.901535 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20699 (* 1 = 2.20699 loss)
I0708 15:38:17.901561 99468 sgd_solver.cpp:105] Iteration 36840, lr = 0.001
I0708 15:39:34.427042 99468 solver.cpp:218] Iteration 36880 (0.522718 iter/s, 76.5231s/40 iters), loss = 3.66351
I0708 15:39:34.427281 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.88275 (* 0.3 = 0.564824 loss)
I0708 15:39:34.427302 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.88766 (* 0.3 = 0.566299 loss)
I0708 15:39:34.427316 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.86803 (* 1 = 1.86803 loss)
I0708 15:39:34.427333 99468 sgd_solver.cpp:105] Iteration 36880, lr = 0.001
I0708 15:40:50.927014 99468 solver.cpp:218] Iteration 36920 (0.522895 iter/s, 76.4972s/40 iters), loss = 3.72912
I0708 15:40:50.927254 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29381 (* 0.3 = 0.688142 loss)
I0708 15:40:50.927311 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29004 (* 0.3 = 0.687012 loss)
I0708 15:40:50.927330 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29438 (* 1 = 2.29438 loss)
I0708 15:40:50.927347 99468 sgd_solver.cpp:105] Iteration 36920, lr = 0.001
I0708 15:42:07.442639 99468 solver.cpp:218] Iteration 36960 (0.522788 iter/s, 76.5129s/40 iters), loss = 3.70024
I0708 15:42:07.442898 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.7696 (* 0.3 = 0.830879 loss)
I0708 15:42:07.442955 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.76715 (* 0.3 = 0.830145 loss)
I0708 15:42:07.442970 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.77053 (* 1 = 2.77053 loss)
I0708 15:42:07.442987 99468 sgd_solver.cpp:105] Iteration 36960, lr = 0.001
I0708 15:43:24.000589 99468 solver.cpp:218] Iteration 37000 (0.522499 iter/s, 76.5552s/40 iters), loss = 3.72353
I0708 15:43:24.000838 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14985 (* 0.3 = 0.644955 loss)
I0708 15:43:24.000864 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14847 (* 0.3 = 0.644541 loss)
I0708 15:43:24.000913 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12935 (* 1 = 2.12935 loss)
I0708 15:43:24.000931 99468 sgd_solver.cpp:105] Iteration 37000, lr = 0.001
I0708 15:44:40.536731 99468 solver.cpp:218] Iteration 37040 (0.522648 iter/s, 76.5334s/40 iters), loss = 3.71009
I0708 15:44:40.536959 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04479 (* 0.3 = 0.613438 loss)
I0708 15:44:40.537017 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03924 (* 0.3 = 0.611771 loss)
I0708 15:44:40.537032 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02761 (* 1 = 2.02761 loss)
I0708 15:44:40.537070 99468 sgd_solver.cpp:105] Iteration 37040, lr = 0.001
I0708 15:45:56.965023 99468 solver.cpp:218] Iteration 37080 (0.523385 iter/s, 76.4255s/40 iters), loss = 3.73437
I0708 15:45:56.965270 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51898 (* 0.3 = 0.755693 loss)
I0708 15:45:56.965293 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51724 (* 0.3 = 0.755172 loss)
I0708 15:45:56.965312 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5205 (* 1 = 2.5205 loss)
I0708 15:45:56.965328 99468 sgd_solver.cpp:105] Iteration 37080, lr = 0.001
I0708 15:47:13.505658 99468 solver.cpp:218] Iteration 37120 (0.522628 iter/s, 76.5363s/40 iters), loss = 3.69807
I0708 15:47:13.505928 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36651 (* 0.3 = 0.709952 loss)
I0708 15:47:13.505960 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38199 (* 0.3 = 0.714596 loss)
I0708 15:47:13.505980 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36728 (* 1 = 2.36728 loss)
I0708 15:47:13.506000 99468 sgd_solver.cpp:105] Iteration 37120, lr = 0.001
I0708 15:48:30.019634 99468 solver.cpp:218] Iteration 37160 (0.522799 iter/s, 76.5112s/40 iters), loss = 3.72337
I0708 15:48:30.019856 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36533 (* 0.3 = 0.709601 loss)
I0708 15:48:30.019881 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37189 (* 0.3 = 0.711567 loss)
I0708 15:48:30.019896 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36954 (* 1 = 2.36954 loss)
I0708 15:48:30.019912 99468 sgd_solver.cpp:105] Iteration 37160, lr = 0.001
I0708 15:49:46.483813 99468 solver.cpp:218] Iteration 37200 (0.52314 iter/s, 76.4614s/40 iters), loss = 3.71515
I0708 15:49:46.484040 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55505 (* 0.3 = 0.766514 loss)
I0708 15:49:46.484061 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.56692 (* 0.3 = 0.770076 loss)
I0708 15:49:46.484076 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.56608 (* 1 = 2.56608 loss)
I0708 15:49:46.484094 99468 sgd_solver.cpp:105] Iteration 37200, lr = 0.001
I0708 15:51:02.951542 99468 solver.cpp:218] Iteration 37240 (0.523115 iter/s, 76.465s/40 iters), loss = 3.72083
I0708 15:51:02.951781 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.59365 (* 0.3 = 0.778094 loss)
I0708 15:51:02.951802 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59372 (* 0.3 = 0.778116 loss)
I0708 15:51:02.951817 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.5913 (* 1 = 2.5913 loss)
I0708 15:51:02.951840 99468 sgd_solver.cpp:105] Iteration 37240, lr = 0.001
I0708 15:52:19.395517 99468 solver.cpp:218] Iteration 37280 (0.523278 iter/s, 76.4412s/40 iters), loss = 3.72273
I0708 15:52:19.395797 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44121 (* 0.3 = 0.732362 loss)
I0708 15:52:19.395862 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42832 (* 0.3 = 0.728496 loss)
I0708 15:52:19.395876 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45976 (* 1 = 2.45976 loss)
I0708 15:52:19.395897 99468 sgd_solver.cpp:105] Iteration 37280, lr = 0.001
I0708 15:53:35.662245 99468 solver.cpp:218] Iteration 37320 (0.524494 iter/s, 76.2639s/40 iters), loss = 3.72571
I0708 15:53:35.662474 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37711 (* 0.3 = 0.713134 loss)
I0708 15:53:35.662498 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37168 (* 0.3 = 0.711503 loss)
I0708 15:53:35.662514 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38945 (* 1 = 2.38945 loss)
I0708 15:53:35.662531 99468 sgd_solver.cpp:105] Iteration 37320, lr = 0.001
I0708 15:54:52.130731 99468 solver.cpp:218] Iteration 37360 (0.52311 iter/s, 76.4657s/40 iters), loss = 3.70518
I0708 15:54:52.130959 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38633 (* 0.3 = 0.715899 loss)
I0708 15:54:52.130985 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37669 (* 0.3 = 0.713008 loss)
I0708 15:54:52.130998 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37747 (* 1 = 2.37747 loss)
I0708 15:54:52.131060 99468 sgd_solver.cpp:105] Iteration 37360, lr = 0.001
I0708 15:56:08.695111 99468 solver.cpp:218] Iteration 37400 (0.522455 iter/s, 76.5616s/40 iters), loss = 3.73874
I0708 15:56:08.695335 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21622 (* 0.3 = 0.664865 loss)
I0708 15:56:08.695359 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2129 (* 0.3 = 0.663871 loss)
I0708 15:56:08.695374 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21346 (* 1 = 2.21346 loss)
I0708 15:56:08.695430 99468 sgd_solver.cpp:105] Iteration 37400, lr = 0.001
I0708 15:57:25.167256 99468 solver.cpp:218] Iteration 37440 (0.523085 iter/s, 76.4694s/40 iters), loss = 3.72669
I0708 15:57:25.167490 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38203 (* 0.3 = 0.714608 loss)
I0708 15:57:25.167513 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38298 (* 0.3 = 0.714894 loss)
I0708 15:57:25.167528 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3797 (* 1 = 2.3797 loss)
I0708 15:57:25.167549 99468 sgd_solver.cpp:105] Iteration 37440, lr = 0.001
I0708 15:58:41.701248 99468 solver.cpp:218] Iteration 37480 (0.522662 iter/s, 76.5312s/40 iters), loss = 3.68366
I0708 15:58:41.701474 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27534 (* 0.3 = 0.682602 loss)
I0708 15:58:41.701494 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27605 (* 0.3 = 0.682815 loss)
I0708 15:58:41.701508 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27582 (* 1 = 2.27582 loss)
I0708 15:58:41.701565 99468 sgd_solver.cpp:105] Iteration 37480, lr = 0.001
I0708 15:59:58.084753 99468 solver.cpp:218] Iteration 37520 (0.523692 iter/s, 76.3807s/40 iters), loss = 3.68619
I0708 15:59:58.084985 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37936 (* 0.3 = 0.713808 loss)
I0708 15:59:58.085005 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38761 (* 0.3 = 0.716284 loss)
I0708 15:59:58.085021 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38527 (* 1 = 2.38527 loss)
I0708 15:59:58.085037 99468 sgd_solver.cpp:105] Iteration 37520, lr = 0.001
I0708 16:01:14.549429 99468 solver.cpp:218] Iteration 37560 (0.523136 iter/s, 76.4619s/40 iters), loss = 3.65879
I0708 16:01:14.549717 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30426 (* 0.3 = 0.691278 loss)
I0708 16:01:14.549741 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30854 (* 0.3 = 0.692563 loss)
I0708 16:01:14.549757 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30291 (* 1 = 2.30291 loss)
I0708 16:01:14.549773 99468 sgd_solver.cpp:105] Iteration 37560, lr = 0.001
I0708 16:02:30.892884 99468 solver.cpp:218] Iteration 37600 (0.523967 iter/s, 76.3406s/40 iters), loss = 3.67621
I0708 16:02:30.893131 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16847 (* 0.3 = 0.650542 loss)
I0708 16:02:30.893187 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16969 (* 0.3 = 0.650908 loss)
I0708 16:02:30.893201 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17339 (* 1 = 2.17339 loss)
I0708 16:02:30.893219 99468 sgd_solver.cpp:105] Iteration 37600, lr = 0.001
I0708 16:03:47.155642 99468 solver.cpp:218] Iteration 37640 (0.524521 iter/s, 76.26s/40 iters), loss = 3.68916
I0708 16:03:47.155877 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36016 (* 0.3 = 0.708048 loss)
I0708 16:03:47.155942 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32965 (* 0.3 = 0.698894 loss)
I0708 16:03:47.155958 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34095 (* 1 = 2.34095 loss)
I0708 16:03:47.155975 99468 sgd_solver.cpp:105] Iteration 37640, lr = 0.001
I0708 16:05:03.379604 99468 solver.cpp:218] Iteration 37680 (0.524788 iter/s, 76.2212s/40 iters), loss = 3.66902
I0708 16:05:03.379833 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18255 (* 0.3 = 0.654765 loss)
I0708 16:05:03.379859 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1849 (* 0.3 = 0.65547 loss)
I0708 16:05:03.379907 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18337 (* 1 = 2.18337 loss)
I0708 16:05:03.379925 99468 sgd_solver.cpp:105] Iteration 37680, lr = 0.001
I0708 16:06:19.743425 99468 solver.cpp:218] Iteration 37720 (0.523827 iter/s, 76.3611s/40 iters), loss = 3.74114
I0708 16:06:19.743664 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1729 (* 0.3 = 0.65187 loss)
I0708 16:06:19.743691 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16924 (* 0.3 = 0.650771 loss)
I0708 16:06:19.743708 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16761 (* 1 = 2.16761 loss)
I0708 16:06:19.743724 99468 sgd_solver.cpp:105] Iteration 37720, lr = 0.001
I0708 16:07:36.304262 99468 solver.cpp:218] Iteration 37760 (0.522479 iter/s, 76.5581s/40 iters), loss = 3.70073
I0708 16:07:36.304499 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46748 (* 0.3 = 0.740244 loss)
I0708 16:07:36.304523 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45423 (* 0.3 = 0.736269 loss)
I0708 16:07:36.304584 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47479 (* 1 = 2.47479 loss)
I0708 16:07:36.304601 99468 sgd_solver.cpp:105] Iteration 37760, lr = 0.001
I0708 16:08:52.931624 99468 solver.cpp:218] Iteration 37800 (0.522026 iter/s, 76.6246s/40 iters), loss = 3.63608
I0708 16:08:52.931859 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22093 (* 0.3 = 0.666279 loss)
I0708 16:08:52.931882 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22201 (* 0.3 = 0.666604 loss)
I0708 16:08:52.931936 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22937 (* 1 = 2.22937 loss)
I0708 16:08:52.931957 99468 sgd_solver.cpp:105] Iteration 37800, lr = 0.001
I0708 16:10:09.467936 99468 solver.cpp:218] Iteration 37840 (0.522647 iter/s, 76.5335s/40 iters), loss = 3.70642
I0708 16:10:09.468184 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20888 (* 0.3 = 0.662665 loss)
I0708 16:10:09.468237 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22121 (* 0.3 = 0.666362 loss)
I0708 16:10:09.468253 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21744 (* 1 = 2.21744 loss)
I0708 16:10:09.468273 99468 sgd_solver.cpp:105] Iteration 37840, lr = 0.001
I0708 16:11:25.741268 99468 solver.cpp:218] Iteration 37880 (0.524449 iter/s, 76.2706s/40 iters), loss = 3.68611
I0708 16:11:25.741541 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26658 (* 0.3 = 0.679974 loss)
I0708 16:11:25.741576 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2641 (* 0.3 = 0.679231 loss)
I0708 16:11:25.741591 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26896 (* 1 = 2.26896 loss)
I0708 16:11:25.741607 99468 sgd_solver.cpp:105] Iteration 37880, lr = 0.001
I0708 16:12:42.007154 99468 solver.cpp:218] Iteration 37920 (0.5245 iter/s, 76.2631s/40 iters), loss = 3.72051
I0708 16:12:42.007386 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16651 (* 0.3 = 0.649952 loss)
I0708 16:12:42.007441 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17976 (* 0.3 = 0.653927 loss)
I0708 16:12:42.007455 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16924 (* 1 = 2.16924 loss)
I0708 16:12:42.007477 99468 sgd_solver.cpp:105] Iteration 37920, lr = 0.001
I0708 16:13:58.532841 99468 solver.cpp:218] Iteration 37960 (0.522719 iter/s, 76.5229s/40 iters), loss = 3.72298
I0708 16:13:58.533100 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18298 (* 0.3 = 0.654895 loss)
I0708 16:13:58.533150 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1928 (* 0.3 = 0.65784 loss)
I0708 16:13:58.533164 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17154 (* 1 = 2.17154 loss)
I0708 16:13:58.533200 99468 sgd_solver.cpp:105] Iteration 37960, lr = 0.001
I0708 16:15:14.784030 99468 solver.cpp:218] Iteration 38000 (0.524601 iter/s, 76.2484s/40 iters), loss = 3.71279
I0708 16:15:14.784272 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27241 (* 0.3 = 0.681722 loss)
I0708 16:15:14.784330 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27138 (* 0.3 = 0.681414 loss)
I0708 16:15:14.784364 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25586 (* 1 = 2.25586 loss)
I0708 16:15:14.784382 99468 sgd_solver.cpp:105] Iteration 38000, lr = 0.001
I0708 16:16:31.018329 99468 solver.cpp:218] Iteration 38040 (0.524717 iter/s, 76.2315s/40 iters), loss = 3.75375
I0708 16:16:31.018595 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30817 (* 0.3 = 0.69245 loss)
I0708 16:16:31.018626 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30824 (* 0.3 = 0.692472 loss)
I0708 16:16:31.018643 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30891 (* 1 = 2.30891 loss)
I0708 16:16:31.018659 99468 sgd_solver.cpp:105] Iteration 38040, lr = 0.001
I0708 16:17:47.228292 99468 solver.cpp:218] Iteration 38080 (0.524885 iter/s, 76.2072s/40 iters), loss = 3.73699
I0708 16:17:47.228549 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44016 (* 0.3 = 0.732049 loss)
I0708 16:17:47.228579 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4427 (* 0.3 = 0.732811 loss)
I0708 16:17:47.228593 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4315 (* 1 = 2.4315 loss)
I0708 16:17:47.228610 99468 sgd_solver.cpp:105] Iteration 38080, lr = 0.001
I0708 16:19:03.551585 99468 solver.cpp:218] Iteration 38120 (0.524106 iter/s, 76.3204s/40 iters), loss = 3.71737
I0708 16:19:03.551796 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42681 (* 0.3 = 0.728043 loss)
I0708 16:19:03.551838 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41017 (* 0.3 = 0.72305 loss)
I0708 16:19:03.551853 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42349 (* 1 = 2.42349 loss)
I0708 16:19:03.551874 99468 sgd_solver.cpp:105] Iteration 38120, lr = 0.001
I0708 16:20:19.999733 99468 solver.cpp:218] Iteration 38160 (0.523249 iter/s, 76.4454s/40 iters), loss = 3.65441
I0708 16:20:19.999984 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40142 (* 0.3 = 0.720425 loss)
I0708 16:20:20.000011 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39688 (* 0.3 = 0.719065 loss)
I0708 16:20:20.000027 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39083 (* 1 = 2.39083 loss)
I0708 16:20:20.000046 99468 sgd_solver.cpp:105] Iteration 38160, lr = 0.001
I0708 16:21:36.263480 99468 solver.cpp:218] Iteration 38200 (0.524515 iter/s, 76.261s/40 iters), loss = 3.7093
I0708 16:21:36.263772 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08873 (* 0.3 = 0.626618 loss)
I0708 16:21:36.263798 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08167 (* 0.3 = 0.624502 loss)
I0708 16:21:36.263818 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0866 (* 1 = 2.0866 loss)
I0708 16:21:36.263835 99468 sgd_solver.cpp:105] Iteration 38200, lr = 0.001
I0708 16:22:52.828738 99468 solver.cpp:218] Iteration 38240 (0.522449 iter/s, 76.5624s/40 iters), loss = 3.72588
I0708 16:22:52.828971 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.253 (* 0.3 = 0.675899 loss)
I0708 16:22:52.829030 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26071 (* 0.3 = 0.678213 loss)
I0708 16:22:52.829046 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26321 (* 1 = 2.26321 loss)
I0708 16:22:52.829062 99468 sgd_solver.cpp:105] Iteration 38240, lr = 0.001
I0708 16:24:09.168696 99468 solver.cpp:218] Iteration 38280 (0.523991 iter/s, 76.3372s/40 iters), loss = 3.721
I0708 16:24:09.168934 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39307 (* 0.3 = 0.71792 loss)
I0708 16:24:09.168964 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40237 (* 0.3 = 0.720712 loss)
I0708 16:24:09.168982 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39737 (* 1 = 2.39737 loss)
I0708 16:24:09.168998 99468 sgd_solver.cpp:105] Iteration 38280, lr = 0.001
I0708 16:25:25.487709 99468 solver.cpp:218] Iteration 38320 (0.524135 iter/s, 76.3163s/40 iters), loss = 3.68832
I0708 16:25:25.487936 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20312 (* 0.3 = 0.660935 loss)
I0708 16:25:25.487959 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19018 (* 0.3 = 0.657054 loss)
I0708 16:25:25.488008 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19494 (* 1 = 2.19494 loss)
I0708 16:25:25.488029 99468 sgd_solver.cpp:105] Iteration 38320, lr = 0.001
I0708 16:26:41.793948 99468 solver.cpp:218] Iteration 38360 (0.524222 iter/s, 76.3035s/40 iters), loss = 3.71572
I0708 16:26:41.794215 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51761 (* 0.3 = 0.755284 loss)
I0708 16:26:41.794244 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50431 (* 0.3 = 0.751293 loss)
I0708 16:26:41.794260 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50863 (* 1 = 2.50863 loss)
I0708 16:26:41.794275 99468 sgd_solver.cpp:105] Iteration 38360, lr = 0.001
I0708 16:27:58.322104 99468 solver.cpp:218] Iteration 38400 (0.522702 iter/s, 76.5254s/40 iters), loss = 3.6947
I0708 16:27:58.322335 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41472 (* 0.3 = 0.724417 loss)
I0708 16:27:58.322357 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41367 (* 0.3 = 0.7241 loss)
I0708 16:27:58.322371 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39772 (* 1 = 2.39772 loss)
I0708 16:27:58.322389 99468 sgd_solver.cpp:105] Iteration 38400, lr = 0.001
I0708 16:29:14.943954 99468 solver.cpp:218] Iteration 38440 (0.522063 iter/s, 76.6191s/40 iters), loss = 3.66597
I0708 16:29:14.944176 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47202 (* 0.3 = 0.741605 loss)
I0708 16:29:14.944231 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47915 (* 0.3 = 0.743746 loss)
I0708 16:29:14.944248 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47073 (* 1 = 2.47073 loss)
I0708 16:29:14.944283 99468 sgd_solver.cpp:105] Iteration 38440, lr = 0.001
I0708 16:30:31.500010 99468 solver.cpp:218] Iteration 38480 (0.522512 iter/s, 76.5533s/40 iters), loss = 3.72521
I0708 16:30:31.500244 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50338 (* 0.3 = 0.751014 loss)
I0708 16:30:31.500269 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50861 (* 0.3 = 0.752584 loss)
I0708 16:30:31.500319 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51276 (* 1 = 2.51276 loss)
I0708 16:30:31.500336 99468 sgd_solver.cpp:105] Iteration 38480, lr = 0.001
I0708 16:31:47.997793 99468 solver.cpp:218] Iteration 38520 (0.52291 iter/s, 76.495s/40 iters), loss = 3.76231
I0708 16:31:47.998056 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.63228 (* 0.3 = 0.789683 loss)
I0708 16:31:47.998112 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.6102 (* 0.3 = 0.783059 loss)
I0708 16:31:47.998127 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.63089 (* 1 = 2.63089 loss)
I0708 16:31:47.998145 99468 sgd_solver.cpp:105] Iteration 38520, lr = 0.001
I0708 16:33:04.481251 99468 solver.cpp:218] Iteration 38560 (0.523008 iter/s, 76.4807s/40 iters), loss = 3.70033
I0708 16:33:04.481497 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28327 (* 0.3 = 0.68498 loss)
I0708 16:33:04.481523 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29 (* 0.3 = 0.686999 loss)
I0708 16:33:04.481536 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28666 (* 1 = 2.28666 loss)
I0708 16:33:04.481559 99468 sgd_solver.cpp:105] Iteration 38560, lr = 0.001
I0708 16:34:21.008321 99468 solver.cpp:218] Iteration 38600 (0.52271 iter/s, 76.5243s/40 iters), loss = 3.68798
I0708 16:34:21.008576 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29341 (* 0.3 = 0.688024 loss)
I0708 16:34:21.008601 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28781 (* 0.3 = 0.686344 loss)
I0708 16:34:21.008618 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28763 (* 1 = 2.28763 loss)
I0708 16:34:21.008633 99468 sgd_solver.cpp:105] Iteration 38600, lr = 0.001
I0708 16:35:37.539361 99468 solver.cpp:218] Iteration 38640 (0.522683 iter/s, 76.5283s/40 iters), loss = 3.71549
I0708 16:35:37.539613 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15946 (* 0.3 = 0.647837 loss)
I0708 16:35:37.539690 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16318 (* 0.3 = 0.648953 loss)
I0708 16:35:37.539706 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1793 (* 1 = 2.1793 loss)
I0708 16:35:37.539727 99468 sgd_solver.cpp:105] Iteration 38640, lr = 0.001
I0708 16:36:53.984653 99468 solver.cpp:218] Iteration 38680 (0.523269 iter/s, 76.4425s/40 iters), loss = 3.74708
I0708 16:36:53.984884 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51034 (* 0.3 = 0.753101 loss)
I0708 16:36:53.984956 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50884 (* 0.3 = 0.752653 loss)
I0708 16:36:53.984971 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51043 (* 1 = 2.51043 loss)
I0708 16:36:53.984989 99468 sgd_solver.cpp:105] Iteration 38680, lr = 0.001
I0708 16:38:10.535751 99468 solver.cpp:218] Iteration 38720 (0.522546 iter/s, 76.5483s/40 iters), loss = 3.67701
I0708 16:38:10.535980 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.03363 (* 0.3 = 0.61009 loss)
I0708 16:38:10.536041 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00958 (* 0.3 = 0.602874 loss)
I0708 16:38:10.536054 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02928 (* 1 = 2.02928 loss)
I0708 16:38:10.536075 99468 sgd_solver.cpp:105] Iteration 38720, lr = 0.001
I0708 16:39:27.149984 99468 solver.cpp:218] Iteration 38760 (0.522115 iter/s, 76.6115s/40 iters), loss = 3.68438
I0708 16:39:27.150228 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.72408 (* 0.3 = 0.817225 loss)
I0708 16:39:27.150250 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.71426 (* 0.3 = 0.814278 loss)
I0708 16:39:27.150265 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.71943 (* 1 = 2.71943 loss)
I0708 16:39:27.150282 99468 sgd_solver.cpp:105] Iteration 38760, lr = 0.001
I0708 16:40:43.667165 99468 solver.cpp:218] Iteration 38800 (0.522777 iter/s, 76.5144s/40 iters), loss = 3.67818
I0708 16:40:43.667464 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52981 (* 0.3 = 0.758942 loss)
I0708 16:40:43.667485 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51676 (* 0.3 = 0.755028 loss)
I0708 16:40:43.667503 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51866 (* 1 = 2.51866 loss)
I0708 16:40:43.667521 99468 sgd_solver.cpp:105] Iteration 38800, lr = 0.001
I0708 16:42:00.219327 99468 solver.cpp:218] Iteration 38840 (0.522539 iter/s, 76.5493s/40 iters), loss = 3.6413
I0708 16:42:00.219606 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40808 (* 0.3 = 0.722424 loss)
I0708 16:42:00.219638 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43296 (* 0.3 = 0.729887 loss)
I0708 16:42:00.219657 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41336 (* 1 = 2.41336 loss)
I0708 16:42:00.219678 99468 sgd_solver.cpp:105] Iteration 38840, lr = 0.001
I0708 16:43:16.726646 99468 solver.cpp:218] Iteration 38880 (0.522845 iter/s, 76.5045s/40 iters), loss = 3.72995
I0708 16:43:16.726899 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.306 (* 0.3 = 0.691799 loss)
I0708 16:43:16.726932 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31027 (* 0.3 = 0.693081 loss)
I0708 16:43:16.726950 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30265 (* 1 = 2.30265 loss)
I0708 16:43:16.726970 99468 sgd_solver.cpp:105] Iteration 38880, lr = 0.001
I0708 16:44:33.150786 99468 solver.cpp:218] Iteration 38920 (0.523414 iter/s, 76.4214s/40 iters), loss = 3.68527
I0708 16:44:33.151015 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40916 (* 0.3 = 0.722748 loss)
I0708 16:44:33.151078 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4117 (* 0.3 = 0.723509 loss)
I0708 16:44:33.151093 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4123 (* 1 = 2.4123 loss)
I0708 16:44:33.151111 99468 sgd_solver.cpp:105] Iteration 38920, lr = 0.001
I0708 16:45:49.615288 99468 solver.cpp:218] Iteration 38960 (0.523137 iter/s, 76.4617s/40 iters), loss = 3.6689
I0708 16:45:49.615566 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40561 (* 0.3 = 0.721684 loss)
I0708 16:45:49.615595 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40673 (* 0.3 = 0.722018 loss)
I0708 16:45:49.615612 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40405 (* 1 = 2.40405 loss)
I0708 16:45:49.615629 99468 sgd_solver.cpp:105] Iteration 38960, lr = 0.001
I0708 16:47:06.072325 99468 solver.cpp:218] Iteration 39000 (0.523189 iter/s, 76.4542s/40 iters), loss = 3.6898
I0708 16:47:06.072561 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44184 (* 0.3 = 0.732551 loss)
I0708 16:47:06.072585 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42815 (* 0.3 = 0.728445 loss)
I0708 16:47:06.072600 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43575 (* 1 = 2.43575 loss)
I0708 16:47:06.072616 99468 sgd_solver.cpp:105] Iteration 39000, lr = 0.001
I0708 16:48:22.573047 99468 solver.cpp:218] Iteration 39040 (0.52289 iter/s, 76.498s/40 iters), loss = 3.68356
I0708 16:48:22.573320 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25676 (* 0.3 = 0.677029 loss)
I0708 16:48:22.573348 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2613 (* 0.3 = 0.678389 loss)
I0708 16:48:22.573367 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25472 (* 1 = 2.25472 loss)
I0708 16:48:22.573387 99468 sgd_solver.cpp:105] Iteration 39040, lr = 0.001
I0708 16:49:39.065325 99468 solver.cpp:218] Iteration 39080 (0.522948 iter/s, 76.4895s/40 iters), loss = 3.71476
I0708 16:49:39.065560 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48407 (* 0.3 = 0.745222 loss)
I0708 16:49:39.065580 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.48331 (* 0.3 = 0.744993 loss)
I0708 16:49:39.065594 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47709 (* 1 = 2.47709 loss)
I0708 16:49:39.065610 99468 sgd_solver.cpp:105] Iteration 39080, lr = 0.001
I0708 16:50:55.442365 99468 solver.cpp:218] Iteration 39120 (0.523736 iter/s, 76.3743s/40 iters), loss = 3.71408
I0708 16:50:55.443440 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18363 (* 0.3 = 0.65509 loss)
I0708 16:50:55.443506 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20164 (* 0.3 = 0.660491 loss)
I0708 16:50:55.443534 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18806 (* 1 = 2.18806 loss)
I0708 16:50:55.443584 99468 sgd_solver.cpp:105] Iteration 39120, lr = 0.001
I0708 16:52:11.942517 99468 solver.cpp:218] Iteration 39160 (0.522899 iter/s, 76.4966s/40 iters), loss = 3.6918
I0708 16:52:11.942769 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45459 (* 0.3 = 0.736376 loss)
I0708 16:52:11.942791 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45516 (* 0.3 = 0.736548 loss)
I0708 16:52:11.942839 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45848 (* 1 = 2.45848 loss)
I0708 16:52:11.942859 99468 sgd_solver.cpp:105] Iteration 39160, lr = 0.001
I0708 16:53:28.416975 99468 solver.cpp:218] Iteration 39200 (0.523069 iter/s, 76.4717s/40 iters), loss = 3.71458
I0708 16:53:28.417206 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37094 (* 0.3 = 0.711281 loss)
I0708 16:53:28.417261 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38261 (* 0.3 = 0.714782 loss)
I0708 16:53:28.417275 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38184 (* 1 = 2.38184 loss)
I0708 16:53:28.417299 99468 sgd_solver.cpp:105] Iteration 39200, lr = 0.001
I0708 16:54:44.855823 99468 solver.cpp:218] Iteration 39240 (0.523344 iter/s, 76.4316s/40 iters), loss = 3.74673
I0708 16:54:44.856076 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3846 (* 0.3 = 0.715379 loss)
I0708 16:54:44.856107 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39112 (* 0.3 = 0.717337 loss)
I0708 16:54:44.856127 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38408 (* 1 = 2.38408 loss)
I0708 16:54:44.856189 99468 sgd_solver.cpp:105] Iteration 39240, lr = 0.001
I0708 16:56:01.314648 99468 solver.cpp:218] Iteration 39280 (0.523176 iter/s, 76.4561s/40 iters), loss = 3.70836
I0708 16:56:01.314874 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.68578 (* 0.3 = 0.805735 loss)
I0708 16:56:01.314901 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.68874 (* 0.3 = 0.806623 loss)
I0708 16:56:01.314951 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.68864 (* 1 = 2.68864 loss)
I0708 16:56:01.314968 99468 sgd_solver.cpp:105] Iteration 39280, lr = 0.001
I0708 16:57:17.634802 99468 solver.cpp:218] Iteration 39320 (0.524129 iter/s, 76.3171s/40 iters), loss = 3.74517
I0708 16:57:17.635112 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36162 (* 0.3 = 0.708485 loss)
I0708 16:57:17.635156 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37483 (* 0.3 = 0.712449 loss)
I0708 16:57:17.635215 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36694 (* 1 = 2.36694 loss)
I0708 16:57:17.635268 99468 sgd_solver.cpp:105] Iteration 39320, lr = 0.001
I0708 16:58:34.050081 99468 solver.cpp:218] Iteration 39360 (0.523475 iter/s, 76.4125s/40 iters), loss = 3.68864
I0708 16:58:34.050339 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30681 (* 0.3 = 0.692044 loss)
I0708 16:58:34.050367 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30828 (* 0.3 = 0.692484 loss)
I0708 16:58:34.050384 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29415 (* 1 = 2.29415 loss)
I0708 16:58:34.050400 99468 sgd_solver.cpp:105] Iteration 39360, lr = 0.001
I0708 16:59:50.587194 99468 solver.cpp:218] Iteration 39400 (0.522641 iter/s, 76.5343s/40 iters), loss = 3.73639
I0708 16:59:50.587424 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1378 (* 0.3 = 0.641339 loss)
I0708 16:59:50.587452 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12919 (* 0.3 = 0.638756 loss)
I0708 16:59:50.587499 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11639 (* 1 = 2.11639 loss)
I0708 16:59:50.587517 99468 sgd_solver.cpp:105] Iteration 39400, lr = 0.001
I0708 17:01:07.151099 99468 solver.cpp:218] Iteration 39440 (0.522458 iter/s, 76.5611s/40 iters), loss = 3.70978
I0708 17:01:07.151374 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33634 (* 0.3 = 0.700901 loss)
I0708 17:01:07.151401 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33322 (* 0.3 = 0.699966 loss)
I0708 17:01:07.151460 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32642 (* 1 = 2.32642 loss)
I0708 17:01:07.151477 99468 sgd_solver.cpp:105] Iteration 39440, lr = 0.001
I0708 17:02:23.687676 99468 solver.cpp:218] Iteration 39480 (0.522645 iter/s, 76.5338s/40 iters), loss = 3.6988
I0708 17:02:23.687921 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40821 (* 0.3 = 0.722464 loss)
I0708 17:02:23.687944 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39834 (* 0.3 = 0.719502 loss)
I0708 17:02:23.687999 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3923 (* 1 = 2.3923 loss)
I0708 17:02:23.688015 99468 sgd_solver.cpp:105] Iteration 39480, lr = 0.001
I0708 17:03:40.249732 99468 solver.cpp:218] Iteration 39520 (0.522471 iter/s, 76.5593s/40 iters), loss = 3.64046
I0708 17:03:40.249971 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01839 (* 0.3 = 0.605518 loss)
I0708 17:03:40.249996 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03037 (* 0.3 = 0.60911 loss)
I0708 17:03:40.250010 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02288 (* 1 = 2.02288 loss)
I0708 17:03:40.250033 99468 sgd_solver.cpp:105] Iteration 39520, lr = 0.001
I0708 17:04:56.805173 99468 solver.cpp:218] Iteration 39560 (0.522516 iter/s, 76.5527s/40 iters), loss = 3.73799
I0708 17:04:56.805402 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50716 (* 0.3 = 0.75215 loss)
I0708 17:04:56.805423 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49394 (* 0.3 = 0.748183 loss)
I0708 17:04:56.805438 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.49922 (* 1 = 2.49922 loss)
I0708 17:04:56.805490 99468 sgd_solver.cpp:105] Iteration 39560, lr = 0.001
I0708 17:06:13.384289 99468 solver.cpp:218] Iteration 39600 (0.522354 iter/s, 76.5764s/40 iters), loss = 3.68431
I0708 17:06:13.384522 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25869 (* 0.3 = 0.677606 loss)
I0708 17:06:13.384543 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26026 (* 0.3 = 0.678079 loss)
I0708 17:06:13.384565 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26459 (* 1 = 2.26459 loss)
I0708 17:06:13.384582 99468 sgd_solver.cpp:105] Iteration 39600, lr = 0.001
I0708 17:07:29.880254 99468 solver.cpp:218] Iteration 39640 (0.522922 iter/s, 76.4932s/40 iters), loss = 3.7062
I0708 17:07:29.880486 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07473 (* 0.3 = 0.622419 loss)
I0708 17:07:29.880515 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07854 (* 0.3 = 0.623562 loss)
I0708 17:07:29.880534 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07666 (* 1 = 2.07666 loss)
I0708 17:07:29.880550 99468 sgd_solver.cpp:105] Iteration 39640, lr = 0.001
I0708 17:08:46.183655 99468 solver.cpp:218] Iteration 39680 (0.524242 iter/s, 76.3006s/40 iters), loss = 3.65865
I0708 17:08:46.183953 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27576 (* 0.3 = 0.682727 loss)
I0708 17:08:46.183997 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2642 (* 0.3 = 0.679261 loss)
I0708 17:08:46.184027 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27047 (* 1 = 2.27047 loss)
I0708 17:08:46.184099 99468 sgd_solver.cpp:105] Iteration 39680, lr = 0.001
I0708 17:10:02.486629 99468 solver.cpp:218] Iteration 39720 (0.524245 iter/s, 76.3002s/40 iters), loss = 3.74467
I0708 17:10:02.486860 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5888 (* 0.3 = 0.77664 loss)
I0708 17:10:02.486886 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.58265 (* 0.3 = 0.774794 loss)
I0708 17:10:02.486898 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.58357 (* 1 = 2.58357 loss)
I0708 17:10:02.486915 99468 sgd_solver.cpp:105] Iteration 39720, lr = 0.001
I0708 17:11:18.915093 99468 solver.cpp:218] Iteration 39760 (0.523384 iter/s, 76.4257s/40 iters), loss = 3.67989
I0708 17:11:18.915351 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16053 (* 0.3 = 0.64816 loss)
I0708 17:11:18.915416 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17532 (* 0.3 = 0.652597 loss)
I0708 17:11:18.915436 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17229 (* 1 = 2.17229 loss)
I0708 17:11:18.915452 99468 sgd_solver.cpp:105] Iteration 39760, lr = 0.001
I0708 17:12:35.440322 99468 solver.cpp:218] Iteration 39800 (0.522722 iter/s, 76.5224s/40 iters), loss = 3.65856
I0708 17:12:35.440573 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9773 (* 0.3 = 0.593191 loss)
I0708 17:12:35.440598 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.97682 (* 0.3 = 0.593047 loss)
I0708 17:12:35.440646 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.97268 (* 1 = 1.97268 loss)
I0708 17:12:35.440665 99468 sgd_solver.cpp:105] Iteration 39800, lr = 0.001
I0708 17:13:51.988809 99468 solver.cpp:218] Iteration 39840 (0.52261 iter/s, 76.5389s/40 iters), loss = 3.72296
I0708 17:13:51.989055 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15947 (* 0.3 = 0.647842 loss)
I0708 17:13:51.989082 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.16451 (* 0.3 = 0.649353 loss)
I0708 17:13:51.989131 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16209 (* 1 = 2.16209 loss)
I0708 17:13:51.989150 99468 sgd_solver.cpp:105] Iteration 39840, lr = 0.001
I0708 17:15:08.606523 99468 solver.cpp:218] Iteration 39880 (0.522094 iter/s, 76.6146s/40 iters), loss = 3.68555
I0708 17:15:08.606760 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41488 (* 0.3 = 0.724465 loss)
I0708 17:15:08.606781 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41042 (* 0.3 = 0.723126 loss)
I0708 17:15:08.606794 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4103 (* 1 = 2.4103 loss)
I0708 17:15:08.606817 99468 sgd_solver.cpp:105] Iteration 39880, lr = 0.001
I0708 17:16:25.171418 99468 solver.cpp:218] Iteration 39920 (0.522451 iter/s, 76.5621s/40 iters), loss = 3.73864
I0708 17:16:25.171655 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36307 (* 0.3 = 0.70892 loss)
I0708 17:16:25.171716 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33636 (* 0.3 = 0.700908 loss)
I0708 17:16:25.171735 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35357 (* 1 = 2.35357 loss)
I0708 17:16:25.171769 99468 sgd_solver.cpp:105] Iteration 39920, lr = 0.001
I0708 17:17:41.617244 99468 solver.cpp:218] Iteration 39960 (0.523265 iter/s, 76.4431s/40 iters), loss = 3.67881
I0708 17:17:41.617486 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33196 (* 0.3 = 0.699589 loss)
I0708 17:17:41.617513 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30943 (* 0.3 = 0.692828 loss)
I0708 17:17:41.617528 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32028 (* 1 = 2.32028 loss)
I0708 17:17:41.617544 99468 sgd_solver.cpp:105] Iteration 39960, lr = 0.001
I0708 17:18:55.263113 99468 solver.cpp:447] Snapshotting to binary proto file /data04/googlenet/caffemodel/_iter_40000.caffemodel
I0708 17:18:56.210646 99468 sgd_solver.cpp:273] Snapshotting solver state to binary proto file /data04/googlenet/caffemodel/_iter_40000.solverstate
I0708 17:18:56.300104 99468 solver.cpp:330] Iteration 40000, Testing net (#0)
I0708 17:28:45.949859 99629 data_layer.cpp:73] Restarting data prefetching from start.
I0708 17:29:23.580020 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07045 (* 0.3 = 0.621135 loss)
I0708 17:29:23.580320 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.367647
I0708 17:29:23.580340 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794742
I0708 17:29:23.580358 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07009 (* 0.3 = 0.621026 loss)
I0708 17:29:23.580371 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.367647
I0708 17:29:23.580428 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794742
I0708 17:29:23.580447 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.06782 (* 1 = 2.06782 loss)
I0708 17:29:23.580458 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.367647
I0708 17:29:23.580468 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794742
I0708 17:29:25.485664 99468 solver.cpp:218] Iteration 40000 (0.0568307 iter/s, 703.845s/40 iters), loss = 3.66746
I0708 17:29:25.485764 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.74459 (* 0.3 = 0.823376 loss)
I0708 17:29:25.485781 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.7504 (* 0.3 = 0.82512 loss)
I0708 17:29:25.485798 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.75713 (* 1 = 2.75713 loss)
I0708 17:29:25.485816 99468 sgd_solver.cpp:105] Iteration 40000, lr = 0.001
I0708 17:30:42.101366 99468 solver.cpp:218] Iteration 40040 (0.522104 iter/s, 76.6131s/40 iters), loss = 3.74657
I0708 17:30:42.101604 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43398 (* 0.3 = 0.730195 loss)
I0708 17:30:42.101670 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42521 (* 0.3 = 0.727562 loss)
I0708 17:30:42.101683 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42833 (* 1 = 2.42833 loss)
I0708 17:30:42.101702 99468 sgd_solver.cpp:105] Iteration 40040, lr = 0.001
I0708 17:31:58.751485 99468 solver.cpp:218] Iteration 40080 (0.521871 iter/s, 76.6474s/40 iters), loss = 3.71076
I0708 17:31:58.751715 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16752 (* 0.3 = 0.650255 loss)
I0708 17:31:58.751739 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17354 (* 0.3 = 0.652061 loss)
I0708 17:31:58.751754 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17554 (* 1 = 2.17554 loss)
I0708 17:31:58.751768 99468 sgd_solver.cpp:105] Iteration 40080, lr = 0.001
I0708 17:33:15.243791 99468 solver.cpp:218] Iteration 40120 (0.522947 iter/s, 76.4895s/40 iters), loss = 3.69388
I0708 17:33:15.244032 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.50358 (* 0.3 = 0.751073 loss)
I0708 17:33:15.244093 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5154 (* 0.3 = 0.754621 loss)
I0708 17:33:15.244107 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50718 (* 1 = 2.50718 loss)
I0708 17:33:15.244140 99468 sgd_solver.cpp:105] Iteration 40120, lr = 0.001
I0708 17:34:31.777606 99468 solver.cpp:218] Iteration 40160 (0.522664 iter/s, 76.5311s/40 iters), loss = 3.70377
I0708 17:34:31.777838 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37862 (* 0.3 = 0.713585 loss)
I0708 17:34:31.777887 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3786 (* 0.3 = 0.713581 loss)
I0708 17:34:31.777917 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36762 (* 1 = 2.36762 loss)
I0708 17:34:31.777935 99468 sgd_solver.cpp:105] Iteration 40160, lr = 0.001
I0708 17:35:48.455440 99468 solver.cpp:218] Iteration 40200 (0.521682 iter/s, 76.6751s/40 iters), loss = 3.6889
I0708 17:35:48.455673 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5528 (* 0.3 = 0.765839 loss)
I0708 17:35:48.455735 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5509 (* 0.3 = 0.765269 loss)
I0708 17:35:48.455749 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55251 (* 1 = 2.55251 loss)
I0708 17:35:48.455768 99468 sgd_solver.cpp:105] Iteration 40200, lr = 0.001
I0708 17:37:05.021291 99468 solver.cpp:218] Iteration 40240 (0.522445 iter/s, 76.5631s/40 iters), loss = 3.73076
I0708 17:37:05.021526 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.52955 (* 0.3 = 0.758864 loss)
I0708 17:37:05.021561 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.54315 (* 0.3 = 0.762944 loss)
I0708 17:37:05.021575 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.53536 (* 1 = 2.53536 loss)
I0708 17:37:05.021623 99468 sgd_solver.cpp:105] Iteration 40240, lr = 0.001
I0708 17:38:21.638996 99468 solver.cpp:218] Iteration 40280 (0.522092 iter/s, 76.6149s/40 iters), loss = 3.71318
I0708 17:38:21.639297 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47115 (* 0.3 = 0.741344 loss)
I0708 17:38:21.639354 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47376 (* 0.3 = 0.742128 loss)
I0708 17:38:21.639367 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4686 (* 1 = 2.4686 loss)
I0708 17:38:21.639382 99468 sgd_solver.cpp:105] Iteration 40280, lr = 0.001
I0708 17:39:38.258859 99468 solver.cpp:218] Iteration 40320 (0.522077 iter/s, 76.617s/40 iters), loss = 3.72164
I0708 17:39:38.259091 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.0558 (* 0.3 = 0.616741 loss)
I0708 17:39:38.259114 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04612 (* 0.3 = 0.613835 loss)
I0708 17:39:38.259160 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04744 (* 1 = 2.04744 loss)
I0708 17:39:38.259181 99468 sgd_solver.cpp:105] Iteration 40320, lr = 0.001
I0708 17:40:54.883251 99468 solver.cpp:218] Iteration 40360 (0.522046 iter/s, 76.6216s/40 iters), loss = 3.70496
I0708 17:40:54.883488 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07491 (* 0.3 = 0.622472 loss)
I0708 17:40:54.883517 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07921 (* 0.3 = 0.623764 loss)
I0708 17:40:54.883536 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07611 (* 1 = 2.07611 loss)
I0708 17:40:54.883551 99468 sgd_solver.cpp:105] Iteration 40360, lr = 0.001
I0708 17:42:11.467433 99468 solver.cpp:218] Iteration 40400 (0.52232 iter/s, 76.5814s/40 iters), loss = 3.73646
I0708 17:42:11.467720 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44205 (* 0.3 = 0.732614 loss)
I0708 17:42:11.467748 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45071 (* 0.3 = 0.735212 loss)
I0708 17:42:11.467767 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44504 (* 1 = 2.44504 loss)
I0708 17:42:11.467784 99468 sgd_solver.cpp:105] Iteration 40400, lr = 0.001
I0708 17:43:27.923633 99468 solver.cpp:218] Iteration 40440 (0.523195 iter/s, 76.4534s/40 iters), loss = 3.6864
I0708 17:43:27.923862 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33568 (* 0.3 = 0.700703 loss)
I0708 17:43:27.923919 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35893 (* 0.3 = 0.70768 loss)
I0708 17:43:27.923933 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34971 (* 1 = 2.34971 loss)
I0708 17:43:27.923952 99468 sgd_solver.cpp:105] Iteration 40440, lr = 0.001
I0708 17:44:44.427857 99468 solver.cpp:218] Iteration 40480 (0.522866 iter/s, 76.5015s/40 iters), loss = 3.76107
I0708 17:44:44.428088 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51735 (* 0.3 = 0.755205 loss)
I0708 17:44:44.428138 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.51615 (* 0.3 = 0.754846 loss)
I0708 17:44:44.428155 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51042 (* 1 = 2.51042 loss)
I0708 17:44:44.428171 99468 sgd_solver.cpp:105] Iteration 40480, lr = 0.001
I0708 17:46:00.946180 99468 solver.cpp:218] Iteration 40520 (0.522769 iter/s, 76.5156s/40 iters), loss = 3.69086
I0708 17:46:00.946399 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.99821 (* 0.3 = 0.599462 loss)
I0708 17:46:00.946422 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.99761 (* 0.3 = 0.599284 loss)
I0708 17:46:00.946435 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.00428 (* 1 = 2.00428 loss)
I0708 17:46:00.946451 99468 sgd_solver.cpp:105] Iteration 40520, lr = 0.001
I0708 17:47:17.608124 99468 solver.cpp:218] Iteration 40560 (0.52179 iter/s, 76.6592s/40 iters), loss = 3.71951
I0708 17:47:17.608379 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.00691 (* 0.3 = 0.602073 loss)
I0708 17:47:17.608400 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00883 (* 0.3 = 0.602648 loss)
I0708 17:47:17.608412 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.99945 (* 1 = 1.99945 loss)
I0708 17:47:17.608431 99468 sgd_solver.cpp:105] Iteration 40560, lr = 0.001
I0708 17:48:34.025363 99468 solver.cpp:218] Iteration 40600 (0.523461 iter/s, 76.4145s/40 iters), loss = 3.71836
I0708 17:48:34.025607 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18069 (* 0.3 = 0.654206 loss)
I0708 17:48:34.025671 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18347 (* 0.3 = 0.655042 loss)
I0708 17:48:34.025684 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18055 (* 1 = 2.18055 loss)
I0708 17:48:34.025699 99468 sgd_solver.cpp:105] Iteration 40600, lr = 0.001
I0708 17:49:50.565877 99468 solver.cpp:218] Iteration 40640 (0.522618 iter/s, 76.5377s/40 iters), loss = 3.65918
I0708 17:49:50.566107 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08924 (* 0.3 = 0.626772 loss)
I0708 17:49:50.566167 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09064 (* 0.3 = 0.627192 loss)
I0708 17:49:50.566181 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08664 (* 1 = 2.08664 loss)
I0708 17:49:50.566200 99468 sgd_solver.cpp:105] Iteration 40640, lr = 0.001
I0708 17:51:07.085180 99468 solver.cpp:218] Iteration 40680 (0.522763 iter/s, 76.5166s/40 iters), loss = 3.65075
I0708 17:51:07.085412 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39784 (* 0.3 = 0.719353 loss)
I0708 17:51:07.085431 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38967 (* 0.3 = 0.716901 loss)
I0708 17:51:07.085444 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39064 (* 1 = 2.39064 loss)
I0708 17:51:07.085461 99468 sgd_solver.cpp:105] Iteration 40680, lr = 0.001
I0708 17:52:23.703078 99468 solver.cpp:218] Iteration 40720 (0.52209 iter/s, 76.6151s/40 iters), loss = 3.6871
I0708 17:52:23.703294 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2243 (* 0.3 = 0.667291 loss)
I0708 17:52:23.703317 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24544 (* 0.3 = 0.673631 loss)
I0708 17:52:23.703332 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23433 (* 1 = 2.23433 loss)
I0708 17:52:23.703348 99468 sgd_solver.cpp:105] Iteration 40720, lr = 0.001
I0708 17:53:40.142266 99468 solver.cpp:218] Iteration 40760 (0.52331 iter/s, 76.4365s/40 iters), loss = 3.73475
I0708 17:53:40.142493 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4748 (* 0.3 = 0.742439 loss)
I0708 17:53:40.142515 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4593 (* 0.3 = 0.73779 loss)
I0708 17:53:40.142529 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4543 (* 1 = 2.4543 loss)
I0708 17:53:40.142546 99468 sgd_solver.cpp:105] Iteration 40760, lr = 0.001
I0708 17:54:56.428437 99468 solver.cpp:218] Iteration 40800 (0.52436 iter/s, 76.2834s/40 iters), loss = 3.74309
I0708 17:54:56.428668 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09742 (* 0.3 = 0.629226 loss)
I0708 17:54:56.428730 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.096 (* 0.3 = 0.628799 loss)
I0708 17:54:56.428742 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09411 (* 1 = 2.09411 loss)
I0708 17:54:56.428762 99468 sgd_solver.cpp:105] Iteration 40800, lr = 0.001
I0708 17:56:12.801854 99468 solver.cpp:218] Iteration 40840 (0.523761 iter/s, 76.3707s/40 iters), loss = 3.663
I0708 17:56:12.802075 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29533 (* 0.3 = 0.688599 loss)
I0708 17:56:12.802098 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30484 (* 0.3 = 0.691452 loss)
I0708 17:56:12.802112 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30339 (* 1 = 2.30339 loss)
I0708 17:56:12.802131 99468 sgd_solver.cpp:105] Iteration 40840, lr = 0.001
I0708 17:57:29.204025 99468 solver.cpp:218] Iteration 40880 (0.523564 iter/s, 76.3994s/40 iters), loss = 3.65939
I0708 17:57:29.204295 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32549 (* 0.3 = 0.697646 loss)
I0708 17:57:29.204361 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32654 (* 0.3 = 0.697962 loss)
I0708 17:57:29.204375 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31939 (* 1 = 2.31939 loss)
I0708 17:57:29.204392 99468 sgd_solver.cpp:105] Iteration 40880, lr = 0.001
I0708 17:58:45.866760 99468 solver.cpp:218] Iteration 40920 (0.521785 iter/s, 76.6599s/40 iters), loss = 3.66876
I0708 17:58:45.867007 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.87663 (* 0.3 = 0.562988 loss)
I0708 17:58:45.867030 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.878 (* 0.3 = 0.563401 loss)
I0708 17:58:45.867043 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.86998 (* 1 = 1.86998 loss)
I0708 17:58:45.867060 99468 sgd_solver.cpp:105] Iteration 40920, lr = 0.001
I0708 18:00:02.452672 99468 solver.cpp:218] Iteration 40960 (0.522308 iter/s, 76.5831s/40 iters), loss = 3.73327
I0708 18:00:02.452893 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20662 (* 0.3 = 0.661986 loss)
I0708 18:00:02.452914 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20153 (* 0.3 = 0.660461 loss)
I0708 18:00:02.452929 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20742 (* 1 = 2.20742 loss)
I0708 18:00:02.452945 99468 sgd_solver.cpp:105] Iteration 40960, lr = 0.001
I0708 18:01:18.897001 99468 solver.cpp:218] Iteration 41000 (0.523275 iter/s, 76.4416s/40 iters), loss = 3.70122
I0708 18:01:18.897245 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26383 (* 0.3 = 0.679149 loss)
I0708 18:01:18.897272 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23804 (* 0.3 = 0.671413 loss)
I0708 18:01:18.897326 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24733 (* 1 = 2.24733 loss)
I0708 18:01:18.897342 99468 sgd_solver.cpp:105] Iteration 41000, lr = 0.001
I0708 18:02:35.507270 99468 solver.cpp:218] Iteration 41040 (0.522142 iter/s, 76.6075s/40 iters), loss = 3.76043
I0708 18:02:35.507514 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3623 (* 0.3 = 0.708689 loss)
I0708 18:02:35.507537 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37252 (* 0.3 = 0.711757 loss)
I0708 18:02:35.507591 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37555 (* 1 = 2.37555 loss)
I0708 18:02:35.507606 99468 sgd_solver.cpp:105] Iteration 41040, lr = 0.001
I0708 18:03:52.046602 99468 solver.cpp:218] Iteration 41080 (0.522626 iter/s, 76.5366s/40 iters), loss = 3.68222
I0708 18:03:52.046852 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32911 (* 0.3 = 0.698732 loss)
I0708 18:03:52.046876 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34346 (* 0.3 = 0.703037 loss)
I0708 18:03:52.046890 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33551 (* 1 = 2.33551 loss)
I0708 18:03:52.046906 99468 sgd_solver.cpp:105] Iteration 41080, lr = 0.001
I0708 18:05:08.739262 99468 solver.cpp:218] Iteration 41120 (0.521581 iter/s, 76.6899s/40 iters), loss = 3.71791
I0708 18:05:08.739503 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22133 (* 0.3 = 0.666398 loss)
I0708 18:05:08.739526 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21876 (* 0.3 = 0.665627 loss)
I0708 18:05:08.739539 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22648 (* 1 = 2.22648 loss)
I0708 18:05:08.739567 99468 sgd_solver.cpp:105] Iteration 41120, lr = 0.001
I0708 18:06:25.133991 99468 solver.cpp:218] Iteration 41160 (0.523652 iter/s, 76.3867s/40 iters), loss = 3.75897
I0708 18:06:25.134232 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34066 (* 0.3 = 0.702197 loss)
I0708 18:06:25.134284 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33778 (* 0.3 = 0.701334 loss)
I0708 18:06:25.134297 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34295 (* 1 = 2.34295 loss)
I0708 18:06:25.134331 99468 sgd_solver.cpp:105] Iteration 41160, lr = 0.001
I0708 18:07:41.741984 99468 solver.cpp:218] Iteration 41200 (0.522158 iter/s, 76.6052s/40 iters), loss = 3.69814
I0708 18:07:41.742254 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22525 (* 0.3 = 0.667576 loss)
I0708 18:07:41.742278 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23558 (* 0.3 = 0.670675 loss)
I0708 18:07:41.742292 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22744 (* 1 = 2.22744 loss)
I0708 18:07:41.742307 99468 sgd_solver.cpp:105] Iteration 41200, lr = 0.001
I0708 18:08:58.220643 99468 solver.cpp:218] Iteration 41240 (0.523041 iter/s, 76.4759s/40 iters), loss = 3.7421
I0708 18:08:58.220904 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.48502 (* 0.3 = 0.745506 loss)
I0708 18:08:58.220957 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.46084 (* 0.3 = 0.738253 loss)
I0708 18:08:58.220970 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47115 (* 1 = 2.47115 loss)
I0708 18:08:58.220986 99468 sgd_solver.cpp:105] Iteration 41240, lr = 0.001
I0708 18:10:14.855886 99468 solver.cpp:218] Iteration 41280 (0.521972 iter/s, 76.6325s/40 iters), loss = 3.68623
I0708 18:10:14.856122 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14138 (* 0.3 = 0.642413 loss)
I0708 18:10:14.856145 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13903 (* 0.3 = 0.641708 loss)
I0708 18:10:14.856158 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14198 (* 1 = 2.14198 loss)
I0708 18:10:14.856173 99468 sgd_solver.cpp:105] Iteration 41280, lr = 0.001
I0708 18:11:31.257251 99468 solver.cpp:218] Iteration 41320 (0.52357 iter/s, 76.3986s/40 iters), loss = 3.69889
I0708 18:11:31.257483 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19369 (* 0.3 = 0.658107 loss)
I0708 18:11:31.257508 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19506 (* 0.3 = 0.658519 loss)
I0708 18:11:31.257524 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19765 (* 1 = 2.19765 loss)
I0708 18:11:31.257540 99468 sgd_solver.cpp:105] Iteration 41320, lr = 0.001
I0708 18:12:47.675290 99468 solver.cpp:218] Iteration 41360 (0.523456 iter/s, 76.4153s/40 iters), loss = 3.65985
I0708 18:12:47.675520 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4388 (* 0.3 = 0.731641 loss)
I0708 18:12:47.675581 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4405 (* 0.3 = 0.732149 loss)
I0708 18:12:47.675595 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42868 (* 1 = 2.42868 loss)
I0708 18:12:47.675609 99468 sgd_solver.cpp:105] Iteration 41360, lr = 0.001
I0708 18:14:04.292551 99468 solver.cpp:218] Iteration 41400 (0.522094 iter/s, 76.6145s/40 iters), loss = 3.75909
I0708 18:14:04.292794 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.65988 (* 0.3 = 0.797965 loss)
I0708 18:14:04.292853 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.66863 (* 0.3 = 0.80059 loss)
I0708 18:14:04.292867 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.66758 (* 1 = 2.66758 loss)
I0708 18:14:04.292882 99468 sgd_solver.cpp:105] Iteration 41400, lr = 0.001
I0708 18:15:20.889670 99468 solver.cpp:218] Iteration 41440 (0.522232 iter/s, 76.5943s/40 iters), loss = 3.64718
I0708 18:15:20.889909 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26731 (* 0.3 = 0.680193 loss)
I0708 18:15:20.889966 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26927 (* 0.3 = 0.68078 loss)
I0708 18:15:20.889981 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27423 (* 1 = 2.27423 loss)
I0708 18:15:20.889997 99468 sgd_solver.cpp:105] Iteration 41440, lr = 0.001
I0708 18:16:37.217227 99468 solver.cpp:218] Iteration 41480 (0.524076 iter/s, 76.3248s/40 iters), loss = 3.70196
I0708 18:16:37.217506 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.416 (* 0.3 = 0.724801 loss)
I0708 18:16:37.217566 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40423 (* 0.3 = 0.721269 loss)
I0708 18:16:37.217578 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40162 (* 1 = 2.40162 loss)
I0708 18:16:37.217600 99468 sgd_solver.cpp:105] Iteration 41480, lr = 0.001
I0708 18:17:53.668808 99468 solver.cpp:218] Iteration 41520 (0.523226 iter/s, 76.4488s/40 iters), loss = 3.73839
I0708 18:17:53.669039 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.67479 (* 0.3 = 0.802438 loss)
I0708 18:17:53.669095 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.66319 (* 0.3 = 0.798957 loss)
I0708 18:17:53.669109 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.67048 (* 1 = 2.67048 loss)
I0708 18:17:53.669124 99468 sgd_solver.cpp:105] Iteration 41520, lr = 0.001
I0708 18:19:10.229502 99468 solver.cpp:218] Iteration 41560 (0.52248 iter/s, 76.5579s/40 iters), loss = 3.67582
I0708 18:19:10.229733 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29552 (* 0.3 = 0.688655 loss)
I0708 18:19:10.229753 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28792 (* 0.3 = 0.686377 loss)
I0708 18:19:10.229764 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28757 (* 1 = 2.28757 loss)
I0708 18:19:10.229820 99468 sgd_solver.cpp:105] Iteration 41560, lr = 0.001
I0708 18:20:26.871309 99468 solver.cpp:218] Iteration 41600 (0.521927 iter/s, 76.639s/40 iters), loss = 3.65055
I0708 18:20:26.871533 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.99051 (* 0.3 = 0.597154 loss)
I0708 18:20:26.871562 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.99401 (* 0.3 = 0.598203 loss)
I0708 18:20:26.871578 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.98157 (* 1 = 1.98157 loss)
I0708 18:20:26.871593 99468 sgd_solver.cpp:105] Iteration 41600, lr = 0.001
I0708 18:21:43.545619 99468 solver.cpp:218] Iteration 41640 (0.521706 iter/s, 76.6716s/40 iters), loss = 3.6923
I0708 18:21:43.545836 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36495 (* 0.3 = 0.709485 loss)
I0708 18:21:43.545861 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37763 (* 0.3 = 0.713288 loss)
I0708 18:21:43.545874 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36589 (* 1 = 2.36589 loss)
I0708 18:21:43.545889 99468 sgd_solver.cpp:105] Iteration 41640, lr = 0.001
I0708 18:23:00.145042 99468 solver.cpp:218] Iteration 41680 (0.522216 iter/s, 76.5967s/40 iters), loss = 3.66807
I0708 18:23:00.145263 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.61557 (* 0.3 = 0.784671 loss)
I0708 18:23:00.145321 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.63831 (* 0.3 = 0.791493 loss)
I0708 18:23:00.145337 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.64328 (* 1 = 2.64328 loss)
I0708 18:23:00.145352 99468 sgd_solver.cpp:105] Iteration 41680, lr = 0.001
I0708 18:24:16.669095 99468 solver.cpp:218] Iteration 41720 (0.52273 iter/s, 76.5213s/40 iters), loss = 3.72551
I0708 18:24:16.669319 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25312 (* 0.3 = 0.675937 loss)
I0708 18:24:16.669344 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25818 (* 0.3 = 0.677455 loss)
I0708 18:24:16.669391 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25296 (* 1 = 2.25296 loss)
I0708 18:24:16.669409 99468 sgd_solver.cpp:105] Iteration 41720, lr = 0.001
I0708 18:25:33.184159 99468 solver.cpp:218] Iteration 41760 (0.522792 iter/s, 76.5123s/40 iters), loss = 3.65434
I0708 18:25:33.184388 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.95714 (* 0.3 = 0.587141 loss)
I0708 18:25:33.184438 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.9572 (* 0.3 = 0.58716 loss)
I0708 18:25:33.184453 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.94739 (* 1 = 1.94739 loss)
I0708 18:25:33.184473 99468 sgd_solver.cpp:105] Iteration 41760, lr = 0.001
I0708 18:26:49.772364 99468 solver.cpp:218] Iteration 41800 (0.522292 iter/s, 76.5855s/40 iters), loss = 3.69755
I0708 18:26:49.772810 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22597 (* 0.3 = 0.667792 loss)
I0708 18:26:49.772831 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22647 (* 0.3 = 0.66794 loss)
I0708 18:26:49.772845 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23491 (* 1 = 2.23491 loss)
I0708 18:26:49.772862 99468 sgd_solver.cpp:105] Iteration 41800, lr = 0.001
I0708 18:28:06.367533 99468 solver.cpp:218] Iteration 41840 (0.522246 iter/s, 76.5922s/40 iters), loss = 3.75246
I0708 18:28:06.367777 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.53005 (* 0.3 = 0.759014 loss)
I0708 18:28:06.367800 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.53271 (* 0.3 = 0.759812 loss)
I0708 18:28:06.367813 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.52835 (* 1 = 2.52835 loss)
I0708 18:28:06.367861 99468 sgd_solver.cpp:105] Iteration 41840, lr = 0.001
I0708 18:29:22.973305 99468 solver.cpp:218] Iteration 41880 (0.522173 iter/s, 76.603s/40 iters), loss = 3.7204
I0708 18:29:22.973528 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37569 (* 0.3 = 0.712708 loss)
I0708 18:29:22.973587 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3891 (* 0.3 = 0.71673 loss)
I0708 18:29:22.973598 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36853 (* 1 = 2.36853 loss)
I0708 18:29:22.973614 99468 sgd_solver.cpp:105] Iteration 41880, lr = 0.001
I0708 18:30:39.529816 99468 solver.cpp:218] Iteration 41920 (0.522509 iter/s, 76.5538s/40 iters), loss = 3.66694
I0708 18:30:39.530048 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41852 (* 0.3 = 0.725555 loss)
I0708 18:30:39.530102 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42288 (* 0.3 = 0.726864 loss)
I0708 18:30:39.530133 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43071 (* 1 = 2.43071 loss)
I0708 18:30:39.530149 99468 sgd_solver.cpp:105] Iteration 41920, lr = 0.001
I0708 18:31:55.779494 99468 solver.cpp:218] Iteration 41960 (0.524611 iter/s, 76.2469s/40 iters), loss = 3.73475
I0708 18:31:55.779736 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06953 (* 0.3 = 0.620858 loss)
I0708 18:31:55.779764 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0674 (* 0.3 = 0.620219 loss)
I0708 18:31:55.779778 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.05775 (* 1 = 2.05775 loss)
I0708 18:31:55.779795 99468 sgd_solver.cpp:105] Iteration 41960, lr = 0.001
I0708 18:33:11.994477 99468 solver.cpp:218] Iteration 42000 (0.52485 iter/s, 76.2122s/40 iters), loss = 3.71851
I0708 18:33:11.994719 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.84383 (* 0.3 = 0.853149 loss)
I0708 18:33:11.994745 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.86656 (* 0.3 = 0.859967 loss)
I0708 18:33:11.994794 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.85958 (* 1 = 2.85958 loss)
I0708 18:33:11.994812 99468 sgd_solver.cpp:105] Iteration 42000, lr = 0.001
I0708 18:34:28.268947 99468 solver.cpp:218] Iteration 42040 (0.524441 iter/s, 76.2717s/40 iters), loss = 3.7917
I0708 18:34:28.269194 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43719 (* 0.3 = 0.731157 loss)
I0708 18:34:28.269222 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43802 (* 0.3 = 0.731405 loss)
I0708 18:34:28.269238 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43991 (* 1 = 2.43991 loss)
I0708 18:34:28.269254 99468 sgd_solver.cpp:105] Iteration 42040, lr = 0.001
I0708 18:35:44.521237 99468 solver.cpp:218] Iteration 42080 (0.524593 iter/s, 76.2495s/40 iters), loss = 3.69117
I0708 18:35:44.521474 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18465 (* 0.3 = 0.655396 loss)
I0708 18:35:44.521531 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18118 (* 0.3 = 0.654353 loss)
I0708 18:35:44.521545 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18595 (* 1 = 2.18595 loss)
I0708 18:35:44.521571 99468 sgd_solver.cpp:105] Iteration 42080, lr = 0.001
I0708 18:37:01.108026 99468 solver.cpp:218] Iteration 42120 (0.522302 iter/s, 76.584s/40 iters), loss = 3.6795
I0708 18:37:01.108285 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11686 (* 0.3 = 0.635059 loss)
I0708 18:37:01.108345 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1125 (* 0.3 = 0.633749 loss)
I0708 18:37:01.108359 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11764 (* 1 = 2.11764 loss)
I0708 18:37:01.108376 99468 sgd_solver.cpp:105] Iteration 42120, lr = 0.001
I0708 18:38:17.672343 99468 solver.cpp:218] Iteration 42160 (0.522456 iter/s, 76.5615s/40 iters), loss = 3.66108
I0708 18:38:17.672585 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2193 (* 0.3 = 0.665789 loss)
I0708 18:38:17.672608 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2063 (* 0.3 = 0.661891 loss)
I0708 18:38:17.672658 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22079 (* 1 = 2.22079 loss)
I0708 18:38:17.672677 99468 sgd_solver.cpp:105] Iteration 42160, lr = 0.001
I0708 18:39:34.276945 99468 solver.cpp:218] Iteration 42200 (0.522181 iter/s, 76.6018s/40 iters), loss = 3.69318
I0708 18:39:34.277184 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46827 (* 0.3 = 0.74048 loss)
I0708 18:39:34.277207 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45442 (* 0.3 = 0.736325 loss)
I0708 18:39:34.277252 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45786 (* 1 = 2.45786 loss)
I0708 18:39:34.277271 99468 sgd_solver.cpp:105] Iteration 42200, lr = 0.001
I0708 18:40:50.759579 99468 solver.cpp:218] Iteration 42240 (0.523014 iter/s, 76.4799s/40 iters), loss = 3.70886
I0708 18:40:50.759876 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37074 (* 0.3 = 0.711222 loss)
I0708 18:40:50.759902 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35589 (* 0.3 = 0.706766 loss)
I0708 18:40:50.759922 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36154 (* 1 = 2.36154 loss)
I0708 18:40:50.759939 99468 sgd_solver.cpp:105] Iteration 42240, lr = 0.001
I0708 18:42:07.189218 99468 solver.cpp:218] Iteration 42280 (0.523376 iter/s, 76.4268s/40 iters), loss = 3.70321
I0708 18:42:07.189450 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3249 (* 0.3 = 0.697471 loss)
I0708 18:42:07.189502 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3426 (* 0.3 = 0.702779 loss)
I0708 18:42:07.189517 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32515 (* 1 = 2.32515 loss)
I0708 18:42:07.189532 99468 sgd_solver.cpp:105] Iteration 42280, lr = 0.001
I0708 18:43:23.754510 99468 solver.cpp:218] Iteration 42320 (0.522449 iter/s, 76.5625s/40 iters), loss = 3.71653
I0708 18:43:23.754762 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.63378 (* 0.3 = 0.790135 loss)
I0708 18:43:23.754815 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.64578 (* 0.3 = 0.793733 loss)
I0708 18:43:23.754827 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.64698 (* 1 = 2.64698 loss)
I0708 18:43:23.754848 99468 sgd_solver.cpp:105] Iteration 42320, lr = 0.001
I0708 18:44:40.369081 99468 solver.cpp:218] Iteration 42360 (0.522113 iter/s, 76.6118s/40 iters), loss = 3.71223
I0708 18:44:40.369314 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45204 (* 0.3 = 0.735611 loss)
I0708 18:44:40.369339 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4501 (* 0.3 = 0.735031 loss)
I0708 18:44:40.369351 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44524 (* 1 = 2.44524 loss)
I0708 18:44:40.369402 99468 sgd_solver.cpp:105] Iteration 42360, lr = 0.001
I0708 18:45:56.814862 99468 solver.cpp:218] Iteration 42400 (0.523266 iter/s, 76.443s/40 iters), loss = 3.65828
I0708 18:45:56.815102 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23647 (* 0.3 = 0.670942 loss)
I0708 18:45:56.815155 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22678 (* 0.3 = 0.668033 loss)
I0708 18:45:56.815168 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23356 (* 1 = 2.23356 loss)
I0708 18:45:56.815184 99468 sgd_solver.cpp:105] Iteration 42400, lr = 0.001
I0708 18:47:13.358328 99468 solver.cpp:218] Iteration 42440 (0.522598 iter/s, 76.5407s/40 iters), loss = 3.67038
I0708 18:47:13.358613 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27157 (* 0.3 = 0.681472 loss)
I0708 18:47:13.358636 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26664 (* 0.3 = 0.679992 loss)
I0708 18:47:13.358681 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27403 (* 1 = 2.27403 loss)
I0708 18:47:13.358702 99468 sgd_solver.cpp:105] Iteration 42440, lr = 0.001
I0708 18:48:29.840572 99468 solver.cpp:218] Iteration 42480 (0.523016 iter/s, 76.4794s/40 iters), loss = 3.74463
I0708 18:48:29.840806 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43297 (* 0.3 = 0.729892 loss)
I0708 18:48:29.840862 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4326 (* 0.3 = 0.729781 loss)
I0708 18:48:29.840875 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43319 (* 1 = 2.43319 loss)
I0708 18:48:29.840909 99468 sgd_solver.cpp:105] Iteration 42480, lr = 0.001
I0708 18:49:46.488118 99468 solver.cpp:218] Iteration 42520 (0.521888 iter/s, 76.6448s/40 iters), loss = 3.68679
I0708 18:49:46.488364 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1924 (* 0.3 = 0.657722 loss)
I0708 18:49:46.488420 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21684 (* 0.3 = 0.665052 loss)
I0708 18:49:46.488433 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20514 (* 1 = 2.20514 loss)
I0708 18:49:46.488451 99468 sgd_solver.cpp:105] Iteration 42520, lr = 0.001
I0708 18:51:03.110414 99468 solver.cpp:218] Iteration 42560 (0.52206 iter/s, 76.6195s/40 iters), loss = 3.75612
I0708 18:51:03.110646 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9755 (* 0.3 = 0.59265 loss)
I0708 18:51:03.110666 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.98404 (* 0.3 = 0.595213 loss)
I0708 18:51:03.110680 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.97063 (* 1 = 1.97063 loss)
I0708 18:51:03.110700 99468 sgd_solver.cpp:105] Iteration 42560, lr = 0.001
I0708 18:52:19.668500 99468 solver.cpp:218] Iteration 42600 (0.522498 iter/s, 76.5553s/40 iters), loss = 3.67617
I0708 18:52:19.668728 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38081 (* 0.3 = 0.714244 loss)
I0708 18:52:19.668754 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38649 (* 0.3 = 0.715946 loss)
I0708 18:52:19.668808 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38227 (* 1 = 2.38227 loss)
I0708 18:52:19.668824 99468 sgd_solver.cpp:105] Iteration 42600, lr = 0.001
I0708 18:53:36.308208 99468 solver.cpp:218] Iteration 42640 (0.521941 iter/s, 76.6369s/40 iters), loss = 3.7227
I0708 18:53:36.308446 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.0267 (* 0.3 = 0.608009 loss)
I0708 18:53:36.308502 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03297 (* 0.3 = 0.609892 loss)
I0708 18:53:36.308516 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02746 (* 1 = 2.02746 loss)
I0708 18:53:36.308549 99468 sgd_solver.cpp:105] Iteration 42640, lr = 0.001
I0708 18:54:52.908084 99468 solver.cpp:218] Iteration 42680 (0.522243 iter/s, 76.5927s/40 iters), loss = 3.71608
I0708 18:54:52.908309 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35746 (* 0.3 = 0.707237 loss)
I0708 18:54:52.908329 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35786 (* 0.3 = 0.707358 loss)
I0708 18:54:52.908341 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34319 (* 1 = 2.34319 loss)
I0708 18:54:52.908399 99468 sgd_solver.cpp:105] Iteration 42680, lr = 0.001
I0708 18:56:09.536618 99468 solver.cpp:218] Iteration 42720 (0.522018 iter/s, 76.6258s/40 iters), loss = 3.73923
I0708 18:56:09.536885 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.95912 (* 0.3 = 0.587736 loss)
I0708 18:56:09.536906 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.94197 (* 0.3 = 0.58259 loss)
I0708 18:56:09.536921 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.95155 (* 1 = 1.95155 loss)
I0708 18:56:09.536937 99468 sgd_solver.cpp:105] Iteration 42720, lr = 0.001
I0708 18:57:26.139915 99468 solver.cpp:218] Iteration 42760 (0.52219 iter/s, 76.6005s/40 iters), loss = 3.74565
I0708 18:57:26.140151 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11842 (* 0.3 = 0.635525 loss)
I0708 18:57:26.140205 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12332 (* 0.3 = 0.636995 loss)
I0708 18:57:26.140218 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12984 (* 1 = 2.12984 loss)
I0708 18:57:26.140251 99468 sgd_solver.cpp:105] Iteration 42760, lr = 0.001
I0708 18:58:42.713820 99468 solver.cpp:218] Iteration 42800 (0.52239 iter/s, 76.5711s/40 iters), loss = 3.70907
I0708 18:58:42.714043 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02341 (* 0.3 = 0.607023 loss)
I0708 18:58:42.714066 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03201 (* 0.3 = 0.609603 loss)
I0708 18:58:42.714115 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0344 (* 1 = 2.0344 loss)
I0708 18:58:42.714134 99468 sgd_solver.cpp:105] Iteration 42800, lr = 0.001
I0708 18:59:59.289831 99468 solver.cpp:218] Iteration 42840 (0.522376 iter/s, 76.5732s/40 iters), loss = 3.66804
I0708 18:59:59.290057 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44249 (* 0.3 = 0.732746 loss)
I0708 18:59:59.290081 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45638 (* 0.3 = 0.736914 loss)
I0708 18:59:59.290093 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4447 (* 1 = 2.4447 loss)
I0708 18:59:59.290109 99468 sgd_solver.cpp:105] Iteration 42840, lr = 0.001
I0708 19:01:15.649549 99468 solver.cpp:218] Iteration 42880 (0.523855 iter/s, 76.357s/40 iters), loss = 3.67642
I0708 19:01:15.649778 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32567 (* 0.3 = 0.6977 loss)
I0708 19:01:15.649801 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33741 (* 0.3 = 0.701224 loss)
I0708 19:01:15.649816 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32846 (* 1 = 2.32846 loss)
I0708 19:01:15.649832 99468 sgd_solver.cpp:105] Iteration 42880, lr = 0.001
I0708 19:02:32.213632 99468 solver.cpp:218] Iteration 42920 (0.522457 iter/s, 76.5613s/40 iters), loss = 3.68016
I0708 19:02:32.213861 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.91237 (* 0.3 = 0.57371 loss)
I0708 19:02:32.213888 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.92138 (* 0.3 = 0.576413 loss)
I0708 19:02:32.213933 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.92892 (* 1 = 1.92892 loss)
I0708 19:02:32.213950 99468 sgd_solver.cpp:105] Iteration 42920, lr = 0.001
I0708 19:03:48.680944 99468 solver.cpp:218] Iteration 42960 (0.523118 iter/s, 76.4646s/40 iters), loss = 3.68048
I0708 19:03:48.681181 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.46468 (* 0.3 = 0.739403 loss)
I0708 19:03:48.681203 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.4659 (* 0.3 = 0.739769 loss)
I0708 19:03:48.681216 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.46835 (* 1 = 2.46835 loss)
I0708 19:03:48.681231 99468 sgd_solver.cpp:105] Iteration 42960, lr = 0.001
I0708 19:05:05.323701 99468 solver.cpp:218] Iteration 43000 (0.521921 iter/s, 76.64s/40 iters), loss = 3.66017
I0708 19:05:05.323932 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38963 (* 0.3 = 0.716889 loss)
I0708 19:05:05.323985 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40645 (* 0.3 = 0.721935 loss)
I0708 19:05:05.324000 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38834 (* 1 = 2.38834 loss)
I0708 19:05:05.324021 99468 sgd_solver.cpp:105] Iteration 43000, lr = 0.001
I0708 19:06:21.642560 99468 solver.cpp:218] Iteration 43040 (0.524136 iter/s, 76.3161s/40 iters), loss = 3.69459
I0708 19:06:21.642832 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02258 (* 0.3 = 0.606775 loss)
I0708 19:06:21.642885 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00331 (* 0.3 = 0.600992 loss)
I0708 19:06:21.642897 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.00917 (* 1 = 2.00917 loss)
I0708 19:06:21.642917 99468 sgd_solver.cpp:105] Iteration 43040, lr = 0.001
I0708 19:07:38.030095 99468 solver.cpp:218] Iteration 43080 (0.523665 iter/s, 76.3848s/40 iters), loss = 3.65201
I0708 19:07:38.030325 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22689 (* 0.3 = 0.668067 loss)
I0708 19:07:38.030350 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23599 (* 0.3 = 0.670796 loss)
I0708 19:07:38.030397 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23034 (* 1 = 2.23034 loss)
I0708 19:07:38.030416 99468 sgd_solver.cpp:105] Iteration 43080, lr = 0.001
I0708 19:08:54.679754 99468 solver.cpp:218] Iteration 43120 (0.521874 iter/s, 76.6469s/40 iters), loss = 3.67236
I0708 19:08:54.679971 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31151 (* 0.3 = 0.693452 loss)
I0708 19:08:54.679992 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3142 (* 0.3 = 0.69426 loss)
I0708 19:08:54.680006 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30912 (* 1 = 2.30912 loss)
I0708 19:08:54.680027 99468 sgd_solver.cpp:105] Iteration 43120, lr = 0.001
I0708 19:10:11.295634 99468 solver.cpp:218] Iteration 43160 (0.522104 iter/s, 76.6131s/40 iters), loss = 3.68542
I0708 19:10:11.295871 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17659 (* 0.3 = 0.652978 loss)
I0708 19:10:11.295927 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18046 (* 0.3 = 0.654137 loss)
I0708 19:10:11.295940 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16989 (* 1 = 2.16989 loss)
I0708 19:10:11.295971 99468 sgd_solver.cpp:105] Iteration 43160, lr = 0.001
I0708 19:11:27.924787 99468 solver.cpp:218] Iteration 43200 (0.52202 iter/s, 76.6254s/40 iters), loss = 3.70423
I0708 19:11:27.925025 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10238 (* 0.3 = 0.630714 loss)
I0708 19:11:27.925077 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11697 (* 0.3 = 0.63509 loss)
I0708 19:11:27.925089 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10001 (* 1 = 2.10001 loss)
I0708 19:11:27.925125 99468 sgd_solver.cpp:105] Iteration 43200, lr = 0.001
I0708 19:12:44.511157 99468 solver.cpp:218] Iteration 43240 (0.522305 iter/s, 76.5836s/40 iters), loss = 3.68332
I0708 19:12:44.511392 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.16958 (* 0.3 = 0.650874 loss)
I0708 19:12:44.511417 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.15511 (* 0.3 = 0.646533 loss)
I0708 19:12:44.511466 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16074 (* 1 = 2.16074 loss)
I0708 19:12:44.511487 99468 sgd_solver.cpp:105] Iteration 43240, lr = 0.001
I0708 19:14:00.887183 99468 solver.cpp:218] Iteration 43280 (0.523743 iter/s, 76.3733s/40 iters), loss = 3.67823
I0708 19:14:00.887408 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1145 (* 0.3 = 0.634351 loss)
I0708 19:14:00.887465 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11443 (* 0.3 = 0.634329 loss)
I0708 19:14:00.887480 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10703 (* 1 = 2.10703 loss)
I0708 19:14:00.887495 99468 sgd_solver.cpp:105] Iteration 43280, lr = 0.001
I0708 19:15:17.269835 99468 solver.cpp:218] Iteration 43320 (0.523698 iter/s, 76.3799s/40 iters), loss = 3.66929
I0708 19:15:17.270058 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17795 (* 0.3 = 0.653384 loss)
I0708 19:15:17.270083 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1683 (* 0.3 = 0.650489 loss)
I0708 19:15:17.270097 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17025 (* 1 = 2.17025 loss)
I0708 19:15:17.270112 99468 sgd_solver.cpp:105] Iteration 43320, lr = 0.001
I0708 19:16:33.578470 99468 solver.cpp:218] Iteration 43360 (0.524206 iter/s, 76.3059s/40 iters), loss = 3.68234
I0708 19:16:33.578743 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51501 (* 0.3 = 0.754503 loss)
I0708 19:16:33.578802 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49826 (* 0.3 = 0.749479 loss)
I0708 19:16:33.578835 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50271 (* 1 = 2.50271 loss)
I0708 19:16:33.578852 99468 sgd_solver.cpp:105] Iteration 43360, lr = 0.001
I0708 19:17:49.952505 99468 solver.cpp:218] Iteration 43400 (0.523757 iter/s, 76.3712s/40 iters), loss = 3.64021
I0708 19:17:49.952754 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36712 (* 0.3 = 0.710135 loss)
I0708 19:17:49.952811 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37181 (* 0.3 = 0.711542 loss)
I0708 19:17:49.952826 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36947 (* 1 = 2.36947 loss)
I0708 19:17:49.952844 99468 sgd_solver.cpp:105] Iteration 43400, lr = 0.001
I0708 19:19:06.248632 99468 solver.cpp:218] Iteration 43440 (0.524292 iter/s, 76.2934s/40 iters), loss = 3.73037
I0708 19:19:06.248857 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37272 (* 0.3 = 0.711815 loss)
I0708 19:19:06.248915 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37789 (* 0.3 = 0.713366 loss)
I0708 19:19:06.248945 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3794 (* 1 = 2.3794 loss)
I0708 19:19:06.248965 99468 sgd_solver.cpp:105] Iteration 43440, lr = 0.001
I0708 19:20:22.564530 99468 solver.cpp:218] Iteration 43480 (0.524193 iter/s, 76.3078s/40 iters), loss = 3.73563
I0708 19:20:22.564761 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24184 (* 0.3 = 0.672553 loss)
I0708 19:20:22.564786 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2443 (* 0.3 = 0.673289 loss)
I0708 19:20:22.564833 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23992 (* 1 = 2.23992 loss)
I0708 19:20:22.564854 99468 sgd_solver.cpp:105] Iteration 43480, lr = 0.001
I0708 19:21:38.879276 99468 solver.cpp:218] Iteration 43520 (0.524164 iter/s, 76.312s/40 iters), loss = 3.71393
I0708 19:21:38.879508 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38068 (* 0.3 = 0.714203 loss)
I0708 19:21:38.879528 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37819 (* 0.3 = 0.713457 loss)
I0708 19:21:38.879545 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38466 (* 1 = 2.38466 loss)
I0708 19:21:38.879567 99468 sgd_solver.cpp:105] Iteration 43520, lr = 0.001
I0708 19:22:55.172018 99468 solver.cpp:218] Iteration 43560 (0.524315 iter/s, 76.29s/40 iters), loss = 3.71179
I0708 19:22:55.172237 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33033 (* 0.3 = 0.6991 loss)
I0708 19:22:55.172294 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32418 (* 0.3 = 0.697255 loss)
I0708 19:22:55.172307 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31884 (* 1 = 2.31884 loss)
I0708 19:22:55.172323 99468 sgd_solver.cpp:105] Iteration 43560, lr = 0.001
I0708 19:24:11.600646 99468 solver.cpp:218] Iteration 43600 (0.523383 iter/s, 76.4259s/40 iters), loss = 3.72166
I0708 19:24:11.600869 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34398 (* 0.3 = 0.703194 loss)
I0708 19:24:11.600891 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34632 (* 0.3 = 0.703896 loss)
I0708 19:24:11.600904 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34619 (* 1 = 2.34619 loss)
I0708 19:24:11.600960 99468 sgd_solver.cpp:105] Iteration 43600, lr = 0.001
I0708 19:25:28.140655 99468 solver.cpp:218] Iteration 43640 (0.522621 iter/s, 76.5373s/40 iters), loss = 3.67391
I0708 19:25:28.140873 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42385 (* 0.3 = 0.727155 loss)
I0708 19:25:28.140934 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41798 (* 0.3 = 0.725393 loss)
I0708 19:25:28.140950 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41613 (* 1 = 2.41613 loss)
I0708 19:25:28.140967 99468 sgd_solver.cpp:105] Iteration 43640, lr = 0.001
I0708 19:26:44.683969 99468 solver.cpp:218] Iteration 43680 (0.522599 iter/s, 76.5406s/40 iters), loss = 3.70416
I0708 19:26:44.684253 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26462 (* 0.3 = 0.679387 loss)
I0708 19:26:44.684307 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24988 (* 0.3 = 0.674964 loss)
I0708 19:26:44.684325 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25966 (* 1 = 2.25966 loss)
I0708 19:26:44.684341 99468 sgd_solver.cpp:105] Iteration 43680, lr = 0.001
I0708 19:28:01.239619 99468 solver.cpp:218] Iteration 43720 (0.522515 iter/s, 76.5528s/40 iters), loss = 3.72556
I0708 19:28:01.239856 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13334 (* 0.3 = 0.640001 loss)
I0708 19:28:01.239883 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13726 (* 0.3 = 0.641178 loss)
I0708 19:28:01.239933 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12948 (* 1 = 2.12948 loss)
I0708 19:28:01.239949 99468 sgd_solver.cpp:105] Iteration 43720, lr = 0.001
I0708 19:29:17.863384 99468 solver.cpp:218] Iteration 43760 (0.52205 iter/s, 76.621s/40 iters), loss = 3.69391
I0708 19:29:17.863637 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.13584 (* 0.3 = 0.640752 loss)
I0708 19:29:17.863693 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13891 (* 0.3 = 0.641674 loss)
I0708 19:29:17.863723 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13791 (* 1 = 2.13791 loss)
I0708 19:29:17.863739 99468 sgd_solver.cpp:105] Iteration 43760, lr = 0.001
I0708 19:30:34.395473 99468 solver.cpp:218] Iteration 43800 (0.522676 iter/s, 76.5293s/40 iters), loss = 3.67238
I0708 19:30:34.395714 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19712 (* 0.3 = 0.659137 loss)
I0708 19:30:34.395740 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19909 (* 0.3 = 0.659727 loss)
I0708 19:30:34.395756 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20153 (* 1 = 2.20153 loss)
I0708 19:30:34.395772 99468 sgd_solver.cpp:105] Iteration 43800, lr = 0.001
I0708 19:31:50.713577 99468 solver.cpp:218] Iteration 43840 (0.524141 iter/s, 76.3153s/40 iters), loss = 3.74038
I0708 19:31:50.713809 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02022 (* 0.3 = 0.606067 loss)
I0708 19:31:50.713830 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.02188 (* 0.3 = 0.606565 loss)
I0708 19:31:50.713845 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.00869 (* 1 = 2.00869 loss)
I0708 19:31:50.713863 99468 sgd_solver.cpp:105] Iteration 43840, lr = 0.001
I0708 19:33:07.072536 99468 solver.cpp:218] Iteration 43880 (0.52386 iter/s, 76.3562s/40 iters), loss = 3.69388
I0708 19:33:07.072755 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.9839 (* 0.3 = 0.59517 loss)
I0708 19:33:07.072813 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.99026 (* 0.3 = 0.597077 loss)
I0708 19:33:07.072831 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.98583 (* 1 = 1.98583 loss)
I0708 19:33:07.072863 99468 sgd_solver.cpp:105] Iteration 43880, lr = 0.001
I0708 19:34:23.739460 99468 solver.cpp:218] Iteration 43920 (0.521756 iter/s, 76.6642s/40 iters), loss = 3.75642
I0708 19:34:23.739689 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26434 (* 0.3 = 0.679303 loss)
I0708 19:34:23.739709 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26152 (* 0.3 = 0.678456 loss)
I0708 19:34:23.739723 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27314 (* 1 = 2.27314 loss)
I0708 19:34:23.739740 99468 sgd_solver.cpp:105] Iteration 43920, lr = 0.001
I0708 19:35:40.200630 99468 solver.cpp:218] Iteration 43960 (0.52316 iter/s, 76.4584s/40 iters), loss = 3.74145
I0708 19:35:40.200897 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3933 (* 0.3 = 0.717991 loss)
I0708 19:35:40.200918 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40394 (* 0.3 = 0.721183 loss)
I0708 19:35:40.200933 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39308 (* 1 = 2.39308 loss)
I0708 19:35:40.200949 99468 sgd_solver.cpp:105] Iteration 43960, lr = 0.001
I0708 19:36:54.346815 99468 solver.cpp:330] Iteration 44000, Testing net (#0)
I0708 19:47:22.695025 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07445 (* 0.3 = 0.622336 loss)
I0708 19:47:22.695276 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.366674
I0708 19:47:22.695299 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794315
I0708 19:47:22.695322 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07416 (* 0.3 = 0.622249 loss)
I0708 19:47:22.695336 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.366674
I0708 19:47:22.695346 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794315
I0708 19:47:22.695360 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07437 (* 1 = 2.07437 loss)
I0708 19:47:22.695374 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.366674
I0708 19:47:22.695382 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794315
I0708 19:47:24.591076 99468 solver.cpp:218] Iteration 44000 (0.0567886 iter/s, 704.367s/40 iters), loss = 3.63946
I0708 19:47:24.591178 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60038 (* 0.3 = 0.780113 loss)
I0708 19:47:24.591195 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61267 (* 0.3 = 0.783801 loss)
I0708 19:47:24.591209 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.60713 (* 1 = 2.60713 loss)
I0708 19:47:24.591267 99468 sgd_solver.cpp:105] Iteration 44000, lr = 0.001
I0708 19:48:40.954627 99468 solver.cpp:218] Iteration 44040 (0.523828 iter/s, 76.3609s/40 iters), loss = 3.68909
I0708 19:48:40.954872 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25262 (* 0.3 = 0.675787 loss)
I0708 19:48:40.954895 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.25634 (* 0.3 = 0.676901 loss)
I0708 19:48:40.954908 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26597 (* 1 = 2.26597 loss)
I0708 19:48:40.954959 99468 sgd_solver.cpp:105] Iteration 44040, lr = 0.001
I0708 19:49:57.584240 99468 solver.cpp:218] Iteration 44080 (0.52201 iter/s, 76.6268s/40 iters), loss = 3.68546
I0708 19:49:57.584465 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33911 (* 0.3 = 0.701732 loss)
I0708 19:49:57.584487 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.35507 (* 0.3 = 0.70652 loss)
I0708 19:49:57.584502 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3384 (* 1 = 2.3384 loss)
I0708 19:49:57.584522 99468 sgd_solver.cpp:105] Iteration 44080, lr = 0.001
I0708 19:51:14.057214 99468 solver.cpp:218] Iteration 44120 (0.52308 iter/s, 76.4702s/40 iters), loss = 3.70575
I0708 19:51:14.057451 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11099 (* 0.3 = 0.633298 loss)
I0708 19:51:14.057476 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08552 (* 0.3 = 0.625655 loss)
I0708 19:51:14.057492 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08739 (* 1 = 2.08739 loss)
I0708 19:51:14.057509 99468 sgd_solver.cpp:105] Iteration 44120, lr = 0.001
I0708 19:52:30.376386 99468 solver.cpp:218] Iteration 44160 (0.524134 iter/s, 76.3164s/40 iters), loss = 3.72229
I0708 19:52:30.377146 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4559 (* 0.3 = 0.736771 loss)
I0708 19:52:30.377171 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44911 (* 0.3 = 0.734732 loss)
I0708 19:52:30.377234 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45885 (* 1 = 2.45885 loss)
I0708 19:52:30.377251 99468 sgd_solver.cpp:105] Iteration 44160, lr = 0.001
I0708 19:53:47.034843 99468 solver.cpp:218] Iteration 44200 (0.52185 iter/s, 76.6503s/40 iters), loss = 3.74362
I0708 19:53:47.035156 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43787 (* 0.3 = 0.731362 loss)
I0708 19:53:47.035177 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42902 (* 0.3 = 0.728705 loss)
I0708 19:53:47.035192 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42507 (* 1 = 2.42507 loss)
I0708 19:53:47.035207 99468 sgd_solver.cpp:105] Iteration 44200, lr = 0.001
I0708 19:55:03.653044 99468 solver.cpp:218] Iteration 44240 (0.522089 iter/s, 76.6154s/40 iters), loss = 3.73565
I0708 19:55:03.653291 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40801 (* 0.3 = 0.722404 loss)
I0708 19:55:03.653312 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39727 (* 0.3 = 0.719181 loss)
I0708 19:55:03.653326 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40591 (* 1 = 2.40591 loss)
I0708 19:55:03.653342 99468 sgd_solver.cpp:105] Iteration 44240, lr = 0.001
I0708 19:56:20.268180 99468 solver.cpp:218] Iteration 44280 (0.522109 iter/s, 76.6124s/40 iters), loss = 3.67437
I0708 19:56:20.268399 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.58128 (* 0.3 = 0.774383 loss)
I0708 19:56:20.268422 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59084 (* 0.3 = 0.777251 loss)
I0708 19:56:20.268436 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59133 (* 1 = 2.59133 loss)
I0708 19:56:20.268491 99468 sgd_solver.cpp:105] Iteration 44280, lr = 0.001
I0708 19:57:36.906877 99468 solver.cpp:218] Iteration 44320 (0.521948 iter/s, 76.6359s/40 iters), loss = 3.72076
I0708 19:57:36.907133 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30722 (* 0.3 = 0.692165 loss)
I0708 19:57:36.907160 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29809 (* 0.3 = 0.689428 loss)
I0708 19:57:36.907207 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30251 (* 1 = 2.30251 loss)
I0708 19:57:36.907224 99468 sgd_solver.cpp:105] Iteration 44320, lr = 0.001
I0708 19:58:53.387255 99468 solver.cpp:218] Iteration 44360 (0.523029 iter/s, 76.4776s/40 iters), loss = 3.68787
I0708 19:58:53.388218 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08792 (* 0.3 = 0.626375 loss)
I0708 19:58:53.388245 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08166 (* 0.3 = 0.624499 loss)
I0708 19:58:53.388259 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07815 (* 1 = 2.07815 loss)
I0708 19:58:53.388275 99468 sgd_solver.cpp:105] Iteration 44360, lr = 0.001
I0708 20:00:09.979667 99468 solver.cpp:218] Iteration 44400 (0.522264 iter/s, 76.5896s/40 iters), loss = 3.76309
I0708 20:00:09.979898 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02715 (* 0.3 = 0.608145 loss)
I0708 20:00:09.979956 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.02826 (* 0.3 = 0.608477 loss)
I0708 20:00:09.979974 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02336 (* 1 = 2.02336 loss)
I0708 20:00:09.979990 99468 sgd_solver.cpp:105] Iteration 44400, lr = 0.001
I0708 20:01:26.565541 99468 solver.cpp:218] Iteration 44440 (0.522308 iter/s, 76.5831s/40 iters), loss = 3.71256
I0708 20:01:26.565793 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22584 (* 0.3 = 0.667753 loss)
I0708 20:01:26.565819 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24008 (* 0.3 = 0.672025 loss)
I0708 20:01:26.565836 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23422 (* 1 = 2.23422 loss)
I0708 20:01:26.565850 99468 sgd_solver.cpp:105] Iteration 44440, lr = 0.001
I0708 20:02:43.181051 99468 solver.cpp:218] Iteration 44480 (0.522106 iter/s, 76.6127s/40 iters), loss = 3.71387
I0708 20:02:43.181282 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40701 (* 0.3 = 0.722102 loss)
I0708 20:02:43.181303 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40773 (* 0.3 = 0.72232 loss)
I0708 20:02:43.181316 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40711 (* 1 = 2.40711 loss)
I0708 20:02:43.181331 99468 sgd_solver.cpp:105] Iteration 44480, lr = 0.001
I0708 20:03:59.769572 99468 solver.cpp:218] Iteration 44520 (0.52229 iter/s, 76.5858s/40 iters), loss = 3.74668
I0708 20:03:59.769865 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3706 (* 0.3 = 0.71118 loss)
I0708 20:03:59.769888 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36291 (* 0.3 = 0.708873 loss)
I0708 20:03:59.769901 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35545 (* 1 = 2.35545 loss)
I0708 20:03:59.769918 99468 sgd_solver.cpp:105] Iteration 44520, lr = 0.001
I0708 20:05:16.374963 99468 solver.cpp:218] Iteration 44560 (0.522176 iter/s, 76.6026s/40 iters), loss = 3.6775
I0708 20:05:16.375210 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36358 (* 0.3 = 0.709074 loss)
I0708 20:05:16.375232 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37045 (* 0.3 = 0.711135 loss)
I0708 20:05:16.375247 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35977 (* 1 = 2.35977 loss)
I0708 20:05:16.375263 99468 sgd_solver.cpp:105] Iteration 44560, lr = 0.001
I0708 20:06:33.003435 99468 solver.cpp:218] Iteration 44600 (0.522018 iter/s, 76.6257s/40 iters), loss = 3.71131
I0708 20:06:33.003655 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17296 (* 0.3 = 0.651888 loss)
I0708 20:06:33.003715 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.177 (* 0.3 = 0.653099 loss)
I0708 20:06:33.003731 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.16488 (* 1 = 2.16488 loss)
I0708 20:06:33.003746 99468 sgd_solver.cpp:105] Iteration 44600, lr = 0.001
I0708 20:07:49.610368 99468 solver.cpp:218] Iteration 44640 (0.522165 iter/s, 76.6042s/40 iters), loss = 3.70656
I0708 20:07:49.610599 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17453 (* 0.3 = 0.652358 loss)
I0708 20:07:49.610625 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1665 (* 0.3 = 0.649951 loss)
I0708 20:07:49.610638 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.15944 (* 1 = 2.15944 loss)
I0708 20:07:49.610654 99468 sgd_solver.cpp:105] Iteration 44640, lr = 0.001
I0708 20:09:06.245883 99468 solver.cpp:218] Iteration 44680 (0.52197 iter/s, 76.6328s/40 iters), loss = 3.67538
I0708 20:09:06.246098 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44518 (* 0.3 = 0.733553 loss)
I0708 20:09:06.246124 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44061 (* 0.3 = 0.732183 loss)
I0708 20:09:06.246136 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43994 (* 1 = 2.43994 loss)
I0708 20:09:06.246151 99468 sgd_solver.cpp:105] Iteration 44680, lr = 0.001
I0708 20:10:22.887979 99468 solver.cpp:218] Iteration 44720 (0.521925 iter/s, 76.6394s/40 iters), loss = 3.73
I0708 20:10:22.888208 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27406 (* 0.3 = 0.682219 loss)
I0708 20:10:22.888267 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28668 (* 0.3 = 0.686004 loss)
I0708 20:10:22.888283 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27346 (* 1 = 2.27346 loss)
I0708 20:10:22.888298 99468 sgd_solver.cpp:105] Iteration 44720, lr = 0.001
I0708 20:11:39.459341 99468 solver.cpp:218] Iteration 44760 (0.522407 iter/s, 76.5686s/40 iters), loss = 3.66026
I0708 20:11:39.459579 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1248 (* 0.3 = 0.637439 loss)
I0708 20:11:39.459604 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12298 (* 0.3 = 0.636895 loss)
I0708 20:11:39.459655 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11703 (* 1 = 2.11703 loss)
I0708 20:11:39.459669 99468 sgd_solver.cpp:105] Iteration 44760, lr = 0.001
I0708 20:12:56.026270 99468 solver.cpp:218] Iteration 44800 (0.522437 iter/s, 76.5642s/40 iters), loss = 3.69605
I0708 20:12:56.026491 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29554 (* 0.3 = 0.688661 loss)
I0708 20:12:56.026515 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30778 (* 0.3 = 0.692335 loss)
I0708 20:12:56.026530 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30803 (* 1 = 2.30803 loss)
I0708 20:12:56.026549 99468 sgd_solver.cpp:105] Iteration 44800, lr = 0.001
I0708 20:14:12.606945 99468 solver.cpp:218] Iteration 44840 (0.522344 iter/s, 76.5779s/40 iters), loss = 3.7487
I0708 20:14:12.607241 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41892 (* 0.3 = 0.725676 loss)
I0708 20:14:12.607297 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42469 (* 0.3 = 0.727407 loss)
I0708 20:14:12.607312 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42827 (* 1 = 2.42827 loss)
I0708 20:14:12.607327 99468 sgd_solver.cpp:105] Iteration 44840, lr = 0.001
I0708 20:15:29.216279 99468 solver.cpp:218] Iteration 44880 (0.522149 iter/s, 76.6065s/40 iters), loss = 3.6934
I0708 20:15:29.216511 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.58716 (* 0.3 = 0.776148 loss)
I0708 20:15:29.216534 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59205 (* 0.3 = 0.777616 loss)
I0708 20:15:29.216547 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59245 (* 1 = 2.59245 loss)
I0708 20:15:29.216575 99468 sgd_solver.cpp:105] Iteration 44880, lr = 0.001
I0708 20:16:45.854041 99468 solver.cpp:218] Iteration 44920 (0.521955 iter/s, 76.635s/40 iters), loss = 3.6743
I0708 20:16:45.854271 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26804 (* 0.3 = 0.680412 loss)
I0708 20:16:45.854298 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27111 (* 0.3 = 0.681334 loss)
I0708 20:16:45.854317 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26114 (* 1 = 2.26114 loss)
I0708 20:16:45.854331 99468 sgd_solver.cpp:105] Iteration 44920, lr = 0.001
I0708 20:18:02.437165 99468 solver.cpp:218] Iteration 44960 (0.522327 iter/s, 76.5804s/40 iters), loss = 3.73258
I0708 20:18:02.437408 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04542 (* 0.3 = 0.613627 loss)
I0708 20:18:02.437433 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0503 (* 0.3 = 0.61509 loss)
I0708 20:18:02.437450 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.05521 (* 1 = 2.05521 loss)
I0708 20:18:02.437465 99468 sgd_solver.cpp:105] Iteration 44960, lr = 0.001
I0708 20:19:19.025804 99468 solver.cpp:218] Iteration 45000 (0.52229 iter/s, 76.5859s/40 iters), loss = 3.67131
I0708 20:19:19.026034 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.35918 (* 0.3 = 0.707754 loss)
I0708 20:19:19.026060 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36143 (* 0.3 = 0.70843 loss)
I0708 20:19:19.026109 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36245 (* 1 = 2.36245 loss)
I0708 20:19:19.026125 99468 sgd_solver.cpp:105] Iteration 45000, lr = 0.001
I0708 20:20:35.644238 99468 solver.cpp:218] Iteration 45040 (0.522087 iter/s, 76.6157s/40 iters), loss = 3.71073
I0708 20:20:35.644493 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32394 (* 0.3 = 0.697182 loss)
I0708 20:20:35.644515 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32244 (* 0.3 = 0.696733 loss)
I0708 20:20:35.644568 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32342 (* 1 = 2.32342 loss)
I0708 20:20:35.644587 99468 sgd_solver.cpp:105] Iteration 45040, lr = 0.001
I0708 20:21:52.268198 99468 solver.cpp:218] Iteration 45080 (0.522049 iter/s, 76.6212s/40 iters), loss = 3.69143
I0708 20:21:52.268422 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.72611 (* 0.3 = 0.817832 loss)
I0708 20:21:52.268445 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.72599 (* 0.3 = 0.817796 loss)
I0708 20:21:52.268460 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.72107 (* 1 = 2.72107 loss)
I0708 20:21:52.268476 99468 sgd_solver.cpp:105] Iteration 45080, lr = 0.001
I0708 20:23:08.831759 99468 solver.cpp:218] Iteration 45120 (0.52246 iter/s, 76.5608s/40 iters), loss = 3.72304
I0708 20:23:08.832041 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34746 (* 0.3 = 0.704239 loss)
I0708 20:23:08.832098 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3374 (* 0.3 = 0.701221 loss)
I0708 20:23:08.832113 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34375 (* 1 = 2.34375 loss)
I0708 20:23:08.832129 99468 sgd_solver.cpp:105] Iteration 45120, lr = 0.001
I0708 20:24:25.516744 99468 solver.cpp:218] Iteration 45160 (0.521634 iter/s, 76.6822s/40 iters), loss = 3.67227
I0708 20:24:25.517004 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15565 (* 0.3 = 0.646696 loss)
I0708 20:24:25.517026 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14857 (* 0.3 = 0.644571 loss)
I0708 20:24:25.517072 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.13973 (* 1 = 2.13973 loss)
I0708 20:24:25.517088 99468 sgd_solver.cpp:105] Iteration 45160, lr = 0.001
I0708 20:25:42.105388 99468 solver.cpp:218] Iteration 45200 (0.52229 iter/s, 76.5858s/40 iters), loss = 3.70262
I0708 20:25:42.105657 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23939 (* 0.3 = 0.671816 loss)
I0708 20:25:42.105679 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24611 (* 0.3 = 0.673834 loss)
I0708 20:25:42.105695 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23841 (* 1 = 2.23841 loss)
I0708 20:25:42.105711 99468 sgd_solver.cpp:105] Iteration 45200, lr = 0.001
I0708 20:26:58.457309 99468 solver.cpp:218] Iteration 45240 (0.523909 iter/s, 76.3491s/40 iters), loss = 3.67861
I0708 20:26:58.457547 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10968 (* 0.3 = 0.632904 loss)
I0708 20:26:58.457577 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.11346 (* 0.3 = 0.634039 loss)
I0708 20:26:58.457592 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.11082 (* 1 = 2.11082 loss)
I0708 20:26:58.457607 99468 sgd_solver.cpp:105] Iteration 45240, lr = 0.001
I0708 20:28:15.088326 99468 solver.cpp:218] Iteration 45280 (0.522001 iter/s, 76.6283s/40 iters), loss = 3.6337
I0708 20:28:15.088560 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3865 (* 0.3 = 0.71595 loss)
I0708 20:28:15.088620 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39674 (* 0.3 = 0.719021 loss)
I0708 20:28:15.088634 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38857 (* 1 = 2.38857 loss)
I0708 20:28:15.088654 99468 sgd_solver.cpp:105] Iteration 45280, lr = 0.001
I0708 20:29:31.648025 99468 solver.cpp:218] Iteration 45320 (0.522487 iter/s, 76.5569s/40 iters), loss = 3.71975
I0708 20:29:31.648255 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.69501 (* 0.3 = 0.808503 loss)
I0708 20:29:31.648313 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.70216 (* 0.3 = 0.810649 loss)
I0708 20:29:31.648326 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.70322 (* 1 = 2.70322 loss)
I0708 20:29:31.648344 99468 sgd_solver.cpp:105] Iteration 45320, lr = 0.001
I0708 20:30:48.211522 99468 solver.cpp:218] Iteration 45360 (0.522461 iter/s, 76.5607s/40 iters), loss = 3.6794
I0708 20:30:48.211768 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38918 (* 0.3 = 0.716753 loss)
I0708 20:30:48.211791 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38744 (* 0.3 = 0.716232 loss)
I0708 20:30:48.211807 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37947 (* 1 = 2.37947 loss)
I0708 20:30:48.211822 99468 sgd_solver.cpp:105] Iteration 45360, lr = 0.001
I0708 20:32:04.673774 99468 solver.cpp:218] Iteration 45400 (0.523153 iter/s, 76.4595s/40 iters), loss = 3.71021
I0708 20:32:04.673997 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.37099 (* 0.3 = 0.711297 loss)
I0708 20:32:04.674019 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38203 (* 0.3 = 0.714609 loss)
I0708 20:32:04.674033 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37441 (* 1 = 2.37441 loss)
I0708 20:32:04.674054 99468 sgd_solver.cpp:105] Iteration 45400, lr = 0.001
I0708 20:33:21.307752 99468 solver.cpp:218] Iteration 45440 (0.52198 iter/s, 76.6312s/40 iters), loss = 3.67322
I0708 20:33:21.308048 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01632 (* 0.3 = 0.604896 loss)
I0708 20:33:21.308075 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.00768 (* 0.3 = 0.602306 loss)
I0708 20:33:21.308121 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02185 (* 1 = 2.02185 loss)
I0708 20:33:21.308140 99468 sgd_solver.cpp:105] Iteration 45440, lr = 0.001
I0708 20:34:37.906858 99468 solver.cpp:218] Iteration 45480 (0.522219 iter/s, 76.5963s/40 iters), loss = 3.73292
I0708 20:34:37.907091 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.472 (* 0.3 = 0.7416 loss)
I0708 20:34:37.907116 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47576 (* 0.3 = 0.742727 loss)
I0708 20:34:37.907161 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.47147 (* 1 = 2.47147 loss)
I0708 20:34:37.907177 99468 sgd_solver.cpp:105] Iteration 45480, lr = 0.001
I0708 20:35:54.441305 99468 solver.cpp:218] Iteration 45520 (0.522659 iter/s, 76.5317s/40 iters), loss = 3.71717
I0708 20:35:54.441548 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.57373 (* 0.3 = 0.772119 loss)
I0708 20:35:54.441576 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.57399 (* 0.3 = 0.772196 loss)
I0708 20:35:54.441589 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.57642 (* 1 = 2.57642 loss)
I0708 20:35:54.441606 99468 sgd_solver.cpp:105] Iteration 45520, lr = 0.001
I0708 20:37:10.809288 99468 solver.cpp:218] Iteration 45560 (0.523799 iter/s, 76.3652s/40 iters), loss = 3.71175
I0708 20:37:10.809520 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.19521 (* 0.3 = 0.658564 loss)
I0708 20:37:10.809545 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20489 (* 0.3 = 0.661466 loss)
I0708 20:37:10.809567 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.19188 (* 1 = 2.19188 loss)
I0708 20:37:10.809582 99468 sgd_solver.cpp:105] Iteration 45560, lr = 0.001
I0708 20:38:27.274420 99468 solver.cpp:218] Iteration 45600 (0.523133 iter/s, 76.4624s/40 iters), loss = 3.70959
I0708 20:38:27.274673 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.25518 (* 0.3 = 0.676553 loss)
I0708 20:38:27.274725 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26025 (* 0.3 = 0.678074 loss)
I0708 20:38:27.274739 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.25406 (* 1 = 2.25406 loss)
I0708 20:38:27.274773 99468 sgd_solver.cpp:105] Iteration 45600, lr = 0.001
I0708 20:39:43.690079 99468 solver.cpp:218] Iteration 45640 (0.523479 iter/s, 76.4118s/40 iters), loss = 3.73004
I0708 20:39:43.690395 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.60809 (* 0.3 = 0.782426 loss)
I0708 20:39:43.690472 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.61157 (* 0.3 = 0.783472 loss)
I0708 20:39:43.690521 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.61277 (* 1 = 2.61277 loss)
I0708 20:39:43.690549 99468 sgd_solver.cpp:105] Iteration 45640, lr = 0.001
I0708 20:39:55.243199 99628 data_layer.cpp:73] Restarting data prefetching from start.
I0708 20:41:00.115828 99468 solver.cpp:218] Iteration 45680 (0.523403 iter/s, 76.4229s/40 iters), loss = 3.72401
I0708 20:41:00.116078 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39231 (* 0.3 = 0.717693 loss)
I0708 20:41:00.116104 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39634 (* 0.3 = 0.718901 loss)
I0708 20:41:00.116119 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38153 (* 1 = 2.38153 loss)
I0708 20:41:00.116134 99468 sgd_solver.cpp:105] Iteration 45680, lr = 0.001
I0708 20:42:16.613339 99468 solver.cpp:218] Iteration 45720 (0.522912 iter/s, 76.4947s/40 iters), loss = 3.68064
I0708 20:42:16.613586 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.32651 (* 0.3 = 0.697952 loss)
I0708 20:42:16.613646 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31868 (* 0.3 = 0.695603 loss)
I0708 20:42:16.613661 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31989 (* 1 = 2.31989 loss)
I0708 20:42:16.613677 99468 sgd_solver.cpp:105] Iteration 45720, lr = 0.001
I0708 20:43:33.125434 99468 solver.cpp:218] Iteration 45760 (0.522813 iter/s, 76.5092s/40 iters), loss = 3.70117
I0708 20:43:33.125792 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.71744 (* 0.3 = 0.815231 loss)
I0708 20:43:33.125816 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.71889 (* 0.3 = 0.815666 loss)
I0708 20:43:33.125834 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.70516 (* 1 = 2.70516 loss)
I0708 20:43:33.125851 99468 sgd_solver.cpp:105] Iteration 45760, lr = 0.001
I0708 20:44:49.711031 99468 solver.cpp:218] Iteration 45800 (0.522311 iter/s, 76.5827s/40 iters), loss = 3.70916
I0708 20:44:49.711263 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43529 (* 0.3 = 0.730588 loss)
I0708 20:44:49.711320 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43449 (* 0.3 = 0.730347 loss)
I0708 20:44:49.711336 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42887 (* 1 = 2.42887 loss)
I0708 20:44:49.711351 99468 sgd_solver.cpp:105] Iteration 45800, lr = 0.001
I0708 20:46:06.370865 99468 solver.cpp:218] Iteration 45840 (0.521804 iter/s, 76.6571s/40 iters), loss = 3.68998
I0708 20:46:06.371099 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14944 (* 0.3 = 0.644832 loss)
I0708 20:46:06.371155 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1347 (* 0.3 = 0.64041 loss)
I0708 20:46:06.371168 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1421 (* 1 = 2.1421 loss)
I0708 20:46:06.371188 99468 sgd_solver.cpp:105] Iteration 45840, lr = 0.001
I0708 20:47:22.994318 99468 solver.cpp:218] Iteration 45880 (0.522052 iter/s, 76.6207s/40 iters), loss = 3.72469
I0708 20:47:22.994544 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33195 (* 0.3 = 0.699587 loss)
I0708 20:47:22.994575 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.33606 (* 0.3 = 0.700819 loss)
I0708 20:47:22.994588 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33639 (* 1 = 2.33639 loss)
I0708 20:47:22.994602 99468 sgd_solver.cpp:105] Iteration 45880, lr = 0.001
I0708 20:48:39.555621 99468 solver.cpp:218] Iteration 45920 (0.522476 iter/s, 76.5585s/40 iters), loss = 3.72572
I0708 20:48:39.555860 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38332 (* 0.3 = 0.714995 loss)
I0708 20:48:39.555884 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3859 (* 0.3 = 0.715771 loss)
I0708 20:48:39.555898 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37699 (* 1 = 2.37699 loss)
I0708 20:48:39.555915 99468 sgd_solver.cpp:105] Iteration 45920, lr = 0.001
I0708 20:49:56.121179 99468 solver.cpp:218] Iteration 45960 (0.52245 iter/s, 76.5624s/40 iters), loss = 3.67733
I0708 20:49:56.121384 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.36458 (* 0.3 = 0.709375 loss)
I0708 20:49:56.121454 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.36162 (* 0.3 = 0.708485 loss)
I0708 20:49:56.121469 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.35911 (* 1 = 2.35911 loss)
I0708 20:49:56.121484 99468 sgd_solver.cpp:105] Iteration 45960, lr = 0.001
I0708 20:51:12.735673 99468 solver.cpp:218] Iteration 46000 (0.522113 iter/s, 76.6117s/40 iters), loss = 3.71182
I0708 20:51:12.735987 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.29796 (* 0.3 = 0.689388 loss)
I0708 20:51:12.736037 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29295 (* 0.3 = 0.687886 loss)
I0708 20:51:12.736099 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29904 (* 1 = 2.29904 loss)
I0708 20:51:12.736127 99468 sgd_solver.cpp:105] Iteration 46000, lr = 0.001
I0708 20:52:29.256187 99468 solver.cpp:218] Iteration 46040 (0.522755 iter/s, 76.5177s/40 iters), loss = 3.68719
I0708 20:52:29.256489 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41455 (* 0.3 = 0.724366 loss)
I0708 20:52:29.256512 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40196 (* 0.3 = 0.720588 loss)
I0708 20:52:29.256526 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4035 (* 1 = 2.4035 loss)
I0708 20:52:29.256541 99468 sgd_solver.cpp:105] Iteration 46040, lr = 0.001
I0708 20:53:45.806843 99468 solver.cpp:218] Iteration 46080 (0.522549 iter/s, 76.5478s/40 iters), loss = 3.70521
I0708 20:53:45.807132 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.06405 (* 0.3 = 0.619215 loss)
I0708 20:53:45.807159 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.0683 (* 0.3 = 0.620489 loss)
I0708 20:53:45.807176 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.06355 (* 1 = 2.06355 loss)
I0708 20:53:45.807194 99468 sgd_solver.cpp:105] Iteration 46080, lr = 0.001
I0708 20:55:02.368904 99468 solver.cpp:218] Iteration 46120 (0.522471 iter/s, 76.5592s/40 iters), loss = 3.72989
I0708 20:55:02.369138 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15375 (* 0.3 = 0.646124 loss)
I0708 20:55:02.369192 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.1516 (* 0.3 = 0.645479 loss)
I0708 20:55:02.369206 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14521 (* 1 = 2.14521 loss)
I0708 20:55:02.369222 99468 sgd_solver.cpp:105] Iteration 46120, lr = 0.001
I0708 20:56:18.934734 99468 solver.cpp:218] Iteration 46160 (0.522445 iter/s, 76.5631s/40 iters), loss = 3.70304
I0708 20:56:18.934996 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07067 (* 0.3 = 0.621202 loss)
I0708 20:56:18.935029 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.06059 (* 0.3 = 0.618176 loss)
I0708 20:56:18.935046 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07759 (* 1 = 2.07759 loss)
I0708 20:56:18.935065 99468 sgd_solver.cpp:105] Iteration 46160, lr = 0.001
I0708 20:57:35.455255 99468 solver.cpp:218] Iteration 46200 (0.522755 iter/s, 76.5177s/40 iters), loss = 3.71014
I0708 20:57:35.455512 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42292 (* 0.3 = 0.726875 loss)
I0708 20:57:35.455533 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43334 (* 0.3 = 0.730003 loss)
I0708 20:57:35.455548 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42907 (* 1 = 2.42907 loss)
I0708 20:57:35.455571 99468 sgd_solver.cpp:105] Iteration 46200, lr = 0.001
I0708 20:58:51.973299 99468 solver.cpp:218] Iteration 46240 (0.522772 iter/s, 76.5152s/40 iters), loss = 3.74469
I0708 20:58:51.973597 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.66284 (* 0.3 = 0.798851 loss)
I0708 20:58:51.973620 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.64967 (* 0.3 = 0.7949 loss)
I0708 20:58:51.973635 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.65396 (* 1 = 2.65396 loss)
I0708 20:58:51.973652 99468 sgd_solver.cpp:105] Iteration 46240, lr = 0.001
I0708 21:00:08.538108 99468 solver.cpp:218] Iteration 46280 (0.522453 iter/s, 76.562s/40 iters), loss = 3.68459
I0708 21:00:08.538347 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07615 (* 0.3 = 0.622844 loss)
I0708 21:00:08.538396 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07307 (* 0.3 = 0.621921 loss)
I0708 21:00:08.538411 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07152 (* 1 = 2.07152 loss)
I0708 21:00:08.538429 99468 sgd_solver.cpp:105] Iteration 46280, lr = 0.001
I0708 21:01:25.073509 99468 solver.cpp:218] Iteration 46320 (0.522683 iter/s, 76.5283s/40 iters), loss = 3.71427
I0708 21:01:25.073753 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.26926 (* 0.3 = 0.680777 loss)
I0708 21:01:25.073781 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26674 (* 0.3 = 0.680021 loss)
I0708 21:01:25.073794 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.26523 (* 1 = 2.26523 loss)
I0708 21:01:25.073810 99468 sgd_solver.cpp:105] Iteration 46320, lr = 0.001
I0708 21:02:41.604295 99468 solver.cpp:218] Iteration 46360 (0.522684 iter/s, 76.528s/40 iters), loss = 3.72849
I0708 21:02:41.604621 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28678 (* 0.3 = 0.686034 loss)
I0708 21:02:41.604655 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28261 (* 0.3 = 0.684782 loss)
I0708 21:02:41.604668 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27522 (* 1 = 2.27522 loss)
I0708 21:02:41.604686 99468 sgd_solver.cpp:105] Iteration 46360, lr = 0.001
I0708 21:03:58.018522 99468 solver.cpp:218] Iteration 46400 (0.523482 iter/s, 76.4114s/40 iters), loss = 3.72273
I0708 21:03:58.018769 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33345 (* 0.3 = 0.700036 loss)
I0708 21:03:58.018795 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32819 (* 0.3 = 0.698458 loss)
I0708 21:03:58.018810 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32615 (* 1 = 2.32615 loss)
I0708 21:03:58.018826 99468 sgd_solver.cpp:105] Iteration 46400, lr = 0.001
I0708 21:05:14.406534 99468 solver.cpp:218] Iteration 46440 (0.523661 iter/s, 76.3852s/40 iters), loss = 3.74173
I0708 21:05:14.406776 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3775 (* 0.3 = 0.713249 loss)
I0708 21:05:14.406801 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39046 (* 0.3 = 0.717137 loss)
I0708 21:05:14.406817 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38705 (* 1 = 2.38705 loss)
I0708 21:05:14.406831 99468 sgd_solver.cpp:105] Iteration 46440, lr = 0.001
I0708 21:06:30.958281 99468 solver.cpp:218] Iteration 46480 (0.522541 iter/s, 76.549s/40 iters), loss = 3.69663
I0708 21:06:30.958503 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20327 (* 0.3 = 0.660982 loss)
I0708 21:06:30.958566 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19912 (* 0.3 = 0.659737 loss)
I0708 21:06:30.958601 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20448 (* 1 = 2.20448 loss)
I0708 21:06:30.958618 99468 sgd_solver.cpp:105] Iteration 46480, lr = 0.001
I0708 21:07:47.398674 99468 solver.cpp:218] Iteration 46520 (0.523302 iter/s, 76.4376s/40 iters), loss = 3.73024
I0708 21:07:47.398916 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.97471 (* 0.3 = 0.592413 loss)
I0708 21:07:47.398972 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.98819 (* 0.3 = 0.596458 loss)
I0708 21:07:47.398985 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.98245 (* 1 = 1.98245 loss)
I0708 21:07:47.399003 99468 sgd_solver.cpp:105] Iteration 46520, lr = 0.001
I0708 21:09:03.892607 99468 solver.cpp:218] Iteration 46560 (0.522936 iter/s, 76.4912s/40 iters), loss = 3.73447
I0708 21:09:03.892838 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23622 (* 0.3 = 0.670867 loss)
I0708 21:09:03.892863 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2265 (* 0.3 = 0.66795 loss)
I0708 21:09:03.892876 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22305 (* 1 = 2.22305 loss)
I0708 21:09:03.892892 99468 sgd_solver.cpp:105] Iteration 46560, lr = 0.001
I0708 21:10:20.417737 99468 solver.cpp:218] Iteration 46600 (0.522723 iter/s, 76.5224s/40 iters), loss = 3.69449
I0708 21:10:20.418004 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.49571 (* 0.3 = 0.748713 loss)
I0708 21:10:20.418032 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49369 (* 0.3 = 0.748107 loss)
I0708 21:10:20.418051 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50078 (* 1 = 2.50078 loss)
I0708 21:10:20.418107 99468 sgd_solver.cpp:105] Iteration 46600, lr = 0.001
I0708 21:11:37.092224 99468 solver.cpp:218] Iteration 46640 (0.521705 iter/s, 76.6717s/40 iters), loss = 3.67484
I0708 21:11:37.092458 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.51715 (* 0.3 = 0.755145 loss)
I0708 21:11:37.092480 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50949 (* 0.3 = 0.752847 loss)
I0708 21:11:37.092494 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.51049 (* 1 = 2.51049 loss)
I0708 21:11:37.092511 99468 sgd_solver.cpp:105] Iteration 46640, lr = 0.001
I0708 21:12:53.444483 99468 solver.cpp:218] Iteration 46680 (0.523907 iter/s, 76.3495s/40 iters), loss = 3.67488
I0708 21:12:53.444782 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.56067 (* 0.3 = 0.768202 loss)
I0708 21:12:53.444838 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55677 (* 0.3 = 0.767031 loss)
I0708 21:12:53.444851 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.54809 (* 1 = 2.54809 loss)
I0708 21:12:53.444869 99468 sgd_solver.cpp:105] Iteration 46680, lr = 0.001
I0708 21:14:09.823148 99468 solver.cpp:218] Iteration 46720 (0.523726 iter/s, 76.3758s/40 iters), loss = 3.70327
I0708 21:14:09.823400 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02546 (* 0.3 = 0.607639 loss)
I0708 21:14:09.823459 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03901 (* 0.3 = 0.611702 loss)
I0708 21:14:09.823473 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03243 (* 1 = 2.03243 loss)
I0708 21:14:09.823493 99468 sgd_solver.cpp:105] Iteration 46720, lr = 0.001
I0708 21:15:26.134877 99468 solver.cpp:218] Iteration 46760 (0.524185 iter/s, 76.309s/40 iters), loss = 3.66592
I0708 21:15:26.135123 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.41926 (* 0.3 = 0.725778 loss)
I0708 21:15:26.135184 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.41683 (* 0.3 = 0.725048 loss)
I0708 21:15:26.135217 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41005 (* 1 = 2.41005 loss)
I0708 21:15:26.135236 99468 sgd_solver.cpp:105] Iteration 46760, lr = 0.001
I0708 21:16:42.490089 99468 solver.cpp:218] Iteration 46800 (0.523886 iter/s, 76.3524s/40 iters), loss = 3.63845
I0708 21:16:42.490329 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43438 (* 0.3 = 0.730314 loss)
I0708 21:16:42.490352 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.44038 (* 0.3 = 0.732114 loss)
I0708 21:16:42.490401 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43019 (* 1 = 2.43019 loss)
I0708 21:16:42.490420 99468 sgd_solver.cpp:105] Iteration 46800, lr = 0.001
I0708 21:17:59.014844 99468 solver.cpp:218] Iteration 46840 (0.522726 iter/s, 76.522s/40 iters), loss = 3.77648
I0708 21:17:59.015075 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.79451 (* 0.3 = 0.838354 loss)
I0708 21:17:59.015096 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.79037 (* 0.3 = 0.837112 loss)
I0708 21:17:59.015110 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.78279 (* 1 = 2.78279 loss)
I0708 21:17:59.015127 99468 sgd_solver.cpp:105] Iteration 46840, lr = 0.001
I0708 21:19:15.497143 99468 solver.cpp:218] Iteration 46880 (0.523031 iter/s, 76.4773s/40 iters), loss = 3.66463
I0708 21:19:15.497383 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.01236 (* 0.3 = 0.603708 loss)
I0708 21:19:15.497408 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.01031 (* 0.3 = 0.603093 loss)
I0708 21:19:15.497426 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0048 (* 1 = 2.0048 loss)
I0708 21:19:15.497443 99468 sgd_solver.cpp:105] Iteration 46880, lr = 0.001
I0708 21:20:32.085405 99468 solver.cpp:218] Iteration 46920 (0.522292 iter/s, 76.5855s/40 iters), loss = 3.62046
I0708 21:20:32.085656 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39267 (* 0.3 = 0.7178 loss)
I0708 21:20:32.085680 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39171 (* 0.3 = 0.717513 loss)
I0708 21:20:32.085695 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.3897 (* 1 = 2.3897 loss)
I0708 21:20:32.085712 99468 sgd_solver.cpp:105] Iteration 46920, lr = 0.001
I0708 21:21:48.681720 99468 solver.cpp:218] Iteration 46960 (0.522237 iter/s, 76.5935s/40 iters), loss = 3.68785
I0708 21:21:48.681941 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.24111 (* 0.3 = 0.672332 loss)
I0708 21:21:48.681965 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24503 (* 0.3 = 0.673509 loss)
I0708 21:21:48.681979 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24885 (* 1 = 2.24885 loss)
I0708 21:21:48.681998 99468 sgd_solver.cpp:105] Iteration 46960, lr = 0.001
I0708 21:23:05.264680 99468 solver.cpp:218] Iteration 47000 (0.522328 iter/s, 76.5802s/40 iters), loss = 3.73007
I0708 21:23:05.264989 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4309 (* 0.3 = 0.729269 loss)
I0708 21:23:05.265046 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43728 (* 0.3 = 0.731183 loss)
I0708 21:23:05.265060 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.44073 (* 1 = 2.44073 loss)
I0708 21:23:05.265080 99468 sgd_solver.cpp:105] Iteration 47000, lr = 0.001
I0708 21:24:21.589527 99468 solver.cpp:218] Iteration 47040 (0.524095 iter/s, 76.322s/40 iters), loss = 3.71162
I0708 21:24:21.589764 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2781 (* 0.3 = 0.683429 loss)
I0708 21:24:21.589790 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.29464 (* 0.3 = 0.688391 loss)
I0708 21:24:21.589805 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2981 (* 1 = 2.2981 loss)
I0708 21:24:21.589821 99468 sgd_solver.cpp:105] Iteration 47040, lr = 0.001
I0708 21:25:38.110110 99468 solver.cpp:218] Iteration 47080 (0.522754 iter/s, 76.5178s/40 iters), loss = 3.74286
I0708 21:25:38.110379 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3717 (* 0.3 = 0.71151 loss)
I0708 21:25:38.110399 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.38019 (* 0.3 = 0.714056 loss)
I0708 21:25:38.110411 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.36513 (* 1 = 2.36513 loss)
I0708 21:25:38.110430 99468 sgd_solver.cpp:105] Iteration 47080, lr = 0.001
I0708 21:26:54.730455 99468 solver.cpp:218] Iteration 47120 (0.522074 iter/s, 76.6175s/40 iters), loss = 3.69609
I0708 21:26:54.730741 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.15522 (* 0.3 = 0.646565 loss)
I0708 21:26:54.730767 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12974 (* 0.3 = 0.638923 loss)
I0708 21:26:54.730783 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14422 (* 1 = 2.14422 loss)
I0708 21:26:54.730798 99468 sgd_solver.cpp:105] Iteration 47120, lr = 0.001
I0708 21:28:11.303401 99468 solver.cpp:218] Iteration 47160 (0.522397 iter/s, 76.5701s/40 iters), loss = 3.75773
I0708 21:28:11.303668 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34595 (* 0.3 = 0.703786 loss)
I0708 21:28:11.303724 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34176 (* 0.3 = 0.702528 loss)
I0708 21:28:11.303737 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33808 (* 1 = 2.33808 loss)
I0708 21:28:11.303761 99468 sgd_solver.cpp:105] Iteration 47160, lr = 0.001
I0708 21:29:27.876065 99468 solver.cpp:218] Iteration 47200 (0.522399 iter/s, 76.5699s/40 iters), loss = 3.70303
I0708 21:29:27.876291 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11799 (* 0.3 = 0.635396 loss)
I0708 21:29:27.876353 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12124 (* 0.3 = 0.636373 loss)
I0708 21:29:27.876368 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12126 (* 1 = 2.12126 loss)
I0708 21:29:27.876385 99468 sgd_solver.cpp:105] Iteration 47200, lr = 0.001
I0708 21:30:44.529312 99468 solver.cpp:218] Iteration 47240 (0.521849 iter/s, 76.6505s/40 iters), loss = 3.74495
I0708 21:30:44.529548 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04571 (* 0.3 = 0.613713 loss)
I0708 21:30:44.529580 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04659 (* 0.3 = 0.613977 loss)
I0708 21:30:44.529595 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04212 (* 1 = 2.04212 loss)
I0708 21:30:44.529610 99468 sgd_solver.cpp:105] Iteration 47240, lr = 0.001
I0708 21:32:01.109299 99468 solver.cpp:218] Iteration 47280 (0.522349 iter/s, 76.5772s/40 iters), loss = 3.66659
I0708 21:32:01.109585 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.14537 (* 0.3 = 0.643611 loss)
I0708 21:32:01.109608 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.14493 (* 0.3 = 0.64348 loss)
I0708 21:32:01.109623 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14077 (* 1 = 2.14077 loss)
I0708 21:32:01.109639 99468 sgd_solver.cpp:105] Iteration 47280, lr = 0.001
I0708 21:33:17.689672 99468 solver.cpp:218] Iteration 47320 (0.522346 iter/s, 76.5776s/40 iters), loss = 3.709
I0708 21:33:17.689915 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08557 (* 0.3 = 0.625672 loss)
I0708 21:33:17.689935 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09752 (* 0.3 = 0.629256 loss)
I0708 21:33:17.689949 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.1038 (* 1 = 2.1038 loss)
I0708 21:33:17.689968 99468 sgd_solver.cpp:105] Iteration 47320, lr = 0.001
I0708 21:34:34.294384 99468 solver.cpp:218] Iteration 47360 (0.52218 iter/s, 76.602s/40 iters), loss = 3.71448
I0708 21:34:34.294642 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.38276 (* 0.3 = 0.714829 loss)
I0708 21:34:34.294669 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.37701 (* 0.3 = 0.713103 loss)
I0708 21:34:34.294718 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37265 (* 1 = 2.37265 loss)
I0708 21:34:34.294735 99468 sgd_solver.cpp:105] Iteration 47360, lr = 0.001
I0708 21:35:50.824215 99468 solver.cpp:218] Iteration 47400 (0.522691 iter/s, 76.527s/40 iters), loss = 3.7108
I0708 21:35:50.824471 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 3.69003 (* 0.3 = 1.10701 loss)
I0708 21:35:50.824494 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 3.68649 (* 0.3 = 1.10595 loss)
I0708 21:35:50.824540 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 3.68475 (* 1 = 3.68475 loss)
I0708 21:35:50.824563 99468 sgd_solver.cpp:105] Iteration 47400, lr = 0.001
I0708 21:37:07.282438 99468 solver.cpp:218] Iteration 47440 (0.523181 iter/s, 76.4554s/40 iters), loss = 3.68382
I0708 21:37:07.282683 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.04349 (* 0.3 = 0.613048 loss)
I0708 21:37:07.282742 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04541 (* 0.3 = 0.613622 loss)
I0708 21:37:07.282757 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.04228 (* 1 = 2.04228 loss)
I0708 21:37:07.282776 99468 sgd_solver.cpp:105] Iteration 47440, lr = 0.001
I0708 21:38:23.654587 99468 solver.cpp:218] Iteration 47480 (0.52377 iter/s, 76.3694s/40 iters), loss = 3.73618
I0708 21:38:23.654816 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.49609 (* 0.3 = 0.748827 loss)
I0708 21:38:23.654840 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.50296 (* 0.3 = 0.750889 loss)
I0708 21:38:23.654889 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.50466 (* 1 = 2.50466 loss)
I0708 21:38:23.654907 99468 sgd_solver.cpp:105] Iteration 47480, lr = 0.001
I0708 21:39:40.107755 99468 solver.cpp:218] Iteration 47520 (0.523215 iter/s, 76.4504s/40 iters), loss = 3.71354
I0708 21:39:40.107988 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.28055 (* 0.3 = 0.684164 loss)
I0708 21:39:40.108011 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27002 (* 0.3 = 0.681007 loss)
I0708 21:39:40.108024 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27171 (* 1 = 2.27171 loss)
I0708 21:39:40.108042 99468 sgd_solver.cpp:105] Iteration 47520, lr = 0.001
I0708 21:40:56.626669 99468 solver.cpp:218] Iteration 47560 (0.522765 iter/s, 76.5162s/40 iters), loss = 3.63701
I0708 21:40:56.626940 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47284 (* 0.3 = 0.741853 loss)
I0708 21:40:56.627007 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.47878 (* 0.3 = 0.743633 loss)
I0708 21:40:56.627027 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48171 (* 1 = 2.48171 loss)
I0708 21:40:56.627044 99468 sgd_solver.cpp:105] Iteration 47560, lr = 0.001
I0708 21:42:13.207746 99468 solver.cpp:218] Iteration 47600 (0.522341 iter/s, 76.5783s/40 iters), loss = 3.69573
I0708 21:42:13.208030 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.1362 (* 0.3 = 0.640861 loss)
I0708 21:42:13.208086 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.13475 (* 0.3 = 0.640424 loss)
I0708 21:42:13.208101 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.14015 (* 1 = 2.14015 loss)
I0708 21:42:13.208117 99468 sgd_solver.cpp:105] Iteration 47600, lr = 0.001
I0708 21:43:29.669904 99468 solver.cpp:218] Iteration 47640 (0.523154 iter/s, 76.4594s/40 iters), loss = 3.78992
I0708 21:43:29.670130 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23997 (* 0.3 = 0.67199 loss)
I0708 21:43:29.670158 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2347 (* 0.3 = 0.67041 loss)
I0708 21:43:29.670171 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23422 (* 1 = 2.23422 loss)
I0708 21:43:29.670187 99468 sgd_solver.cpp:105] Iteration 47640, lr = 0.001
I0708 21:44:46.238561 99468 solver.cpp:218] Iteration 47680 (0.522426 iter/s, 76.5659s/40 iters), loss = 3.71968
I0708 21:44:46.238821 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.85277 (* 0.3 = 0.55583 loss)
I0708 21:44:46.238878 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.86271 (* 0.3 = 0.558813 loss)
I0708 21:44:46.238893 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.85836 (* 1 = 1.85836 loss)
I0708 21:44:46.238910 99468 sgd_solver.cpp:105] Iteration 47680, lr = 0.001
I0708 21:46:02.795791 99468 solver.cpp:218] Iteration 47720 (0.522504 iter/s, 76.5544s/40 iters), loss = 3.67199
I0708 21:46:02.796026 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42648 (* 0.3 = 0.727943 loss)
I0708 21:46:02.796053 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42935 (* 0.3 = 0.728806 loss)
I0708 21:46:02.796102 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42692 (* 1 = 2.42692 loss)
I0708 21:46:02.796118 99468 sgd_solver.cpp:105] Iteration 47720, lr = 0.001
I0708 21:47:19.287082 99468 solver.cpp:218] Iteration 47760 (0.522954 iter/s, 76.4885s/40 iters), loss = 3.70833
I0708 21:47:19.287349 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33327 (* 0.3 = 0.699982 loss)
I0708 21:47:19.287376 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.32557 (* 0.3 = 0.69767 loss)
I0708 21:47:19.287394 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.33219 (* 1 = 2.33219 loss)
I0708 21:47:19.287412 99468 sgd_solver.cpp:105] Iteration 47760, lr = 0.001
I0708 21:48:35.838109 99468 solver.cpp:218] Iteration 47800 (0.522546 iter/s, 76.5482s/40 iters), loss = 3.75139
I0708 21:48:35.838385 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.18766 (* 0.3 = 0.656299 loss)
I0708 21:48:35.838407 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.19937 (* 0.3 = 0.65981 loss)
I0708 21:48:35.838420 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18792 (* 1 = 2.18792 loss)
I0708 21:48:35.838439 99468 sgd_solver.cpp:105] Iteration 47800, lr = 0.001
I0708 21:49:52.450060 99468 solver.cpp:218] Iteration 47840 (0.522131 iter/s, 76.6092s/40 iters), loss = 3.68115
I0708 21:49:52.450286 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23215 (* 0.3 = 0.669645 loss)
I0708 21:49:52.450309 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24284 (* 0.3 = 0.672853 loss)
I0708 21:49:52.450322 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24107 (* 1 = 2.24107 loss)
I0708 21:49:52.450340 99468 sgd_solver.cpp:105] Iteration 47840, lr = 0.001
I0708 21:51:09.042428 99468 solver.cpp:218] Iteration 47880 (0.522264 iter/s, 76.5896s/40 iters), loss = 3.68128
I0708 21:51:09.042716 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.31363 (* 0.3 = 0.694089 loss)
I0708 21:51:09.042773 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.31141 (* 0.3 = 0.693422 loss)
I0708 21:51:09.042789 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.31831 (* 1 = 2.31831 loss)
I0708 21:51:09.042809 99468 sgd_solver.cpp:105] Iteration 47880, lr = 0.001
I0708 21:52:25.529840 99468 solver.cpp:218] Iteration 47920 (0.522981 iter/s, 76.4846s/40 iters), loss = 3.67585
I0708 21:52:25.530136 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43157 (* 0.3 = 0.729471 loss)
I0708 21:52:25.530194 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43124 (* 0.3 = 0.729372 loss)
I0708 21:52:25.530210 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4357 (* 1 = 2.4357 loss)
I0708 21:52:25.530226 99468 sgd_solver.cpp:105] Iteration 47920, lr = 0.001
I0708 21:53:41.929561 99468 solver.cpp:218] Iteration 47960 (0.523582 iter/s, 76.3969s/40 iters), loss = 3.64302
I0708 21:53:41.929786 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.11809 (* 0.3 = 0.635427 loss)
I0708 21:53:41.929810 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12944 (* 0.3 = 0.638832 loss)
I0708 21:53:41.929824 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.12043 (* 1 = 2.12043 loss)
I0708 21:53:41.929844 99468 sgd_solver.cpp:105] Iteration 47960, lr = 0.001
I0708 21:54:56.021843 99468 solver.cpp:330] Iteration 48000, Testing net (#0)
I0708 22:04:38.987025 99629 data_layer.cpp:73] Restarting data prefetching from start.
I0708 22:05:23.801887 99468 solver.cpp:397]     Test net output #0: loss1/loss1 = 2.07656 (* 0.3 = 0.622968 loss)
I0708 22:05:23.802105 99468 solver.cpp:397]     Test net output #1: loss1/top-1 = 0.367581
I0708 22:05:23.802126 99468 solver.cpp:397]     Test net output #2: loss1/top-5 = 0.794675
I0708 22:05:23.802213 99468 solver.cpp:397]     Test net output #3: loss2/loss2 = 2.07646 (* 0.3 = 0.622937 loss)
I0708 22:05:23.802230 99468 solver.cpp:397]     Test net output #4: loss2/top-1 = 0.367581
I0708 22:05:23.802247 99468 solver.cpp:397]     Test net output #5: loss2/top-5 = 0.794675
I0708 22:05:23.802261 99468 solver.cpp:397]     Test net output #6: loss3/loss3 = 2.07925 (* 1 = 2.07925 loss)
I0708 22:05:23.802273 99468 solver.cpp:397]     Test net output #7: loss3/top-1 = 0.367581
I0708 22:05:23.802286 99468 solver.cpp:397]     Test net output #8: loss3/top-5 = 0.794675
I0708 22:05:25.693035 99468 solver.cpp:218] Iteration 48000 (0.0568391 iter/s, 703.74s/40 iters), loss = 3.72934
I0708 22:05:25.693156 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.5964 (* 0.3 = 0.77892 loss)
I0708 22:05:25.693183 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.59039 (* 0.3 = 0.777116 loss)
I0708 22:05:25.693207 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.59106 (* 1 = 2.59106 loss)
I0708 22:05:25.693228 99468 sgd_solver.cpp:105] Iteration 48000, lr = 0.001
I0708 22:06:42.168045 99468 solver.cpp:218] Iteration 48040 (0.523065 iter/s, 76.4724s/40 iters), loss = 3.688
I0708 22:06:42.168287 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.55909 (* 0.3 = 0.767729 loss)
I0708 22:06:42.168314 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.55477 (* 0.3 = 0.766431 loss)
I0708 22:06:42.168330 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.55073 (* 1 = 2.55073 loss)
I0708 22:06:42.168345 99468 sgd_solver.cpp:105] Iteration 48040, lr = 0.001
I0708 22:07:58.747380 99468 solver.cpp:218] Iteration 48080 (0.522353 iter/s, 76.5766s/40 iters), loss = 3.68185
I0708 22:07:58.747668 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.45008 (* 0.3 = 0.735024 loss)
I0708 22:07:58.747687 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.45557 (* 0.3 = 0.736671 loss)
I0708 22:07:58.747704 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.45918 (* 1 = 2.45918 loss)
I0708 22:07:58.747721 99468 sgd_solver.cpp:105] Iteration 48080, lr = 0.001
I0708 22:09:15.278134 99468 solver.cpp:218] Iteration 48120 (0.522685 iter/s, 76.5279s/40 iters), loss = 3.68409
I0708 22:09:15.278367 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40237 (* 0.3 = 0.720711 loss)
I0708 22:09:15.278431 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40456 (* 0.3 = 0.721368 loss)
I0708 22:09:15.278445 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40145 (* 1 = 2.40145 loss)
I0708 22:09:15.278481 99468 sgd_solver.cpp:105] Iteration 48120, lr = 0.001
I0708 22:10:31.786173 99468 solver.cpp:218] Iteration 48160 (0.52284 iter/s, 76.5052s/40 iters), loss = 3.66804
I0708 22:10:31.786469 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42295 (* 0.3 = 0.726885 loss)
I0708 22:10:31.786494 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42938 (* 0.3 = 0.728814 loss)
I0708 22:10:31.786510 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.41936 (* 1 = 2.41936 loss)
I0708 22:10:31.786527 99468 sgd_solver.cpp:105] Iteration 48160, lr = 0.001
I0708 22:11:48.292574 99468 solver.cpp:218] Iteration 48200 (0.522851 iter/s, 76.5036s/40 iters), loss = 3.70242
I0708 22:11:48.292825 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.08664 (* 0.3 = 0.625991 loss)
I0708 22:11:48.292891 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09284 (* 0.3 = 0.627853 loss)
I0708 22:11:48.292924 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.09257 (* 1 = 2.09257 loss)
I0708 22:11:48.292946 99468 sgd_solver.cpp:105] Iteration 48200, lr = 0.001
I0708 22:13:04.789505 99468 solver.cpp:218] Iteration 48240 (0.522916 iter/s, 76.4941s/40 iters), loss = 3.73753
I0708 22:13:04.789747 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23239 (* 0.3 = 0.669717 loss)
I0708 22:13:04.789772 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22779 (* 0.3 = 0.668337 loss)
I0708 22:13:04.789788 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22377 (* 1 = 2.22377 loss)
I0708 22:13:04.789841 99468 sgd_solver.cpp:105] Iteration 48240, lr = 0.001
I0708 22:14:21.402251 99468 solver.cpp:218] Iteration 48280 (0.522125 iter/s, 76.61s/40 iters), loss = 3.66022
I0708 22:14:21.402489 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02189 (* 0.3 = 0.606567 loss)
I0708 22:14:21.402513 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.03129 (* 0.3 = 0.609388 loss)
I0708 22:14:21.402529 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.02827 (* 1 = 2.02827 loss)
I0708 22:14:21.402590 99468 sgd_solver.cpp:105] Iteration 48280, lr = 0.001
I0708 22:15:37.786306 99468 solver.cpp:218] Iteration 48320 (0.523688 iter/s, 76.3813s/40 iters), loss = 3.73213
I0708 22:15:37.786543 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.94553 (* 0.3 = 0.583658 loss)
I0708 22:15:37.786576 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.94268 (* 0.3 = 0.582803 loss)
I0708 22:15:37.786592 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.94131 (* 1 = 1.94131 loss)
I0708 22:15:37.786607 99468 sgd_solver.cpp:105] Iteration 48320, lr = 0.001
I0708 22:16:54.439471 99468 solver.cpp:218] Iteration 48360 (0.52185 iter/s, 76.6504s/40 iters), loss = 3.73605
I0708 22:16:54.439713 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.6708 (* 0.3 = 0.801241 loss)
I0708 22:16:54.439738 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.68361 (* 0.3 = 0.805082 loss)
I0708 22:16:54.439795 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.67145 (* 1 = 2.67145 loss)
I0708 22:16:54.439812 99468 sgd_solver.cpp:105] Iteration 48360, lr = 0.001
I0708 22:18:10.929617 99468 solver.cpp:218] Iteration 48400 (0.522962 iter/s, 76.4874s/40 iters), loss = 3.72857
I0708 22:18:10.929879 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22945 (* 0.3 = 0.668834 loss)
I0708 22:18:10.929904 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.22525 (* 0.3 = 0.667575 loss)
I0708 22:18:10.929922 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23505 (* 1 = 2.23505 loss)
I0708 22:18:10.929936 99468 sgd_solver.cpp:105] Iteration 48400, lr = 0.001
I0708 22:19:27.477816 99468 solver.cpp:218] Iteration 48440 (0.522565 iter/s, 76.5454s/40 iters), loss = 3.74548
I0708 22:19:27.478086 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23656 (* 0.3 = 0.670967 loss)
I0708 22:19:27.478109 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.2374 (* 0.3 = 0.671219 loss)
I0708 22:19:27.478124 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.23943 (* 1 = 2.23943 loss)
I0708 22:19:27.478139 99468 sgd_solver.cpp:105] Iteration 48440, lr = 0.001
I0708 22:20:44.099797 99468 solver.cpp:218] Iteration 48480 (0.522062 iter/s, 76.6192s/40 iters), loss = 3.66581
I0708 22:20:44.100042 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40721 (* 0.3 = 0.722163 loss)
I0708 22:20:44.100064 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.40097 (* 0.3 = 0.72029 loss)
I0708 22:20:44.100078 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.40448 (* 1 = 2.40448 loss)
I0708 22:20:44.100098 99468 sgd_solver.cpp:105] Iteration 48480, lr = 0.001
I0708 22:22:00.522353 99468 solver.cpp:218] Iteration 48520 (0.523425 iter/s, 76.4198s/40 iters), loss = 3.76453
I0708 22:22:00.522599 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.68609 (* 0.3 = 0.805827 loss)
I0708 22:22:00.522627 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.67747 (* 0.3 = 0.803241 loss)
I0708 22:22:00.522644 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.68157 (* 1 = 2.68157 loss)
I0708 22:22:00.522661 99468 sgd_solver.cpp:105] Iteration 48520, lr = 0.001
I0708 22:23:17.130800 99468 solver.cpp:218] Iteration 48560 (0.522155 iter/s, 76.6057s/40 iters), loss = 3.69656
I0708 22:23:17.131028 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 1.98202 (* 0.3 = 0.594605 loss)
I0708 22:23:17.131055 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 1.97319 (* 0.3 = 0.591958 loss)
I0708 22:23:17.131109 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 1.96977 (* 1 = 1.96977 loss)
I0708 22:23:17.131126 99468 sgd_solver.cpp:105] Iteration 48560, lr = 0.001
I0708 22:24:33.725183 99468 solver.cpp:218] Iteration 48600 (0.52225 iter/s, 76.5916s/40 iters), loss = 3.70043
I0708 22:24:33.725426 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.20517 (* 0.3 = 0.66155 loss)
I0708 22:24:33.725450 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21122 (* 0.3 = 0.663367 loss)
I0708 22:24:33.725467 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21146 (* 1 = 2.21146 loss)
I0708 22:24:33.725486 99468 sgd_solver.cpp:105] Iteration 48600, lr = 0.001
I0708 22:25:50.090847 99468 solver.cpp:218] Iteration 48640 (0.523815 iter/s, 76.3629s/40 iters), loss = 3.67684
I0708 22:25:50.091091 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3432 (* 0.3 = 0.702961 loss)
I0708 22:25:50.091152 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.34685 (* 0.3 = 0.704056 loss)
I0708 22:25:50.091166 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34175 (* 1 = 2.34175 loss)
I0708 22:25:50.091182 99468 sgd_solver.cpp:105] Iteration 48640, lr = 0.001
I0708 22:27:06.678912 99468 solver.cpp:218] Iteration 48680 (0.522293 iter/s, 76.5853s/40 iters), loss = 3.65795
I0708 22:27:06.679167 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.22877 (* 0.3 = 0.668631 loss)
I0708 22:27:06.679220 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21793 (* 0.3 = 0.665378 loss)
I0708 22:27:06.679235 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22912 (* 1 = 2.22912 loss)
I0708 22:27:06.679253 99468 sgd_solver.cpp:105] Iteration 48680, lr = 0.001
I0708 22:28:23.010001 99468 solver.cpp:218] Iteration 48720 (0.524052 iter/s, 76.3283s/40 iters), loss = 3.72518
I0708 22:28:23.010248 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.09107 (* 0.3 = 0.627322 loss)
I0708 22:28:23.010272 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.08621 (* 0.3 = 0.625864 loss)
I0708 22:28:23.010321 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0809 (* 1 = 2.0809 loss)
I0708 22:28:23.010339 99468 sgd_solver.cpp:105] Iteration 48720, lr = 0.001
I0708 22:29:39.331192 99468 solver.cpp:218] Iteration 48760 (0.52412 iter/s, 76.3184s/40 iters), loss = 3.68973
I0708 22:29:39.331473 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2227 (* 0.3 = 0.66681 loss)
I0708 22:29:39.331499 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.24941 (* 0.3 = 0.674823 loss)
I0708 22:29:39.331519 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.24144 (* 1 = 2.24144 loss)
I0708 22:29:39.331534 99468 sgd_solver.cpp:105] Iteration 48760, lr = 0.001
I0708 22:30:55.831094 99468 solver.cpp:218] Iteration 48800 (0.522896 iter/s, 76.4971s/40 iters), loss = 3.67324
I0708 22:30:55.831348 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21342 (* 0.3 = 0.664027 loss)
I0708 22:30:55.831378 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.21621 (* 0.3 = 0.664862 loss)
I0708 22:30:55.831395 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.21636 (* 1 = 2.21636 loss)
I0708 22:30:55.831419 99468 sgd_solver.cpp:105] Iteration 48800, lr = 0.001
I0708 22:32:12.290940 99468 solver.cpp:218] Iteration 48840 (0.523169 iter/s, 76.4571s/40 iters), loss = 3.72509
I0708 22:32:12.291190 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.02691 (* 0.3 = 0.608074 loss)
I0708 22:32:12.291224 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.01526 (* 0.3 = 0.604577 loss)
I0708 22:32:12.291283 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.0134 (* 1 = 2.0134 loss)
I0708 22:32:12.291302 99468 sgd_solver.cpp:105] Iteration 48840, lr = 0.001
I0708 22:33:28.908922 99468 solver.cpp:218] Iteration 48880 (0.52209 iter/s, 76.6152s/40 iters), loss = 3.6966
I0708 22:33:28.909173 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07398 (* 0.3 = 0.622195 loss)
I0708 22:33:28.909195 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.06225 (* 0.3 = 0.618675 loss)
I0708 22:33:28.909211 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.08809 (* 1 = 2.08809 loss)
I0708 22:33:28.909232 99468 sgd_solver.cpp:105] Iteration 48880, lr = 0.001
I0708 22:34:45.497153 99468 solver.cpp:218] Iteration 48920 (0.522292 iter/s, 76.5855s/40 iters), loss = 3.66147
I0708 22:34:45.497378 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10266 (* 0.3 = 0.630798 loss)
I0708 22:34:45.497402 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.12432 (* 0.3 = 0.637295 loss)
I0708 22:34:45.497417 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10935 (* 1 = 2.10935 loss)
I0708 22:34:45.497438 99468 sgd_solver.cpp:105] Iteration 48920, lr = 0.001
I0708 22:36:01.835325 99468 solver.cpp:218] Iteration 48960 (0.524003 iter/s, 76.3354s/40 iters), loss = 3.71744
I0708 22:36:01.835561 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.2948 (* 0.3 = 0.688441 loss)
I0708 22:36:01.835587 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.27955 (* 0.3 = 0.683866 loss)
I0708 22:36:01.835603 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.27497 (* 1 = 2.27497 loss)
I0708 22:36:01.835618 99468 sgd_solver.cpp:105] Iteration 48960, lr = 0.001
I0708 22:37:18.167001 99468 solver.cpp:218] Iteration 49000 (0.524048 iter/s, 76.3289s/40 iters), loss = 3.70097
I0708 22:37:18.167237 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.43151 (* 0.3 = 0.729453 loss)
I0708 22:37:18.167266 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43268 (* 0.3 = 0.729805 loss)
I0708 22:37:18.167320 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43458 (* 1 = 2.43458 loss)
I0708 22:37:18.167341 99468 sgd_solver.cpp:105] Iteration 49000, lr = 0.001
I0708 22:38:34.558938 99468 solver.cpp:218] Iteration 49040 (0.523634 iter/s, 76.3892s/40 iters), loss = 3.74337
I0708 22:38:34.559170 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30453 (* 0.3 = 0.69136 loss)
I0708 22:38:34.559198 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3018 (* 0.3 = 0.690539 loss)
I0708 22:38:34.559252 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.30663 (* 1 = 2.30663 loss)
I0708 22:38:34.559268 99468 sgd_solver.cpp:105] Iteration 49040, lr = 0.001
I0708 22:39:50.891646 99468 solver.cpp:218] Iteration 49080 (0.524041 iter/s, 76.33s/40 iters), loss = 3.65079
I0708 22:39:50.891922 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.33304 (* 0.3 = 0.699912 loss)
I0708 22:39:50.891955 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3247 (* 0.3 = 0.697409 loss)
I0708 22:39:50.891973 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.32369 (* 1 = 2.32369 loss)
I0708 22:39:50.891994 99468 sgd_solver.cpp:105] Iteration 49080, lr = 0.001
I0708 22:41:07.209127 99468 solver.cpp:218] Iteration 49120 (0.524146 iter/s, 76.3147s/40 iters), loss = 3.68461
I0708 22:41:07.209374 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.76688 (* 0.3 = 0.830063 loss)
I0708 22:41:07.209403 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.76896 (* 0.3 = 0.830687 loss)
I0708 22:41:07.209420 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.77983 (* 1 = 2.77983 loss)
I0708 22:41:07.209439 99468 sgd_solver.cpp:105] Iteration 49120, lr = 0.001
I0708 22:42:23.569250 99468 solver.cpp:218] Iteration 49160 (0.523853 iter/s, 76.3574s/40 iters), loss = 3.7469
I0708 22:42:23.569499 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.6264 (* 0.3 = 0.787921 loss)
I0708 22:42:23.569567 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.62424 (* 0.3 = 0.787272 loss)
I0708 22:42:23.569584 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.6222 (* 1 = 2.6222 loss)
I0708 22:42:23.569602 99468 sgd_solver.cpp:105] Iteration 49160, lr = 0.001
I0708 22:43:40.181097 99468 solver.cpp:218] Iteration 49200 (0.522131 iter/s, 76.6091s/40 iters), loss = 3.69516
I0708 22:43:40.181329 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27227 (* 0.3 = 0.68168 loss)
I0708 22:43:40.181352 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.28629 (* 0.3 = 0.685887 loss)
I0708 22:43:40.181367 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.2701 (* 1 = 2.2701 loss)
I0708 22:43:40.181385 99468 sgd_solver.cpp:105] Iteration 49200, lr = 0.001
I0708 22:44:56.842627 99468 solver.cpp:218] Iteration 49240 (0.521793 iter/s, 76.6588s/40 iters), loss = 3.71517
I0708 22:44:56.842871 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.30889 (* 0.3 = 0.692667 loss)
I0708 22:44:56.842898 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.30581 (* 0.3 = 0.691742 loss)
I0708 22:44:56.842916 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.29975 (* 1 = 2.29975 loss)
I0708 22:44:56.842932 99468 sgd_solver.cpp:105] Iteration 49240, lr = 0.001
I0708 22:46:13.454780 99468 solver.cpp:218] Iteration 49280 (0.522129 iter/s, 76.6094s/40 iters), loss = 3.70305
I0708 22:46:13.455013 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.4077 (* 0.3 = 0.722311 loss)
I0708 22:46:13.455044 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.42333 (* 0.3 = 0.726998 loss)
I0708 22:46:13.455063 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.42115 (* 1 = 2.42115 loss)
I0708 22:46:13.455080 99468 sgd_solver.cpp:105] Iteration 49280, lr = 0.001
I0708 22:47:30.085047 99468 solver.cpp:218] Iteration 49320 (0.522006 iter/s, 76.6275s/40 iters), loss = 3.67179
I0708 22:47:30.085289 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.44605 (* 0.3 = 0.733816 loss)
I0708 22:47:30.085316 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43759 (* 0.3 = 0.731277 loss)
I0708 22:47:30.085372 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.4321 (* 1 = 2.4321 loss)
I0708 22:47:30.085391 99468 sgd_solver.cpp:105] Iteration 49320, lr = 0.001
I0708 22:48:46.651422 99468 solver.cpp:218] Iteration 49360 (0.522441 iter/s, 76.5636s/40 iters), loss = 3.71437
I0708 22:48:46.651736 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.10309 (* 0.3 = 0.630926 loss)
I0708 22:48:46.651793 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.09531 (* 0.3 = 0.628592 loss)
I0708 22:48:46.651808 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.10261 (* 1 = 2.10261 loss)
I0708 22:48:46.651825 99468 sgd_solver.cpp:105] Iteration 49360, lr = 0.001
I0708 22:50:03.277048 99468 solver.cpp:218] Iteration 49400 (0.522121 iter/s, 76.6105s/40 iters), loss = 3.71008
I0708 22:50:03.277305 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.03409 (* 0.3 = 0.610228 loss)
I0708 22:50:03.277333 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.04032 (* 0.3 = 0.612096 loss)
I0708 22:50:03.277349 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.03172 (* 1 = 2.03172 loss)
I0708 22:50:03.277400 99468 sgd_solver.cpp:105] Iteration 49400, lr = 0.001
I0708 22:51:19.879340 99468 solver.cpp:218] Iteration 49440 (0.522196 iter/s, 76.5995s/40 iters), loss = 3.74579
I0708 22:51:19.879617 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.58194 (* 0.3 = 0.774582 loss)
I0708 22:51:19.879662 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.5827 (* 0.3 = 0.774811 loss)
I0708 22:51:19.879678 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.58273 (* 1 = 2.58273 loss)
I0708 22:51:19.879714 99468 sgd_solver.cpp:105] Iteration 49440, lr = 0.001
I0708 22:52:36.484484 99468 solver.cpp:218] Iteration 49480 (0.522177 iter/s, 76.6023s/40 iters), loss = 3.7025
I0708 22:52:36.484724 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17316 (* 0.3 = 0.651948 loss)
I0708 22:52:36.484776 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.17901 (* 0.3 = 0.653704 loss)
I0708 22:52:36.484791 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.17448 (* 1 = 2.17448 loss)
I0708 22:52:36.484810 99468 sgd_solver.cpp:105] Iteration 49480, lr = 0.001
I0708 22:53:53.104547 99468 solver.cpp:218] Iteration 49520 (0.522075 iter/s, 76.6173s/40 iters), loss = 3.71452
I0708 22:53:53.105298 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.47554 (* 0.3 = 0.742663 loss)
I0708 22:53:53.105357 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.49782 (* 0.3 = 0.749345 loss)
I0708 22:53:53.105373 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.48883 (* 1 = 2.48883 loss)
I0708 22:53:53.105389 99468 sgd_solver.cpp:105] Iteration 49520, lr = 0.001
I0708 22:55:09.700757 99468 solver.cpp:218] Iteration 49560 (0.522241 iter/s, 76.5929s/40 iters), loss = 3.69482
I0708 22:55:09.700987 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.17838 (* 0.3 = 0.653513 loss)
I0708 22:55:09.701007 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.18183 (* 0.3 = 0.654548 loss)
I0708 22:55:09.701022 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.18198 (* 1 = 2.18198 loss)
I0708 22:55:09.701076 99468 sgd_solver.cpp:105] Iteration 49560, lr = 0.001
I0708 22:56:26.341532 99468 solver.cpp:218] Iteration 49600 (0.521934 iter/s, 76.638s/40 iters), loss = 3.77103
I0708 22:56:26.341773 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.3831 (* 0.3 = 0.71493 loss)
I0708 22:56:26.341799 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3863 (* 0.3 = 0.715891 loss)
I0708 22:56:26.341848 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.37855 (* 1 = 2.37855 loss)
I0708 22:56:26.341866 99468 sgd_solver.cpp:105] Iteration 49600, lr = 0.001
I0708 22:57:42.854746 99468 solver.cpp:218] Iteration 49640 (0.522804 iter/s, 76.5104s/40 iters), loss = 3.70114
I0708 22:57:42.854979 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.40168 (* 0.3 = 0.720505 loss)
I0708 22:57:42.855006 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39229 (* 0.3 = 0.717686 loss)
I0708 22:57:42.855057 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.38557 (* 1 = 2.38557 loss)
I0708 22:57:42.855073 99468 sgd_solver.cpp:105] Iteration 49640, lr = 0.001
I0708 22:58:59.254925 99468 solver.cpp:218] Iteration 49680 (0.523578 iter/s, 76.3974s/40 iters), loss = 3.71079
I0708 22:58:59.255218 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.21058 (* 0.3 = 0.663174 loss)
I0708 22:58:59.255275 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.20215 (* 0.3 = 0.660644 loss)
I0708 22:58:59.255288 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.20635 (* 1 = 2.20635 loss)
I0708 22:58:59.255307 99468 sgd_solver.cpp:105] Iteration 49680, lr = 0.001
I0708 23:00:15.853015 99468 solver.cpp:218] Iteration 49720 (0.522225 iter/s, 76.5953s/40 iters), loss = 3.71502
I0708 23:00:15.853281 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.07621 (* 0.3 = 0.622863 loss)
I0708 23:00:15.853307 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.07954 (* 0.3 = 0.623863 loss)
I0708 23:00:15.853322 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.07036 (* 1 = 2.07036 loss)
I0708 23:00:15.853374 99468 sgd_solver.cpp:105] Iteration 49720, lr = 0.001
I0708 23:01:32.466379 99468 solver.cpp:218] Iteration 49760 (0.522121 iter/s, 76.6106s/40 iters), loss = 3.65164
I0708 23:01:32.466627 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.39696 (* 0.3 = 0.719087 loss)
I0708 23:01:32.466687 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.39385 (* 0.3 = 0.718154 loss)
I0708 23:01:32.466703 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.39283 (* 1 = 2.39283 loss)
I0708 23:01:32.466722 99468 sgd_solver.cpp:105] Iteration 49760, lr = 0.001
I0708 23:02:48.986902 99468 solver.cpp:218] Iteration 49800 (0.522754 iter/s, 76.5178s/40 iters), loss = 3.66991
I0708 23:02:48.987139 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.75705 (* 0.3 = 0.827115 loss)
I0708 23:02:48.987197 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.77391 (* 0.3 = 0.832172 loss)
I0708 23:02:48.987213 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.75764 (* 1 = 2.75764 loss)
I0708 23:02:48.987232 99468 sgd_solver.cpp:105] Iteration 49800, lr = 0.001
I0708 23:04:05.664381 99468 solver.cpp:218] Iteration 49840 (0.521685 iter/s, 76.6747s/40 iters), loss = 3.68761
I0708 23:04:05.664650 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.27643 (* 0.3 = 0.682929 loss)
I0708 23:04:05.664675 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.26933 (* 0.3 = 0.6808 loss)
I0708 23:04:05.664691 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.28729 (* 1 = 2.28729 loss)
I0708 23:04:05.664744 99468 sgd_solver.cpp:105] Iteration 49840, lr = 0.001
I0708 23:05:22.255897 99468 solver.cpp:218] Iteration 49880 (0.52227 iter/s, 76.5887s/40 iters), loss = 3.70475
I0708 23:05:22.256137 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.23909 (* 0.3 = 0.671728 loss)
I0708 23:05:22.256193 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.23169 (* 0.3 = 0.669507 loss)
I0708 23:05:22.256209 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.22051 (* 1 = 2.22051 loss)
I0708 23:05:22.256227 99468 sgd_solver.cpp:105] Iteration 49880, lr = 0.001
I0708 23:06:38.901861 99468 solver.cpp:218] Iteration 49920 (0.521899 iter/s, 76.6432s/40 iters), loss = 3.74522
I0708 23:06:38.902092 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.34477 (* 0.3 = 0.70343 loss)
I0708 23:06:38.902117 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.3378 (* 0.3 = 0.70134 loss)
I0708 23:06:38.902164 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.34873 (* 1 = 2.34873 loss)
I0708 23:06:38.902181 99468 sgd_solver.cpp:105] Iteration 49920, lr = 0.001
I0708 23:07:55.430269 99468 solver.cpp:218] Iteration 49960 (0.5227 iter/s, 76.5257s/40 iters), loss = 3.69629
I0708 23:07:55.430505 99468 solver.cpp:237]     Train net output #0: loss1/loss1 = 2.42696 (* 0.3 = 0.728088 loss)
I0708 23:07:55.430529 99468 solver.cpp:237]     Train net output #1: loss2/loss2 = 2.43421 (* 0.3 = 0.730264 loss)
I0708 23:07:55.430546 99468 solver.cpp:237]     Train net output #2: loss3/loss3 = 2.43831 (* 1 = 2.43831 loss)
I0708 23:07:55.430569 99468 sgd_solver.cpp:105] Iteration 49960, lr = 0.001
I0708 23:09:09.444447 99468 solver.cpp:447] Snapshotting to binary proto file /data04/googlenet/caffemodel/_iter_50000.caffemodel
I0708 23:09:10.356015 99468 sgd_solver.cpp:273] Snapshotting solver state to binary proto file /data04/googlenet/caffemodel/_iter_50000.solverstate
I0708 23:09:10.714017 99468 solver.cpp:310] Iteration 50000, loss = 3.66706
I0708 23:09:10.714097 99468 solver.cpp:315] Optimization Done.
I0708 23:09:10.714112 99468 caffe.cpp:259] Optimization Done.