aws_logfile_caffe_flow_miniGoogleNet.txt

TRAINING. Remember that: <Epoch_index = floor((iteration_index * batch_size) / (# data_samples))>
I0121 17:48:34.554952  1741 caffe.cpp:218] Using GPUs 0
I0121 17:48:34.774744  1741 caffe.cpp:223] GPU 0: Tesla K80
I0121 17:48:35.786353  1741 solver.cpp:44] Initializing solver from parameters: 
test_iter: 180
test_interval: 1000
base_lr: 0.1
display: 100
max_iter: 40000
lr_policy: "step"
gamma: 0.1
momentum: 0.9
weight_decay: 0.001
stepsize: 10000
snapshot: 10000
snapshot_prefix: "cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet_"
solver_mode: GPU
device_id: 0
random_seed: 1201
net: "cifar10/caffe/models/miniGoogleNet/m3/train_val_3_miniGoogleNet.prototxt"
train_state {
  level: 0
  stage: ""
}
type: "SGD"
I0121 17:48:35.786638  1741 solver.cpp:87] Creating training net from net file: cifar10/caffe/models/miniGoogleNet/m3/train_val_3_miniGoogleNet.prototxt
I0121 17:48:35.789472  1741 upgrade_proto.cpp:77] Attempting to upgrade batch norm layers using deprecated params: cifar10/caffe/models/miniGoogleNet/m3/train_val_3_miniGoogleNet.prototxt
I0121 17:48:35.789505  1741 upgrade_proto.cpp:80] Successfully upgraded batch norm layers using deprecated params.
I0121 17:48:35.789752  1741 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer data
I0121 17:48:35.789845  1741 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy
I0121 17:48:35.790426  1741 net.cpp:51] Initializing net from parameters: 
name: "miniGoogleNet for CIFAR10, model 3"
state {
  phase: TRAIN
  level: 0
  stage: ""
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    mean_file: "cifar10/input/mean.binaryproto"
  }
  data_param {
    source: "cifar10/input/lmdb/train_lmdb"
    batch_size: 128
    backend: LMDB
  }
}
layer {
  name: "conv1/3x3_s1"
  type: "Convolution"
  bottom: "data"
  top: "conv1/3x3_s1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/bn1"
  type: "BatchNorm"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "conv1/scale1"
  type: "Scale"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv1/relu1"
  type: "ReLU"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
}
layer {
  name: "inception_2a/1x1"
  type: "Convolution"
  bottom: "conv1/3x3_s1"
  top: "inception_2a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_2a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_2a/1x1/scale1"
  type: "Scale"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_2a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
}
layer {
  name: "inception_2a/3x3"
  type: "Convolution"
  bottom: "conv1/3x3_s1"
  top: "inception_2a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_2a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_2a/3x3/scale1"
  type: "Scale"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_2a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
}
layer {
  name: "inception_2a/output"
  type: "Concat"
  bottom: "inception_2a/1x1"
  bottom: "inception_2a/3x3"
  top: "inception_2a/output"
}
layer {
  name: "inception_3a/1x1"
  type: "Convolution"
  bottom: "inception_2a/output"
  top: "inception_3a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_3a/1x1/scale1"
  type: "Scale"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_3a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
}
layer {
  name: "inception_3a/3x3"
  type: "Convolution"
  bottom: "inception_2a/output"
  top: "inception_3a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_3a/3x3/scale1"
  type: "Scale"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_3a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
}
layer {
  name: "inception_3a/output"
  type: "Concat"
  bottom: "inception_3a/1x1"
  bottom: "inception_3a/3x3"
  top: "inception_3a/output"
}
layer {
  name: "downsample_4/3x3_s2"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "downsample_4/3x3_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "downsample_4/3x3_s2/bn1"
  type: "BatchNorm"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "downsample_4/3x3_s2/scale1"
  type: "Scale"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "downsample_4/3x3_s2/relu1"
  type: "ReLU"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
}
layer {
  name: "downsample_4/pool_s2"
  type: "Pooling"
  bottom: "inception_3a/output"
  top: "downsample_4/pool_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "downsample_4/output"
  type: "Concat"
  bottom: "downsample_4/3x3_s2"
  bottom: "downsample_4/pool_s2"
  top: "downsample_4/output"
}
layer {
  name: "inception_5a/1x1"
  type: "Convolution"
  bottom: "downsample_4/output"
  top: "inception_5a/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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_5a/1x1/scale1"
  type: "Scale"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_5a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
}
layer {
  name: "inception_5a/3x3"
  type: "Convolution"
  bottom: "downsample_4/output"
  top: "inception_5a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_5a/3x3/scale1"
  type: "Scale"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_5a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
}
layer {
  name: "inception_5a/output"
  type: "Concat"
  bottom: "inception_5a/1x1"
  bottom: "inception_5a/3x3"
  top: "inception_5a/output"
}
layer {
  name: "inception_6a/1x1"
  type: "Convolution"
  bottom: "inception_5a/output"
  top: "inception_6a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_6a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_6a/1x1/scale1"
  type: "Scale"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_6a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
}
layer {
  name: "inception_6a/3x3"
  type: "Convolution"
  bottom: "inception_5a/output"
  top: "inception_6a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_6a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_6a/3x3/scale1"
  type: "Scale"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_6a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
}
layer {
  name: "inception_6a/output"
  type: "Concat"
  bottom: "inception_6a/1x1"
  bottom: "inception_6a/3x3"
  top: "inception_6a/output"
}
layer {
  name: "inception_7a/1x1"
  type: "Convolution"
  bottom: "inception_6a/output"
  top: "inception_7a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_7a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_7a/1x1/scale1"
  type: "Scale"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_7a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
}
layer {
  name: "inception_7a/3x3"
  type: "Convolution"
  bottom: "inception_6a/output"
  top: "inception_7a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_7a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_7a/3x3/scale1"
  type: "Scale"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_7a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
}
layer {
  name: "inception_7a/output"
  type: "Concat"
  bottom: "inception_7a/1x1"
  bottom: "inception_7a/3x3"
  top: "inception_7a/output"
}
layer {
  name: "inception_8a/1x1"
  type: "Convolution"
  bottom: "inception_7a/output"
  top: "inception_8a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_8a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_8a/1x1/scale1"
  type: "Scale"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_8a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
}
layer {
  name: "inception_8a/3x3"
  type: "Convolution"
  bottom: "inception_7a/output"
  top: "inception_8a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_8a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_8a/3x3/scale1"
  type: "Scale"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_8a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
}
layer {
  name: "inception_8a/output"
  type: "Concat"
  bottom: "inception_8a/1x1"
  bottom: "inception_8a/3x3"
  top: "inception_8a/output"
}
layer {
  name: "downsample_9/3x3_s2"
  type: "Convolution"
  bottom: "inception_8a/output"
  top: "downsample_9/3x3_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "downsample_9/3x3_s2/bn1"
  type: "BatchNorm"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "downsample_9/3x3_s2/scale1"
  type: "Scale"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "downsample_9/3x3_s2/relu1"
  type: "ReLU"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
}
layer {
  name: "downsample_9/pool_s2"
  type: "Pooling"
  bottom: "inception_8a/output"
  top: "downsample_9/pool_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "downsample_9/output"
  type: "Concat"
  bottom: "downsample_9/3x3_s2"
  bottom: "downsample_9/pool_s2"
  top: "downsample_9/output"
}
layer {
  name: "inception_10a/1x1"
  type: "Convolution"
  bottom: "downsample_9/output"
  top: "inception_10a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 176
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_10a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_10a/1x1/scale1"
  type: "Scale"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_10a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
}
layer {
  name: "inception_10a/3x3"
  type: "Convolution"
  bottom: "downsample_9/output"
  top: "inception_10a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_10a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_10a/3x3/scale1"
  type: "Scale"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_10a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
}
layer {
  name: "inception_10a/output"
  type: "Concat"
  bottom: "inception_10a/1x1"
  bottom: "inception_10a/3x3"
  top: "inception_10a/output"
}
layer {
  name: "inception_11a/1x1"
  type: "Convolution"
  bottom: "inception_10a/output"
  top: "inception_11a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 176
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_11a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_11a/1x1/scale1"
  type: "Scale"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_11a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
}
layer {
  name: "inception_11a/3x3"
  type: "Convolution"
  bottom: "inception_10a/output"
  top: "inception_11a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_11a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_11a/3x3/scale1"
  type: "Scale"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_11a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
}
layer {
  name: "inception_11a/output"
  type: "Concat"
  bottom: "inception_11a/1x1"
  bottom: "inception_11a/3x3"
  top: "inception_11a/output"
}
layer {
  name: "avg_pool_12/8x8_s1"
  type: "Pooling"
  bottom: "inception_11a/output"
  top: "avg_pool_12/8x8_s1"
  pooling_param {
    pool: AVE
    kernel_size: 8
    stride: 1
  }
}
layer {
  name: "drop_8x8_s1"
  type: "Dropout"
  bottom: "avg_pool_12/8x8_s1"
  top: "avg_pool_12/8x8_s1"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "loss/classifier"
  type: "InnerProduct"
  bottom: "avg_pool_12/8x8_s1"
  top: "loss/classifier"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 10
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "loss/classifier"
  bottom: "label"
  top: "loss"
}
I0121 17:48:35.792948  1741 layer_factory.hpp:77] Creating layer data
I0121 17:48:35.803140  1741 db_lmdb.cpp:35] Opened lmdb cifar10/input/lmdb/train_lmdb
I0121 17:48:35.812201  1741 net.cpp:84] Creating Layer data
I0121 17:48:35.812224  1741 net.cpp:380] data -> data
I0121 17:48:35.812258  1741 net.cpp:380] data -> label
I0121 17:48:35.812321  1741 data_transformer.cpp:25] Loading mean file from: cifar10/input/mean.binaryproto
I0121 17:48:35.814724  1741 data_layer.cpp:45] output data size: 128,3,32,32
I0121 17:48:35.820502  1741 net.cpp:122] Setting up data
I0121 17:48:35.820536  1741 net.cpp:129] Top shape: 128 3 32 32 (393216)
I0121 17:48:35.820544  1741 net.cpp:129] Top shape: 128 (128)
I0121 17:48:35.820555  1741 net.cpp:137] Memory required for data: 1573376
I0121 17:48:35.820570  1741 layer_factory.hpp:77] Creating layer conv1/3x3_s1
I0121 17:48:35.820605  1741 net.cpp:84] Creating Layer conv1/3x3_s1
I0121 17:48:35.820637  1741 net.cpp:406] conv1/3x3_s1 <- data
I0121 17:48:35.820684  1741 net.cpp:380] conv1/3x3_s1 -> conv1/3x3_s1
I0121 17:48:37.359288  1741 net.cpp:122] Setting up conv1/3x3_s1
I0121 17:48:37.359350  1741 net.cpp:129] Top shape: 128 96 32 32 (12582912)
I0121 17:48:37.359360  1741 net.cpp:137] Memory required for data: 51905024
I0121 17:48:37.359395  1741 layer_factory.hpp:77] Creating layer conv1/bn1
I0121 17:48:37.359426  1741 net.cpp:84] Creating Layer conv1/bn1
I0121 17:48:37.359457  1741 net.cpp:406] conv1/bn1 <- conv1/3x3_s1
I0121 17:48:37.359472  1741 net.cpp:367] conv1/bn1 -> conv1/3x3_s1 (in-place)
I0121 17:48:37.359737  1741 net.cpp:122] Setting up conv1/bn1
I0121 17:48:37.359758  1741 net.cpp:129] Top shape: 128 96 32 32 (12582912)
I0121 17:48:37.359767  1741 net.cpp:137] Memory required for data: 102236672
I0121 17:48:37.359792  1741 layer_factory.hpp:77] Creating layer conv1/scale1
I0121 17:48:37.359865  1741 net.cpp:84] Creating Layer conv1/scale1
I0121 17:48:37.359891  1741 net.cpp:406] conv1/scale1 <- conv1/3x3_s1
I0121 17:48:37.359900  1741 net.cpp:367] conv1/scale1 -> conv1/3x3_s1 (in-place)
I0121 17:48:37.359978  1741 layer_factory.hpp:77] Creating layer conv1/scale1
I0121 17:48:37.360146  1741 net.cpp:122] Setting up conv1/scale1
I0121 17:48:37.360162  1741 net.cpp:129] Top shape: 128 96 32 32 (12582912)
I0121 17:48:37.360168  1741 net.cpp:137] Memory required for data: 152568320
I0121 17:48:37.360177  1741 layer_factory.hpp:77] Creating layer conv1/relu1
I0121 17:48:37.360188  1741 net.cpp:84] Creating Layer conv1/relu1
I0121 17:48:37.360198  1741 net.cpp:406] conv1/relu1 <- conv1/3x3_s1
I0121 17:48:37.360210  1741 net.cpp:367] conv1/relu1 -> conv1/3x3_s1 (in-place)
I0121 17:48:37.361358  1741 net.cpp:122] Setting up conv1/relu1
I0121 17:48:37.361380  1741 net.cpp:129] Top shape: 128 96 32 32 (12582912)
I0121 17:48:37.361385  1741 net.cpp:137] Memory required for data: 202899968
I0121 17:48:37.361392  1741 layer_factory.hpp:77] Creating layer conv1/3x3_s1_conv1/relu1_0_split
I0121 17:48:37.361403  1741 net.cpp:84] Creating Layer conv1/3x3_s1_conv1/relu1_0_split
I0121 17:48:37.361409  1741 net.cpp:406] conv1/3x3_s1_conv1/relu1_0_split <- conv1/3x3_s1
I0121 17:48:37.361418  1741 net.cpp:380] conv1/3x3_s1_conv1/relu1_0_split -> conv1/3x3_s1_conv1/relu1_0_split_0
I0121 17:48:37.361440  1741 net.cpp:380] conv1/3x3_s1_conv1/relu1_0_split -> conv1/3x3_s1_conv1/relu1_0_split_1
I0121 17:48:37.361507  1741 net.cpp:122] Setting up conv1/3x3_s1_conv1/relu1_0_split
I0121 17:48:37.361524  1741 net.cpp:129] Top shape: 128 96 32 32 (12582912)
I0121 17:48:37.361531  1741 net.cpp:129] Top shape: 128 96 32 32 (12582912)
I0121 17:48:37.361536  1741 net.cpp:137] Memory required for data: 303563264
I0121 17:48:37.361541  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1
I0121 17:48:37.361593  1741 net.cpp:84] Creating Layer inception_2a/1x1
I0121 17:48:37.361606  1741 net.cpp:406] inception_2a/1x1 <- conv1/3x3_s1_conv1/relu1_0_split_0
I0121 17:48:37.361615  1741 net.cpp:380] inception_2a/1x1 -> inception_2a/1x1
I0121 17:48:37.362445  1741 net.cpp:122] Setting up inception_2a/1x1
I0121 17:48:37.362470  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.362475  1741 net.cpp:137] Memory required for data: 320340480
I0121 17:48:37.362488  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/bn1
I0121 17:48:37.362498  1741 net.cpp:84] Creating Layer inception_2a/1x1/bn1
I0121 17:48:37.362509  1741 net.cpp:406] inception_2a/1x1/bn1 <- inception_2a/1x1
I0121 17:48:37.362519  1741 net.cpp:367] inception_2a/1x1/bn1 -> inception_2a/1x1 (in-place)
I0121 17:48:37.362732  1741 net.cpp:122] Setting up inception_2a/1x1/bn1
I0121 17:48:37.362751  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.362756  1741 net.cpp:137] Memory required for data: 337117696
I0121 17:48:37.362766  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/scale1
I0121 17:48:37.362776  1741 net.cpp:84] Creating Layer inception_2a/1x1/scale1
I0121 17:48:37.362783  1741 net.cpp:406] inception_2a/1x1/scale1 <- inception_2a/1x1
I0121 17:48:37.362792  1741 net.cpp:367] inception_2a/1x1/scale1 -> inception_2a/1x1 (in-place)
I0121 17:48:37.362850  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/scale1
I0121 17:48:37.362996  1741 net.cpp:122] Setting up inception_2a/1x1/scale1
I0121 17:48:37.363014  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.363019  1741 net.cpp:137] Memory required for data: 353894912
I0121 17:48:37.363042  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/relu1
I0121 17:48:37.363056  1741 net.cpp:84] Creating Layer inception_2a/1x1/relu1
I0121 17:48:37.363063  1741 net.cpp:406] inception_2a/1x1/relu1 <- inception_2a/1x1
I0121 17:48:37.363072  1741 net.cpp:367] inception_2a/1x1/relu1 -> inception_2a/1x1 (in-place)
I0121 17:48:37.363387  1741 net.cpp:122] Setting up inception_2a/1x1/relu1
I0121 17:48:37.363412  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.363417  1741 net.cpp:137] Memory required for data: 370672128
I0121 17:48:37.363423  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3
I0121 17:48:37.363438  1741 net.cpp:84] Creating Layer inception_2a/3x3
I0121 17:48:37.363456  1741 net.cpp:406] inception_2a/3x3 <- conv1/3x3_s1_conv1/relu1_0_split_1
I0121 17:48:37.363469  1741 net.cpp:380] inception_2a/3x3 -> inception_2a/3x3
I0121 17:48:37.365247  1741 net.cpp:122] Setting up inception_2a/3x3
I0121 17:48:37.365273  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.365279  1741 net.cpp:137] Memory required for data: 387449344
I0121 17:48:37.365288  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/bn1
I0121 17:48:37.365300  1741 net.cpp:84] Creating Layer inception_2a/3x3/bn1
I0121 17:48:37.365309  1741 net.cpp:406] inception_2a/3x3/bn1 <- inception_2a/3x3
I0121 17:48:37.365321  1741 net.cpp:367] inception_2a/3x3/bn1 -> inception_2a/3x3 (in-place)
I0121 17:48:37.365573  1741 net.cpp:122] Setting up inception_2a/3x3/bn1
I0121 17:48:37.365593  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.365598  1741 net.cpp:137] Memory required for data: 404226560
I0121 17:48:37.365612  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/scale1
I0121 17:48:37.365623  1741 net.cpp:84] Creating Layer inception_2a/3x3/scale1
I0121 17:48:37.365631  1741 net.cpp:406] inception_2a/3x3/scale1 <- inception_2a/3x3
I0121 17:48:37.365649  1741 net.cpp:367] inception_2a/3x3/scale1 -> inception_2a/3x3 (in-place)
I0121 17:48:37.365717  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/scale1
I0121 17:48:37.365909  1741 net.cpp:122] Setting up inception_2a/3x3/scale1
I0121 17:48:37.365929  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.365934  1741 net.cpp:137] Memory required for data: 421003776
I0121 17:48:37.365943  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/relu1
I0121 17:48:37.365953  1741 net.cpp:84] Creating Layer inception_2a/3x3/relu1
I0121 17:48:37.365962  1741 net.cpp:406] inception_2a/3x3/relu1 <- inception_2a/3x3
I0121 17:48:37.365967  1741 net.cpp:367] inception_2a/3x3/relu1 -> inception_2a/3x3 (in-place)
I0121 17:48:37.366127  1741 net.cpp:122] Setting up inception_2a/3x3/relu1
I0121 17:48:37.366148  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.366153  1741 net.cpp:137] Memory required for data: 437780992
I0121 17:48:37.366158  1741 layer_factory.hpp:77] Creating layer inception_2a/output
I0121 17:48:37.366168  1741 net.cpp:84] Creating Layer inception_2a/output
I0121 17:48:37.366174  1741 net.cpp:406] inception_2a/output <- inception_2a/1x1
I0121 17:48:37.366180  1741 net.cpp:406] inception_2a/output <- inception_2a/3x3
I0121 17:48:37.366186  1741 net.cpp:380] inception_2a/output -> inception_2a/output
I0121 17:48:37.366681  1741 net.cpp:122] Setting up inception_2a/output
I0121 17:48:37.366701  1741 net.cpp:129] Top shape: 128 64 32 32 (8388608)
I0121 17:48:37.366706  1741 net.cpp:137] Memory required for data: 471335424
I0121 17:48:37.366711  1741 layer_factory.hpp:77] Creating layer inception_2a/output_inception_2a/output_0_split
I0121 17:48:37.366719  1741 net.cpp:84] Creating Layer inception_2a/output_inception_2a/output_0_split
I0121 17:48:37.366724  1741 net.cpp:406] inception_2a/output_inception_2a/output_0_split <- inception_2a/output
I0121 17:48:37.366735  1741 net.cpp:380] inception_2a/output_inception_2a/output_0_split -> inception_2a/output_inception_2a/output_0_split_0
I0121 17:48:37.366744  1741 net.cpp:380] inception_2a/output_inception_2a/output_0_split -> inception_2a/output_inception_2a/output_0_split_1
I0121 17:48:37.366820  1741 net.cpp:122] Setting up inception_2a/output_inception_2a/output_0_split
I0121 17:48:37.366842  1741 net.cpp:129] Top shape: 128 64 32 32 (8388608)
I0121 17:48:37.366849  1741 net.cpp:129] Top shape: 128 64 32 32 (8388608)
I0121 17:48:37.366853  1741 net.cpp:137] Memory required for data: 538444288
I0121 17:48:37.366859  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1
I0121 17:48:37.366876  1741 net.cpp:84] Creating Layer inception_3a/1x1
I0121 17:48:37.366911  1741 net.cpp:406] inception_3a/1x1 <- inception_2a/output_inception_2a/output_0_split_0
I0121 17:48:37.366950  1741 net.cpp:380] inception_3a/1x1 -> inception_3a/1x1
I0121 17:48:37.367928  1741 net.cpp:122] Setting up inception_3a/1x1
I0121 17:48:37.367957  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.367964  1741 net.cpp:137] Memory required for data: 555221504
I0121 17:48:37.367971  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/bn1
I0121 17:48:37.367985  1741 net.cpp:84] Creating Layer inception_3a/1x1/bn1
I0121 17:48:37.367990  1741 net.cpp:406] inception_3a/1x1/bn1 <- inception_3a/1x1
I0121 17:48:37.368000  1741 net.cpp:367] inception_3a/1x1/bn1 -> inception_3a/1x1 (in-place)
I0121 17:48:37.368239  1741 net.cpp:122] Setting up inception_3a/1x1/bn1
I0121 17:48:37.368258  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.368263  1741 net.cpp:137] Memory required for data: 571998720
I0121 17:48:37.368275  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/scale1
I0121 17:48:37.368285  1741 net.cpp:84] Creating Layer inception_3a/1x1/scale1
I0121 17:48:37.368291  1741 net.cpp:406] inception_3a/1x1/scale1 <- inception_3a/1x1
I0121 17:48:37.368297  1741 net.cpp:367] inception_3a/1x1/scale1 -> inception_3a/1x1 (in-place)
I0121 17:48:37.368347  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/scale1
I0121 17:48:37.368516  1741 net.cpp:122] Setting up inception_3a/1x1/scale1
I0121 17:48:37.368535  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.368540  1741 net.cpp:137] Memory required for data: 588775936
I0121 17:48:37.368547  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/relu1
I0121 17:48:37.368556  1741 net.cpp:84] Creating Layer inception_3a/1x1/relu1
I0121 17:48:37.368569  1741 net.cpp:406] inception_3a/1x1/relu1 <- inception_3a/1x1
I0121 17:48:37.368578  1741 net.cpp:367] inception_3a/1x1/relu1 -> inception_3a/1x1 (in-place)
I0121 17:48:37.368877  1741 net.cpp:122] Setting up inception_3a/1x1/relu1
I0121 17:48:37.368901  1741 net.cpp:129] Top shape: 128 32 32 32 (4194304)
I0121 17:48:37.368907  1741 net.cpp:137] Memory required for data: 605553152
I0121 17:48:37.368912  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3
I0121 17:48:37.368923  1741 net.cpp:84] Creating Layer inception_3a/3x3
I0121 17:48:37.368934  1741 net.cpp:406] inception_3a/3x3 <- inception_2a/output_inception_2a/output_0_split_1
I0121 17:48:37.368947  1741 net.cpp:380] inception_3a/3x3 -> inception_3a/3x3
I0121 17:48:37.370070  1741 net.cpp:122] Setting up inception_3a/3x3
I0121 17:48:37.370100  1741 net.cpp:129] Top shape: 128 48 32 32 (6291456)
I0121 17:48:37.370105  1741 net.cpp:137] Memory required for data: 630718976
I0121 17:48:37.370115  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/bn1
I0121 17:48:37.370126  1741 net.cpp:84] Creating Layer inception_3a/3x3/bn1
I0121 17:48:37.370133  1741 net.cpp:406] inception_3a/3x3/bn1 <- inception_3a/3x3
I0121 17:48:37.370142  1741 net.cpp:367] inception_3a/3x3/bn1 -> inception_3a/3x3 (in-place)
I0121 17:48:37.370404  1741 net.cpp:122] Setting up inception_3a/3x3/bn1
I0121 17:48:37.370425  1741 net.cpp:129] Top shape: 128 48 32 32 (6291456)
I0121 17:48:37.370430  1741 net.cpp:137] Memory required for data: 655884800
I0121 17:48:37.370448  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/scale1
I0121 17:48:37.370465  1741 net.cpp:84] Creating Layer inception_3a/3x3/scale1
I0121 17:48:37.370470  1741 net.cpp:406] inception_3a/3x3/scale1 <- inception_3a/3x3
I0121 17:48:37.370494  1741 net.cpp:367] inception_3a/3x3/scale1 -> inception_3a/3x3 (in-place)
I0121 17:48:37.370555  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/scale1
I0121 17:48:37.370718  1741 net.cpp:122] Setting up inception_3a/3x3/scale1
I0121 17:48:37.370736  1741 net.cpp:129] Top shape: 128 48 32 32 (6291456)
I0121 17:48:37.370741  1741 net.cpp:137] Memory required for data: 681050624
I0121 17:48:37.370749  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/relu1
I0121 17:48:37.370759  1741 net.cpp:84] Creating Layer inception_3a/3x3/relu1
I0121 17:48:37.370764  1741 net.cpp:406] inception_3a/3x3/relu1 <- inception_3a/3x3
I0121 17:48:37.370772  1741 net.cpp:367] inception_3a/3x3/relu1 -> inception_3a/3x3 (in-place)
I0121 17:48:37.370935  1741 net.cpp:122] Setting up inception_3a/3x3/relu1
I0121 17:48:37.370956  1741 net.cpp:129] Top shape: 128 48 32 32 (6291456)
I0121 17:48:37.370961  1741 net.cpp:137] Memory required for data: 706216448
I0121 17:48:37.370966  1741 layer_factory.hpp:77] Creating layer inception_3a/output
I0121 17:48:37.370973  1741 net.cpp:84] Creating Layer inception_3a/output
I0121 17:48:37.370981  1741 net.cpp:406] inception_3a/output <- inception_3a/1x1
I0121 17:48:37.370987  1741 net.cpp:406] inception_3a/output <- inception_3a/3x3
I0121 17:48:37.370995  1741 net.cpp:380] inception_3a/output -> inception_3a/output
I0121 17:48:37.371037  1741 net.cpp:122] Setting up inception_3a/output
I0121 17:48:37.371058  1741 net.cpp:129] Top shape: 128 80 32 32 (10485760)
I0121 17:48:37.371065  1741 net.cpp:137] Memory required for data: 748159488
I0121 17:48:37.371073  1741 layer_factory.hpp:77] Creating layer inception_3a/output_inception_3a/output_0_split
I0121 17:48:37.371083  1741 net.cpp:84] Creating Layer inception_3a/output_inception_3a/output_0_split
I0121 17:48:37.371093  1741 net.cpp:406] inception_3a/output_inception_3a/output_0_split <- inception_3a/output
I0121 17:48:37.371103  1741 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_0
I0121 17:48:37.371115  1741 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_1
I0121 17:48:37.371176  1741 net.cpp:122] Setting up inception_3a/output_inception_3a/output_0_split
I0121 17:48:37.371198  1741 net.cpp:129] Top shape: 128 80 32 32 (10485760)
I0121 17:48:37.371209  1741 net.cpp:129] Top shape: 128 80 32 32 (10485760)
I0121 17:48:37.371215  1741 net.cpp:137] Memory required for data: 832045568
I0121 17:48:37.371222  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2
I0121 17:48:37.371239  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2
I0121 17:48:37.371249  1741 net.cpp:406] downsample_4/3x3_s2 <- inception_3a/output_inception_3a/output_0_split_0
I0121 17:48:37.371259  1741 net.cpp:380] downsample_4/3x3_s2 -> downsample_4/3x3_s2
I0121 17:48:37.372498  1741 net.cpp:122] Setting up downsample_4/3x3_s2
I0121 17:48:37.372525  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.372530  1741 net.cpp:137] Memory required for data: 842531328
I0121 17:48:37.372539  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/bn1
I0121 17:48:37.372551  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2/bn1
I0121 17:48:37.372566  1741 net.cpp:406] downsample_4/3x3_s2/bn1 <- downsample_4/3x3_s2
I0121 17:48:37.372578  1741 net.cpp:367] downsample_4/3x3_s2/bn1 -> downsample_4/3x3_s2 (in-place)
I0121 17:48:37.372814  1741 net.cpp:122] Setting up downsample_4/3x3_s2/bn1
I0121 17:48:37.372833  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.372843  1741 net.cpp:137] Memory required for data: 853017088
I0121 17:48:37.372856  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/scale1
I0121 17:48:37.372874  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2/scale1
I0121 17:48:37.372882  1741 net.cpp:406] downsample_4/3x3_s2/scale1 <- downsample_4/3x3_s2
I0121 17:48:37.372892  1741 net.cpp:367] downsample_4/3x3_s2/scale1 -> downsample_4/3x3_s2 (in-place)
I0121 17:48:37.372973  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/scale1
I0121 17:48:37.373154  1741 net.cpp:122] Setting up downsample_4/3x3_s2/scale1
I0121 17:48:37.373176  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.373185  1741 net.cpp:137] Memory required for data: 863502848
I0121 17:48:37.373196  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/relu1
I0121 17:48:37.373215  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2/relu1
I0121 17:48:37.373229  1741 net.cpp:406] downsample_4/3x3_s2/relu1 <- downsample_4/3x3_s2
I0121 17:48:37.373240  1741 net.cpp:367] downsample_4/3x3_s2/relu1 -> downsample_4/3x3_s2 (in-place)
I0121 17:48:37.373543  1741 net.cpp:122] Setting up downsample_4/3x3_s2/relu1
I0121 17:48:37.373570  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.373579  1741 net.cpp:137] Memory required for data: 873988608
I0121 17:48:37.373586  1741 layer_factory.hpp:77] Creating layer downsample_4/pool_s2
I0121 17:48:37.373603  1741 net.cpp:84] Creating Layer downsample_4/pool_s2
I0121 17:48:37.373617  1741 net.cpp:406] downsample_4/pool_s2 <- inception_3a/output_inception_3a/output_0_split_1
I0121 17:48:37.373630  1741 net.cpp:380] downsample_4/pool_s2 -> downsample_4/pool_s2
I0121 17:48:37.373734  1741 net.cpp:122] Setting up downsample_4/pool_s2
I0121 17:48:37.373756  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.373785  1741 net.cpp:137] Memory required for data: 884474368
I0121 17:48:37.373795  1741 layer_factory.hpp:77] Creating layer downsample_4/output
I0121 17:48:37.373806  1741 net.cpp:84] Creating Layer downsample_4/output
I0121 17:48:37.373813  1741 net.cpp:406] downsample_4/output <- downsample_4/3x3_s2
I0121 17:48:37.373822  1741 net.cpp:406] downsample_4/output <- downsample_4/pool_s2
I0121 17:48:37.373842  1741 net.cpp:380] downsample_4/output -> downsample_4/output
I0121 17:48:37.373890  1741 net.cpp:122] Setting up downsample_4/output
I0121 17:48:37.373908  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.373916  1741 net.cpp:137] Memory required for data: 905445888
I0121 17:48:37.373922  1741 layer_factory.hpp:77] Creating layer downsample_4/output_downsample_4/output_0_split
I0121 17:48:37.373939  1741 net.cpp:84] Creating Layer downsample_4/output_downsample_4/output_0_split
I0121 17:48:37.373946  1741 net.cpp:406] downsample_4/output_downsample_4/output_0_split <- downsample_4/output
I0121 17:48:37.373961  1741 net.cpp:380] downsample_4/output_downsample_4/output_0_split -> downsample_4/output_downsample_4/output_0_split_0
I0121 17:48:37.373972  1741 net.cpp:380] downsample_4/output_downsample_4/output_0_split -> downsample_4/output_downsample_4/output_0_split_1
I0121 17:48:37.374037  1741 net.cpp:122] Setting up downsample_4/output_downsample_4/output_0_split
I0121 17:48:37.374058  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.374068  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.374073  1741 net.cpp:137] Memory required for data: 947388928
I0121 17:48:37.374084  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1
I0121 17:48:37.374104  1741 net.cpp:84] Creating Layer inception_5a/1x1
I0121 17:48:37.374111  1741 net.cpp:406] inception_5a/1x1 <- downsample_4/output_downsample_4/output_0_split_0
I0121 17:48:37.374121  1741 net.cpp:380] inception_5a/1x1 -> inception_5a/1x1
I0121 17:48:37.375341  1741 net.cpp:122] Setting up inception_5a/1x1
I0121 17:48:37.375367  1741 net.cpp:129] Top shape: 128 112 16 16 (3670016)
I0121 17:48:37.375372  1741 net.cpp:137] Memory required for data: 962068992
I0121 17:48:37.375385  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/bn1
I0121 17:48:37.375412  1741 net.cpp:84] Creating Layer inception_5a/1x1/bn1
I0121 17:48:37.375430  1741 net.cpp:406] inception_5a/1x1/bn1 <- inception_5a/1x1
I0121 17:48:37.375442  1741 net.cpp:367] inception_5a/1x1/bn1 -> inception_5a/1x1 (in-place)
I0121 17:48:37.375671  1741 net.cpp:122] Setting up inception_5a/1x1/bn1
I0121 17:48:37.375690  1741 net.cpp:129] Top shape: 128 112 16 16 (3670016)
I0121 17:48:37.375706  1741 net.cpp:137] Memory required for data: 976749056
I0121 17:48:37.375720  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/scale1
I0121 17:48:37.375730  1741 net.cpp:84] Creating Layer inception_5a/1x1/scale1
I0121 17:48:37.375742  1741 net.cpp:406] inception_5a/1x1/scale1 <- inception_5a/1x1
I0121 17:48:37.375751  1741 net.cpp:367] inception_5a/1x1/scale1 -> inception_5a/1x1 (in-place)
I0121 17:48:37.375811  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/scale1
I0121 17:48:37.375967  1741 net.cpp:122] Setting up inception_5a/1x1/scale1
I0121 17:48:37.375985  1741 net.cpp:129] Top shape: 128 112 16 16 (3670016)
I0121 17:48:37.375989  1741 net.cpp:137] Memory required for data: 991429120
I0121 17:48:37.375998  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/relu1
I0121 17:48:37.376008  1741 net.cpp:84] Creating Layer inception_5a/1x1/relu1
I0121 17:48:37.376021  1741 net.cpp:406] inception_5a/1x1/relu1 <- inception_5a/1x1
I0121 17:48:37.376031  1741 net.cpp:367] inception_5a/1x1/relu1 -> inception_5a/1x1 (in-place)
I0121 17:48:37.376200  1741 net.cpp:122] Setting up inception_5a/1x1/relu1
I0121 17:48:37.376225  1741 net.cpp:129] Top shape: 128 112 16 16 (3670016)
I0121 17:48:37.376231  1741 net.cpp:137] Memory required for data: 1006109184
I0121 17:48:37.376236  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3
I0121 17:48:37.376250  1741 net.cpp:84] Creating Layer inception_5a/3x3
I0121 17:48:37.376266  1741 net.cpp:406] inception_5a/3x3 <- downsample_4/output_downsample_4/output_0_split_1
I0121 17:48:37.376278  1741 net.cpp:380] inception_5a/3x3 -> inception_5a/3x3
I0121 17:48:37.378468  1741 net.cpp:122] Setting up inception_5a/3x3
I0121 17:48:37.378497  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.378504  1741 net.cpp:137] Memory required for data: 1012400640
I0121 17:48:37.378512  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/bn1
I0121 17:48:37.378530  1741 net.cpp:84] Creating Layer inception_5a/3x3/bn1
I0121 17:48:37.378540  1741 net.cpp:406] inception_5a/3x3/bn1 <- inception_5a/3x3
I0121 17:48:37.378562  1741 net.cpp:367] inception_5a/3x3/bn1 -> inception_5a/3x3 (in-place)
I0121 17:48:37.378803  1741 net.cpp:122] Setting up inception_5a/3x3/bn1
I0121 17:48:37.378821  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.378825  1741 net.cpp:137] Memory required for data: 1018692096
I0121 17:48:37.378834  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/scale1
I0121 17:48:37.378844  1741 net.cpp:84] Creating Layer inception_5a/3x3/scale1
I0121 17:48:37.378859  1741 net.cpp:406] inception_5a/3x3/scale1 <- inception_5a/3x3
I0121 17:48:37.378868  1741 net.cpp:367] inception_5a/3x3/scale1 -> inception_5a/3x3 (in-place)
I0121 17:48:37.378962  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/scale1
I0121 17:48:37.379124  1741 net.cpp:122] Setting up inception_5a/3x3/scale1
I0121 17:48:37.379142  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.379148  1741 net.cpp:137] Memory required for data: 1024983552
I0121 17:48:37.379155  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/relu1
I0121 17:48:37.379173  1741 net.cpp:84] Creating Layer inception_5a/3x3/relu1
I0121 17:48:37.379180  1741 net.cpp:406] inception_5a/3x3/relu1 <- inception_5a/3x3
I0121 17:48:37.379194  1741 net.cpp:367] inception_5a/3x3/relu1 -> inception_5a/3x3 (in-place)
I0121 17:48:37.379513  1741 net.cpp:122] Setting up inception_5a/3x3/relu1
I0121 17:48:37.379536  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.379541  1741 net.cpp:137] Memory required for data: 1031275008
I0121 17:48:37.379547  1741 layer_factory.hpp:77] Creating layer inception_5a/output
I0121 17:48:37.379555  1741 net.cpp:84] Creating Layer inception_5a/output
I0121 17:48:37.379564  1741 net.cpp:406] inception_5a/output <- inception_5a/1x1
I0121 17:48:37.379571  1741 net.cpp:406] inception_5a/output <- inception_5a/3x3
I0121 17:48:37.379585  1741 net.cpp:380] inception_5a/output -> inception_5a/output
I0121 17:48:37.379640  1741 net.cpp:122] Setting up inception_5a/output
I0121 17:48:37.379663  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.379675  1741 net.cpp:137] Memory required for data: 1052246528
I0121 17:48:37.379683  1741 layer_factory.hpp:77] Creating layer inception_5a/output_inception_5a/output_0_split
I0121 17:48:37.379693  1741 net.cpp:84] Creating Layer inception_5a/output_inception_5a/output_0_split
I0121 17:48:37.379707  1741 net.cpp:406] inception_5a/output_inception_5a/output_0_split <- inception_5a/output
I0121 17:48:37.379719  1741 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_0
I0121 17:48:37.379747  1741 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_1
I0121 17:48:37.379833  1741 net.cpp:122] Setting up inception_5a/output_inception_5a/output_0_split
I0121 17:48:37.379853  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.379859  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.379863  1741 net.cpp:137] Memory required for data: 1094189568
I0121 17:48:37.379871  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1
I0121 17:48:37.379899  1741 net.cpp:84] Creating Layer inception_6a/1x1
I0121 17:48:37.379916  1741 net.cpp:406] inception_6a/1x1 <- inception_5a/output_inception_5a/output_0_split_0
I0121 17:48:37.379928  1741 net.cpp:380] inception_6a/1x1 -> inception_6a/1x1
I0121 17:48:37.381588  1741 net.cpp:122] Setting up inception_6a/1x1
I0121 17:48:37.381615  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.381620  1741 net.cpp:137] Memory required for data: 1106772480
I0121 17:48:37.381629  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/bn1
I0121 17:48:37.381649  1741 net.cpp:84] Creating Layer inception_6a/1x1/bn1
I0121 17:48:37.381659  1741 net.cpp:406] inception_6a/1x1/bn1 <- inception_6a/1x1
I0121 17:48:37.381682  1741 net.cpp:367] inception_6a/1x1/bn1 -> inception_6a/1x1 (in-place)
I0121 17:48:37.381956  1741 net.cpp:122] Setting up inception_6a/1x1/bn1
I0121 17:48:37.381975  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.381981  1741 net.cpp:137] Memory required for data: 1119355392
I0121 17:48:37.381991  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/scale1
I0121 17:48:37.381999  1741 net.cpp:84] Creating Layer inception_6a/1x1/scale1
I0121 17:48:37.382006  1741 net.cpp:406] inception_6a/1x1/scale1 <- inception_6a/1x1
I0121 17:48:37.382014  1741 net.cpp:367] inception_6a/1x1/scale1 -> inception_6a/1x1 (in-place)
I0121 17:48:37.382083  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/scale1
I0121 17:48:37.382247  1741 net.cpp:122] Setting up inception_6a/1x1/scale1
I0121 17:48:37.382267  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.382277  1741 net.cpp:137] Memory required for data: 1131938304
I0121 17:48:37.382287  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/relu1
I0121 17:48:37.382305  1741 net.cpp:84] Creating Layer inception_6a/1x1/relu1
I0121 17:48:37.382319  1741 net.cpp:406] inception_6a/1x1/relu1 <- inception_6a/1x1
I0121 17:48:37.382331  1741 net.cpp:367] inception_6a/1x1/relu1 -> inception_6a/1x1 (in-place)
I0121 17:48:37.382619  1741 net.cpp:122] Setting up inception_6a/1x1/relu1
I0121 17:48:37.382647  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.382654  1741 net.cpp:137] Memory required for data: 1144521216
I0121 17:48:37.382663  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3
I0121 17:48:37.382683  1741 net.cpp:84] Creating Layer inception_6a/3x3
I0121 17:48:37.382714  1741 net.cpp:406] inception_6a/3x3 <- inception_5a/output_inception_5a/output_0_split_1
I0121 17:48:37.382740  1741 net.cpp:380] inception_6a/3x3 -> inception_6a/3x3
I0121 17:48:37.384187  1741 net.cpp:122] Setting up inception_6a/3x3
I0121 17:48:37.384217  1741 net.cpp:129] Top shape: 128 64 16 16 (2097152)
I0121 17:48:37.384224  1741 net.cpp:137] Memory required for data: 1152909824
I0121 17:48:37.384271  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/bn1
I0121 17:48:37.384299  1741 net.cpp:84] Creating Layer inception_6a/3x3/bn1
I0121 17:48:37.384308  1741 net.cpp:406] inception_6a/3x3/bn1 <- inception_6a/3x3
I0121 17:48:37.384331  1741 net.cpp:367] inception_6a/3x3/bn1 -> inception_6a/3x3 (in-place)
I0121 17:48:37.384568  1741 net.cpp:122] Setting up inception_6a/3x3/bn1
I0121 17:48:37.384589  1741 net.cpp:129] Top shape: 128 64 16 16 (2097152)
I0121 17:48:37.384598  1741 net.cpp:137] Memory required for data: 1161298432
I0121 17:48:37.384610  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/scale1
I0121 17:48:37.384630  1741 net.cpp:84] Creating Layer inception_6a/3x3/scale1
I0121 17:48:37.384640  1741 net.cpp:406] inception_6a/3x3/scale1 <- inception_6a/3x3
I0121 17:48:37.384649  1741 net.cpp:367] inception_6a/3x3/scale1 -> inception_6a/3x3 (in-place)
I0121 17:48:37.384743  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/scale1
I0121 17:48:37.384914  1741 net.cpp:122] Setting up inception_6a/3x3/scale1
I0121 17:48:37.384934  1741 net.cpp:129] Top shape: 128 64 16 16 (2097152)
I0121 17:48:37.384941  1741 net.cpp:137] Memory required for data: 1169687040
I0121 17:48:37.384953  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/relu1
I0121 17:48:37.384979  1741 net.cpp:84] Creating Layer inception_6a/3x3/relu1
I0121 17:48:37.384989  1741 net.cpp:406] inception_6a/3x3/relu1 <- inception_6a/3x3
I0121 17:48:37.384999  1741 net.cpp:367] inception_6a/3x3/relu1 -> inception_6a/3x3 (in-place)
I0121 17:48:37.385172  1741 net.cpp:122] Setting up inception_6a/3x3/relu1
I0121 17:48:37.385195  1741 net.cpp:129] Top shape: 128 64 16 16 (2097152)
I0121 17:48:37.385203  1741 net.cpp:137] Memory required for data: 1178075648
I0121 17:48:37.385210  1741 layer_factory.hpp:77] Creating layer inception_6a/output
I0121 17:48:37.385221  1741 net.cpp:84] Creating Layer inception_6a/output
I0121 17:48:37.385236  1741 net.cpp:406] inception_6a/output <- inception_6a/1x1
I0121 17:48:37.385246  1741 net.cpp:406] inception_6a/output <- inception_6a/3x3
I0121 17:48:37.385255  1741 net.cpp:380] inception_6a/output -> inception_6a/output
I0121 17:48:37.385300  1741 net.cpp:122] Setting up inception_6a/output
I0121 17:48:37.385319  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.385327  1741 net.cpp:137] Memory required for data: 1199047168
I0121 17:48:37.385334  1741 layer_factory.hpp:77] Creating layer inception_6a/output_inception_6a/output_0_split
I0121 17:48:37.385344  1741 net.cpp:84] Creating Layer inception_6a/output_inception_6a/output_0_split
I0121 17:48:37.385359  1741 net.cpp:406] inception_6a/output_inception_6a/output_0_split <- inception_6a/output
I0121 17:48:37.385375  1741 net.cpp:380] inception_6a/output_inception_6a/output_0_split -> inception_6a/output_inception_6a/output_0_split_0
I0121 17:48:37.385388  1741 net.cpp:380] inception_6a/output_inception_6a/output_0_split -> inception_6a/output_inception_6a/output_0_split_1
I0121 17:48:37.385457  1741 net.cpp:122] Setting up inception_6a/output_inception_6a/output_0_split
I0121 17:48:37.385478  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.385488  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.385494  1741 net.cpp:137] Memory required for data: 1240990208
I0121 17:48:37.385509  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1
I0121 17:48:37.385529  1741 net.cpp:84] Creating Layer inception_7a/1x1
I0121 17:48:37.385545  1741 net.cpp:406] inception_7a/1x1 <- inception_6a/output_inception_6a/output_0_split_0
I0121 17:48:37.385556  1741 net.cpp:380] inception_7a/1x1 -> inception_7a/1x1
I0121 17:48:37.386636  1741 net.cpp:122] Setting up inception_7a/1x1
I0121 17:48:37.386662  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.386669  1741 net.cpp:137] Memory required for data: 1251475968
I0121 17:48:37.386680  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/bn1
I0121 17:48:37.386740  1741 net.cpp:84] Creating Layer inception_7a/1x1/bn1
I0121 17:48:37.386757  1741 net.cpp:406] inception_7a/1x1/bn1 <- inception_7a/1x1
I0121 17:48:37.386775  1741 net.cpp:367] inception_7a/1x1/bn1 -> inception_7a/1x1 (in-place)
I0121 17:48:37.387004  1741 net.cpp:122] Setting up inception_7a/1x1/bn1
I0121 17:48:37.387023  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.387032  1741 net.cpp:137] Memory required for data: 1261961728
I0121 17:48:37.387046  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/scale1
I0121 17:48:37.387071  1741 net.cpp:84] Creating Layer inception_7a/1x1/scale1
I0121 17:48:37.387080  1741 net.cpp:406] inception_7a/1x1/scale1 <- inception_7a/1x1
I0121 17:48:37.387091  1741 net.cpp:367] inception_7a/1x1/scale1 -> inception_7a/1x1 (in-place)
I0121 17:48:37.387156  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/scale1
I0121 17:48:37.387311  1741 net.cpp:122] Setting up inception_7a/1x1/scale1
I0121 17:48:37.387331  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.387337  1741 net.cpp:137] Memory required for data: 1272447488
I0121 17:48:37.387351  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/relu1
I0121 17:48:37.387368  1741 net.cpp:84] Creating Layer inception_7a/1x1/relu1
I0121 17:48:37.387377  1741 net.cpp:406] inception_7a/1x1/relu1 <- inception_7a/1x1
I0121 17:48:37.387389  1741 net.cpp:367] inception_7a/1x1/relu1 -> inception_7a/1x1 (in-place)
I0121 17:48:37.387691  1741 net.cpp:122] Setting up inception_7a/1x1/relu1
I0121 17:48:37.387720  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.387728  1741 net.cpp:137] Memory required for data: 1282933248
I0121 17:48:37.387735  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3
I0121 17:48:37.387753  1741 net.cpp:84] Creating Layer inception_7a/3x3
I0121 17:48:37.387766  1741 net.cpp:406] inception_7a/3x3 <- inception_6a/output_inception_6a/output_0_split_1
I0121 17:48:37.387779  1741 net.cpp:380] inception_7a/3x3 -> inception_7a/3x3
I0121 17:48:37.390136  1741 net.cpp:122] Setting up inception_7a/3x3
I0121 17:48:37.390164  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.390169  1741 net.cpp:137] Memory required for data: 1293419008
I0121 17:48:37.390182  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/bn1
I0121 17:48:37.390208  1741 net.cpp:84] Creating Layer inception_7a/3x3/bn1
I0121 17:48:37.390225  1741 net.cpp:406] inception_7a/3x3/bn1 <- inception_7a/3x3
I0121 17:48:37.390236  1741 net.cpp:367] inception_7a/3x3/bn1 -> inception_7a/3x3 (in-place)
I0121 17:48:37.390476  1741 net.cpp:122] Setting up inception_7a/3x3/bn1
I0121 17:48:37.390494  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.390501  1741 net.cpp:137] Memory required for data: 1303904768
I0121 17:48:37.390517  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/scale1
I0121 17:48:37.390548  1741 net.cpp:84] Creating Layer inception_7a/3x3/scale1
I0121 17:48:37.390563  1741 net.cpp:406] inception_7a/3x3/scale1 <- inception_7a/3x3
I0121 17:48:37.390578  1741 net.cpp:367] inception_7a/3x3/scale1 -> inception_7a/3x3 (in-place)
I0121 17:48:37.390643  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/scale1
I0121 17:48:37.390803  1741 net.cpp:122] Setting up inception_7a/3x3/scale1
I0121 17:48:37.390823  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.390832  1741 net.cpp:137] Memory required for data: 1314390528
I0121 17:48:37.390844  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/relu1
I0121 17:48:37.390866  1741 net.cpp:84] Creating Layer inception_7a/3x3/relu1
I0121 17:48:37.390873  1741 net.cpp:406] inception_7a/3x3/relu1 <- inception_7a/3x3
I0121 17:48:37.390898  1741 net.cpp:367] inception_7a/3x3/relu1 -> inception_7a/3x3 (in-place)
I0121 17:48:37.391085  1741 net.cpp:122] Setting up inception_7a/3x3/relu1
I0121 17:48:37.391106  1741 net.cpp:129] Top shape: 128 80 16 16 (2621440)
I0121 17:48:37.391111  1741 net.cpp:137] Memory required for data: 1324876288
I0121 17:48:37.391119  1741 layer_factory.hpp:77] Creating layer inception_7a/output
I0121 17:48:37.391161  1741 net.cpp:84] Creating Layer inception_7a/output
I0121 17:48:37.391178  1741 net.cpp:406] inception_7a/output <- inception_7a/1x1
I0121 17:48:37.391188  1741 net.cpp:406] inception_7a/output <- inception_7a/3x3
I0121 17:48:37.391199  1741 net.cpp:380] inception_7a/output -> inception_7a/output
I0121 17:48:37.391255  1741 net.cpp:122] Setting up inception_7a/output
I0121 17:48:37.391274  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.391283  1741 net.cpp:137] Memory required for data: 1345847808
I0121 17:48:37.391289  1741 layer_factory.hpp:77] Creating layer inception_7a/output_inception_7a/output_0_split
I0121 17:48:37.391312  1741 net.cpp:84] Creating Layer inception_7a/output_inception_7a/output_0_split
I0121 17:48:37.391320  1741 net.cpp:406] inception_7a/output_inception_7a/output_0_split <- inception_7a/output
I0121 17:48:37.391360  1741 net.cpp:380] inception_7a/output_inception_7a/output_0_split -> inception_7a/output_inception_7a/output_0_split_0
I0121 17:48:37.391391  1741 net.cpp:380] inception_7a/output_inception_7a/output_0_split -> inception_7a/output_inception_7a/output_0_split_1
I0121 17:48:37.391485  1741 net.cpp:122] Setting up inception_7a/output_inception_7a/output_0_split
I0121 17:48:37.391503  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.391510  1741 net.cpp:129] Top shape: 128 160 16 16 (5242880)
I0121 17:48:37.391515  1741 net.cpp:137] Memory required for data: 1387790848
I0121 17:48:37.391530  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1
I0121 17:48:37.391551  1741 net.cpp:84] Creating Layer inception_8a/1x1
I0121 17:48:37.391564  1741 net.cpp:406] inception_8a/1x1 <- inception_7a/output_inception_7a/output_0_split_0
I0121 17:48:37.391582  1741 net.cpp:380] inception_8a/1x1 -> inception_8a/1x1
I0121 17:48:37.392606  1741 net.cpp:122] Setting up inception_8a/1x1
I0121 17:48:37.392632  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.392637  1741 net.cpp:137] Memory required for data: 1394082304
I0121 17:48:37.392647  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/bn1
I0121 17:48:37.392681  1741 net.cpp:84] Creating Layer inception_8a/1x1/bn1
I0121 17:48:37.392719  1741 net.cpp:406] inception_8a/1x1/bn1 <- inception_8a/1x1
I0121 17:48:37.392758  1741 net.cpp:367] inception_8a/1x1/bn1 -> inception_8a/1x1 (in-place)
I0121 17:48:37.393029  1741 net.cpp:122] Setting up inception_8a/1x1/bn1
I0121 17:48:37.393049  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.393054  1741 net.cpp:137] Memory required for data: 1400373760
I0121 17:48:37.393066  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/scale1
I0121 17:48:37.393082  1741 net.cpp:84] Creating Layer inception_8a/1x1/scale1
I0121 17:48:37.393091  1741 net.cpp:406] inception_8a/1x1/scale1 <- inception_8a/1x1
I0121 17:48:37.393110  1741 net.cpp:367] inception_8a/1x1/scale1 -> inception_8a/1x1 (in-place)
I0121 17:48:37.393174  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/scale1
I0121 17:48:37.393335  1741 net.cpp:122] Setting up inception_8a/1x1/scale1
I0121 17:48:37.393352  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.393357  1741 net.cpp:137] Memory required for data: 1406665216
I0121 17:48:37.393365  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/relu1
I0121 17:48:37.393383  1741 net.cpp:84] Creating Layer inception_8a/1x1/relu1
I0121 17:48:37.393390  1741 net.cpp:406] inception_8a/1x1/relu1 <- inception_8a/1x1
I0121 17:48:37.393412  1741 net.cpp:367] inception_8a/1x1/relu1 -> inception_8a/1x1 (in-place)
I0121 17:48:37.393734  1741 net.cpp:122] Setting up inception_8a/1x1/relu1
I0121 17:48:37.393759  1741 net.cpp:129] Top shape: 128 48 16 16 (1572864)
I0121 17:48:37.393784  1741 net.cpp:137] Memory required for data: 1412956672
I0121 17:48:37.393800  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3
I0121 17:48:37.393817  1741 net.cpp:84] Creating Layer inception_8a/3x3
I0121 17:48:37.393856  1741 net.cpp:406] inception_8a/3x3 <- inception_7a/output_inception_7a/output_0_split_1
I0121 17:48:37.393906  1741 net.cpp:380] inception_8a/3x3 -> inception_8a/3x3
I0121 17:48:37.395642  1741 net.cpp:122] Setting up inception_8a/3x3
I0121 17:48:37.395668  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.395674  1741 net.cpp:137] Memory required for data: 1425539584
I0121 17:48:37.395684  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/bn1
I0121 17:48:37.395695  1741 net.cpp:84] Creating Layer inception_8a/3x3/bn1
I0121 17:48:37.395711  1741 net.cpp:406] inception_8a/3x3/bn1 <- inception_8a/3x3
I0121 17:48:37.395728  1741 net.cpp:367] inception_8a/3x3/bn1 -> inception_8a/3x3 (in-place)
I0121 17:48:37.395972  1741 net.cpp:122] Setting up inception_8a/3x3/bn1
I0121 17:48:37.395989  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.395994  1741 net.cpp:137] Memory required for data: 1438122496
I0121 17:48:37.396004  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/scale1
I0121 17:48:37.396014  1741 net.cpp:84] Creating Layer inception_8a/3x3/scale1
I0121 17:48:37.396030  1741 net.cpp:406] inception_8a/3x3/scale1 <- inception_8a/3x3
I0121 17:48:37.396040  1741 net.cpp:367] inception_8a/3x3/scale1 -> inception_8a/3x3 (in-place)
I0121 17:48:37.396100  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/scale1
I0121 17:48:37.396272  1741 net.cpp:122] Setting up inception_8a/3x3/scale1
I0121 17:48:37.396289  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.396294  1741 net.cpp:137] Memory required for data: 1450705408
I0121 17:48:37.396303  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/relu1
I0121 17:48:37.396311  1741 net.cpp:84] Creating Layer inception_8a/3x3/relu1
I0121 17:48:37.396317  1741 net.cpp:406] inception_8a/3x3/relu1 <- inception_8a/3x3
I0121 17:48:37.396323  1741 net.cpp:367] inception_8a/3x3/relu1 -> inception_8a/3x3 (in-place)
I0121 17:48:37.396488  1741 net.cpp:122] Setting up inception_8a/3x3/relu1
I0121 17:48:37.396507  1741 net.cpp:129] Top shape: 128 96 16 16 (3145728)
I0121 17:48:37.396512  1741 net.cpp:137] Memory required for data: 1463288320
I0121 17:48:37.396517  1741 layer_factory.hpp:77] Creating layer inception_8a/output
I0121 17:48:37.396525  1741 net.cpp:84] Creating Layer inception_8a/output
I0121 17:48:37.396533  1741 net.cpp:406] inception_8a/output <- inception_8a/1x1
I0121 17:48:37.396538  1741 net.cpp:406] inception_8a/output <- inception_8a/3x3
I0121 17:48:37.396553  1741 net.cpp:380] inception_8a/output -> inception_8a/output
I0121 17:48:37.396595  1741 net.cpp:122] Setting up inception_8a/output
I0121 17:48:37.396615  1741 net.cpp:129] Top shape: 128 144 16 16 (4718592)
I0121 17:48:37.396622  1741 net.cpp:137] Memory required for data: 1482162688
I0121 17:48:37.396639  1741 layer_factory.hpp:77] Creating layer inception_8a/output_inception_8a/output_0_split
I0121 17:48:37.396653  1741 net.cpp:84] Creating Layer inception_8a/output_inception_8a/output_0_split
I0121 17:48:37.396661  1741 net.cpp:406] inception_8a/output_inception_8a/output_0_split <- inception_8a/output
I0121 17:48:37.396670  1741 net.cpp:380] inception_8a/output_inception_8a/output_0_split -> inception_8a/output_inception_8a/output_0_split_0
I0121 17:48:37.396713  1741 net.cpp:380] inception_8a/output_inception_8a/output_0_split -> inception_8a/output_inception_8a/output_0_split_1
I0121 17:48:37.396800  1741 net.cpp:122] Setting up inception_8a/output_inception_8a/output_0_split
I0121 17:48:37.396816  1741 net.cpp:129] Top shape: 128 144 16 16 (4718592)
I0121 17:48:37.396822  1741 net.cpp:129] Top shape: 128 144 16 16 (4718592)
I0121 17:48:37.396826  1741 net.cpp:137] Memory required for data: 1519911424
I0121 17:48:37.396832  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2
I0121 17:48:37.396845  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2
I0121 17:48:37.396858  1741 net.cpp:406] downsample_9/3x3_s2 <- inception_8a/output_inception_8a/output_0_split_0
I0121 17:48:37.396875  1741 net.cpp:380] downsample_9/3x3_s2 -> downsample_9/3x3_s2
I0121 17:48:37.399399  1741 net.cpp:122] Setting up downsample_9/3x3_s2
I0121 17:48:37.399425  1741 net.cpp:129] Top shape: 128 96 8 8 (786432)
I0121 17:48:37.399430  1741 net.cpp:137] Memory required for data: 1523057152
I0121 17:48:37.399443  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/bn1
I0121 17:48:37.399463  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2/bn1
I0121 17:48:37.399473  1741 net.cpp:406] downsample_9/3x3_s2/bn1 <- downsample_9/3x3_s2
I0121 17:48:37.399487  1741 net.cpp:367] downsample_9/3x3_s2/bn1 -> downsample_9/3x3_s2 (in-place)
I0121 17:48:37.399749  1741 net.cpp:122] Setting up downsample_9/3x3_s2/bn1
I0121 17:48:37.399767  1741 net.cpp:129] Top shape: 128 96 8 8 (786432)
I0121 17:48:37.399772  1741 net.cpp:137] Memory required for data: 1526202880
I0121 17:48:37.399781  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/scale1
I0121 17:48:37.399791  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2/scale1
I0121 17:48:37.399798  1741 net.cpp:406] downsample_9/3x3_s2/scale1 <- downsample_9/3x3_s2
I0121 17:48:37.399808  1741 net.cpp:367] downsample_9/3x3_s2/scale1 -> downsample_9/3x3_s2 (in-place)
I0121 17:48:37.399883  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/scale1
I0121 17:48:37.400066  1741 net.cpp:122] Setting up downsample_9/3x3_s2/scale1
I0121 17:48:37.400087  1741 net.cpp:129] Top shape: 128 96 8 8 (786432)
I0121 17:48:37.400094  1741 net.cpp:137] Memory required for data: 1529348608
I0121 17:48:37.400106  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/relu1
I0121 17:48:37.400126  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2/relu1
I0121 17:48:37.400136  1741 net.cpp:406] downsample_9/3x3_s2/relu1 <- downsample_9/3x3_s2
I0121 17:48:37.400144  1741 net.cpp:367] downsample_9/3x3_s2/relu1 -> downsample_9/3x3_s2 (in-place)
I0121 17:48:37.400604  1741 net.cpp:122] Setting up downsample_9/3x3_s2/relu1
I0121 17:48:37.400631  1741 net.cpp:129] Top shape: 128 96 8 8 (786432)
I0121 17:48:37.400638  1741 net.cpp:137] Memory required for data: 1532494336
I0121 17:48:37.400643  1741 layer_factory.hpp:77] Creating layer downsample_9/pool_s2
I0121 17:48:37.400653  1741 net.cpp:84] Creating Layer downsample_9/pool_s2
I0121 17:48:37.400668  1741 net.cpp:406] downsample_9/pool_s2 <- inception_8a/output_inception_8a/output_0_split_1
I0121 17:48:37.400682  1741 net.cpp:380] downsample_9/pool_s2 -> downsample_9/pool_s2
I0121 17:48:37.400754  1741 net.cpp:122] Setting up downsample_9/pool_s2
I0121 17:48:37.400771  1741 net.cpp:129] Top shape: 128 144 8 8 (1179648)
I0121 17:48:37.400776  1741 net.cpp:137] Memory required for data: 1537212928
I0121 17:48:37.400782  1741 layer_factory.hpp:77] Creating layer downsample_9/output
I0121 17:48:37.400789  1741 net.cpp:84] Creating Layer downsample_9/output
I0121 17:48:37.400796  1741 net.cpp:406] downsample_9/output <- downsample_9/3x3_s2
I0121 17:48:37.400801  1741 net.cpp:406] downsample_9/output <- downsample_9/pool_s2
I0121 17:48:37.400815  1741 net.cpp:380] downsample_9/output -> downsample_9/output
I0121 17:48:37.400861  1741 net.cpp:122] Setting up downsample_9/output
I0121 17:48:37.400884  1741 net.cpp:129] Top shape: 128 240 8 8 (1966080)
I0121 17:48:37.400892  1741 net.cpp:137] Memory required for data: 1545077248
I0121 17:48:37.400900  1741 layer_factory.hpp:77] Creating layer downsample_9/output_downsample_9/output_0_split
I0121 17:48:37.400913  1741 net.cpp:84] Creating Layer downsample_9/output_downsample_9/output_0_split
I0121 17:48:37.400919  1741 net.cpp:406] downsample_9/output_downsample_9/output_0_split <- downsample_9/output
I0121 17:48:37.400929  1741 net.cpp:380] downsample_9/output_downsample_9/output_0_split -> downsample_9/output_downsample_9/output_0_split_0
I0121 17:48:37.400966  1741 net.cpp:380] downsample_9/output_downsample_9/output_0_split -> downsample_9/output_downsample_9/output_0_split_1
I0121 17:48:37.401060  1741 net.cpp:122] Setting up downsample_9/output_downsample_9/output_0_split
I0121 17:48:37.401080  1741 net.cpp:129] Top shape: 128 240 8 8 (1966080)
I0121 17:48:37.401098  1741 net.cpp:129] Top shape: 128 240 8 8 (1966080)
I0121 17:48:37.401104  1741 net.cpp:137] Memory required for data: 1560805888
I0121 17:48:37.401109  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1
I0121 17:48:37.401132  1741 net.cpp:84] Creating Layer inception_10a/1x1
I0121 17:48:37.401166  1741 net.cpp:406] inception_10a/1x1 <- downsample_9/output_downsample_9/output_0_split_0
I0121 17:48:37.401208  1741 net.cpp:380] inception_10a/1x1 -> inception_10a/1x1
I0121 17:48:37.403466  1741 net.cpp:122] Setting up inception_10a/1x1
I0121 17:48:37.403497  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.403506  1741 net.cpp:137] Memory required for data: 1566573056
I0121 17:48:37.403519  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/bn1
I0121 17:48:37.403535  1741 net.cpp:84] Creating Layer inception_10a/1x1/bn1
I0121 17:48:37.403551  1741 net.cpp:406] inception_10a/1x1/bn1 <- inception_10a/1x1
I0121 17:48:37.403565  1741 net.cpp:367] inception_10a/1x1/bn1 -> inception_10a/1x1 (in-place)
I0121 17:48:37.403834  1741 net.cpp:122] Setting up inception_10a/1x1/bn1
I0121 17:48:37.403854  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.403861  1741 net.cpp:137] Memory required for data: 1572340224
I0121 17:48:37.403875  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/scale1
I0121 17:48:37.403894  1741 net.cpp:84] Creating Layer inception_10a/1x1/scale1
I0121 17:48:37.403903  1741 net.cpp:406] inception_10a/1x1/scale1 <- inception_10a/1x1
I0121 17:48:37.403915  1741 net.cpp:367] inception_10a/1x1/scale1 -> inception_10a/1x1 (in-place)
I0121 17:48:37.403985  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/scale1
I0121 17:48:37.404156  1741 net.cpp:122] Setting up inception_10a/1x1/scale1
I0121 17:48:37.404175  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.404183  1741 net.cpp:137] Memory required for data: 1578107392
I0121 17:48:37.404196  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/relu1
I0121 17:48:37.404218  1741 net.cpp:84] Creating Layer inception_10a/1x1/relu1
I0121 17:48:37.404227  1741 net.cpp:406] inception_10a/1x1/relu1 <- inception_10a/1x1
I0121 17:48:37.404239  1741 net.cpp:367] inception_10a/1x1/relu1 -> inception_10a/1x1 (in-place)
I0121 17:48:37.404402  1741 net.cpp:122] Setting up inception_10a/1x1/relu1
I0121 17:48:37.404423  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.404431  1741 net.cpp:137] Memory required for data: 1583874560
I0121 17:48:37.404438  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3
I0121 17:48:37.404456  1741 net.cpp:84] Creating Layer inception_10a/3x3
I0121 17:48:37.404471  1741 net.cpp:406] inception_10a/3x3 <- downsample_9/output_downsample_9/output_0_split_1
I0121 17:48:37.404484  1741 net.cpp:380] inception_10a/3x3 -> inception_10a/3x3
I0121 17:48:37.408319  1741 net.cpp:122] Setting up inception_10a/3x3
I0121 17:48:37.408347  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.408354  1741 net.cpp:137] Memory required for data: 1589117440
I0121 17:48:37.408365  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/bn1
I0121 17:48:37.408392  1741 net.cpp:84] Creating Layer inception_10a/3x3/bn1
I0121 17:48:37.408411  1741 net.cpp:406] inception_10a/3x3/bn1 <- inception_10a/3x3
I0121 17:48:37.408426  1741 net.cpp:367] inception_10a/3x3/bn1 -> inception_10a/3x3 (in-place)
I0121 17:48:37.408695  1741 net.cpp:122] Setting up inception_10a/3x3/bn1
I0121 17:48:37.408715  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.408720  1741 net.cpp:137] Memory required for data: 1594360320
I0121 17:48:37.408732  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/scale1
I0121 17:48:37.408740  1741 net.cpp:84] Creating Layer inception_10a/3x3/scale1
I0121 17:48:37.408747  1741 net.cpp:406] inception_10a/3x3/scale1 <- inception_10a/3x3
I0121 17:48:37.408756  1741 net.cpp:367] inception_10a/3x3/scale1 -> inception_10a/3x3 (in-place)
I0121 17:48:37.408833  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/scale1
I0121 17:48:37.409041  1741 net.cpp:122] Setting up inception_10a/3x3/scale1
I0121 17:48:37.409060  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.409065  1741 net.cpp:137] Memory required for data: 1599603200
I0121 17:48:37.409075  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/relu1
I0121 17:48:37.409085  1741 net.cpp:84] Creating Layer inception_10a/3x3/relu1
I0121 17:48:37.409096  1741 net.cpp:406] inception_10a/3x3/relu1 <- inception_10a/3x3
I0121 17:48:37.409106  1741 net.cpp:367] inception_10a/3x3/relu1 -> inception_10a/3x3 (in-place)
I0121 17:48:37.409425  1741 net.cpp:122] Setting up inception_10a/3x3/relu1
I0121 17:48:37.409451  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.409456  1741 net.cpp:137] Memory required for data: 1604846080
I0121 17:48:37.409461  1741 layer_factory.hpp:77] Creating layer inception_10a/output
I0121 17:48:37.409469  1741 net.cpp:84] Creating Layer inception_10a/output
I0121 17:48:37.409476  1741 net.cpp:406] inception_10a/output <- inception_10a/1x1
I0121 17:48:37.409482  1741 net.cpp:406] inception_10a/output <- inception_10a/3x3
I0121 17:48:37.409502  1741 net.cpp:380] inception_10a/output -> inception_10a/output
I0121 17:48:37.409549  1741 net.cpp:122] Setting up inception_10a/output
I0121 17:48:37.409588  1741 net.cpp:129] Top shape: 128 336 8 8 (2752512)
I0121 17:48:37.409615  1741 net.cpp:137] Memory required for data: 1615856128
I0121 17:48:37.409644  1741 layer_factory.hpp:77] Creating layer inception_10a/output_inception_10a/output_0_split
I0121 17:48:37.409670  1741 net.cpp:84] Creating Layer inception_10a/output_inception_10a/output_0_split
I0121 17:48:37.409699  1741 net.cpp:406] inception_10a/output_inception_10a/output_0_split <- inception_10a/output
I0121 17:48:37.409721  1741 net.cpp:380] inception_10a/output_inception_10a/output_0_split -> inception_10a/output_inception_10a/output_0_split_0
I0121 17:48:37.409734  1741 net.cpp:380] inception_10a/output_inception_10a/output_0_split -> inception_10a/output_inception_10a/output_0_split_1
I0121 17:48:37.409834  1741 net.cpp:122] Setting up inception_10a/output_inception_10a/output_0_split
I0121 17:48:37.409858  1741 net.cpp:129] Top shape: 128 336 8 8 (2752512)
I0121 17:48:37.409869  1741 net.cpp:129] Top shape: 128 336 8 8 (2752512)
I0121 17:48:37.409874  1741 net.cpp:137] Memory required for data: 1637876224
I0121 17:48:37.409885  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1
I0121 17:48:37.409925  1741 net.cpp:84] Creating Layer inception_11a/1x1
I0121 17:48:37.409955  1741 net.cpp:406] inception_11a/1x1 <- inception_10a/output_inception_10a/output_0_split_0
I0121 17:48:37.409974  1741 net.cpp:380] inception_11a/1x1 -> inception_11a/1x1
I0121 17:48:37.411280  1741 net.cpp:122] Setting up inception_11a/1x1
I0121 17:48:37.411309  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.411317  1741 net.cpp:137] Memory required for data: 1643643392
I0121 17:48:37.411330  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/bn1
I0121 17:48:37.411348  1741 net.cpp:84] Creating Layer inception_11a/1x1/bn1
I0121 17:48:37.411365  1741 net.cpp:406] inception_11a/1x1/bn1 <- inception_11a/1x1
I0121 17:48:37.411379  1741 net.cpp:367] inception_11a/1x1/bn1 -> inception_11a/1x1 (in-place)
I0121 17:48:37.411654  1741 net.cpp:122] Setting up inception_11a/1x1/bn1
I0121 17:48:37.411674  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.411679  1741 net.cpp:137] Memory required for data: 1649410560
I0121 17:48:37.411695  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/scale1
I0121 17:48:37.411715  1741 net.cpp:84] Creating Layer inception_11a/1x1/scale1
I0121 17:48:37.411727  1741 net.cpp:406] inception_11a/1x1/scale1 <- inception_11a/1x1
I0121 17:48:37.411738  1741 net.cpp:367] inception_11a/1x1/scale1 -> inception_11a/1x1 (in-place)
I0121 17:48:37.411849  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/scale1
I0121 17:48:37.412041  1741 net.cpp:122] Setting up inception_11a/1x1/scale1
I0121 17:48:37.412078  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.412086  1741 net.cpp:137] Memory required for data: 1655177728
I0121 17:48:37.412098  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/relu1
I0121 17:48:37.412111  1741 net.cpp:84] Creating Layer inception_11a/1x1/relu1
I0121 17:48:37.412120  1741 net.cpp:406] inception_11a/1x1/relu1 <- inception_11a/1x1
I0121 17:48:37.412133  1741 net.cpp:367] inception_11a/1x1/relu1 -> inception_11a/1x1 (in-place)
I0121 17:48:37.412444  1741 net.cpp:122] Setting up inception_11a/1x1/relu1
I0121 17:48:37.412470  1741 net.cpp:129] Top shape: 128 176 8 8 (1441792)
I0121 17:48:37.412480  1741 net.cpp:137] Memory required for data: 1660944896
I0121 17:48:37.412487  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3
I0121 17:48:37.412508  1741 net.cpp:84] Creating Layer inception_11a/3x3
I0121 17:48:37.412525  1741 net.cpp:406] inception_11a/3x3 <- inception_10a/output_inception_10a/output_0_split_1
I0121 17:48:37.412540  1741 net.cpp:380] inception_11a/3x3 -> inception_11a/3x3
I0121 17:48:37.417474  1741 net.cpp:122] Setting up inception_11a/3x3
I0121 17:48:37.417502  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.417510  1741 net.cpp:137] Memory required for data: 1666187776
I0121 17:48:37.417524  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/bn1
I0121 17:48:37.417552  1741 net.cpp:84] Creating Layer inception_11a/3x3/bn1
I0121 17:48:37.417562  1741 net.cpp:406] inception_11a/3x3/bn1 <- inception_11a/3x3
I0121 17:48:37.417589  1741 net.cpp:367] inception_11a/3x3/bn1 -> inception_11a/3x3 (in-place)
I0121 17:48:37.417898  1741 net.cpp:122] Setting up inception_11a/3x3/bn1
I0121 17:48:37.417920  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.417927  1741 net.cpp:137] Memory required for data: 1671430656
I0121 17:48:37.417973  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/scale1
I0121 17:48:37.417992  1741 net.cpp:84] Creating Layer inception_11a/3x3/scale1
I0121 17:48:37.418000  1741 net.cpp:406] inception_11a/3x3/scale1 <- inception_11a/3x3
I0121 17:48:37.418013  1741 net.cpp:367] inception_11a/3x3/scale1 -> inception_11a/3x3 (in-place)
I0121 17:48:37.418083  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/scale1
I0121 17:48:37.418248  1741 net.cpp:122] Setting up inception_11a/3x3/scale1
I0121 17:48:37.418267  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.418275  1741 net.cpp:137] Memory required for data: 1676673536
I0121 17:48:37.418287  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/relu1
I0121 17:48:37.418308  1741 net.cpp:84] Creating Layer inception_11a/3x3/relu1
I0121 17:48:37.418315  1741 net.cpp:406] inception_11a/3x3/relu1 <- inception_11a/3x3
I0121 17:48:37.418323  1741 net.cpp:367] inception_11a/3x3/relu1 -> inception_11a/3x3 (in-place)
I0121 17:48:37.418521  1741 net.cpp:122] Setting up inception_11a/3x3/relu1
I0121 17:48:37.418545  1741 net.cpp:129] Top shape: 128 160 8 8 (1310720)
I0121 17:48:37.418552  1741 net.cpp:137] Memory required for data: 1681916416
I0121 17:48:37.418560  1741 layer_factory.hpp:77] Creating layer inception_11a/output
I0121 17:48:37.418570  1741 net.cpp:84] Creating Layer inception_11a/output
I0121 17:48:37.418584  1741 net.cpp:406] inception_11a/output <- inception_11a/1x1
I0121 17:48:37.418593  1741 net.cpp:406] inception_11a/output <- inception_11a/3x3
I0121 17:48:37.418607  1741 net.cpp:380] inception_11a/output -> inception_11a/output
I0121 17:48:37.418656  1741 net.cpp:122] Setting up inception_11a/output
I0121 17:48:37.418679  1741 net.cpp:129] Top shape: 128 336 8 8 (2752512)
I0121 17:48:37.418686  1741 net.cpp:137] Memory required for data: 1692926464
I0121 17:48:37.418694  1741 layer_factory.hpp:77] Creating layer avg_pool_12/8x8_s1
I0121 17:48:37.418704  1741 net.cpp:84] Creating Layer avg_pool_12/8x8_s1
I0121 17:48:37.418718  1741 net.cpp:406] avg_pool_12/8x8_s1 <- inception_11a/output
I0121 17:48:37.418730  1741 net.cpp:380] avg_pool_12/8x8_s1 -> avg_pool_12/8x8_s1
I0121 17:48:37.419087  1741 net.cpp:122] Setting up avg_pool_12/8x8_s1
I0121 17:48:37.419117  1741 net.cpp:129] Top shape: 128 336 1 1 (43008)
I0121 17:48:37.419126  1741 net.cpp:137] Memory required for data: 1693098496
I0121 17:48:37.419133  1741 layer_factory.hpp:77] Creating layer drop_8x8_s1
I0121 17:48:37.419147  1741 net.cpp:84] Creating Layer drop_8x8_s1
I0121 17:48:37.419160  1741 net.cpp:406] drop_8x8_s1 <- avg_pool_12/8x8_s1
I0121 17:48:37.419173  1741 net.cpp:367] drop_8x8_s1 -> avg_pool_12/8x8_s1 (in-place)
I0121 17:48:37.419230  1741 net.cpp:122] Setting up drop_8x8_s1
I0121 17:48:37.419251  1741 net.cpp:129] Top shape: 128 336 1 1 (43008)
I0121 17:48:37.419260  1741 net.cpp:137] Memory required for data: 1693270528
I0121 17:48:37.419267  1741 layer_factory.hpp:77] Creating layer loss/classifier
I0121 17:48:37.419288  1741 net.cpp:84] Creating Layer loss/classifier
I0121 17:48:37.419301  1741 net.cpp:406] loss/classifier <- avg_pool_12/8x8_s1
I0121 17:48:37.419313  1741 net.cpp:380] loss/classifier -> loss/classifier
I0121 17:48:37.419513  1741 net.cpp:122] Setting up loss/classifier
I0121 17:48:37.419533  1741 net.cpp:129] Top shape: 128 10 (1280)
I0121 17:48:37.419538  1741 net.cpp:137] Memory required for data: 1693275648
I0121 17:48:37.419546  1741 layer_factory.hpp:77] Creating layer loss
I0121 17:48:37.419562  1741 net.cpp:84] Creating Layer loss
I0121 17:48:37.419600  1741 net.cpp:406] loss <- loss/classifier
I0121 17:48:37.419626  1741 net.cpp:406] loss <- label
I0121 17:48:37.419657  1741 net.cpp:380] loss -> loss
I0121 17:48:37.419703  1741 layer_factory.hpp:77] Creating layer loss
I0121 17:48:37.420153  1741 net.cpp:122] Setting up loss
I0121 17:48:37.420181  1741 net.cpp:129] Top shape: (1)
I0121 17:48:37.420186  1741 net.cpp:132]     with loss weight 1
I0121 17:48:37.420248  1741 net.cpp:137] Memory required for data: 1693275652
I0121 17:48:37.420258  1741 net.cpp:198] loss needs backward computation.
I0121 17:48:37.420266  1741 net.cpp:198] loss/classifier needs backward computation.
I0121 17:48:37.420290  1741 net.cpp:198] drop_8x8_s1 needs backward computation.
I0121 17:48:37.420315  1741 net.cpp:198] avg_pool_12/8x8_s1 needs backward computation.
I0121 17:48:37.420346  1741 net.cpp:198] inception_11a/output needs backward computation.
I0121 17:48:37.420369  1741 net.cpp:198] inception_11a/3x3/relu1 needs backward computation.
I0121 17:48:37.420382  1741 net.cpp:198] inception_11a/3x3/scale1 needs backward computation.
I0121 17:48:37.420392  1741 net.cpp:198] inception_11a/3x3/bn1 needs backward computation.
I0121 17:48:37.420397  1741 net.cpp:198] inception_11a/3x3 needs backward computation.
I0121 17:48:37.420404  1741 net.cpp:198] inception_11a/1x1/relu1 needs backward computation.
I0121 17:48:37.420423  1741 net.cpp:198] inception_11a/1x1/scale1 needs backward computation.
I0121 17:48:37.420445  1741 net.cpp:198] inception_11a/1x1/bn1 needs backward computation.
I0121 17:48:37.420466  1741 net.cpp:198] inception_11a/1x1 needs backward computation.
I0121 17:48:37.420487  1741 net.cpp:198] inception_10a/output_inception_10a/output_0_split needs backward computation.
I0121 17:48:37.420508  1741 net.cpp:198] inception_10a/output needs backward computation.
I0121 17:48:37.420531  1741 net.cpp:198] inception_10a/3x3/relu1 needs backward computation.
I0121 17:48:37.420552  1741 net.cpp:198] inception_10a/3x3/scale1 needs backward computation.
I0121 17:48:37.420573  1741 net.cpp:198] inception_10a/3x3/bn1 needs backward computation.
I0121 17:48:37.420593  1741 net.cpp:198] inception_10a/3x3 needs backward computation.
I0121 17:48:37.420616  1741 net.cpp:198] inception_10a/1x1/relu1 needs backward computation.
I0121 17:48:37.420637  1741 net.cpp:198] inception_10a/1x1/scale1 needs backward computation.
I0121 17:48:37.420658  1741 net.cpp:198] inception_10a/1x1/bn1 needs backward computation.
I0121 17:48:37.420678  1741 net.cpp:198] inception_10a/1x1 needs backward computation.
I0121 17:48:37.420701  1741 net.cpp:198] downsample_9/output_downsample_9/output_0_split needs backward computation.
I0121 17:48:37.420742  1741 net.cpp:198] downsample_9/output needs backward computation.
I0121 17:48:37.420761  1741 net.cpp:198] downsample_9/pool_s2 needs backward computation.
I0121 17:48:37.420771  1741 net.cpp:198] downsample_9/3x3_s2/relu1 needs backward computation.
I0121 17:48:37.420778  1741 net.cpp:198] downsample_9/3x3_s2/scale1 needs backward computation.
I0121 17:48:37.420785  1741 net.cpp:198] downsample_9/3x3_s2/bn1 needs backward computation.
I0121 17:48:37.420799  1741 net.cpp:198] downsample_9/3x3_s2 needs backward computation.
I0121 17:48:37.420809  1741 net.cpp:198] inception_8a/output_inception_8a/output_0_split needs backward computation.
I0121 17:48:37.420815  1741 net.cpp:198] inception_8a/output needs backward computation.
I0121 17:48:37.420823  1741 net.cpp:198] inception_8a/3x3/relu1 needs backward computation.
I0121 17:48:37.420850  1741 net.cpp:198] inception_8a/3x3/scale1 needs backward computation.
I0121 17:48:37.420876  1741 net.cpp:198] inception_8a/3x3/bn1 needs backward computation.
I0121 17:48:37.420904  1741 net.cpp:198] inception_8a/3x3 needs backward computation.
I0121 17:48:37.420918  1741 net.cpp:198] inception_8a/1x1/relu1 needs backward computation.
I0121 17:48:37.420927  1741 net.cpp:198] inception_8a/1x1/scale1 needs backward computation.
I0121 17:48:37.420933  1741 net.cpp:198] inception_8a/1x1/bn1 needs backward computation.
I0121 17:48:37.420939  1741 net.cpp:198] inception_8a/1x1 needs backward computation.
I0121 17:48:37.420959  1741 net.cpp:198] inception_7a/output_inception_7a/output_0_split needs backward computation.
I0121 17:48:37.420974  1741 net.cpp:198] inception_7a/output needs backward computation.
I0121 17:48:37.420982  1741 net.cpp:198] inception_7a/3x3/relu1 needs backward computation.
I0121 17:48:37.421005  1741 net.cpp:198] inception_7a/3x3/scale1 needs backward computation.
I0121 17:48:37.421021  1741 net.cpp:198] inception_7a/3x3/bn1 needs backward computation.
I0121 17:48:37.421030  1741 net.cpp:198] inception_7a/3x3 needs backward computation.
I0121 17:48:37.421038  1741 net.cpp:198] inception_7a/1x1/relu1 needs backward computation.
I0121 17:48:37.421058  1741 net.cpp:198] inception_7a/1x1/scale1 needs backward computation.
I0121 17:48:37.421080  1741 net.cpp:198] inception_7a/1x1/bn1 needs backward computation.
I0121 17:48:37.421102  1741 net.cpp:198] inception_7a/1x1 needs backward computation.
I0121 17:48:37.421123  1741 net.cpp:198] inception_6a/output_inception_6a/output_0_split needs backward computation.
I0121 17:48:37.421146  1741 net.cpp:198] inception_6a/output needs backward computation.
I0121 17:48:37.421169  1741 net.cpp:198] inception_6a/3x3/relu1 needs backward computation.
I0121 17:48:37.421200  1741 net.cpp:198] inception_6a/3x3/scale1 needs backward computation.
I0121 17:48:37.421229  1741 net.cpp:198] inception_6a/3x3/bn1 needs backward computation.
I0121 17:48:37.421260  1741 net.cpp:198] inception_6a/3x3 needs backward computation.
I0121 17:48:37.421278  1741 net.cpp:198] inception_6a/1x1/relu1 needs backward computation.
I0121 17:48:37.421288  1741 net.cpp:198] inception_6a/1x1/scale1 needs backward computation.
I0121 17:48:37.421294  1741 net.cpp:198] inception_6a/1x1/bn1 needs backward computation.
I0121 17:48:37.421309  1741 net.cpp:198] inception_6a/1x1 needs backward computation.
I0121 17:48:37.421317  1741 net.cpp:198] inception_5a/output_inception_5a/output_0_split needs backward computation.
I0121 17:48:37.421324  1741 net.cpp:198] inception_5a/output needs backward computation.
I0121 17:48:37.421332  1741 net.cpp:198] inception_5a/3x3/relu1 needs backward computation.
I0121 17:48:37.421365  1741 net.cpp:198] inception_5a/3x3/scale1 needs backward computation.
I0121 17:48:37.421389  1741 net.cpp:198] inception_5a/3x3/bn1 needs backward computation.
I0121 17:48:37.421411  1741 net.cpp:198] inception_5a/3x3 needs backward computation.
I0121 17:48:37.421432  1741 net.cpp:198] inception_5a/1x1/relu1 needs backward computation.
I0121 17:48:37.421456  1741 net.cpp:198] inception_5a/1x1/scale1 needs backward computation.
I0121 17:48:37.421494  1741 net.cpp:198] inception_5a/1x1/bn1 needs backward computation.
I0121 17:48:37.421512  1741 net.cpp:198] inception_5a/1x1 needs backward computation.
I0121 17:48:37.421522  1741 net.cpp:198] downsample_4/output_downsample_4/output_0_split needs backward computation.
I0121 17:48:37.421531  1741 net.cpp:198] downsample_4/output needs backward computation.
I0121 17:48:37.421540  1741 net.cpp:198] downsample_4/pool_s2 needs backward computation.
I0121 17:48:37.421562  1741 net.cpp:198] downsample_4/3x3_s2/relu1 needs backward computation.
I0121 17:48:37.421593  1741 net.cpp:198] downsample_4/3x3_s2/scale1 needs backward computation.
I0121 17:48:37.421615  1741 net.cpp:198] downsample_4/3x3_s2/bn1 needs backward computation.
I0121 17:48:37.421643  1741 net.cpp:198] downsample_4/3x3_s2 needs backward computation.
I0121 17:48:37.421664  1741 net.cpp:198] inception_3a/output_inception_3a/output_0_split needs backward computation.
I0121 17:48:37.421694  1741 net.cpp:198] inception_3a/output needs backward computation.
I0121 17:48:37.421733  1741 net.cpp:198] inception_3a/3x3/relu1 needs backward computation.
I0121 17:48:37.421761  1741 net.cpp:198] inception_3a/3x3/scale1 needs backward computation.
I0121 17:48:37.421795  1741 net.cpp:198] inception_3a/3x3/bn1 needs backward computation.
I0121 17:48:37.421803  1741 net.cpp:198] inception_3a/3x3 needs backward computation.
I0121 17:48:37.421809  1741 net.cpp:198] inception_3a/1x1/relu1 needs backward computation.
I0121 17:48:37.421814  1741 net.cpp:198] inception_3a/1x1/scale1 needs backward computation.
I0121 17:48:37.421818  1741 net.cpp:198] inception_3a/1x1/bn1 needs backward computation.
I0121 17:48:37.421823  1741 net.cpp:198] inception_3a/1x1 needs backward computation.
I0121 17:48:37.421833  1741 net.cpp:198] inception_2a/output_inception_2a/output_0_split needs backward computation.
I0121 17:48:37.421839  1741 net.cpp:198] inception_2a/output needs backward computation.
I0121 17:48:37.421850  1741 net.cpp:198] inception_2a/3x3/relu1 needs backward computation.
I0121 17:48:37.421859  1741 net.cpp:198] inception_2a/3x3/scale1 needs backward computation.
I0121 17:48:37.421866  1741 net.cpp:198] inception_2a/3x3/bn1 needs backward computation.
I0121 17:48:37.421874  1741 net.cpp:198] inception_2a/3x3 needs backward computation.
I0121 17:48:37.421890  1741 net.cpp:198] inception_2a/1x1/relu1 needs backward computation.
I0121 17:48:37.421897  1741 net.cpp:198] inception_2a/1x1/scale1 needs backward computation.
I0121 17:48:37.421906  1741 net.cpp:198] inception_2a/1x1/bn1 needs backward computation.
I0121 17:48:37.421916  1741 net.cpp:198] inception_2a/1x1 needs backward computation.
I0121 17:48:37.421923  1741 net.cpp:198] conv1/3x3_s1_conv1/relu1_0_split needs backward computation.
I0121 17:48:37.421931  1741 net.cpp:198] conv1/relu1 needs backward computation.
I0121 17:48:37.421959  1741 net.cpp:198] conv1/scale1 needs backward computation.
I0121 17:48:37.421993  1741 net.cpp:198] conv1/bn1 needs backward computation.
I0121 17:48:37.422008  1741 net.cpp:198] conv1/3x3_s1 needs backward computation.
I0121 17:48:37.422016  1741 net.cpp:200] data does not need backward computation.
I0121 17:48:37.422024  1741 net.cpp:242] This network produces output loss
I0121 17:48:37.422111  1741 net.cpp:255] Network initialization done.
I0121 17:48:37.424540  1741 upgrade_proto.cpp:77] Attempting to upgrade batch norm layers using deprecated params: cifar10/caffe/models/miniGoogleNet/m3/train_val_3_miniGoogleNet.prototxt
I0121 17:48:37.424568  1741 upgrade_proto.cpp:80] Successfully upgraded batch norm layers using deprecated params.
I0121 17:48:37.424580  1741 solver.cpp:172] Creating test net (#0) specified by net file: cifar10/caffe/models/miniGoogleNet/m3/train_val_3_miniGoogleNet.prototxt
I0121 17:48:37.424726  1741 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer data
I0121 17:48:37.425326  1741 net.cpp:51] Initializing net from parameters: 
name: "miniGoogleNet for CIFAR10, model 3"
state {
  phase: TEST
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    mirror: false
    mean_file: "cifar10/input/mean.binaryproto"
  }
  data_param {
    source: "cifar10/input/lmdb/valid_lmdb"
    batch_size: 50
    backend: LMDB
  }
}
layer {
  name: "conv1/3x3_s1"
  type: "Convolution"
  bottom: "data"
  top: "conv1/3x3_s1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/bn1"
  type: "BatchNorm"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "conv1/scale1"
  type: "Scale"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv1/relu1"
  type: "ReLU"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
}
layer {
  name: "inception_2a/1x1"
  type: "Convolution"
  bottom: "conv1/3x3_s1"
  top: "inception_2a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_2a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_2a/1x1/scale1"
  type: "Scale"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_2a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
}
layer {
  name: "inception_2a/3x3"
  type: "Convolution"
  bottom: "conv1/3x3_s1"
  top: "inception_2a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_2a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_2a/3x3/scale1"
  type: "Scale"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_2a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
}
layer {
  name: "inception_2a/output"
  type: "Concat"
  bottom: "inception_2a/1x1"
  bottom: "inception_2a/3x3"
  top: "inception_2a/output"
}
layer {
  name: "inception_3a/1x1"
  type: "Convolution"
  bottom: "inception_2a/output"
  top: "inception_3a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_3a/1x1/scale1"
  type: "Scale"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_3a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
}
layer {
  name: "inception_3a/3x3"
  type: "Convolution"
  bottom: "inception_2a/output"
  top: "inception_3a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_3a/3x3/scale1"
  type: "Scale"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_3a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
}
layer {
  name: "inception_3a/output"
  type: "Concat"
  bottom: "inception_3a/1x1"
  bottom: "inception_3a/3x3"
  top: "inception_3a/output"
}
layer {
  name: "downsample_4/3x3_s2"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "downsample_4/3x3_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "downsample_4/3x3_s2/bn1"
  type: "BatchNorm"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "downsample_4/3x3_s2/scale1"
  type: "Scale"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "downsample_4/3x3_s2/relu1"
  type: "ReLU"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
}
layer {
  name: "downsample_4/pool_s2"
  type: "Pooling"
  bottom: "inception_3a/output"
  top: "downsample_4/pool_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "downsample_4/output"
  type: "Concat"
  bottom: "downsample_4/3x3_s2"
  bottom: "downsample_4/pool_s2"
  top: "downsample_4/output"
}
layer {
  name: "inception_5a/1x1"
  type: "Convolution"
  bottom: "downsample_4/output"
  top: "inception_5a/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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_5a/1x1/scale1"
  type: "Scale"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_5a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
}
layer {
  name: "inception_5a/3x3"
  type: "Convolution"
  bottom: "downsample_4/output"
  top: "inception_5a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_5a/3x3/scale1"
  type: "Scale"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_5a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
}
layer {
  name: "inception_5a/output"
  type: "Concat"
  bottom: "inception_5a/1x1"
  bottom: "inception_5a/3x3"
  top: "inception_5a/output"
}
layer {
  name: "inception_6a/1x1"
  type: "Convolution"
  bottom: "inception_5a/output"
  top: "inception_6a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_6a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_6a/1x1/scale1"
  type: "Scale"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_6a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
}
layer {
  name: "inception_6a/3x3"
  type: "Convolution"
  bottom: "inception_5a/output"
  top: "inception_6a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_6a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_6a/3x3/scale1"
  type: "Scale"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_6a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
}
layer {
  name: "inception_6a/output"
  type: "Concat"
  bottom: "inception_6a/1x1"
  bottom: "inception_6a/3x3"
  top: "inception_6a/output"
}
layer {
  name: "inception_7a/1x1"
  type: "Convolution"
  bottom: "inception_6a/output"
  top: "inception_7a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_7a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_7a/1x1/scale1"
  type: "Scale"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_7a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
}
layer {
  name: "inception_7a/3x3"
  type: "Convolution"
  bottom: "inception_6a/output"
  top: "inception_7a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_7a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_7a/3x3/scale1"
  type: "Scale"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_7a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
}
layer {
  name: "inception_7a/output"
  type: "Concat"
  bottom: "inception_7a/1x1"
  bottom: "inception_7a/3x3"
  top: "inception_7a/output"
}
layer {
  name: "inception_8a/1x1"
  type: "Convolution"
  bottom: "inception_7a/output"
  top: "inception_8a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_8a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_8a/1x1/scale1"
  type: "Scale"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_8a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
}
layer {
  name: "inception_8a/3x3"
  type: "Convolution"
  bottom: "inception_7a/output"
  top: "inception_8a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_8a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_8a/3x3/scale1"
  type: "Scale"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_8a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
}
layer {
  name: "inception_8a/output"
  type: "Concat"
  bottom: "inception_8a/1x1"
  bottom: "inception_8a/3x3"
  top: "inception_8a/output"
}
layer {
  name: "downsample_9/3x3_s2"
  type: "Convolution"
  bottom: "inception_8a/output"
  top: "downsample_9/3x3_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "downsample_9/3x3_s2/bn1"
  type: "BatchNorm"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "downsample_9/3x3_s2/scale1"
  type: "Scale"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "downsample_9/3x3_s2/relu1"
  type: "ReLU"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
}
layer {
  name: "downsample_9/pool_s2"
  type: "Pooling"
  bottom: "inception_8a/output"
  top: "downsample_9/pool_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "downsample_9/output"
  type: "Concat"
  bottom: "downsample_9/3x3_s2"
  bottom: "downsample_9/pool_s2"
  top: "downsample_9/output"
}
layer {
  name: "inception_10a/1x1"
  type: "Convolution"
  bottom: "downsample_9/output"
  top: "inception_10a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 176
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_10a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_10a/1x1/scale1"
  type: "Scale"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_10a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
}
layer {
  name: "inception_10a/3x3"
  type: "Convolution"
  bottom: "downsample_9/output"
  top: "inception_10a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_10a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_10a/3x3/scale1"
  type: "Scale"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_10a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
}
layer {
  name: "inception_10a/output"
  type: "Concat"
  bottom: "inception_10a/1x1"
  bottom: "inception_10a/3x3"
  top: "inception_10a/output"
}
layer {
  name: "inception_11a/1x1"
  type: "Convolution"
  bottom: "inception_10a/output"
  top: "inception_11a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 176
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_11a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_11a/1x1/scale1"
  type: "Scale"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_11a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
}
layer {
  name: "inception_11a/3x3"
  type: "Convolution"
  bottom: "inception_10a/output"
  top: "inception_11a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_11a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "inception_11a/3x3/scale1"
  type: "Scale"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_11a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
}
layer {
  name: "inception_11a/output"
  type: "Concat"
  bottom: "inception_11a/1x1"
  bottom: "inception_11a/3x3"
  top: "inception_11a/output"
}
layer {
  name: "avg_pool_12/8x8_s1"
  type: "Pooling"
  bottom: "inception_11a/output"
  top: "avg_pool_12/8x8_s1"
  pooling_param {
    pool: AVE
    kernel_size: 8
    stride: 1
  }
}
layer {
  name: "drop_8x8_s1"
  type: "Dropout"
  bottom: "avg_pool_12/8x8_s1"
  top: "avg_pool_12/8x8_s1"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "loss/classifier"
  type: "InnerProduct"
  bottom: "avg_pool_12/8x8_s1"
  top: "loss/classifier"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 10
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "loss/classifier"
  bottom: "label"
  top: "loss"
}
layer {
  name: "accuracy"
  type: "Accuracy"
  bottom: "loss/classifier"
  bottom: "label"
  top: "accuracy"
  include {
    phase: TEST
  }
}
I0121 17:48:37.425995  1741 layer_factory.hpp:77] Creating layer data
I0121 17:48:37.428432  1741 db_lmdb.cpp:35] Opened lmdb cifar10/input/lmdb/valid_lmdb
I0121 17:48:37.429630  1741 net.cpp:84] Creating Layer data
I0121 17:48:37.429647  1741 net.cpp:380] data -> data
I0121 17:48:37.429658  1741 net.cpp:380] data -> label
I0121 17:48:37.429667  1741 data_transformer.cpp:25] Loading mean file from: cifar10/input/mean.binaryproto
I0121 17:48:37.429929  1741 data_layer.cpp:45] output data size: 50,3,32,32
I0121 17:48:37.434978  1741 net.cpp:122] Setting up data
I0121 17:48:37.435010  1741 net.cpp:129] Top shape: 50 3 32 32 (153600)
I0121 17:48:37.435019  1741 net.cpp:129] Top shape: 50 (50)
I0121 17:48:37.435022  1741 net.cpp:137] Memory required for data: 614600
I0121 17:48:37.435037  1741 layer_factory.hpp:77] Creating layer label_data_1_split
I0121 17:48:37.435052  1741 net.cpp:84] Creating Layer label_data_1_split
I0121 17:48:37.435061  1741 net.cpp:406] label_data_1_split <- label
I0121 17:48:37.435072  1741 net.cpp:380] label_data_1_split -> label_data_1_split_0
I0121 17:48:37.435111  1741 net.cpp:380] label_data_1_split -> label_data_1_split_1
I0121 17:48:37.435319  1741 net.cpp:122] Setting up label_data_1_split
I0121 17:48:37.435353  1741 net.cpp:129] Top shape: 50 (50)
I0121 17:48:37.435362  1741 net.cpp:129] Top shape: 50 (50)
I0121 17:48:37.435369  1741 net.cpp:137] Memory required for data: 615000
I0121 17:48:37.435377  1741 layer_factory.hpp:77] Creating layer conv1/3x3_s1
I0121 17:48:37.435402  1741 net.cpp:84] Creating Layer conv1/3x3_s1
I0121 17:48:37.435412  1741 net.cpp:406] conv1/3x3_s1 <- data
I0121 17:48:37.435426  1741 net.cpp:380] conv1/3x3_s1 -> conv1/3x3_s1
I0121 17:48:37.436755  1741 net.cpp:122] Setting up conv1/3x3_s1
I0121 17:48:37.436789  1741 net.cpp:129] Top shape: 50 96 32 32 (4915200)
I0121 17:48:37.436797  1741 net.cpp:137] Memory required for data: 20275800
I0121 17:48:37.436815  1741 layer_factory.hpp:77] Creating layer conv1/bn1
I0121 17:48:37.436842  1741 net.cpp:84] Creating Layer conv1/bn1
I0121 17:48:37.436852  1741 net.cpp:406] conv1/bn1 <- conv1/3x3_s1
I0121 17:48:37.436866  1741 net.cpp:367] conv1/bn1 -> conv1/3x3_s1 (in-place)
I0121 17:48:37.437131  1741 net.cpp:122] Setting up conv1/bn1
I0121 17:48:37.437151  1741 net.cpp:129] Top shape: 50 96 32 32 (4915200)
I0121 17:48:37.437160  1741 net.cpp:137] Memory required for data: 39936600
I0121 17:48:37.437178  1741 layer_factory.hpp:77] Creating layer conv1/scale1
I0121 17:48:37.437198  1741 net.cpp:84] Creating Layer conv1/scale1
I0121 17:48:37.437206  1741 net.cpp:406] conv1/scale1 <- conv1/3x3_s1
I0121 17:48:37.437222  1741 net.cpp:367] conv1/scale1 -> conv1/3x3_s1 (in-place)
I0121 17:48:37.437319  1741 layer_factory.hpp:77] Creating layer conv1/scale1
I0121 17:48:37.437515  1741 net.cpp:122] Setting up conv1/scale1
I0121 17:48:37.437536  1741 net.cpp:129] Top shape: 50 96 32 32 (4915200)
I0121 17:48:37.437544  1741 net.cpp:137] Memory required for data: 59597400
I0121 17:48:37.437556  1741 layer_factory.hpp:77] Creating layer conv1/relu1
I0121 17:48:37.437567  1741 net.cpp:84] Creating Layer conv1/relu1
I0121 17:48:37.437573  1741 net.cpp:406] conv1/relu1 <- conv1/3x3_s1
I0121 17:48:37.437592  1741 net.cpp:367] conv1/relu1 -> conv1/3x3_s1 (in-place)
I0121 17:48:37.437944  1741 net.cpp:122] Setting up conv1/relu1
I0121 17:48:37.437979  1741 net.cpp:129] Top shape: 50 96 32 32 (4915200)
I0121 17:48:37.437988  1741 net.cpp:137] Memory required for data: 79258200
I0121 17:48:37.437995  1741 layer_factory.hpp:77] Creating layer conv1/3x3_s1_conv1/relu1_0_split
I0121 17:48:37.438017  1741 net.cpp:84] Creating Layer conv1/3x3_s1_conv1/relu1_0_split
I0121 17:48:37.438032  1741 net.cpp:406] conv1/3x3_s1_conv1/relu1_0_split <- conv1/3x3_s1
I0121 17:48:37.438056  1741 net.cpp:380] conv1/3x3_s1_conv1/relu1_0_split -> conv1/3x3_s1_conv1/relu1_0_split_0
I0121 17:48:37.438081  1741 net.cpp:380] conv1/3x3_s1_conv1/relu1_0_split -> conv1/3x3_s1_conv1/relu1_0_split_1
I0121 17:48:37.438168  1741 net.cpp:122] Setting up conv1/3x3_s1_conv1/relu1_0_split
I0121 17:48:37.438196  1741 net.cpp:129] Top shape: 50 96 32 32 (4915200)
I0121 17:48:37.438208  1741 net.cpp:129] Top shape: 50 96 32 32 (4915200)
I0121 17:48:37.438218  1741 net.cpp:137] Memory required for data: 118579800
I0121 17:48:37.438225  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1
I0121 17:48:37.438243  1741 net.cpp:84] Creating Layer inception_2a/1x1
I0121 17:48:37.438258  1741 net.cpp:406] inception_2a/1x1 <- conv1/3x3_s1_conv1/relu1_0_split_0
I0121 17:48:37.438271  1741 net.cpp:380] inception_2a/1x1 -> inception_2a/1x1
I0121 17:48:37.439817  1741 net.cpp:122] Setting up inception_2a/1x1
I0121 17:48:37.439843  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.439862  1741 net.cpp:137] Memory required for data: 125133400
I0121 17:48:37.439885  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/bn1
I0121 17:48:37.439911  1741 net.cpp:84] Creating Layer inception_2a/1x1/bn1
I0121 17:48:37.439924  1741 net.cpp:406] inception_2a/1x1/bn1 <- inception_2a/1x1
I0121 17:48:37.439935  1741 net.cpp:367] inception_2a/1x1/bn1 -> inception_2a/1x1 (in-place)
I0121 17:48:37.440227  1741 net.cpp:122] Setting up inception_2a/1x1/bn1
I0121 17:48:37.440248  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.440269  1741 net.cpp:137] Memory required for data: 131687000
I0121 17:48:37.440284  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/scale1
I0121 17:48:37.440305  1741 net.cpp:84] Creating Layer inception_2a/1x1/scale1
I0121 17:48:37.440313  1741 net.cpp:406] inception_2a/1x1/scale1 <- inception_2a/1x1
I0121 17:48:37.440366  1741 net.cpp:367] inception_2a/1x1/scale1 -> inception_2a/1x1 (in-place)
I0121 17:48:37.440456  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/scale1
I0121 17:48:37.440695  1741 net.cpp:122] Setting up inception_2a/1x1/scale1
I0121 17:48:37.440713  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.440721  1741 net.cpp:137] Memory required for data: 138240600
I0121 17:48:37.440733  1741 layer_factory.hpp:77] Creating layer inception_2a/1x1/relu1
I0121 17:48:37.440750  1741 net.cpp:84] Creating Layer inception_2a/1x1/relu1
I0121 17:48:37.440759  1741 net.cpp:406] inception_2a/1x1/relu1 <- inception_2a/1x1
I0121 17:48:37.440768  1741 net.cpp:367] inception_2a/1x1/relu1 -> inception_2a/1x1 (in-place)
I0121 17:48:37.441131  1741 net.cpp:122] Setting up inception_2a/1x1/relu1
I0121 17:48:37.441159  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.441165  1741 net.cpp:137] Memory required for data: 144794200
I0121 17:48:37.441172  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3
I0121 17:48:37.441187  1741 net.cpp:84] Creating Layer inception_2a/3x3
I0121 17:48:37.441210  1741 net.cpp:406] inception_2a/3x3 <- conv1/3x3_s1_conv1/relu1_0_split_1
I0121 17:48:37.441224  1741 net.cpp:380] inception_2a/3x3 -> inception_2a/3x3
I0121 17:48:37.442631  1741 net.cpp:122] Setting up inception_2a/3x3
I0121 17:48:37.442664  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.442674  1741 net.cpp:137] Memory required for data: 151347800
I0121 17:48:37.442687  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/bn1
I0121 17:48:37.442709  1741 net.cpp:84] Creating Layer inception_2a/3x3/bn1
I0121 17:48:37.442718  1741 net.cpp:406] inception_2a/3x3/bn1 <- inception_2a/3x3
I0121 17:48:37.442732  1741 net.cpp:367] inception_2a/3x3/bn1 -> inception_2a/3x3 (in-place)
I0121 17:48:37.443018  1741 net.cpp:122] Setting up inception_2a/3x3/bn1
I0121 17:48:37.443039  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.443048  1741 net.cpp:137] Memory required for data: 157901400
I0121 17:48:37.443074  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/scale1
I0121 17:48:37.443090  1741 net.cpp:84] Creating Layer inception_2a/3x3/scale1
I0121 17:48:37.443099  1741 net.cpp:406] inception_2a/3x3/scale1 <- inception_2a/3x3
I0121 17:48:37.443107  1741 net.cpp:367] inception_2a/3x3/scale1 -> inception_2a/3x3 (in-place)
I0121 17:48:37.443202  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/scale1
I0121 17:48:37.443392  1741 net.cpp:122] Setting up inception_2a/3x3/scale1
I0121 17:48:37.443410  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.443418  1741 net.cpp:137] Memory required for data: 164455000
I0121 17:48:37.443431  1741 layer_factory.hpp:77] Creating layer inception_2a/3x3/relu1
I0121 17:48:37.443457  1741 net.cpp:84] Creating Layer inception_2a/3x3/relu1
I0121 17:48:37.443465  1741 net.cpp:406] inception_2a/3x3/relu1 <- inception_2a/3x3
I0121 17:48:37.443475  1741 net.cpp:367] inception_2a/3x3/relu1 -> inception_2a/3x3 (in-place)
I0121 17:48:37.443794  1741 net.cpp:122] Setting up inception_2a/3x3/relu1
I0121 17:48:37.443820  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.443828  1741 net.cpp:137] Memory required for data: 171008600
I0121 17:48:37.443835  1741 layer_factory.hpp:77] Creating layer inception_2a/output
I0121 17:48:37.443847  1741 net.cpp:84] Creating Layer inception_2a/output
I0121 17:48:37.443862  1741 net.cpp:406] inception_2a/output <- inception_2a/1x1
I0121 17:48:37.443872  1741 net.cpp:406] inception_2a/output <- inception_2a/3x3
I0121 17:48:37.443881  1741 net.cpp:380] inception_2a/output -> inception_2a/output
I0121 17:48:37.443940  1741 net.cpp:122] Setting up inception_2a/output
I0121 17:48:37.443962  1741 net.cpp:129] Top shape: 50 64 32 32 (3276800)
I0121 17:48:37.443969  1741 net.cpp:137] Memory required for data: 184115800
I0121 17:48:37.443976  1741 layer_factory.hpp:77] Creating layer inception_2a/output_inception_2a/output_0_split
I0121 17:48:37.443994  1741 net.cpp:84] Creating Layer inception_2a/output_inception_2a/output_0_split
I0121 17:48:37.444007  1741 net.cpp:406] inception_2a/output_inception_2a/output_0_split <- inception_2a/output
I0121 17:48:37.444017  1741 net.cpp:380] inception_2a/output_inception_2a/output_0_split -> inception_2a/output_inception_2a/output_0_split_0
I0121 17:48:37.444028  1741 net.cpp:380] inception_2a/output_inception_2a/output_0_split -> inception_2a/output_inception_2a/output_0_split_1
I0121 17:48:37.444116  1741 net.cpp:122] Setting up inception_2a/output_inception_2a/output_0_split
I0121 17:48:37.444134  1741 net.cpp:129] Top shape: 50 64 32 32 (3276800)
I0121 17:48:37.444144  1741 net.cpp:129] Top shape: 50 64 32 32 (3276800)
I0121 17:48:37.444150  1741 net.cpp:137] Memory required for data: 210330200
I0121 17:48:37.444159  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1
I0121 17:48:37.444182  1741 net.cpp:84] Creating Layer inception_3a/1x1
I0121 17:48:37.444191  1741 net.cpp:406] inception_3a/1x1 <- inception_2a/output_inception_2a/output_0_split_0
I0121 17:48:37.444207  1741 net.cpp:380] inception_3a/1x1 -> inception_3a/1x1
I0121 17:48:37.445262  1741 net.cpp:122] Setting up inception_3a/1x1
I0121 17:48:37.445293  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.445302  1741 net.cpp:137] Memory required for data: 216883800
I0121 17:48:37.445314  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/bn1
I0121 17:48:37.445338  1741 net.cpp:84] Creating Layer inception_3a/1x1/bn1
I0121 17:48:37.445345  1741 net.cpp:406] inception_3a/1x1/bn1 <- inception_3a/1x1
I0121 17:48:37.445359  1741 net.cpp:367] inception_3a/1x1/bn1 -> inception_3a/1x1 (in-place)
I0121 17:48:37.445654  1741 net.cpp:122] Setting up inception_3a/1x1/bn1
I0121 17:48:37.445674  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.445678  1741 net.cpp:137] Memory required for data: 223437400
I0121 17:48:37.445694  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/scale1
I0121 17:48:37.445714  1741 net.cpp:84] Creating Layer inception_3a/1x1/scale1
I0121 17:48:37.445724  1741 net.cpp:406] inception_3a/1x1/scale1 <- inception_3a/1x1
I0121 17:48:37.445744  1741 net.cpp:367] inception_3a/1x1/scale1 -> inception_3a/1x1 (in-place)
I0121 17:48:37.445842  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/scale1
I0121 17:48:37.446022  1741 net.cpp:122] Setting up inception_3a/1x1/scale1
I0121 17:48:37.446041  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.446046  1741 net.cpp:137] Memory required for data: 229991000
I0121 17:48:37.446054  1741 layer_factory.hpp:77] Creating layer inception_3a/1x1/relu1
I0121 17:48:37.446069  1741 net.cpp:84] Creating Layer inception_3a/1x1/relu1
I0121 17:48:37.446106  1741 net.cpp:406] inception_3a/1x1/relu1 <- inception_3a/1x1
I0121 17:48:37.446128  1741 net.cpp:367] inception_3a/1x1/relu1 -> inception_3a/1x1 (in-place)
I0121 17:48:37.446297  1741 net.cpp:122] Setting up inception_3a/1x1/relu1
I0121 17:48:37.446321  1741 net.cpp:129] Top shape: 50 32 32 32 (1638400)
I0121 17:48:37.446331  1741 net.cpp:137] Memory required for data: 236544600
I0121 17:48:37.446337  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3
I0121 17:48:37.446352  1741 net.cpp:84] Creating Layer inception_3a/3x3
I0121 17:48:37.446364  1741 net.cpp:406] inception_3a/3x3 <- inception_2a/output_inception_2a/output_0_split_1
I0121 17:48:37.446378  1741 net.cpp:380] inception_3a/3x3 -> inception_3a/3x3
I0121 17:48:37.448784  1741 net.cpp:122] Setting up inception_3a/3x3
I0121 17:48:37.448817  1741 net.cpp:129] Top shape: 50 48 32 32 (2457600)
I0121 17:48:37.448824  1741 net.cpp:137] Memory required for data: 246375000
I0121 17:48:37.448838  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/bn1
I0121 17:48:37.448863  1741 net.cpp:84] Creating Layer inception_3a/3x3/bn1
I0121 17:48:37.448870  1741 net.cpp:406] inception_3a/3x3/bn1 <- inception_3a/3x3
I0121 17:48:37.448884  1741 net.cpp:367] inception_3a/3x3/bn1 -> inception_3a/3x3 (in-place)
I0121 17:48:37.449393  1741 net.cpp:122] Setting up inception_3a/3x3/bn1
I0121 17:48:37.449416  1741 net.cpp:129] Top shape: 50 48 32 32 (2457600)
I0121 17:48:37.449424  1741 net.cpp:137] Memory required for data: 256205400
I0121 17:48:37.449447  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/scale1
I0121 17:48:37.449470  1741 net.cpp:84] Creating Layer inception_3a/3x3/scale1
I0121 17:48:37.449476  1741 net.cpp:406] inception_3a/3x3/scale1 <- inception_3a/3x3
I0121 17:48:37.449492  1741 net.cpp:367] inception_3a/3x3/scale1 -> inception_3a/3x3 (in-place)
I0121 17:48:37.449591  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/scale1
I0121 17:48:37.449872  1741 net.cpp:122] Setting up inception_3a/3x3/scale1
I0121 17:48:37.449896  1741 net.cpp:129] Top shape: 50 48 32 32 (2457600)
I0121 17:48:37.449904  1741 net.cpp:137] Memory required for data: 266035800
I0121 17:48:37.449916  1741 layer_factory.hpp:77] Creating layer inception_3a/3x3/relu1
I0121 17:48:37.449957  1741 net.cpp:84] Creating Layer inception_3a/3x3/relu1
I0121 17:48:37.449992  1741 net.cpp:406] inception_3a/3x3/relu1 <- inception_3a/3x3
I0121 17:48:37.450037  1741 net.cpp:367] inception_3a/3x3/relu1 -> inception_3a/3x3 (in-place)
I0121 17:48:37.450417  1741 net.cpp:122] Setting up inception_3a/3x3/relu1
I0121 17:48:37.450441  1741 net.cpp:129] Top shape: 50 48 32 32 (2457600)
I0121 17:48:37.450448  1741 net.cpp:137] Memory required for data: 275866200
I0121 17:48:37.450453  1741 layer_factory.hpp:77] Creating layer inception_3a/output
I0121 17:48:37.450460  1741 net.cpp:84] Creating Layer inception_3a/output
I0121 17:48:37.450474  1741 net.cpp:406] inception_3a/output <- inception_3a/1x1
I0121 17:48:37.450480  1741 net.cpp:406] inception_3a/output <- inception_3a/3x3
I0121 17:48:37.450486  1741 net.cpp:380] inception_3a/output -> inception_3a/output
I0121 17:48:37.450531  1741 net.cpp:122] Setting up inception_3a/output
I0121 17:48:37.450547  1741 net.cpp:129] Top shape: 50 80 32 32 (4096000)
I0121 17:48:37.450556  1741 net.cpp:137] Memory required for data: 292250200
I0121 17:48:37.450561  1741 layer_factory.hpp:77] Creating layer inception_3a/output_inception_3a/output_0_split
I0121 17:48:37.450567  1741 net.cpp:84] Creating Layer inception_3a/output_inception_3a/output_0_split
I0121 17:48:37.450574  1741 net.cpp:406] inception_3a/output_inception_3a/output_0_split <- inception_3a/output
I0121 17:48:37.450580  1741 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_0
I0121 17:48:37.450587  1741 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_1
I0121 17:48:37.450644  1741 net.cpp:122] Setting up inception_3a/output_inception_3a/output_0_split
I0121 17:48:37.450659  1741 net.cpp:129] Top shape: 50 80 32 32 (4096000)
I0121 17:48:37.450665  1741 net.cpp:129] Top shape: 50 80 32 32 (4096000)
I0121 17:48:37.450670  1741 net.cpp:137] Memory required for data: 325018200
I0121 17:48:37.450675  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2
I0121 17:48:37.450690  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2
I0121 17:48:37.450696  1741 net.cpp:406] downsample_4/3x3_s2 <- inception_3a/output_inception_3a/output_0_split_0
I0121 17:48:37.450708  1741 net.cpp:380] downsample_4/3x3_s2 -> downsample_4/3x3_s2
I0121 17:48:37.452121  1741 net.cpp:122] Setting up downsample_4/3x3_s2
I0121 17:48:37.452147  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.452153  1741 net.cpp:137] Memory required for data: 329114200
I0121 17:48:37.452162  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/bn1
I0121 17:48:37.452173  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2/bn1
I0121 17:48:37.452186  1741 net.cpp:406] downsample_4/3x3_s2/bn1 <- downsample_4/3x3_s2
I0121 17:48:37.452193  1741 net.cpp:367] downsample_4/3x3_s2/bn1 -> downsample_4/3x3_s2 (in-place)
I0121 17:48:37.452448  1741 net.cpp:122] Setting up downsample_4/3x3_s2/bn1
I0121 17:48:37.452463  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.452468  1741 net.cpp:137] Memory required for data: 333210200
I0121 17:48:37.452477  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/scale1
I0121 17:48:37.452486  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2/scale1
I0121 17:48:37.452492  1741 net.cpp:406] downsample_4/3x3_s2/scale1 <- downsample_4/3x3_s2
I0121 17:48:37.452499  1741 net.cpp:367] downsample_4/3x3_s2/scale1 -> downsample_4/3x3_s2 (in-place)
I0121 17:48:37.452555  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/scale1
I0121 17:48:37.452714  1741 net.cpp:122] Setting up downsample_4/3x3_s2/scale1
I0121 17:48:37.452730  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.452735  1741 net.cpp:137] Memory required for data: 337306200
I0121 17:48:37.452744  1741 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/relu1
I0121 17:48:37.452750  1741 net.cpp:84] Creating Layer downsample_4/3x3_s2/relu1
I0121 17:48:37.452757  1741 net.cpp:406] downsample_4/3x3_s2/relu1 <- downsample_4/3x3_s2
I0121 17:48:37.452766  1741 net.cpp:367] downsample_4/3x3_s2/relu1 -> downsample_4/3x3_s2 (in-place)
I0121 17:48:37.452951  1741 net.cpp:122] Setting up downsample_4/3x3_s2/relu1
I0121 17:48:37.452973  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.453025  1741 net.cpp:137] Memory required for data: 341402200
I0121 17:48:37.453044  1741 layer_factory.hpp:77] Creating layer downsample_4/pool_s2
I0121 17:48:37.453058  1741 net.cpp:84] Creating Layer downsample_4/pool_s2
I0121 17:48:37.453066  1741 net.cpp:406] downsample_4/pool_s2 <- inception_3a/output_inception_3a/output_0_split_1
I0121 17:48:37.453076  1741 net.cpp:380] downsample_4/pool_s2 -> downsample_4/pool_s2
I0121 17:48:37.453153  1741 net.cpp:122] Setting up downsample_4/pool_s2
I0121 17:48:37.453176  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.453182  1741 net.cpp:137] Memory required for data: 345498200
I0121 17:48:37.453189  1741 layer_factory.hpp:77] Creating layer downsample_4/output
I0121 17:48:37.453212  1741 net.cpp:84] Creating Layer downsample_4/output
I0121 17:48:37.453220  1741 net.cpp:406] downsample_4/output <- downsample_4/3x3_s2
I0121 17:48:37.453228  1741 net.cpp:406] downsample_4/output <- downsample_4/pool_s2
I0121 17:48:37.453244  1741 net.cpp:380] downsample_4/output -> downsample_4/output
I0121 17:48:37.453292  1741 net.cpp:122] Setting up downsample_4/output
I0121 17:48:37.453310  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.453320  1741 net.cpp:137] Memory required for data: 353690200
I0121 17:48:37.453327  1741 layer_factory.hpp:77] Creating layer downsample_4/output_downsample_4/output_0_split
I0121 17:48:37.453346  1741 net.cpp:84] Creating Layer downsample_4/output_downsample_4/output_0_split
I0121 17:48:37.453354  1741 net.cpp:406] downsample_4/output_downsample_4/output_0_split <- downsample_4/output
I0121 17:48:37.453362  1741 net.cpp:380] downsample_4/output_downsample_4/output_0_split -> downsample_4/output_downsample_4/output_0_split_0
I0121 17:48:37.453373  1741 net.cpp:380] downsample_4/output_downsample_4/output_0_split -> downsample_4/output_downsample_4/output_0_split_1
I0121 17:48:37.453450  1741 net.cpp:122] Setting up downsample_4/output_downsample_4/output_0_split
I0121 17:48:37.453465  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.453470  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.453474  1741 net.cpp:137] Memory required for data: 370074200
I0121 17:48:37.453480  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1
I0121 17:48:37.453498  1741 net.cpp:84] Creating Layer inception_5a/1x1
I0121 17:48:37.453514  1741 net.cpp:406] inception_5a/1x1 <- downsample_4/output_downsample_4/output_0_split_0
I0121 17:48:37.453528  1741 net.cpp:380] inception_5a/1x1 -> inception_5a/1x1
I0121 17:48:37.454803  1741 net.cpp:122] Setting up inception_5a/1x1
I0121 17:48:37.454833  1741 net.cpp:129] Top shape: 50 112 16 16 (1433600)
I0121 17:48:37.454838  1741 net.cpp:137] Memory required for data: 375808600
I0121 17:48:37.454851  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/bn1
I0121 17:48:37.454875  1741 net.cpp:84] Creating Layer inception_5a/1x1/bn1
I0121 17:48:37.454883  1741 net.cpp:406] inception_5a/1x1/bn1 <- inception_5a/1x1
I0121 17:48:37.454898  1741 net.cpp:367] inception_5a/1x1/bn1 -> inception_5a/1x1 (in-place)
I0121 17:48:37.455178  1741 net.cpp:122] Setting up inception_5a/1x1/bn1
I0121 17:48:37.455195  1741 net.cpp:129] Top shape: 50 112 16 16 (1433600)
I0121 17:48:37.455200  1741 net.cpp:137] Memory required for data: 381543000
I0121 17:48:37.455211  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/scale1
I0121 17:48:37.455230  1741 net.cpp:84] Creating Layer inception_5a/1x1/scale1
I0121 17:48:37.455240  1741 net.cpp:406] inception_5a/1x1/scale1 <- inception_5a/1x1
I0121 17:48:37.455250  1741 net.cpp:367] inception_5a/1x1/scale1 -> inception_5a/1x1 (in-place)
I0121 17:48:37.455327  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/scale1
I0121 17:48:37.455509  1741 net.cpp:122] Setting up inception_5a/1x1/scale1
I0121 17:48:37.455528  1741 net.cpp:129] Top shape: 50 112 16 16 (1433600)
I0121 17:48:37.455548  1741 net.cpp:137] Memory required for data: 387277400
I0121 17:48:37.455569  1741 layer_factory.hpp:77] Creating layer inception_5a/1x1/relu1
I0121 17:48:37.455583  1741 net.cpp:84] Creating Layer inception_5a/1x1/relu1
I0121 17:48:37.455592  1741 net.cpp:406] inception_5a/1x1/relu1 <- inception_5a/1x1
I0121 17:48:37.455602  1741 net.cpp:367] inception_5a/1x1/relu1 -> inception_5a/1x1 (in-place)
I0121 17:48:37.455984  1741 net.cpp:122] Setting up inception_5a/1x1/relu1
I0121 17:48:37.456007  1741 net.cpp:129] Top shape: 50 112 16 16 (1433600)
I0121 17:48:37.456013  1741 net.cpp:137] Memory required for data: 393011800
I0121 17:48:37.456019  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3
I0121 17:48:37.456041  1741 net.cpp:84] Creating Layer inception_5a/3x3
I0121 17:48:37.456079  1741 net.cpp:406] inception_5a/3x3 <- downsample_4/output_downsample_4/output_0_split_1
I0121 17:48:37.456110  1741 net.cpp:380] inception_5a/3x3 -> inception_5a/3x3
I0121 17:48:37.457623  1741 net.cpp:122] Setting up inception_5a/3x3
I0121 17:48:37.457648  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.457653  1741 net.cpp:137] Memory required for data: 395469400
I0121 17:48:37.457666  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/bn1
I0121 17:48:37.457691  1741 net.cpp:84] Creating Layer inception_5a/3x3/bn1
I0121 17:48:37.457701  1741 net.cpp:406] inception_5a/3x3/bn1 <- inception_5a/3x3
I0121 17:48:37.457711  1741 net.cpp:367] inception_5a/3x3/bn1 -> inception_5a/3x3 (in-place)
I0121 17:48:37.458019  1741 net.cpp:122] Setting up inception_5a/3x3/bn1
I0121 17:48:37.458037  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.458042  1741 net.cpp:137] Memory required for data: 397927000
I0121 17:48:37.458055  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/scale1
I0121 17:48:37.458076  1741 net.cpp:84] Creating Layer inception_5a/3x3/scale1
I0121 17:48:37.458084  1741 net.cpp:406] inception_5a/3x3/scale1 <- inception_5a/3x3
I0121 17:48:37.458093  1741 net.cpp:367] inception_5a/3x3/scale1 -> inception_5a/3x3 (in-place)
I0121 17:48:37.458173  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/scale1
I0121 17:48:37.458361  1741 net.cpp:122] Setting up inception_5a/3x3/scale1
I0121 17:48:37.458379  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.458382  1741 net.cpp:137] Memory required for data: 400384600
I0121 17:48:37.458391  1741 layer_factory.hpp:77] Creating layer inception_5a/3x3/relu1
I0121 17:48:37.458411  1741 net.cpp:84] Creating Layer inception_5a/3x3/relu1
I0121 17:48:37.458420  1741 net.cpp:406] inception_5a/3x3/relu1 <- inception_5a/3x3
I0121 17:48:37.458433  1741 net.cpp:367] inception_5a/3x3/relu1 -> inception_5a/3x3 (in-place)
I0121 17:48:37.458609  1741 net.cpp:122] Setting up inception_5a/3x3/relu1
I0121 17:48:37.458629  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.458634  1741 net.cpp:137] Memory required for data: 402842200
I0121 17:48:37.458640  1741 layer_factory.hpp:77] Creating layer inception_5a/output
I0121 17:48:37.458652  1741 net.cpp:84] Creating Layer inception_5a/output
I0121 17:48:37.458667  1741 net.cpp:406] inception_5a/output <- inception_5a/1x1
I0121 17:48:37.458675  1741 net.cpp:406] inception_5a/output <- inception_5a/3x3
I0121 17:48:37.458684  1741 net.cpp:380] inception_5a/output -> inception_5a/output
I0121 17:48:37.458729  1741 net.cpp:122] Setting up inception_5a/output
I0121 17:48:37.458753  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.458761  1741 net.cpp:137] Memory required for data: 411034200
I0121 17:48:37.458768  1741 layer_factory.hpp:77] Creating layer inception_5a/output_inception_5a/output_0_split
I0121 17:48:37.458787  1741 net.cpp:84] Creating Layer inception_5a/output_inception_5a/output_0_split
I0121 17:48:37.458796  1741 net.cpp:406] inception_5a/output_inception_5a/output_0_split <- inception_5a/output
I0121 17:48:37.458804  1741 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_0
I0121 17:48:37.458844  1741 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_1
I0121 17:48:37.458917  1741 net.cpp:122] Setting up inception_5a/output_inception_5a/output_0_split
I0121 17:48:37.458935  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.458940  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.458945  1741 net.cpp:137] Memory required for data: 427418200
I0121 17:48:37.458950  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1
I0121 17:48:37.458968  1741 net.cpp:84] Creating Layer inception_6a/1x1
I0121 17:48:37.458983  1741 net.cpp:406] inception_6a/1x1 <- inception_5a/output_inception_5a/output_0_split_0
I0121 17:48:37.458997  1741 net.cpp:380] inception_6a/1x1 -> inception_6a/1x1
I0121 17:48:37.460216  1741 net.cpp:122] Setting up inception_6a/1x1
I0121 17:48:37.460243  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.460249  1741 net.cpp:137] Memory required for data: 432333400
I0121 17:48:37.460261  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/bn1
I0121 17:48:37.460285  1741 net.cpp:84] Creating Layer inception_6a/1x1/bn1
I0121 17:48:37.460296  1741 net.cpp:406] inception_6a/1x1/bn1 <- inception_6a/1x1
I0121 17:48:37.460306  1741 net.cpp:367] inception_6a/1x1/bn1 -> inception_6a/1x1 (in-place)
I0121 17:48:37.460566  1741 net.cpp:122] Setting up inception_6a/1x1/bn1
I0121 17:48:37.460583  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.460589  1741 net.cpp:137] Memory required for data: 437248600
I0121 17:48:37.460604  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/scale1
I0121 17:48:37.460623  1741 net.cpp:84] Creating Layer inception_6a/1x1/scale1
I0121 17:48:37.460631  1741 net.cpp:406] inception_6a/1x1/scale1 <- inception_6a/1x1
I0121 17:48:37.460642  1741 net.cpp:367] inception_6a/1x1/scale1 -> inception_6a/1x1 (in-place)
I0121 17:48:37.460714  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/scale1
I0121 17:48:37.460969  1741 net.cpp:122] Setting up inception_6a/1x1/scale1
I0121 17:48:37.460992  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.461001  1741 net.cpp:137] Memory required for data: 442163800
I0121 17:48:37.461014  1741 layer_factory.hpp:77] Creating layer inception_6a/1x1/relu1
I0121 17:48:37.461036  1741 net.cpp:84] Creating Layer inception_6a/1x1/relu1
I0121 17:48:37.461045  1741 net.cpp:406] inception_6a/1x1/relu1 <- inception_6a/1x1
I0121 17:48:37.461051  1741 net.cpp:367] inception_6a/1x1/relu1 -> inception_6a/1x1 (in-place)
I0121 17:48:37.461366  1741 net.cpp:122] Setting up inception_6a/1x1/relu1
I0121 17:48:37.461392  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.461400  1741 net.cpp:137] Memory required for data: 447079000
I0121 17:48:37.461408  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3
I0121 17:48:37.461431  1741 net.cpp:84] Creating Layer inception_6a/3x3
I0121 17:48:37.461446  1741 net.cpp:406] inception_6a/3x3 <- inception_5a/output_inception_5a/output_0_split_1
I0121 17:48:37.461459  1741 net.cpp:380] inception_6a/3x3 -> inception_6a/3x3
I0121 17:48:37.463119  1741 net.cpp:122] Setting up inception_6a/3x3
I0121 17:48:37.463147  1741 net.cpp:129] Top shape: 50 64 16 16 (819200)
I0121 17:48:37.463156  1741 net.cpp:137] Memory required for data: 450355800
I0121 17:48:37.463191  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/bn1
I0121 17:48:37.463214  1741 net.cpp:84] Creating Layer inception_6a/3x3/bn1
I0121 17:48:37.463223  1741 net.cpp:406] inception_6a/3x3/bn1 <- inception_6a/3x3
I0121 17:48:37.463243  1741 net.cpp:367] inception_6a/3x3/bn1 -> inception_6a/3x3 (in-place)
I0121 17:48:37.463505  1741 net.cpp:122] Setting up inception_6a/3x3/bn1
I0121 17:48:37.463526  1741 net.cpp:129] Top shape: 50 64 16 16 (819200)
I0121 17:48:37.463532  1741 net.cpp:137] Memory required for data: 453632600
I0121 17:48:37.463547  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/scale1
I0121 17:48:37.463578  1741 net.cpp:84] Creating Layer inception_6a/3x3/scale1
I0121 17:48:37.463588  1741 net.cpp:406] inception_6a/3x3/scale1 <- inception_6a/3x3
I0121 17:48:37.463598  1741 net.cpp:367] inception_6a/3x3/scale1 -> inception_6a/3x3 (in-place)
I0121 17:48:37.463665  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/scale1
I0121 17:48:37.463837  1741 net.cpp:122] Setting up inception_6a/3x3/scale1
I0121 17:48:37.463860  1741 net.cpp:129] Top shape: 50 64 16 16 (819200)
I0121 17:48:37.463867  1741 net.cpp:137] Memory required for data: 456909400
I0121 17:48:37.463879  1741 layer_factory.hpp:77] Creating layer inception_6a/3x3/relu1
I0121 17:48:37.463897  1741 net.cpp:84] Creating Layer inception_6a/3x3/relu1
I0121 17:48:37.463907  1741 net.cpp:406] inception_6a/3x3/relu1 <- inception_6a/3x3
I0121 17:48:37.463915  1741 net.cpp:367] inception_6a/3x3/relu1 -> inception_6a/3x3 (in-place)
I0121 17:48:37.464232  1741 net.cpp:122] Setting up inception_6a/3x3/relu1
I0121 17:48:37.464262  1741 net.cpp:129] Top shape: 50 64 16 16 (819200)
I0121 17:48:37.464272  1741 net.cpp:137] Memory required for data: 460186200
I0121 17:48:37.464278  1741 layer_factory.hpp:77] Creating layer inception_6a/output
I0121 17:48:37.464289  1741 net.cpp:84] Creating Layer inception_6a/output
I0121 17:48:37.464304  1741 net.cpp:406] inception_6a/output <- inception_6a/1x1
I0121 17:48:37.464315  1741 net.cpp:406] inception_6a/output <- inception_6a/3x3
I0121 17:48:37.464325  1741 net.cpp:380] inception_6a/output -> inception_6a/output
I0121 17:48:37.464378  1741 net.cpp:122] Setting up inception_6a/output
I0121 17:48:37.464396  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.464404  1741 net.cpp:137] Memory required for data: 468378200
I0121 17:48:37.464411  1741 layer_factory.hpp:77] Creating layer inception_6a/output_inception_6a/output_0_split
I0121 17:48:37.464421  1741 net.cpp:84] Creating Layer inception_6a/output_inception_6a/output_0_split
I0121 17:48:37.464435  1741 net.cpp:406] inception_6a/output_inception_6a/output_0_split <- inception_6a/output
I0121 17:48:37.464447  1741 net.cpp:380] inception_6a/output_inception_6a/output_0_split -> inception_6a/output_inception_6a/output_0_split_0
I0121 17:48:37.464462  1741 net.cpp:380] inception_6a/output_inception_6a/output_0_split -> inception_6a/output_inception_6a/output_0_split_1
I0121 17:48:37.464536  1741 net.cpp:122] Setting up inception_6a/output_inception_6a/output_0_split
I0121 17:48:37.464555  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.464565  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.464570  1741 net.cpp:137] Memory required for data: 484762200
I0121 17:48:37.464581  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1
I0121 17:48:37.464608  1741 net.cpp:84] Creating Layer inception_7a/1x1
I0121 17:48:37.464622  1741 net.cpp:406] inception_7a/1x1 <- inception_6a/output_inception_6a/output_0_split_0
I0121 17:48:37.464643  1741 net.cpp:380] inception_7a/1x1 -> inception_7a/1x1
I0121 17:48:37.466055  1741 net.cpp:122] Setting up inception_7a/1x1
I0121 17:48:37.466085  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.466094  1741 net.cpp:137] Memory required for data: 488858200
I0121 17:48:37.466107  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/bn1
I0121 17:48:37.466135  1741 net.cpp:84] Creating Layer inception_7a/1x1/bn1
I0121 17:48:37.466143  1741 net.cpp:406] inception_7a/1x1/bn1 <- inception_7a/1x1
I0121 17:48:37.466158  1741 net.cpp:367] inception_7a/1x1/bn1 -> inception_7a/1x1 (in-place)
I0121 17:48:37.466439  1741 net.cpp:122] Setting up inception_7a/1x1/bn1
I0121 17:48:37.466457  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.466465  1741 net.cpp:137] Memory required for data: 492954200
I0121 17:48:37.466480  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/scale1
I0121 17:48:37.466500  1741 net.cpp:84] Creating Layer inception_7a/1x1/scale1
I0121 17:48:37.466506  1741 net.cpp:406] inception_7a/1x1/scale1 <- inception_7a/1x1
I0121 17:48:37.466537  1741 net.cpp:367] inception_7a/1x1/scale1 -> inception_7a/1x1 (in-place)
I0121 17:48:37.466614  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/scale1
I0121 17:48:37.466790  1741 net.cpp:122] Setting up inception_7a/1x1/scale1
I0121 17:48:37.466809  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.466817  1741 net.cpp:137] Memory required for data: 497050200
I0121 17:48:37.466830  1741 layer_factory.hpp:77] Creating layer inception_7a/1x1/relu1
I0121 17:48:37.466848  1741 net.cpp:84] Creating Layer inception_7a/1x1/relu1
I0121 17:48:37.466856  1741 net.cpp:406] inception_7a/1x1/relu1 <- inception_7a/1x1
I0121 17:48:37.466868  1741 net.cpp:367] inception_7a/1x1/relu1 -> inception_7a/1x1 (in-place)
I0121 17:48:37.467046  1741 net.cpp:122] Setting up inception_7a/1x1/relu1
I0121 17:48:37.467067  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.467075  1741 net.cpp:137] Memory required for data: 501146200
I0121 17:48:37.467082  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3
I0121 17:48:37.467098  1741 net.cpp:84] Creating Layer inception_7a/3x3
I0121 17:48:37.467113  1741 net.cpp:406] inception_7a/3x3 <- inception_6a/output_inception_6a/output_0_split_1
I0121 17:48:37.467129  1741 net.cpp:380] inception_7a/3x3 -> inception_7a/3x3
I0121 17:48:37.468955  1741 net.cpp:122] Setting up inception_7a/3x3
I0121 17:48:37.468984  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.468992  1741 net.cpp:137] Memory required for data: 505242200
I0121 17:48:37.469005  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/bn1
I0121 17:48:37.469033  1741 net.cpp:84] Creating Layer inception_7a/3x3/bn1
I0121 17:48:37.469044  1741 net.cpp:406] inception_7a/3x3/bn1 <- inception_7a/3x3
I0121 17:48:37.469058  1741 net.cpp:367] inception_7a/3x3/bn1 -> inception_7a/3x3 (in-place)
I0121 17:48:37.469334  1741 net.cpp:122] Setting up inception_7a/3x3/bn1
I0121 17:48:37.469353  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.469362  1741 net.cpp:137] Memory required for data: 509338200
I0121 17:48:37.469375  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/scale1
I0121 17:48:37.469398  1741 net.cpp:84] Creating Layer inception_7a/3x3/scale1
I0121 17:48:37.469405  1741 net.cpp:406] inception_7a/3x3/scale1 <- inception_7a/3x3
I0121 17:48:37.469424  1741 net.cpp:367] inception_7a/3x3/scale1 -> inception_7a/3x3 (in-place)
I0121 17:48:37.469494  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/scale1
I0121 17:48:37.469674  1741 net.cpp:122] Setting up inception_7a/3x3/scale1
I0121 17:48:37.469693  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.469702  1741 net.cpp:137] Memory required for data: 513434200
I0121 17:48:37.469714  1741 layer_factory.hpp:77] Creating layer inception_7a/3x3/relu1
I0121 17:48:37.469732  1741 net.cpp:84] Creating Layer inception_7a/3x3/relu1
I0121 17:48:37.469740  1741 net.cpp:406] inception_7a/3x3/relu1 <- inception_7a/3x3
I0121 17:48:37.469754  1741 net.cpp:367] inception_7a/3x3/relu1 -> inception_7a/3x3 (in-place)
I0121 17:48:37.470098  1741 net.cpp:122] Setting up inception_7a/3x3/relu1
I0121 17:48:37.470124  1741 net.cpp:129] Top shape: 50 80 16 16 (1024000)
I0121 17:48:37.470134  1741 net.cpp:137] Memory required for data: 517530200
I0121 17:48:37.470141  1741 layer_factory.hpp:77] Creating layer inception_7a/output
I0121 17:48:37.470151  1741 net.cpp:84] Creating Layer inception_7a/output
I0121 17:48:37.470161  1741 net.cpp:406] inception_7a/output <- inception_7a/1x1
I0121 17:48:37.470170  1741 net.cpp:406] inception_7a/output <- inception_7a/3x3
I0121 17:48:37.470182  1741 net.cpp:380] inception_7a/output -> inception_7a/output
I0121 17:48:37.470225  1741 net.cpp:122] Setting up inception_7a/output
I0121 17:48:37.470247  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.470254  1741 net.cpp:137] Memory required for data: 525722200
I0121 17:48:37.470263  1741 layer_factory.hpp:77] Creating layer inception_7a/output_inception_7a/output_0_split
I0121 17:48:37.470273  1741 net.cpp:84] Creating Layer inception_7a/output_inception_7a/output_0_split
I0121 17:48:37.470299  1741 net.cpp:406] inception_7a/output_inception_7a/output_0_split <- inception_7a/output
I0121 17:48:37.470311  1741 net.cpp:380] inception_7a/output_inception_7a/output_0_split -> inception_7a/output_inception_7a/output_0_split_0
I0121 17:48:37.470324  1741 net.cpp:380] inception_7a/output_inception_7a/output_0_split -> inception_7a/output_inception_7a/output_0_split_1
I0121 17:48:37.470396  1741 net.cpp:122] Setting up inception_7a/output_inception_7a/output_0_split
I0121 17:48:37.470415  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.470424  1741 net.cpp:129] Top shape: 50 160 16 16 (2048000)
I0121 17:48:37.470432  1741 net.cpp:137] Memory required for data: 542106200
I0121 17:48:37.470439  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1
I0121 17:48:37.470471  1741 net.cpp:84] Creating Layer inception_8a/1x1
I0121 17:48:37.470486  1741 net.cpp:406] inception_8a/1x1 <- inception_7a/output_inception_7a/output_0_split_0
I0121 17:48:37.470504  1741 net.cpp:380] inception_8a/1x1 -> inception_8a/1x1
I0121 17:48:37.471719  1741 net.cpp:122] Setting up inception_8a/1x1
I0121 17:48:37.471746  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.471751  1741 net.cpp:137] Memory required for data: 544563800
I0121 17:48:37.471765  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/bn1
I0121 17:48:37.471789  1741 net.cpp:84] Creating Layer inception_8a/1x1/bn1
I0121 17:48:37.471799  1741 net.cpp:406] inception_8a/1x1/bn1 <- inception_8a/1x1
I0121 17:48:37.471812  1741 net.cpp:367] inception_8a/1x1/bn1 -> inception_8a/1x1 (in-place)
I0121 17:48:37.472093  1741 net.cpp:122] Setting up inception_8a/1x1/bn1
I0121 17:48:37.472111  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.472116  1741 net.cpp:137] Memory required for data: 547021400
I0121 17:48:37.472127  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/scale1
I0121 17:48:37.472139  1741 net.cpp:84] Creating Layer inception_8a/1x1/scale1
I0121 17:48:37.472146  1741 net.cpp:406] inception_8a/1x1/scale1 <- inception_8a/1x1
I0121 17:48:37.472154  1741 net.cpp:367] inception_8a/1x1/scale1 -> inception_8a/1x1 (in-place)
I0121 17:48:37.472250  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/scale1
I0121 17:48:37.472436  1741 net.cpp:122] Setting up inception_8a/1x1/scale1
I0121 17:48:37.472455  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.472460  1741 net.cpp:137] Memory required for data: 549479000
I0121 17:48:37.472468  1741 layer_factory.hpp:77] Creating layer inception_8a/1x1/relu1
I0121 17:48:37.472479  1741 net.cpp:84] Creating Layer inception_8a/1x1/relu1
I0121 17:48:37.472486  1741 net.cpp:406] inception_8a/1x1/relu1 <- inception_8a/1x1
I0121 17:48:37.472496  1741 net.cpp:367] inception_8a/1x1/relu1 -> inception_8a/1x1 (in-place)
I0121 17:48:37.472676  1741 net.cpp:122] Setting up inception_8a/1x1/relu1
I0121 17:48:37.472703  1741 net.cpp:129] Top shape: 50 48 16 16 (614400)
I0121 17:48:37.472708  1741 net.cpp:137] Memory required for data: 551936600
I0121 17:48:37.472713  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3
I0121 17:48:37.472724  1741 net.cpp:84] Creating Layer inception_8a/3x3
I0121 17:48:37.472740  1741 net.cpp:406] inception_8a/3x3 <- inception_7a/output_inception_7a/output_0_split_1
I0121 17:48:37.472754  1741 net.cpp:380] inception_8a/3x3 -> inception_8a/3x3
I0121 17:48:37.475352  1741 net.cpp:122] Setting up inception_8a/3x3
I0121 17:48:37.475378  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.475384  1741 net.cpp:137] Memory required for data: 556851800
I0121 17:48:37.475394  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/bn1
I0121 17:48:37.475414  1741 net.cpp:84] Creating Layer inception_8a/3x3/bn1
I0121 17:48:37.475431  1741 net.cpp:406] inception_8a/3x3/bn1 <- inception_8a/3x3
I0121 17:48:37.475445  1741 net.cpp:367] inception_8a/3x3/bn1 -> inception_8a/3x3 (in-place)
I0121 17:48:37.475730  1741 net.cpp:122] Setting up inception_8a/3x3/bn1
I0121 17:48:37.475761  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.475767  1741 net.cpp:137] Memory required for data: 561767000
I0121 17:48:37.475780  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/scale1
I0121 17:48:37.475795  1741 net.cpp:84] Creating Layer inception_8a/3x3/scale1
I0121 17:48:37.475803  1741 net.cpp:406] inception_8a/3x3/scale1 <- inception_8a/3x3
I0121 17:48:37.475821  1741 net.cpp:367] inception_8a/3x3/scale1 -> inception_8a/3x3 (in-place)
I0121 17:48:37.475914  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/scale1
I0121 17:48:37.476109  1741 net.cpp:122] Setting up inception_8a/3x3/scale1
I0121 17:48:37.476126  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.476131  1741 net.cpp:137] Memory required for data: 566682200
I0121 17:48:37.476140  1741 layer_factory.hpp:77] Creating layer inception_8a/3x3/relu1
I0121 17:48:37.476156  1741 net.cpp:84] Creating Layer inception_8a/3x3/relu1
I0121 17:48:37.476164  1741 net.cpp:406] inception_8a/3x3/relu1 <- inception_8a/3x3
I0121 17:48:37.476181  1741 net.cpp:367] inception_8a/3x3/relu1 -> inception_8a/3x3 (in-place)
I0121 17:48:37.476503  1741 net.cpp:122] Setting up inception_8a/3x3/relu1
I0121 17:48:37.476527  1741 net.cpp:129] Top shape: 50 96 16 16 (1228800)
I0121 17:48:37.476532  1741 net.cpp:137] Memory required for data: 571597400
I0121 17:48:37.476537  1741 layer_factory.hpp:77] Creating layer inception_8a/output
I0121 17:48:37.476547  1741 net.cpp:84] Creating Layer inception_8a/output
I0121 17:48:37.476558  1741 net.cpp:406] inception_8a/output <- inception_8a/1x1
I0121 17:48:37.476568  1741 net.cpp:406] inception_8a/output <- inception_8a/3x3
I0121 17:48:37.476586  1741 net.cpp:380] inception_8a/output -> inception_8a/output
I0121 17:48:37.476639  1741 net.cpp:122] Setting up inception_8a/output
I0121 17:48:37.476657  1741 net.cpp:129] Top shape: 50 144 16 16 (1843200)
I0121 17:48:37.476666  1741 net.cpp:137] Memory required for data: 578970200
I0121 17:48:37.476672  1741 layer_factory.hpp:77] Creating layer inception_8a/output_inception_8a/output_0_split
I0121 17:48:37.476683  1741 net.cpp:84] Creating Layer inception_8a/output_inception_8a/output_0_split
I0121 17:48:37.476692  1741 net.cpp:406] inception_8a/output_inception_8a/output_0_split <- inception_8a/output
I0121 17:48:37.476706  1741 net.cpp:380] inception_8a/output_inception_8a/output_0_split -> inception_8a/output_inception_8a/output_0_split_0
I0121 17:48:37.476717  1741 net.cpp:380] inception_8a/output_inception_8a/output_0_split -> inception_8a/output_inception_8a/output_0_split_1
I0121 17:48:37.476801  1741 net.cpp:122] Setting up inception_8a/output_inception_8a/output_0_split
I0121 17:48:37.476824  1741 net.cpp:129] Top shape: 50 144 16 16 (1843200)
I0121 17:48:37.476833  1741 net.cpp:129] Top shape: 50 144 16 16 (1843200)
I0121 17:48:37.476840  1741 net.cpp:137] Memory required for data: 593715800
I0121 17:48:37.476848  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2
I0121 17:48:37.476869  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2
I0121 17:48:37.476877  1741 net.cpp:406] downsample_9/3x3_s2 <- inception_8a/output_inception_8a/output_0_split_0
I0121 17:48:37.476891  1741 net.cpp:380] downsample_9/3x3_s2 -> downsample_9/3x3_s2
I0121 17:48:37.479396  1741 net.cpp:122] Setting up downsample_9/3x3_s2
I0121 17:48:37.479425  1741 net.cpp:129] Top shape: 50 96 8 8 (307200)
I0121 17:48:37.479434  1741 net.cpp:137] Memory required for data: 594944600
I0121 17:48:37.479447  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/bn1
I0121 17:48:37.479466  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2/bn1
I0121 17:48:37.479482  1741 net.cpp:406] downsample_9/3x3_s2/bn1 <- downsample_9/3x3_s2
I0121 17:48:37.479497  1741 net.cpp:367] downsample_9/3x3_s2/bn1 -> downsample_9/3x3_s2 (in-place)
I0121 17:48:37.479805  1741 net.cpp:122] Setting up downsample_9/3x3_s2/bn1
I0121 17:48:37.479826  1741 net.cpp:129] Top shape: 50 96 8 8 (307200)
I0121 17:48:37.479831  1741 net.cpp:137] Memory required for data: 596173400
I0121 17:48:37.479871  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/scale1
I0121 17:48:37.479892  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2/scale1
I0121 17:48:37.479900  1741 net.cpp:406] downsample_9/3x3_s2/scale1 <- downsample_9/3x3_s2
I0121 17:48:37.479907  1741 net.cpp:367] downsample_9/3x3_s2/scale1 -> downsample_9/3x3_s2 (in-place)
I0121 17:48:37.480048  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/scale1
I0121 17:48:37.480250  1741 net.cpp:122] Setting up downsample_9/3x3_s2/scale1
I0121 17:48:37.480269  1741 net.cpp:129] Top shape: 50 96 8 8 (307200)
I0121 17:48:37.480274  1741 net.cpp:137] Memory required for data: 597402200
I0121 17:48:37.480285  1741 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/relu1
I0121 17:48:37.480304  1741 net.cpp:84] Creating Layer downsample_9/3x3_s2/relu1
I0121 17:48:37.480320  1741 net.cpp:406] downsample_9/3x3_s2/relu1 <- downsample_9/3x3_s2
I0121 17:48:37.480332  1741 net.cpp:367] downsample_9/3x3_s2/relu1 -> downsample_9/3x3_s2 (in-place)
I0121 17:48:37.480504  1741 net.cpp:122] Setting up downsample_9/3x3_s2/relu1
I0121 17:48:37.480523  1741 net.cpp:129] Top shape: 50 96 8 8 (307200)
I0121 17:48:37.480530  1741 net.cpp:137] Memory required for data: 598631000
I0121 17:48:37.480535  1741 layer_factory.hpp:77] Creating layer downsample_9/pool_s2
I0121 17:48:37.480559  1741 net.cpp:84] Creating Layer downsample_9/pool_s2
I0121 17:48:37.480576  1741 net.cpp:406] downsample_9/pool_s2 <- inception_8a/output_inception_8a/output_0_split_1
I0121 17:48:37.480588  1741 net.cpp:380] downsample_9/pool_s2 -> downsample_9/pool_s2
I0121 17:48:37.480687  1741 net.cpp:122] Setting up downsample_9/pool_s2
I0121 17:48:37.480706  1741 net.cpp:129] Top shape: 50 144 8 8 (460800)
I0121 17:48:37.480713  1741 net.cpp:137] Memory required for data: 600474200
I0121 17:48:37.480721  1741 layer_factory.hpp:77] Creating layer downsample_9/output
I0121 17:48:37.480731  1741 net.cpp:84] Creating Layer downsample_9/output
I0121 17:48:37.480763  1741 net.cpp:406] downsample_9/output <- downsample_9/3x3_s2
I0121 17:48:37.480792  1741 net.cpp:406] downsample_9/output <- downsample_9/pool_s2
I0121 17:48:37.480814  1741 net.cpp:380] downsample_9/output -> downsample_9/output
I0121 17:48:37.480876  1741 net.cpp:122] Setting up downsample_9/output
I0121 17:48:37.480896  1741 net.cpp:129] Top shape: 50 240 8 8 (768000)
I0121 17:48:37.480904  1741 net.cpp:137] Memory required for data: 603546200
I0121 17:48:37.480912  1741 layer_factory.hpp:77] Creating layer downsample_9/output_downsample_9/output_0_split
I0121 17:48:37.480926  1741 net.cpp:84] Creating Layer downsample_9/output_downsample_9/output_0_split
I0121 17:48:37.480939  1741 net.cpp:406] downsample_9/output_downsample_9/output_0_split <- downsample_9/output
I0121 17:48:37.480950  1741 net.cpp:380] downsample_9/output_downsample_9/output_0_split -> downsample_9/output_downsample_9/output_0_split_0
I0121 17:48:37.480962  1741 net.cpp:380] downsample_9/output_downsample_9/output_0_split -> downsample_9/output_downsample_9/output_0_split_1
I0121 17:48:37.481047  1741 net.cpp:122] Setting up downsample_9/output_downsample_9/output_0_split
I0121 17:48:37.481065  1741 net.cpp:129] Top shape: 50 240 8 8 (768000)
I0121 17:48:37.481071  1741 net.cpp:129] Top shape: 50 240 8 8 (768000)
I0121 17:48:37.481076  1741 net.cpp:137] Memory required for data: 609690200
I0121 17:48:37.481092  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1
I0121 17:48:37.481113  1741 net.cpp:84] Creating Layer inception_10a/1x1
I0121 17:48:37.481128  1741 net.cpp:406] inception_10a/1x1 <- downsample_9/output_downsample_9/output_0_split_0
I0121 17:48:37.481145  1741 net.cpp:380] inception_10a/1x1 -> inception_10a/1x1
I0121 17:48:37.482487  1741 net.cpp:122] Setting up inception_10a/1x1
I0121 17:48:37.482514  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.482523  1741 net.cpp:137] Memory required for data: 611943000
I0121 17:48:37.482547  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/bn1
I0121 17:48:37.482584  1741 net.cpp:84] Creating Layer inception_10a/1x1/bn1
I0121 17:48:37.482594  1741 net.cpp:406] inception_10a/1x1/bn1 <- inception_10a/1x1
I0121 17:48:37.482605  1741 net.cpp:367] inception_10a/1x1/bn1 -> inception_10a/1x1 (in-place)
I0121 17:48:37.482914  1741 net.cpp:122] Setting up inception_10a/1x1/bn1
I0121 17:48:37.482931  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.482936  1741 net.cpp:137] Memory required for data: 614195800
I0121 17:48:37.482950  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/scale1
I0121 17:48:37.482970  1741 net.cpp:84] Creating Layer inception_10a/1x1/scale1
I0121 17:48:37.482978  1741 net.cpp:406] inception_10a/1x1/scale1 <- inception_10a/1x1
I0121 17:48:37.483000  1741 net.cpp:367] inception_10a/1x1/scale1 -> inception_10a/1x1 (in-place)
I0121 17:48:37.483076  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/scale1
I0121 17:48:37.483270  1741 net.cpp:122] Setting up inception_10a/1x1/scale1
I0121 17:48:37.483289  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.483292  1741 net.cpp:137] Memory required for data: 616448600
I0121 17:48:37.483304  1741 layer_factory.hpp:77] Creating layer inception_10a/1x1/relu1
I0121 17:48:37.483322  1741 net.cpp:84] Creating Layer inception_10a/1x1/relu1
I0121 17:48:37.483330  1741 net.cpp:406] inception_10a/1x1/relu1 <- inception_10a/1x1
I0121 17:48:37.483343  1741 net.cpp:367] inception_10a/1x1/relu1 -> inception_10a/1x1 (in-place)
I0121 17:48:37.483675  1741 net.cpp:122] Setting up inception_10a/1x1/relu1
I0121 17:48:37.483700  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.483708  1741 net.cpp:137] Memory required for data: 618701400
I0121 17:48:37.483716  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3
I0121 17:48:37.483731  1741 net.cpp:84] Creating Layer inception_10a/3x3
I0121 17:48:37.483742  1741 net.cpp:406] inception_10a/3x3 <- downsample_9/output_downsample_9/output_0_split_1
I0121 17:48:37.483758  1741 net.cpp:380] inception_10a/3x3 -> inception_10a/3x3
I0121 17:48:37.487378  1741 net.cpp:122] Setting up inception_10a/3x3
I0121 17:48:37.487411  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.487422  1741 net.cpp:137] Memory required for data: 620749400
I0121 17:48:37.487435  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/bn1
I0121 17:48:37.487448  1741 net.cpp:84] Creating Layer inception_10a/3x3/bn1
I0121 17:48:37.487457  1741 net.cpp:406] inception_10a/3x3/bn1 <- inception_10a/3x3
I0121 17:48:37.487478  1741 net.cpp:367] inception_10a/3x3/bn1 -> inception_10a/3x3 (in-place)
I0121 17:48:37.487781  1741 net.cpp:122] Setting up inception_10a/3x3/bn1
I0121 17:48:37.487800  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.487807  1741 net.cpp:137] Memory required for data: 622797400
I0121 17:48:37.487823  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/scale1
I0121 17:48:37.487834  1741 net.cpp:84] Creating Layer inception_10a/3x3/scale1
I0121 17:48:37.487848  1741 net.cpp:406] inception_10a/3x3/scale1 <- inception_10a/3x3
I0121 17:48:37.487859  1741 net.cpp:367] inception_10a/3x3/scale1 -> inception_10a/3x3 (in-place)
I0121 17:48:37.487931  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/scale1
I0121 17:48:37.488121  1741 net.cpp:122] Setting up inception_10a/3x3/scale1
I0121 17:48:37.488140  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.488148  1741 net.cpp:137] Memory required for data: 624845400
I0121 17:48:37.488160  1741 layer_factory.hpp:77] Creating layer inception_10a/3x3/relu1
I0121 17:48:37.488173  1741 net.cpp:84] Creating Layer inception_10a/3x3/relu1
I0121 17:48:37.488186  1741 net.cpp:406] inception_10a/3x3/relu1 <- inception_10a/3x3
I0121 17:48:37.488198  1741 net.cpp:367] inception_10a/3x3/relu1 -> inception_10a/3x3 (in-place)
I0121 17:48:37.488519  1741 net.cpp:122] Setting up inception_10a/3x3/relu1
I0121 17:48:37.488545  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.488554  1741 net.cpp:137] Memory required for data: 626893400
I0121 17:48:37.488577  1741 layer_factory.hpp:77] Creating layer inception_10a/output
I0121 17:48:37.488595  1741 net.cpp:84] Creating Layer inception_10a/output
I0121 17:48:37.488610  1741 net.cpp:406] inception_10a/output <- inception_10a/1x1
I0121 17:48:37.488621  1741 net.cpp:406] inception_10a/output <- inception_10a/3x3
I0121 17:48:37.488631  1741 net.cpp:380] inception_10a/output -> inception_10a/output
I0121 17:48:37.488685  1741 net.cpp:122] Setting up inception_10a/output
I0121 17:48:37.488704  1741 net.cpp:129] Top shape: 50 336 8 8 (1075200)
I0121 17:48:37.488713  1741 net.cpp:137] Memory required for data: 631194200
I0121 17:48:37.488719  1741 layer_factory.hpp:77] Creating layer inception_10a/output_inception_10a/output_0_split
I0121 17:48:37.488730  1741 net.cpp:84] Creating Layer inception_10a/output_inception_10a/output_0_split
I0121 17:48:37.488739  1741 net.cpp:406] inception_10a/output_inception_10a/output_0_split <- inception_10a/output
I0121 17:48:37.488751  1741 net.cpp:380] inception_10a/output_inception_10a/output_0_split -> inception_10a/output_inception_10a/output_0_split_0
I0121 17:48:37.488765  1741 net.cpp:380] inception_10a/output_inception_10a/output_0_split -> inception_10a/output_inception_10a/output_0_split_1
I0121 17:48:37.488838  1741 net.cpp:122] Setting up inception_10a/output_inception_10a/output_0_split
I0121 17:48:37.488857  1741 net.cpp:129] Top shape: 50 336 8 8 (1075200)
I0121 17:48:37.488865  1741 net.cpp:129] Top shape: 50 336 8 8 (1075200)
I0121 17:48:37.488871  1741 net.cpp:137] Memory required for data: 639795800
I0121 17:48:37.488879  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1
I0121 17:48:37.488903  1741 net.cpp:84] Creating Layer inception_11a/1x1
I0121 17:48:37.488917  1741 net.cpp:406] inception_11a/1x1 <- inception_10a/output_inception_10a/output_0_split_0
I0121 17:48:37.488929  1741 net.cpp:380] inception_11a/1x1 -> inception_11a/1x1
I0121 17:48:37.490538  1741 net.cpp:122] Setting up inception_11a/1x1
I0121 17:48:37.490567  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.490577  1741 net.cpp:137] Memory required for data: 642048600
I0121 17:48:37.490589  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/bn1
I0121 17:48:37.490607  1741 net.cpp:84] Creating Layer inception_11a/1x1/bn1
I0121 17:48:37.490623  1741 net.cpp:406] inception_11a/1x1/bn1 <- inception_11a/1x1
I0121 17:48:37.490635  1741 net.cpp:367] inception_11a/1x1/bn1 -> inception_11a/1x1 (in-place)
I0121 17:48:37.490923  1741 net.cpp:122] Setting up inception_11a/1x1/bn1
I0121 17:48:37.490943  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.490952  1741 net.cpp:137] Memory required for data: 644301400
I0121 17:48:37.490964  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/scale1
I0121 17:48:37.490978  1741 net.cpp:84] Creating Layer inception_11a/1x1/scale1
I0121 17:48:37.490988  1741 net.cpp:406] inception_11a/1x1/scale1 <- inception_11a/1x1
I0121 17:48:37.490996  1741 net.cpp:367] inception_11a/1x1/scale1 -> inception_11a/1x1 (in-place)
I0121 17:48:37.491080  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/scale1
I0121 17:48:37.491273  1741 net.cpp:122] Setting up inception_11a/1x1/scale1
I0121 17:48:37.491297  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.491304  1741 net.cpp:137] Memory required for data: 646554200
I0121 17:48:37.491317  1741 layer_factory.hpp:77] Creating layer inception_11a/1x1/relu1
I0121 17:48:37.491328  1741 net.cpp:84] Creating Layer inception_11a/1x1/relu1
I0121 17:48:37.491345  1741 net.cpp:406] inception_11a/1x1/relu1 <- inception_11a/1x1
I0121 17:48:37.491356  1741 net.cpp:367] inception_11a/1x1/relu1 -> inception_11a/1x1 (in-place)
I0121 17:48:37.491525  1741 net.cpp:122] Setting up inception_11a/1x1/relu1
I0121 17:48:37.491546  1741 net.cpp:129] Top shape: 50 176 8 8 (563200)
I0121 17:48:37.491556  1741 net.cpp:137] Memory required for data: 648807000
I0121 17:48:37.491564  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3
I0121 17:48:37.491602  1741 net.cpp:84] Creating Layer inception_11a/3x3
I0121 17:48:37.491612  1741 net.cpp:406] inception_11a/3x3 <- inception_10a/output_inception_10a/output_0_split_1
I0121 17:48:37.491627  1741 net.cpp:380] inception_11a/3x3 -> inception_11a/3x3
I0121 17:48:37.496381  1741 net.cpp:122] Setting up inception_11a/3x3
I0121 17:48:37.496408  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.496414  1741 net.cpp:137] Memory required for data: 650855000
I0121 17:48:37.496428  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/bn1
I0121 17:48:37.496454  1741 net.cpp:84] Creating Layer inception_11a/3x3/bn1
I0121 17:48:37.496470  1741 net.cpp:406] inception_11a/3x3/bn1 <- inception_11a/3x3
I0121 17:48:37.496484  1741 net.cpp:367] inception_11a/3x3/bn1 -> inception_11a/3x3 (in-place)
I0121 17:48:37.496783  1741 net.cpp:122] Setting up inception_11a/3x3/bn1
I0121 17:48:37.496801  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.496806  1741 net.cpp:137] Memory required for data: 652903000
I0121 17:48:37.496855  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/scale1
I0121 17:48:37.496877  1741 net.cpp:84] Creating Layer inception_11a/3x3/scale1
I0121 17:48:37.496886  1741 net.cpp:406] inception_11a/3x3/scale1 <- inception_11a/3x3
I0121 17:48:37.496896  1741 net.cpp:367] inception_11a/3x3/scale1 -> inception_11a/3x3 (in-place)
I0121 17:48:37.496971  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/scale1
I0121 17:48:37.497160  1741 net.cpp:122] Setting up inception_11a/3x3/scale1
I0121 17:48:37.497180  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.497187  1741 net.cpp:137] Memory required for data: 654951000
I0121 17:48:37.497200  1741 layer_factory.hpp:77] Creating layer inception_11a/3x3/relu1
I0121 17:48:37.497220  1741 net.cpp:84] Creating Layer inception_11a/3x3/relu1
I0121 17:48:37.497228  1741 net.cpp:406] inception_11a/3x3/relu1 <- inception_11a/3x3
I0121 17:48:37.497239  1741 net.cpp:367] inception_11a/3x3/relu1 -> inception_11a/3x3 (in-place)
I0121 17:48:37.497603  1741 net.cpp:122] Setting up inception_11a/3x3/relu1
I0121 17:48:37.497633  1741 net.cpp:129] Top shape: 50 160 8 8 (512000)
I0121 17:48:37.497642  1741 net.cpp:137] Memory required for data: 656999000
I0121 17:48:37.497649  1741 layer_factory.hpp:77] Creating layer inception_11a/output
I0121 17:48:37.497660  1741 net.cpp:84] Creating Layer inception_11a/output
I0121 17:48:37.497671  1741 net.cpp:406] inception_11a/output <- inception_11a/1x1
I0121 17:48:37.497681  1741 net.cpp:406] inception_11a/output <- inception_11a/3x3
I0121 17:48:37.497690  1741 net.cpp:380] inception_11a/output -> inception_11a/output
I0121 17:48:37.497750  1741 net.cpp:122] Setting up inception_11a/output
I0121 17:48:37.497792  1741 net.cpp:129] Top shape: 50 336 8 8 (1075200)
I0121 17:48:37.497817  1741 net.cpp:137] Memory required for data: 661299800
I0121 17:48:37.497833  1741 layer_factory.hpp:77] Creating layer avg_pool_12/8x8_s1
I0121 17:48:37.497851  1741 net.cpp:84] Creating Layer avg_pool_12/8x8_s1
I0121 17:48:37.497860  1741 net.cpp:406] avg_pool_12/8x8_s1 <- inception_11a/output
I0121 17:48:37.497872  1741 net.cpp:380] avg_pool_12/8x8_s1 -> avg_pool_12/8x8_s1
I0121 17:48:37.498072  1741 net.cpp:122] Setting up avg_pool_12/8x8_s1
I0121 17:48:37.498095  1741 net.cpp:129] Top shape: 50 336 1 1 (16800)
I0121 17:48:37.498105  1741 net.cpp:137] Memory required for data: 661367000
I0121 17:48:37.498111  1741 layer_factory.hpp:77] Creating layer drop_8x8_s1
I0121 17:48:37.498126  1741 net.cpp:84] Creating Layer drop_8x8_s1
I0121 17:48:37.498139  1741 net.cpp:406] drop_8x8_s1 <- avg_pool_12/8x8_s1
I0121 17:48:37.498152  1741 net.cpp:367] drop_8x8_s1 -> avg_pool_12/8x8_s1 (in-place)
I0121 17:48:37.498208  1741 net.cpp:122] Setting up drop_8x8_s1
I0121 17:48:37.498225  1741 net.cpp:129] Top shape: 50 336 1 1 (16800)
I0121 17:48:37.498234  1741 net.cpp:137] Memory required for data: 661434200
I0121 17:48:37.498241  1741 layer_factory.hpp:77] Creating layer loss/classifier
I0121 17:48:37.498275  1741 net.cpp:84] Creating Layer loss/classifier
I0121 17:48:37.498284  1741 net.cpp:406] loss/classifier <- avg_pool_12/8x8_s1
I0121 17:48:37.498299  1741 net.cpp:380] loss/classifier -> loss/classifier
I0121 17:48:37.498530  1741 net.cpp:122] Setting up loss/classifier
I0121 17:48:37.498548  1741 net.cpp:129] Top shape: 50 10 (500)
I0121 17:48:37.498553  1741 net.cpp:137] Memory required for data: 661436200
I0121 17:48:37.498564  1741 layer_factory.hpp:77] Creating layer loss/classifier_loss/classifier_0_split
I0121 17:48:37.498582  1741 net.cpp:84] Creating Layer loss/classifier_loss/classifier_0_split
I0121 17:48:37.498597  1741 net.cpp:406] loss/classifier_loss/classifier_0_split <- loss/classifier
I0121 17:48:37.498612  1741 net.cpp:380] loss/classifier_loss/classifier_0_split -> loss/classifier_loss/classifier_0_split_0
I0121 17:48:37.498648  1741 net.cpp:380] loss/classifier_loss/classifier_0_split -> loss/classifier_loss/classifier_0_split_1
I0121 17:48:37.498751  1741 net.cpp:122] Setting up loss/classifier_loss/classifier_0_split
I0121 17:48:37.498775  1741 net.cpp:129] Top shape: 50 10 (500)
I0121 17:48:37.498783  1741 net.cpp:129] Top shape: 50 10 (500)
I0121 17:48:37.498790  1741 net.cpp:137] Memory required for data: 661440200
I0121 17:48:37.498797  1741 layer_factory.hpp:77] Creating layer loss
I0121 17:48:37.498809  1741 net.cpp:84] Creating Layer loss
I0121 17:48:37.498817  1741 net.cpp:406] loss <- loss/classifier_loss/classifier_0_split_0
I0121 17:48:37.498826  1741 net.cpp:406] loss <- label_data_1_split_0
I0121 17:48:37.498844  1741 net.cpp:380] loss -> loss
I0121 17:48:37.498860  1741 layer_factory.hpp:77] Creating layer loss
I0121 17:48:37.499291  1741 net.cpp:122] Setting up loss
I0121 17:48:37.499317  1741 net.cpp:129] Top shape: (1)
I0121 17:48:37.499327  1741 net.cpp:132]     with loss weight 1
I0121 17:48:37.499343  1741 net.cpp:137] Memory required for data: 661440204
I0121 17:48:37.499354  1741 layer_factory.hpp:77] Creating layer accuracy
I0121 17:48:37.501391  1741 net.cpp:84] Creating Layer accuracy
I0121 17:48:37.501412  1741 net.cpp:406] accuracy <- loss/classifier_loss/classifier_0_split_1
I0121 17:48:37.501428  1741 net.cpp:406] accuracy <- label_data_1_split_1
I0121 17:48:37.501438  1741 net.cpp:380] accuracy -> accuracy
I0121 17:48:37.501456  1741 net.cpp:122] Setting up accuracy
I0121 17:48:37.501469  1741 net.cpp:129] Top shape: (1)
I0121 17:48:37.501477  1741 net.cpp:137] Memory required for data: 661440208
I0121 17:48:37.501484  1741 net.cpp:200] accuracy does not need backward computation.
I0121 17:48:37.501492  1741 net.cpp:198] loss needs backward computation.
I0121 17:48:37.501502  1741 net.cpp:198] loss/classifier_loss/classifier_0_split needs backward computation.
I0121 17:48:37.501509  1741 net.cpp:198] loss/classifier needs backward computation.
I0121 17:48:37.501518  1741 net.cpp:198] drop_8x8_s1 needs backward computation.
I0121 17:48:37.501523  1741 net.cpp:198] avg_pool_12/8x8_s1 needs backward computation.
I0121 17:48:37.501533  1741 net.cpp:198] inception_11a/output needs backward computation.
I0121 17:48:37.501540  1741 net.cpp:198] inception_11a/3x3/relu1 needs backward computation.
I0121 17:48:37.501547  1741 net.cpp:198] inception_11a/3x3/scale1 needs backward computation.
I0121 17:48:37.501555  1741 net.cpp:198] inception_11a/3x3/bn1 needs backward computation.
I0121 17:48:37.501564  1741 net.cpp:198] inception_11a/3x3 needs backward computation.
I0121 17:48:37.501570  1741 net.cpp:198] inception_11a/1x1/relu1 needs backward computation.
I0121 17:48:37.501577  1741 net.cpp:198] inception_11a/1x1/scale1 needs backward computation.
I0121 17:48:37.501585  1741 net.cpp:198] inception_11a/1x1/bn1 needs backward computation.
I0121 17:48:37.501591  1741 net.cpp:198] inception_11a/1x1 needs backward computation.
I0121 17:48:37.501600  1741 net.cpp:198] inception_10a/output_inception_10a/output_0_split needs backward computation.
I0121 17:48:37.501606  1741 net.cpp:198] inception_10a/output needs backward computation.
I0121 17:48:37.501615  1741 net.cpp:198] inception_10a/3x3/relu1 needs backward computation.
I0121 17:48:37.501641  1741 net.cpp:198] inception_10a/3x3/scale1 needs backward computation.
I0121 17:48:37.501651  1741 net.cpp:198] inception_10a/3x3/bn1 needs backward computation.
I0121 17:48:37.501657  1741 net.cpp:198] inception_10a/3x3 needs backward computation.
I0121 17:48:37.501664  1741 net.cpp:198] inception_10a/1x1/relu1 needs backward computation.
I0121 17:48:37.501672  1741 net.cpp:198] inception_10a/1x1/scale1 needs backward computation.
I0121 17:48:37.501679  1741 net.cpp:198] inception_10a/1x1/bn1 needs backward computation.
I0121 17:48:37.501686  1741 net.cpp:198] inception_10a/1x1 needs backward computation.
I0121 17:48:37.501693  1741 net.cpp:198] downsample_9/output_downsample_9/output_0_split needs backward computation.
I0121 17:48:37.501701  1741 net.cpp:198] downsample_9/output needs backward computation.
I0121 17:48:37.501710  1741 net.cpp:198] downsample_9/pool_s2 needs backward computation.
I0121 17:48:37.501718  1741 net.cpp:198] downsample_9/3x3_s2/relu1 needs backward computation.
I0121 17:48:37.501725  1741 net.cpp:198] downsample_9/3x3_s2/scale1 needs backward computation.
I0121 17:48:37.501734  1741 net.cpp:198] downsample_9/3x3_s2/bn1 needs backward computation.
I0121 17:48:37.501741  1741 net.cpp:198] downsample_9/3x3_s2 needs backward computation.
I0121 17:48:37.501749  1741 net.cpp:198] inception_8a/output_inception_8a/output_0_split needs backward computation.
I0121 17:48:37.501755  1741 net.cpp:198] inception_8a/output needs backward computation.
I0121 17:48:37.501785  1741 net.cpp:198] inception_8a/3x3/relu1 needs backward computation.
I0121 17:48:37.501796  1741 net.cpp:198] inception_8a/3x3/scale1 needs backward computation.
I0121 17:48:37.501804  1741 net.cpp:198] inception_8a/3x3/bn1 needs backward computation.
I0121 17:48:37.501811  1741 net.cpp:198] inception_8a/3x3 needs backward computation.
I0121 17:48:37.501818  1741 net.cpp:198] inception_8a/1x1/relu1 needs backward computation.
I0121 17:48:37.501827  1741 net.cpp:198] inception_8a/1x1/scale1 needs backward computation.
I0121 17:48:37.501832  1741 net.cpp:198] inception_8a/1x1/bn1 needs backward computation.
I0121 17:48:37.501839  1741 net.cpp:198] inception_8a/1x1 needs backward computation.
I0121 17:48:37.501848  1741 net.cpp:198] inception_7a/output_inception_7a/output_0_split needs backward computation.
I0121 17:48:37.501863  1741 net.cpp:198] inception_7a/output needs backward computation.
I0121 17:48:37.501869  1741 net.cpp:198] inception_7a/3x3/relu1 needs backward computation.
I0121 17:48:37.501878  1741 net.cpp:198] inception_7a/3x3/scale1 needs backward computation.
I0121 17:48:37.501885  1741 net.cpp:198] inception_7a/3x3/bn1 needs backward computation.
I0121 17:48:37.501893  1741 net.cpp:198] inception_7a/3x3 needs backward computation.
I0121 17:48:37.501900  1741 net.cpp:198] inception_7a/1x1/relu1 needs backward computation.
I0121 17:48:37.501909  1741 net.cpp:198] inception_7a/1x1/scale1 needs backward computation.
I0121 17:48:37.501916  1741 net.cpp:198] inception_7a/1x1/bn1 needs backward computation.
I0121 17:48:37.501924  1741 net.cpp:198] inception_7a/1x1 needs backward computation.
I0121 17:48:37.501931  1741 net.cpp:198] inception_6a/output_inception_6a/output_0_split needs backward computation.
I0121 17:48:37.501940  1741 net.cpp:198] inception_6a/output needs backward computation.
I0121 17:48:37.501962  1741 net.cpp:198] inception_6a/3x3/relu1 needs backward computation.
I0121 17:48:37.501977  1741 net.cpp:198] inception_6a/3x3/scale1 needs backward computation.
I0121 17:48:37.501986  1741 net.cpp:198] inception_6a/3x3/bn1 needs backward computation.
I0121 17:48:37.501992  1741 net.cpp:198] inception_6a/3x3 needs backward computation.
I0121 17:48:37.502001  1741 net.cpp:198] inception_6a/1x1/relu1 needs backward computation.
I0121 17:48:37.502007  1741 net.cpp:198] inception_6a/1x1/scale1 needs backward computation.
I0121 17:48:37.502014  1741 net.cpp:198] inception_6a/1x1/bn1 needs backward computation.
I0121 17:48:37.502022  1741 net.cpp:198] inception_6a/1x1 needs backward computation.
I0121 17:48:37.502048  1741 net.cpp:198] inception_5a/output_inception_5a/output_0_split needs backward computation.
I0121 17:48:37.502058  1741 net.cpp:198] inception_5a/output needs backward computation.
I0121 17:48:37.502065  1741 net.cpp:198] inception_5a/3x3/relu1 needs backward computation.
I0121 17:48:37.502072  1741 net.cpp:198] inception_5a/3x3/scale1 needs backward computation.
I0121 17:48:37.502081  1741 net.cpp:198] inception_5a/3x3/bn1 needs backward computation.
I0121 17:48:37.502087  1741 net.cpp:198] inception_5a/3x3 needs backward computation.
I0121 17:48:37.502094  1741 net.cpp:198] inception_5a/1x1/relu1 needs backward computation.
I0121 17:48:37.502102  1741 net.cpp:198] inception_5a/1x1/scale1 needs backward computation.
I0121 17:48:37.502110  1741 net.cpp:198] inception_5a/1x1/bn1 needs backward computation.
I0121 17:48:37.502117  1741 net.cpp:198] inception_5a/1x1 needs backward computation.
I0121 17:48:37.502138  1741 net.cpp:198] downsample_4/output_downsample_4/output_0_split needs backward computation.
I0121 17:48:37.502156  1741 net.cpp:198] downsample_4/output needs backward computation.
I0121 17:48:37.502166  1741 net.cpp:198] downsample_4/pool_s2 needs backward computation.
I0121 17:48:37.502174  1741 net.cpp:198] downsample_4/3x3_s2/relu1 needs backward computation.
I0121 17:48:37.502182  1741 net.cpp:198] downsample_4/3x3_s2/scale1 needs backward computation.
I0121 17:48:37.502197  1741 net.cpp:198] downsample_4/3x3_s2/bn1 needs backward computation.
I0121 17:48:37.502207  1741 net.cpp:198] downsample_4/3x3_s2 needs backward computation.
I0121 17:48:37.502213  1741 net.cpp:198] inception_3a/output_inception_3a/output_0_split needs backward computation.
I0121 17:48:37.502221  1741 net.cpp:198] inception_3a/output needs backward computation.
I0121 17:48:37.502229  1741 net.cpp:198] inception_3a/3x3/relu1 needs backward computation.
I0121 17:48:37.502238  1741 net.cpp:198] inception_3a/3x3/scale1 needs backward computation.
I0121 17:48:37.502252  1741 net.cpp:198] inception_3a/3x3/bn1 needs backward computation.
I0121 17:48:37.502259  1741 net.cpp:198] inception_3a/3x3 needs backward computation.
I0121 17:48:37.502264  1741 net.cpp:198] inception_3a/1x1/relu1 needs backward computation.
I0121 17:48:37.502269  1741 net.cpp:198] inception_3a/1x1/scale1 needs backward computation.
I0121 17:48:37.502274  1741 net.cpp:198] inception_3a/1x1/bn1 needs backward computation.
I0121 17:48:37.502281  1741 net.cpp:198] inception_3a/1x1 needs backward computation.
I0121 17:48:37.502297  1741 net.cpp:198] inception_2a/output_inception_2a/output_0_split needs backward computation.
I0121 17:48:37.502307  1741 net.cpp:198] inception_2a/output needs backward computation.
I0121 17:48:37.502315  1741 net.cpp:198] inception_2a/3x3/relu1 needs backward computation.
I0121 17:48:37.502322  1741 net.cpp:198] inception_2a/3x3/scale1 needs backward computation.
I0121 17:48:37.502328  1741 net.cpp:198] inception_2a/3x3/bn1 needs backward computation.
I0121 17:48:37.502343  1741 net.cpp:198] inception_2a/3x3 needs backward computation.
I0121 17:48:37.502351  1741 net.cpp:198] inception_2a/1x1/relu1 needs backward computation.
I0121 17:48:37.502355  1741 net.cpp:198] inception_2a/1x1/scale1 needs backward computation.
I0121 17:48:37.502359  1741 net.cpp:198] inception_2a/1x1/bn1 needs backward computation.
I0121 17:48:37.502368  1741 net.cpp:198] inception_2a/1x1 needs backward computation.
I0121 17:48:37.502382  1741 net.cpp:198] conv1/3x3_s1_conv1/relu1_0_split needs backward computation.
I0121 17:48:37.502391  1741 net.cpp:198] conv1/relu1 needs backward computation.
I0121 17:48:37.502398  1741 net.cpp:198] conv1/scale1 needs backward computation.
I0121 17:48:37.502408  1741 net.cpp:198] conv1/bn1 needs backward computation.
I0121 17:48:37.502414  1741 net.cpp:198] conv1/3x3_s1 needs backward computation.
I0121 17:48:37.502430  1741 net.cpp:200] label_data_1_split does not need backward computation.
I0121 17:48:37.502437  1741 net.cpp:200] data does not need backward computation.
I0121 17:48:37.502480  1741 net.cpp:242] This network produces output accuracy
I0121 17:48:37.502511  1741 net.cpp:242] This network produces output loss
I0121 17:48:37.502630  1741 net.cpp:255] Network initialization done.
I0121 17:48:37.503033  1741 solver.cpp:56] Solver scaffolding done.
I0121 17:48:37.509593  1741 caffe.cpp:248] Starting Optimization
I0121 17:48:37.509615  1741 solver.cpp:272] Solving miniGoogleNet for CIFAR10, model 3
I0121 17:48:37.509620  1741 solver.cpp:273] Learning Rate Policy: step
I0121 17:48:37.513278  1741 solver.cpp:330] Iteration 0, Testing net (#0)
I0121 17:48:47.082695  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 17:48:47.293099  1741 solver.cpp:397]     Test net output #0: accuracy = 0.102111
I0121 17:48:47.293151  1741 solver.cpp:397]     Test net output #1: loss = 2.38631 (* 1 = 2.38631 loss)
I0121 17:48:47.685674  1741 solver.cpp:218] Iteration 0 (0 iter/s, 10.1762s/100 iters), loss = 2.48653
I0121 17:48:47.685755  1741 solver.cpp:237]     Train net output #0: loss = 2.48653 (* 1 = 2.48653 loss)
I0121 17:48:47.685803  1741 sgd_solver.cpp:105] Iteration 0, lr = 0.1
I0121 17:49:28.842061  1741 solver.cpp:218] Iteration 100 (2.42973 iter/s, 41.1568s/100 iters), loss = 1.38795
I0121 17:49:28.842283  1741 solver.cpp:237]     Train net output #0: loss = 1.38795 (* 1 = 1.38795 loss)
I0121 17:49:28.842304  1741 sgd_solver.cpp:105] Iteration 100, lr = 0.1
I0121 17:50:10.245914  1741 solver.cpp:218] Iteration 200 (2.41522 iter/s, 41.404s/100 iters), loss = 1.13971
I0121 17:50:10.246122  1741 solver.cpp:237]     Train net output #0: loss = 1.13971 (* 1 = 1.13971 loss)
I0121 17:50:10.246150  1741 sgd_solver.cpp:105] Iteration 200, lr = 0.1
I0121 17:50:51.764034  1741 solver.cpp:218] Iteration 300 (2.40857 iter/s, 41.5184s/100 iters), loss = 0.926158
I0121 17:50:51.764241  1741 solver.cpp:237]     Train net output #0: loss = 0.926158 (* 1 = 0.926158 loss)
I0121 17:50:51.764271  1741 sgd_solver.cpp:105] Iteration 300, lr = 0.1
I0121 17:51:27.538352  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 17:51:33.353437  1741 solver.cpp:218] Iteration 400 (2.40444 iter/s, 41.5897s/100 iters), loss = 1.06951
I0121 17:51:33.353541  1741 solver.cpp:237]     Train net output #0: loss = 1.06951 (* 1 = 1.06951 loss)
I0121 17:51:33.353559  1741 sgd_solver.cpp:105] Iteration 400, lr = 0.1
I0121 17:52:14.977622  1741 solver.cpp:218] Iteration 500 (2.40242 iter/s, 41.6246s/100 iters), loss = 0.85907
I0121 17:52:14.977833  1741 solver.cpp:237]     Train net output #0: loss = 0.85907 (* 1 = 0.85907 loss)
I0121 17:52:14.977854  1741 sgd_solver.cpp:105] Iteration 500, lr = 0.1
I0121 17:52:56.641324  1741 solver.cpp:218] Iteration 600 (2.40015 iter/s, 41.664s/100 iters), loss = 0.891724
I0121 17:52:56.641527  1741 solver.cpp:237]     Train net output #0: loss = 0.891724 (* 1 = 0.891724 loss)
I0121 17:52:56.641544  1741 sgd_solver.cpp:105] Iteration 600, lr = 0.1
I0121 17:53:38.319404  1741 solver.cpp:218] Iteration 700 (2.39933 iter/s, 41.6784s/100 iters), loss = 0.906215
I0121 17:53:38.319597  1741 solver.cpp:237]     Train net output #0: loss = 0.906215 (* 1 = 0.906215 loss)
I0121 17:53:38.319613  1741 sgd_solver.cpp:105] Iteration 700, lr = 0.1
I0121 17:54:10.443023  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 17:54:20.023324  1741 solver.cpp:218] Iteration 800 (2.39784 iter/s, 41.7042s/100 iters), loss = 0.811311
I0121 17:54:20.023417  1741 solver.cpp:237]     Train net output #0: loss = 0.811311 (* 1 = 0.811311 loss)
I0121 17:54:20.023432  1741 sgd_solver.cpp:105] Iteration 800, lr = 0.1
I0121 17:55:01.706213  1741 solver.cpp:218] Iteration 900 (2.39905 iter/s, 41.6832s/100 iters), loss = 0.714391
I0121 17:55:01.706344  1741 solver.cpp:237]     Train net output #0: loss = 0.714391 (* 1 = 0.714391 loss)
I0121 17:55:01.706359  1741 sgd_solver.cpp:105] Iteration 900, lr = 0.1
I0121 17:55:42.999600  1741 solver.cpp:330] Iteration 1000, Testing net (#0)
I0121 17:55:52.584604  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 17:55:52.800027  1741 solver.cpp:397]     Test net output #0: accuracy = 0.743667
I0121 17:55:52.800098  1741 solver.cpp:397]     Test net output #1: loss = 0.734581 (* 1 = 0.734581 loss)
I0121 17:55:53.216991  1741 solver.cpp:218] Iteration 1000 (1.94132 iter/s, 51.5112s/100 iters), loss = 0.799552
I0121 17:55:53.217073  1741 solver.cpp:237]     Train net output #0: loss = 0.799552 (* 1 = 0.799552 loss)
I0121 17:55:53.217087  1741 sgd_solver.cpp:105] Iteration 1000, lr = 0.1
I0121 17:56:34.818763  1741 solver.cpp:218] Iteration 1100 (2.40372 iter/s, 41.6021s/100 iters), loss = 0.723705
I0121 17:56:34.818958  1741 solver.cpp:237]     Train net output #0: loss = 0.723705 (* 1 = 0.723705 loss)
I0121 17:56:34.818974  1741 sgd_solver.cpp:105] Iteration 1100, lr = 0.1
I0121 17:57:02.747685  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 17:57:16.496852  1741 solver.cpp:218] Iteration 1200 (2.39933 iter/s, 41.6784s/100 iters), loss = 0.675094
I0121 17:57:16.497050  1741 solver.cpp:237]     Train net output #0: loss = 0.675094 (* 1 = 0.675094 loss)
I0121 17:57:16.497066  1741 sgd_solver.cpp:105] Iteration 1200, lr = 0.1
I0121 17:57:58.179787  1741 solver.cpp:218] Iteration 1300 (2.39904 iter/s, 41.6833s/100 iters), loss = 0.660678
I0121 17:57:58.179960  1741 solver.cpp:237]     Train net output #0: loss = 0.660678 (* 1 = 0.660678 loss)
I0121 17:57:58.179975  1741 sgd_solver.cpp:105] Iteration 1300, lr = 0.1
I0121 17:58:39.847739  1741 solver.cpp:218] Iteration 1400 (2.39991 iter/s, 41.6683s/100 iters), loss = 0.661451
I0121 17:58:39.847898  1741 solver.cpp:237]     Train net output #0: loss = 0.661451 (* 1 = 0.661451 loss)
I0121 17:58:39.847913  1741 sgd_solver.cpp:105] Iteration 1400, lr = 0.1
I0121 17:59:21.480638  1741 solver.cpp:218] Iteration 1500 (2.40193 iter/s, 41.6332s/100 iters), loss = 0.81055
I0121 17:59:21.480823  1741 solver.cpp:237]     Train net output #0: loss = 0.81055 (* 1 = 0.81055 loss)
I0121 17:59:21.480846  1741 sgd_solver.cpp:105] Iteration 1500, lr = 0.1
I0121 17:59:45.648226  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:00:03.127316  1741 solver.cpp:218] Iteration 1600 (2.40113 iter/s, 41.647s/100 iters), loss = 0.700922
I0121 18:00:03.127508  1741 solver.cpp:237]     Train net output #0: loss = 0.700922 (* 1 = 0.700922 loss)
I0121 18:00:03.127524  1741 sgd_solver.cpp:105] Iteration 1600, lr = 0.1
I0121 18:00:44.738639  1741 solver.cpp:218] Iteration 1700 (2.40317 iter/s, 41.6116s/100 iters), loss = 0.603608
I0121 18:00:44.738806  1741 solver.cpp:237]     Train net output #0: loss = 0.603608 (* 1 = 0.603608 loss)
I0121 18:00:44.738823  1741 sgd_solver.cpp:105] Iteration 1700, lr = 0.1
I0121 18:01:26.370579  1741 solver.cpp:218] Iteration 1800 (2.40198 iter/s, 41.6323s/100 iters), loss = 0.589694
I0121 18:01:26.370774  1741 solver.cpp:237]     Train net output #0: loss = 0.589694 (* 1 = 0.589694 loss)
I0121 18:01:26.370790  1741 sgd_solver.cpp:105] Iteration 1800, lr = 0.1
I0121 18:02:08.021869  1741 solver.cpp:218] Iteration 1900 (2.40087 iter/s, 41.6516s/100 iters), loss = 0.736803
I0121 18:02:08.022038  1741 solver.cpp:237]     Train net output #0: loss = 0.736803 (* 1 = 0.736803 loss)
I0121 18:02:08.022055  1741 sgd_solver.cpp:105] Iteration 1900, lr = 0.1
I0121 18:02:28.439122  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:02:49.242839  1741 solver.cpp:330] Iteration 2000, Testing net (#0)
I0121 18:02:58.780215  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:02:58.995599  1741 solver.cpp:397]     Test net output #0: accuracy = 0.775
I0121 18:02:58.995661  1741 solver.cpp:397]     Test net output #1: loss = 0.655632 (* 1 = 0.655632 loss)
I0121 18:02:59.410651  1741 solver.cpp:218] Iteration 2000 (1.94593 iter/s, 51.3892s/100 iters), loss = 0.561811
I0121 18:02:59.410740  1741 solver.cpp:237]     Train net output #0: loss = 0.561811 (* 1 = 0.561811 loss)
I0121 18:02:59.410754  1741 sgd_solver.cpp:105] Iteration 2000, lr = 0.1
I0121 18:03:41.013039  1741 solver.cpp:218] Iteration 2100 (2.40368 iter/s, 41.6028s/100 iters), loss = 0.544179
I0121 18:03:41.013258  1741 solver.cpp:237]     Train net output #0: loss = 0.544179 (* 1 = 0.544179 loss)
I0121 18:03:41.013274  1741 sgd_solver.cpp:105] Iteration 2100, lr = 0.1
I0121 18:04:22.627045  1741 solver.cpp:218] Iteration 2200 (2.40302 iter/s, 41.6143s/100 iters), loss = 0.480431
I0121 18:04:22.627177  1741 solver.cpp:237]     Train net output #0: loss = 0.480431 (* 1 = 0.480431 loss)
I0121 18:04:22.627194  1741 sgd_solver.cpp:105] Iteration 2200, lr = 0.1
I0121 18:05:04.251135  1741 solver.cpp:218] Iteration 2300 (2.40243 iter/s, 41.6245s/100 iters), loss = 0.76749
I0121 18:05:04.251312  1741 solver.cpp:237]     Train net output #0: loss = 0.76749 (* 1 = 0.76749 loss)
I0121 18:05:04.251327  1741 sgd_solver.cpp:105] Iteration 2300, lr = 0.1
I0121 18:05:20.494565  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:05:45.876277  1741 solver.cpp:218] Iteration 2400 (2.40238 iter/s, 41.6254s/100 iters), loss = 0.516316
I0121 18:05:45.876446  1741 solver.cpp:237]     Train net output #0: loss = 0.516316 (* 1 = 0.516316 loss)
I0121 18:05:45.876461  1741 sgd_solver.cpp:105] Iteration 2400, lr = 0.1
I0121 18:06:27.525740  1741 solver.cpp:218] Iteration 2500 (2.40097 iter/s, 41.6498s/100 iters), loss = 0.721381
I0121 18:06:27.525921  1741 solver.cpp:237]     Train net output #0: loss = 0.721381 (* 1 = 0.721381 loss)
I0121 18:06:27.525938  1741 sgd_solver.cpp:105] Iteration 2500, lr = 0.1
I0121 18:07:09.148752  1741 solver.cpp:218] Iteration 2600 (2.4025 iter/s, 41.6233s/100 iters), loss = 0.480821
I0121 18:07:09.148928  1741 solver.cpp:237]     Train net output #0: loss = 0.480821 (* 1 = 0.480821 loss)
I0121 18:07:09.148944  1741 sgd_solver.cpp:105] Iteration 2600, lr = 0.1
I0121 18:07:50.780046  1741 solver.cpp:218] Iteration 2700 (2.40202 iter/s, 41.6316s/100 iters), loss = 0.636896
I0121 18:07:50.780246  1741 solver.cpp:237]     Train net output #0: loss = 0.636896 (* 1 = 0.636896 loss)
I0121 18:07:50.780262  1741 sgd_solver.cpp:105] Iteration 2700, lr = 0.1
I0121 18:08:03.273219  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:08:32.413750  1741 solver.cpp:218] Iteration 2800 (2.40188 iter/s, 41.634s/100 iters), loss = 0.924309
I0121 18:08:32.413942  1741 solver.cpp:237]     Train net output #0: loss = 0.924309 (* 1 = 0.924309 loss)
I0121 18:08:32.413959  1741 sgd_solver.cpp:105] Iteration 2800, lr = 0.1
I0121 18:09:14.057191  1741 solver.cpp:218] Iteration 2900 (2.40132 iter/s, 41.6438s/100 iters), loss = 0.527393
I0121 18:09:14.057368  1741 solver.cpp:237]     Train net output #0: loss = 0.527393 (* 1 = 0.527393 loss)
I0121 18:09:14.057384  1741 sgd_solver.cpp:105] Iteration 2900, lr = 0.1
I0121 18:09:55.273187  1741 solver.cpp:330] Iteration 3000, Testing net (#0)
I0121 18:10:04.837234  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:10:05.052460  1741 solver.cpp:397]     Test net output #0: accuracy = 0.791334
I0121 18:10:05.052538  1741 solver.cpp:397]     Test net output #1: loss = 0.608781 (* 1 = 0.608781 loss)
I0121 18:10:05.472416  1741 solver.cpp:218] Iteration 3000 (1.94493 iter/s, 51.4157s/100 iters), loss = 0.571285
I0121 18:10:05.472508  1741 solver.cpp:237]     Train net output #0: loss = 0.571285 (* 1 = 0.571285 loss)
I0121 18:10:05.472523  1741 sgd_solver.cpp:105] Iteration 3000, lr = 0.1
I0121 18:10:47.114576  1741 solver.cpp:218] Iteration 3100 (2.40139 iter/s, 41.6426s/100 iters), loss = 0.474768
I0121 18:10:47.114770  1741 solver.cpp:237]     Train net output #0: loss = 0.474768 (* 1 = 0.474768 loss)
I0121 18:10:47.114785  1741 sgd_solver.cpp:105] Iteration 3100, lr = 0.1
I0121 18:10:55.445036  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:11:28.728090  1741 solver.cpp:218] Iteration 3200 (2.40305 iter/s, 41.6138s/100 iters), loss = 0.53606
I0121 18:11:28.728330  1741 solver.cpp:237]     Train net output #0: loss = 0.53606 (* 1 = 0.53606 loss)
I0121 18:11:28.728348  1741 sgd_solver.cpp:105] Iteration 3200, lr = 0.1
I0121 18:12:10.361838  1741 solver.cpp:218] Iteration 3300 (2.40188 iter/s, 41.634s/100 iters), loss = 0.487826
I0121 18:12:10.362041  1741 solver.cpp:237]     Train net output #0: loss = 0.487826 (* 1 = 0.487826 loss)
I0121 18:12:10.362058  1741 sgd_solver.cpp:105] Iteration 3300, lr = 0.1
I0121 18:12:51.991112  1741 solver.cpp:218] Iteration 3400 (2.40214 iter/s, 41.6296s/100 iters), loss = 0.663651
I0121 18:12:51.991288  1741 solver.cpp:237]     Train net output #0: loss = 0.663651 (* 1 = 0.663651 loss)
I0121 18:12:51.991303  1741 sgd_solver.cpp:105] Iteration 3400, lr = 0.1
I0121 18:13:33.633780  1741 solver.cpp:218] Iteration 3500 (2.40137 iter/s, 41.643s/100 iters), loss = 0.688982
I0121 18:13:33.633965  1741 solver.cpp:237]     Train net output #0: loss = 0.688982 (* 1 = 0.688982 loss)
I0121 18:13:33.633980  1741 sgd_solver.cpp:105] Iteration 3500, lr = 0.1
I0121 18:13:38.217677  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:14:15.264150  1741 solver.cpp:218] Iteration 3600 (2.40207 iter/s, 41.6307s/100 iters), loss = 0.506578
I0121 18:14:15.264335  1741 solver.cpp:237]     Train net output #0: loss = 0.506578 (* 1 = 0.506578 loss)
I0121 18:14:15.264351  1741 sgd_solver.cpp:105] Iteration 3600, lr = 0.1
I0121 18:14:56.897018  1741 solver.cpp:218] Iteration 3700 (2.40193 iter/s, 41.6332s/100 iters), loss = 0.454428
I0121 18:14:56.897181  1741 solver.cpp:237]     Train net output #0: loss = 0.454428 (* 1 = 0.454428 loss)
I0121 18:14:56.897197  1741 sgd_solver.cpp:105] Iteration 3700, lr = 0.1
I0121 18:15:38.506383  1741 solver.cpp:218] Iteration 3800 (2.40329 iter/s, 41.6097s/100 iters), loss = 0.51083
I0121 18:15:38.506557  1741 solver.cpp:237]     Train net output #0: loss = 0.51083 (* 1 = 0.51083 loss)
I0121 18:15:38.506575  1741 sgd_solver.cpp:105] Iteration 3800, lr = 0.1
I0121 18:16:20.111804  1741 solver.cpp:218] Iteration 3900 (2.40351 iter/s, 41.6058s/100 iters), loss = 0.609598
I0121 18:16:20.112006  1741 solver.cpp:237]     Train net output #0: loss = 0.609598 (* 1 = 0.609598 loss)
I0121 18:16:20.112030  1741 sgd_solver.cpp:105] Iteration 3900, lr = 0.1
I0121 18:16:20.951072  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:17:01.311146  1741 solver.cpp:330] Iteration 4000, Testing net (#0)
I0121 18:17:10.861291  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:17:11.077925  1741 solver.cpp:397]     Test net output #0: accuracy = 0.813666
I0121 18:17:11.078002  1741 solver.cpp:397]     Test net output #1: loss = 0.557632 (* 1 = 0.557632 loss)
I0121 18:17:11.495728  1741 solver.cpp:218] Iteration 4000 (1.94612 iter/s, 51.3843s/100 iters), loss = 0.426421
I0121 18:17:11.495832  1741 solver.cpp:237]     Train net output #0: loss = 0.426421 (* 1 = 0.426421 loss)
I0121 18:17:11.495851  1741 sgd_solver.cpp:105] Iteration 4000, lr = 0.1
I0121 18:17:53.083732  1741 solver.cpp:218] Iteration 4100 (2.40452 iter/s, 41.5884s/100 iters), loss = 0.421762
I0121 18:17:53.083909  1741 solver.cpp:237]     Train net output #0: loss = 0.421762 (* 1 = 0.421762 loss)
I0121 18:17:53.083925  1741 sgd_solver.cpp:105] Iteration 4100, lr = 0.1
I0121 18:18:34.677614  1741 solver.cpp:218] Iteration 4200 (2.40418 iter/s, 41.5942s/100 iters), loss = 0.539359
I0121 18:18:34.677774  1741 solver.cpp:237]     Train net output #0: loss = 0.539359 (* 1 = 0.539359 loss)
I0121 18:18:34.677791  1741 sgd_solver.cpp:105] Iteration 4200, lr = 0.1
I0121 18:19:12.981997  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:19:16.314460  1741 solver.cpp:218] Iteration 4300 (2.4017 iter/s, 41.6372s/100 iters), loss = 0.574876
I0121 18:19:16.314553  1741 solver.cpp:237]     Train net output #0: loss = 0.574876 (* 1 = 0.574876 loss)
I0121 18:19:16.314568  1741 sgd_solver.cpp:105] Iteration 4300, lr = 0.1
I0121 18:19:57.936444  1741 solver.cpp:218] Iteration 4400 (2.40255 iter/s, 41.6224s/100 iters), loss = 0.563348
I0121 18:19:57.936661  1741 solver.cpp:237]     Train net output #0: loss = 0.563348 (* 1 = 0.563348 loss)
I0121 18:19:57.936678  1741 sgd_solver.cpp:105] Iteration 4400, lr = 0.1
I0121 18:20:39.592319  1741 solver.cpp:218] Iteration 4500 (2.40061 iter/s, 41.6561s/100 iters), loss = 0.488238
I0121 18:20:39.592521  1741 solver.cpp:237]     Train net output #0: loss = 0.488238 (* 1 = 0.488238 loss)
I0121 18:20:39.592541  1741 sgd_solver.cpp:105] Iteration 4500, lr = 0.1
I0121 18:21:21.214954  1741 solver.cpp:218] Iteration 4600 (2.40252 iter/s, 41.6229s/100 iters), loss = 0.668235
I0121 18:21:21.215142  1741 solver.cpp:237]     Train net output #0: loss = 0.668235 (* 1 = 0.668235 loss)
I0121 18:21:21.215157  1741 sgd_solver.cpp:105] Iteration 4600, lr = 0.1
I0121 18:21:55.750790  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:22:02.816738  1741 solver.cpp:218] Iteration 4700 (2.40373 iter/s, 41.6021s/100 iters), loss = 0.482258
I0121 18:22:02.816845  1741 solver.cpp:237]     Train net output #0: loss = 0.482258 (* 1 = 0.482258 loss)
I0121 18:22:02.816860  1741 sgd_solver.cpp:105] Iteration 4700, lr = 0.1
I0121 18:22:44.422433  1741 solver.cpp:218] Iteration 4800 (2.4035 iter/s, 41.6061s/100 iters), loss = 0.551543
I0121 18:22:44.422619  1741 solver.cpp:237]     Train net output #0: loss = 0.551543 (* 1 = 0.551543 loss)
I0121 18:22:44.422636  1741 sgd_solver.cpp:105] Iteration 4800, lr = 0.1
I0121 18:23:26.059569  1741 solver.cpp:218] Iteration 4900 (2.40168 iter/s, 41.6375s/100 iters), loss = 0.61983
I0121 18:23:26.059748  1741 solver.cpp:237]     Train net output #0: loss = 0.61983 (* 1 = 0.61983 loss)
I0121 18:23:26.059765  1741 sgd_solver.cpp:105] Iteration 4900, lr = 0.1
I0121 18:24:07.323518  1741 solver.cpp:330] Iteration 5000, Testing net (#0)
I0121 18:24:16.880954  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:24:17.095944  1741 solver.cpp:397]     Test net output #0: accuracy = 0.804334
I0121 18:24:17.096014  1741 solver.cpp:397]     Test net output #1: loss = 0.578434 (* 1 = 0.578434 loss)
I0121 18:24:17.513381  1741 solver.cpp:218] Iteration 5000 (1.94347 iter/s, 51.4542s/100 iters), loss = 0.423024
I0121 18:24:17.513475  1741 solver.cpp:237]     Train net output #0: loss = 0.423024 (* 1 = 0.423024 loss)
I0121 18:24:17.513489  1741 sgd_solver.cpp:105] Iteration 5000, lr = 0.1
I0121 18:24:48.346832  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:24:59.165681  1741 solver.cpp:218] Iteration 5100 (2.4008 iter/s, 41.6527s/100 iters), loss = 0.397451
I0121 18:24:59.165791  1741 solver.cpp:237]     Train net output #0: loss = 0.397451 (* 1 = 0.397451 loss)
I0121 18:24:59.165807  1741 sgd_solver.cpp:105] Iteration 5100, lr = 0.1
I0121 18:25:40.783574  1741 solver.cpp:218] Iteration 5200 (2.40279 iter/s, 41.6183s/100 iters), loss = 0.530851
I0121 18:25:40.783732  1741 solver.cpp:237]     Train net output #0: loss = 0.530851 (* 1 = 0.530851 loss)
I0121 18:25:40.783747  1741 sgd_solver.cpp:105] Iteration 5200, lr = 0.1
I0121 18:26:22.392467  1741 solver.cpp:218] Iteration 5300 (2.40332 iter/s, 41.6092s/100 iters), loss = 0.453237
I0121 18:26:22.392649  1741 solver.cpp:237]     Train net output #0: loss = 0.453237 (* 1 = 0.453237 loss)
I0121 18:26:22.392665  1741 sgd_solver.cpp:105] Iteration 5300, lr = 0.1
I0121 18:27:04.006417  1741 solver.cpp:218] Iteration 5400 (2.40302 iter/s, 41.6142s/100 iters), loss = 0.474978
I0121 18:27:04.006588  1741 solver.cpp:237]     Train net output #0: loss = 0.474978 (* 1 = 0.474978 loss)
I0121 18:27:04.006605  1741 sgd_solver.cpp:105] Iteration 5400, lr = 0.1
I0121 18:27:30.654476  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:27:45.622771  1741 solver.cpp:218] Iteration 5500 (2.40288 iter/s, 41.6167s/100 iters), loss = 0.517216
I0121 18:27:45.622943  1741 solver.cpp:237]     Train net output #0: loss = 0.517216 (* 1 = 0.517216 loss)
I0121 18:27:45.622964  1741 sgd_solver.cpp:105] Iteration 5500, lr = 0.1
I0121 18:28:27.229192  1741 solver.cpp:218] Iteration 5600 (2.40346 iter/s, 41.6067s/100 iters), loss = 0.652632
I0121 18:28:27.229411  1741 solver.cpp:237]     Train net output #0: loss = 0.652632 (* 1 = 0.652632 loss)
I0121 18:28:27.229427  1741 sgd_solver.cpp:105] Iteration 5600, lr = 0.1
I0121 18:29:08.851020  1741 solver.cpp:218] Iteration 5700 (2.40257 iter/s, 41.6221s/100 iters), loss = 0.528013
I0121 18:29:08.851222  1741 solver.cpp:237]     Train net output #0: loss = 0.528013 (* 1 = 0.528013 loss)
I0121 18:29:08.851244  1741 sgd_solver.cpp:105] Iteration 5700, lr = 0.1
I0121 18:29:50.460824  1741 solver.cpp:218] Iteration 5800 (2.40326 iter/s, 41.6101s/100 iters), loss = 0.597176
I0121 18:29:50.461015  1741 solver.cpp:237]     Train net output #0: loss = 0.597176 (* 1 = 0.597176 loss)
I0121 18:29:50.461030  1741 sgd_solver.cpp:105] Iteration 5800, lr = 0.1
I0121 18:30:13.347285  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:30:32.063935  1741 solver.cpp:218] Iteration 5900 (2.40365 iter/s, 41.6034s/100 iters), loss = 0.433835
I0121 18:30:32.064064  1741 solver.cpp:237]     Train net output #0: loss = 0.433835 (* 1 = 0.433835 loss)
I0121 18:30:32.064079  1741 sgd_solver.cpp:105] Iteration 5900, lr = 0.1
I0121 18:31:13.258905  1741 solver.cpp:330] Iteration 6000, Testing net (#0)
I0121 18:31:22.814934  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:31:23.029491  1741 solver.cpp:397]     Test net output #0: accuracy = 0.794889
I0121 18:31:23.029564  1741 solver.cpp:397]     Test net output #1: loss = 0.609999 (* 1 = 0.609999 loss)
I0121 18:31:23.446795  1741 solver.cpp:218] Iteration 6000 (1.94616 iter/s, 51.3834s/100 iters), loss = 0.561595
I0121 18:31:23.446884  1741 solver.cpp:237]     Train net output #0: loss = 0.561595 (* 1 = 0.561595 loss)
I0121 18:31:23.446900  1741 sgd_solver.cpp:105] Iteration 6000, lr = 0.1
I0121 18:32:05.057569  1741 solver.cpp:218] Iteration 6100 (2.4032 iter/s, 41.6111s/100 iters), loss = 0.621384
I0121 18:32:05.057750  1741 solver.cpp:237]     Train net output #0: loss = 0.621384 (* 1 = 0.621384 loss)
I0121 18:32:05.057765  1741 sgd_solver.cpp:105] Iteration 6100, lr = 0.1
I0121 18:32:46.649993  1741 solver.cpp:218] Iteration 6200 (2.40427 iter/s, 41.5927s/100 iters), loss = 0.592131
I0121 18:32:46.650125  1741 solver.cpp:237]     Train net output #0: loss = 0.592131 (* 1 = 0.592131 loss)
I0121 18:32:46.650146  1741 sgd_solver.cpp:105] Iteration 6200, lr = 0.1
I0121 18:33:05.391021  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:33:28.265837  1741 solver.cpp:218] Iteration 6300 (2.40291 iter/s, 41.6162s/100 iters), loss = 0.440081
I0121 18:33:28.266010  1741 solver.cpp:237]     Train net output #0: loss = 0.440081 (* 1 = 0.440081 loss)
I0121 18:33:28.266027  1741 sgd_solver.cpp:105] Iteration 6300, lr = 0.1
I0121 18:34:09.873288  1741 solver.cpp:218] Iteration 6400 (2.4034 iter/s, 41.6078s/100 iters), loss = 0.564278
I0121 18:34:09.873423  1741 solver.cpp:237]     Train net output #0: loss = 0.564278 (* 1 = 0.564278 loss)
I0121 18:34:09.873442  1741 sgd_solver.cpp:105] Iteration 6400, lr = 0.1
I0121 18:34:51.479540  1741 solver.cpp:218] Iteration 6500 (2.40347 iter/s, 41.6066s/100 iters), loss = 0.571719
I0121 18:34:51.479696  1741 solver.cpp:237]     Train net output #0: loss = 0.571719 (* 1 = 0.571719 loss)
I0121 18:34:51.479718  1741 sgd_solver.cpp:105] Iteration 6500, lr = 0.1
I0121 18:35:33.065369  1741 solver.cpp:218] Iteration 6600 (2.40465 iter/s, 41.5862s/100 iters), loss = 0.412084
I0121 18:35:33.065511  1741 solver.cpp:237]     Train net output #0: loss = 0.412084 (* 1 = 0.412084 loss)
I0121 18:35:33.065531  1741 sgd_solver.cpp:105] Iteration 6600, lr = 0.1
I0121 18:35:48.050914  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:36:14.674480  1741 solver.cpp:218] Iteration 6700 (2.4033 iter/s, 41.6095s/100 iters), loss = 0.472615
I0121 18:36:14.674666  1741 solver.cpp:237]     Train net output #0: loss = 0.472615 (* 1 = 0.472615 loss)
I0121 18:36:14.674682  1741 sgd_solver.cpp:105] Iteration 6700, lr = 0.1
I0121 18:36:56.274672  1741 solver.cpp:218] Iteration 6800 (2.40382 iter/s, 41.6005s/100 iters), loss = 0.440031
I0121 18:36:56.274884  1741 solver.cpp:237]     Train net output #0: loss = 0.440031 (* 1 = 0.440031 loss)
I0121 18:36:56.274900  1741 sgd_solver.cpp:105] Iteration 6800, lr = 0.1
I0121 18:37:37.861490  1741 solver.cpp:218] Iteration 6900 (2.40459 iter/s, 41.5871s/100 iters), loss = 0.36751
I0121 18:37:37.861660  1741 solver.cpp:237]     Train net output #0: loss = 0.36751 (* 1 = 0.36751 loss)
I0121 18:37:37.861675  1741 sgd_solver.cpp:105] Iteration 6900, lr = 0.1
I0121 18:38:19.086333  1741 solver.cpp:330] Iteration 7000, Testing net (#0)
I0121 18:38:28.637892  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:38:28.852053  1741 solver.cpp:397]     Test net output #0: accuracy = 0.802889
I0121 18:38:28.852133  1741 solver.cpp:397]     Test net output #1: loss = 0.571213 (* 1 = 0.571213 loss)
I0121 18:38:29.266906  1741 solver.cpp:218] Iteration 7000 (1.9453 iter/s, 51.4058s/100 iters), loss = 0.410564
I0121 18:38:29.266996  1741 solver.cpp:237]     Train net output #0: loss = 0.410564 (* 1 = 0.410564 loss)
I0121 18:38:29.267014  1741 sgd_solver.cpp:105] Iteration 7000, lr = 0.1
I0121 18:38:40.509035  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:39:10.868592  1741 solver.cpp:218] Iteration 7100 (2.40372 iter/s, 41.6021s/100 iters), loss = 0.68185
I0121 18:39:10.868721  1741 solver.cpp:237]     Train net output #0: loss = 0.68185 (* 1 = 0.68185 loss)
I0121 18:39:10.868736  1741 sgd_solver.cpp:105] Iteration 7100, lr = 0.1
I0121 18:39:52.382231  1741 solver.cpp:218] Iteration 7200 (2.40883 iter/s, 41.514s/100 iters), loss = 0.514755
I0121 18:39:52.382364  1741 solver.cpp:237]     Train net output #0: loss = 0.514755 (* 1 = 0.514755 loss)
I0121 18:39:52.382380  1741 sgd_solver.cpp:105] Iteration 7200, lr = 0.1
I0121 18:40:33.955669  1741 solver.cpp:218] Iteration 7300 (2.40536 iter/s, 41.5738s/100 iters), loss = 0.400246
I0121 18:40:33.955829  1741 solver.cpp:237]     Train net output #0: loss = 0.400246 (* 1 = 0.400246 loss)
I0121 18:40:33.955845  1741 sgd_solver.cpp:105] Iteration 7300, lr = 0.1
I0121 18:41:15.553794  1741 solver.cpp:218] Iteration 7400 (2.40394 iter/s, 41.5984s/100 iters), loss = 0.513719
I0121 18:41:15.553980  1741 solver.cpp:237]     Train net output #0: loss = 0.513719 (* 1 = 0.513719 loss)
I0121 18:41:15.553997  1741 sgd_solver.cpp:105] Iteration 7400, lr = 0.1
I0121 18:41:22.632490  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:41:57.155611  1741 solver.cpp:218] Iteration 7500 (2.40372 iter/s, 41.6021s/100 iters), loss = 0.39176
I0121 18:41:57.155818  1741 solver.cpp:237]     Train net output #0: loss = 0.39176 (* 1 = 0.39176 loss)
I0121 18:41:57.155834  1741 sgd_solver.cpp:105] Iteration 7500, lr = 0.1
I0121 18:42:38.760222  1741 solver.cpp:218] Iteration 7600 (2.40356 iter/s, 41.6049s/100 iters), loss = 0.550935
I0121 18:42:38.760390  1741 solver.cpp:237]     Train net output #0: loss = 0.550935 (* 1 = 0.550935 loss)
I0121 18:42:38.760406  1741 sgd_solver.cpp:105] Iteration 7600, lr = 0.1
I0121 18:43:20.366896  1741 solver.cpp:218] Iteration 7700 (2.40344 iter/s, 41.607s/100 iters), loss = 0.565261
I0121 18:43:20.367074  1741 solver.cpp:237]     Train net output #0: loss = 0.565261 (* 1 = 0.565261 loss)
I0121 18:43:20.367090  1741 sgd_solver.cpp:105] Iteration 7700, lr = 0.1
I0121 18:44:01.955765  1741 solver.cpp:218] Iteration 7800 (2.40447 iter/s, 41.5892s/100 iters), loss = 0.541205
I0121 18:44:01.955953  1741 solver.cpp:237]     Train net output #0: loss = 0.541205 (* 1 = 0.541205 loss)
I0121 18:44:01.955970  1741 sgd_solver.cpp:105] Iteration 7800, lr = 0.1
I0121 18:44:05.290263  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:44:43.551196  1741 solver.cpp:218] Iteration 7900 (2.40409 iter/s, 41.5957s/100 iters), loss = 0.459245
I0121 18:44:43.551332  1741 solver.cpp:237]     Train net output #0: loss = 0.459245 (* 1 = 0.459245 loss)
I0121 18:44:43.551352  1741 sgd_solver.cpp:105] Iteration 7900, lr = 0.1
I0121 18:45:24.734692  1741 solver.cpp:330] Iteration 8000, Testing net (#0)
I0121 18:45:34.288130  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:45:34.504287  1741 solver.cpp:397]     Test net output #0: accuracy = 0.813444
I0121 18:45:34.504359  1741 solver.cpp:397]     Test net output #1: loss = 0.558727 (* 1 = 0.558727 loss)
I0121 18:45:34.921949  1741 solver.cpp:218] Iteration 8000 (1.94661 iter/s, 51.3712s/100 iters), loss = 0.572463
I0121 18:45:34.922047  1741 solver.cpp:237]     Train net output #0: loss = 0.572463 (* 1 = 0.572463 loss)
I0121 18:45:34.922066  1741 sgd_solver.cpp:105] Iteration 8000, lr = 0.1
I0121 18:46:16.519551  1741 solver.cpp:218] Iteration 8100 (2.40396 iter/s, 41.598s/100 iters), loss = 0.543945
I0121 18:46:16.519740  1741 solver.cpp:237]     Train net output #0: loss = 0.543945 (* 1 = 0.543945 loss)
I0121 18:46:16.519758  1741 sgd_solver.cpp:105] Iteration 8100, lr = 0.1
I0121 18:46:57.717974  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:46:58.131398  1741 solver.cpp:218] Iteration 8200 (2.40314 iter/s, 41.6121s/100 iters), loss = 0.376625
I0121 18:46:58.131496  1741 solver.cpp:237]     Train net output #0: loss = 0.376625 (* 1 = 0.376625 loss)
I0121 18:46:58.131512  1741 sgd_solver.cpp:105] Iteration 8200, lr = 0.1
I0121 18:47:39.730269  1741 solver.cpp:218] Iteration 8300 (2.40389 iter/s, 41.5993s/100 iters), loss = 0.530969
I0121 18:47:39.730448  1741 solver.cpp:237]     Train net output #0: loss = 0.530969 (* 1 = 0.530969 loss)
I0121 18:47:39.730463  1741 sgd_solver.cpp:105] Iteration 8300, lr = 0.1
I0121 18:48:21.298113  1741 solver.cpp:218] Iteration 8400 (2.40569 iter/s, 41.5681s/100 iters), loss = 0.566893
I0121 18:48:21.298300  1741 solver.cpp:237]     Train net output #0: loss = 0.566893 (* 1 = 0.566893 loss)
I0121 18:48:21.298321  1741 sgd_solver.cpp:105] Iteration 8400, lr = 0.1
I0121 18:49:02.888936  1741 solver.cpp:218] Iteration 8500 (2.40436 iter/s, 41.5912s/100 iters), loss = 0.555647
I0121 18:49:02.889117  1741 solver.cpp:237]     Train net output #0: loss = 0.555647 (* 1 = 0.555647 loss)
I0121 18:49:02.889140  1741 sgd_solver.cpp:105] Iteration 8500, lr = 0.1
I0121 18:49:39.919744  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:49:44.493646  1741 solver.cpp:218] Iteration 8600 (2.40356 iter/s, 41.605s/100 iters), loss = 0.59739
I0121 18:49:44.493789  1741 solver.cpp:237]     Train net output #0: loss = 0.59739 (* 1 = 0.59739 loss)
I0121 18:49:44.493811  1741 sgd_solver.cpp:105] Iteration 8600, lr = 0.1
I0121 18:50:26.072818  1741 solver.cpp:218] Iteration 8700 (2.40503 iter/s, 41.5796s/100 iters), loss = 0.397621
I0121 18:50:26.072947  1741 solver.cpp:237]     Train net output #0: loss = 0.397621 (* 1 = 0.397621 loss)
I0121 18:50:26.072965  1741 sgd_solver.cpp:105] Iteration 8700, lr = 0.1
I0121 18:51:07.646446  1741 solver.cpp:218] Iteration 8800 (2.40535 iter/s, 41.574s/100 iters), loss = 0.646893
I0121 18:51:07.646622  1741 solver.cpp:237]     Train net output #0: loss = 0.646893 (* 1 = 0.646893 loss)
I0121 18:51:07.646643  1741 sgd_solver.cpp:105] Iteration 8800, lr = 0.1
I0121 18:51:49.208010  1741 solver.cpp:218] Iteration 8900 (2.40605 iter/s, 41.5619s/100 iters), loss = 0.52249
I0121 18:51:49.208187  1741 solver.cpp:237]     Train net output #0: loss = 0.52249 (* 1 = 0.52249 loss)
I0121 18:51:49.208210  1741 sgd_solver.cpp:105] Iteration 8900, lr = 0.1
I0121 18:52:22.490761  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:52:30.384498  1741 solver.cpp:330] Iteration 9000, Testing net (#0)
I0121 18:52:39.902348  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:52:40.117981  1741 solver.cpp:397]     Test net output #0: accuracy = 0.812445
I0121 18:52:40.118043  1741 solver.cpp:397]     Test net output #1: loss = 0.544267 (* 1 = 0.544267 loss)
I0121 18:52:40.534721  1741 solver.cpp:218] Iteration 9000 (1.94829 iter/s, 51.3272s/100 iters), loss = 0.499524
I0121 18:52:40.534821  1741 solver.cpp:237]     Train net output #0: loss = 0.499524 (* 1 = 0.499524 loss)
I0121 18:52:40.534840  1741 sgd_solver.cpp:105] Iteration 9000, lr = 0.1
I0121 18:53:22.168555  1741 solver.cpp:218] Iteration 9100 (2.40187 iter/s, 41.6342s/100 iters), loss = 0.567261
I0121 18:53:22.168781  1741 solver.cpp:237]     Train net output #0: loss = 0.567261 (* 1 = 0.567261 loss)
I0121 18:53:22.168797  1741 sgd_solver.cpp:105] Iteration 9100, lr = 0.1
I0121 18:54:03.819825  1741 solver.cpp:218] Iteration 9200 (2.40087 iter/s, 41.6516s/100 iters), loss = 0.445508
I0121 18:54:03.820006  1741 solver.cpp:237]     Train net output #0: loss = 0.445508 (* 1 = 0.445508 loss)
I0121 18:54:03.820024  1741 sgd_solver.cpp:105] Iteration 9200, lr = 0.1
I0121 18:54:45.460718  1741 solver.cpp:218] Iteration 9300 (2.40147 iter/s, 41.6412s/100 iters), loss = 0.378947
I0121 18:54:45.460898  1741 solver.cpp:237]     Train net output #0: loss = 0.378947 (* 1 = 0.378947 loss)
I0121 18:54:45.460914  1741 sgd_solver.cpp:105] Iteration 9300, lr = 0.1
I0121 18:55:14.645758  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:55:27.136345  1741 solver.cpp:218] Iteration 9400 (2.39947 iter/s, 41.6759s/100 iters), loss = 0.627149
I0121 18:55:27.136544  1741 solver.cpp:237]     Train net output #0: loss = 0.627149 (* 1 = 0.627149 loss)
I0121 18:55:27.136560  1741 sgd_solver.cpp:105] Iteration 9400, lr = 0.1
I0121 18:56:08.807268  1741 solver.cpp:218] Iteration 9500 (2.39974 iter/s, 41.6712s/100 iters), loss = 0.516024
I0121 18:56:08.807446  1741 solver.cpp:237]     Train net output #0: loss = 0.516024 (* 1 = 0.516024 loss)
I0121 18:56:08.807461  1741 sgd_solver.cpp:105] Iteration 9500, lr = 0.1
I0121 18:56:50.439489  1741 solver.cpp:218] Iteration 9600 (2.40197 iter/s, 41.6325s/100 iters), loss = 0.477526
I0121 18:56:50.439615  1741 solver.cpp:237]     Train net output #0: loss = 0.477526 (* 1 = 0.477526 loss)
I0121 18:56:50.439630  1741 sgd_solver.cpp:105] Iteration 9600, lr = 0.1
I0121 18:57:32.050683  1741 solver.cpp:218] Iteration 9700 (2.40318 iter/s, 41.6116s/100 iters), loss = 0.520569
I0121 18:57:32.050817  1741 solver.cpp:237]     Train net output #0: loss = 0.520569 (* 1 = 0.520569 loss)
I0121 18:57:32.050834  1741 sgd_solver.cpp:105] Iteration 9700, lr = 0.1
I0121 18:57:57.444803  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:58:13.680573  1741 solver.cpp:218] Iteration 9800 (2.4021 iter/s, 41.6302s/100 iters), loss = 0.547972
I0121 18:58:13.680702  1741 solver.cpp:237]     Train net output #0: loss = 0.547972 (* 1 = 0.547972 loss)
I0121 18:58:13.680718  1741 sgd_solver.cpp:105] Iteration 9800, lr = 0.1
I0121 18:58:55.294600  1741 solver.cpp:218] Iteration 9900 (2.40301 iter/s, 41.6144s/100 iters), loss = 0.542583
I0121 18:58:55.294785  1741 solver.cpp:237]     Train net output #0: loss = 0.542583 (* 1 = 0.542583 loss)
I0121 18:58:55.294800  1741 sgd_solver.cpp:105] Iteration 9900, lr = 0.1
I0121 18:59:36.482383  1741 solver.cpp:447] Snapshotting to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_10000.caffemodel
I0121 18:59:36.515317  1741 sgd_solver.cpp:273] Snapshotting solver state to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_10000.solverstate
I0121 18:59:36.521628  1741 solver.cpp:330] Iteration 10000, Testing net (#0)
I0121 18:59:46.052947  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 18:59:46.268229  1741 solver.cpp:397]     Test net output #0: accuracy = 0.803778
I0121 18:59:46.268304  1741 solver.cpp:397]     Test net output #1: loss = 0.579637 (* 1 = 0.579637 loss)
I0121 18:59:46.682371  1741 solver.cpp:218] Iteration 10000 (1.94597 iter/s, 51.3882s/100 iters), loss = 0.569128
I0121 18:59:46.682466  1741 solver.cpp:237]     Train net output #0: loss = 0.569128 (* 1 = 0.569128 loss)
I0121 18:59:46.682480  1741 sgd_solver.cpp:105] Iteration 10000, lr = 0.01
I0121 19:00:28.282094  1741 solver.cpp:218] Iteration 10100 (2.40384 iter/s, 41.6001s/100 iters), loss = 0.423115
I0121 19:00:28.282282  1741 solver.cpp:237]     Train net output #0: loss = 0.423115 (* 1 = 0.423115 loss)
I0121 19:00:28.282297  1741 sgd_solver.cpp:105] Iteration 10100, lr = 0.01
I0121 19:00:49.914158  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:01:09.871356  1741 solver.cpp:218] Iteration 10200 (2.40445 iter/s, 41.5896s/100 iters), loss = 0.310617
I0121 19:01:09.871584  1741 solver.cpp:237]     Train net output #0: loss = 0.310617 (* 1 = 0.310617 loss)
I0121 19:01:09.871600  1741 sgd_solver.cpp:105] Iteration 10200, lr = 0.01
I0121 19:01:51.388799  1741 solver.cpp:218] Iteration 10300 (2.40861 iter/s, 41.5177s/100 iters), loss = 0.202155
I0121 19:01:51.388984  1741 solver.cpp:237]     Train net output #0: loss = 0.202155 (* 1 = 0.202155 loss)
I0121 19:01:51.388999  1741 sgd_solver.cpp:105] Iteration 10300, lr = 0.01
I0121 19:02:32.963584  1741 solver.cpp:218] Iteration 10400 (2.40528 iter/s, 41.5751s/100 iters), loss = 0.30656
I0121 19:02:32.963755  1741 solver.cpp:237]     Train net output #0: loss = 0.30656 (* 1 = 0.30656 loss)
I0121 19:02:32.963774  1741 sgd_solver.cpp:105] Iteration 10400, lr = 0.01
I0121 19:03:14.570170  1741 solver.cpp:218] Iteration 10500 (2.40345 iter/s, 41.6069s/100 iters), loss = 0.371227
I0121 19:03:14.570348  1741 solver.cpp:237]     Train net output #0: loss = 0.371227 (* 1 = 0.371227 loss)
I0121 19:03:14.570363  1741 sgd_solver.cpp:105] Iteration 10500, lr = 0.01
I0121 19:03:32.040372  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:03:56.159713  1741 solver.cpp:218] Iteration 10600 (2.40443 iter/s, 41.5899s/100 iters), loss = 0.32426
I0121 19:03:56.159842  1741 solver.cpp:237]     Train net output #0: loss = 0.32426 (* 1 = 0.32426 loss)
I0121 19:03:56.159857  1741 sgd_solver.cpp:105] Iteration 10600, lr = 0.01
I0121 19:04:37.738679  1741 solver.cpp:218] Iteration 10700 (2.40504 iter/s, 41.5793s/100 iters), loss = 0.136647
I0121 19:04:37.738858  1741 solver.cpp:237]     Train net output #0: loss = 0.136647 (* 1 = 0.136647 loss)
I0121 19:04:37.738874  1741 sgd_solver.cpp:105] Iteration 10700, lr = 0.01
I0121 19:05:19.343479  1741 solver.cpp:218] Iteration 10800 (2.40355 iter/s, 41.6051s/100 iters), loss = 0.259529
I0121 19:05:19.343658  1741 solver.cpp:237]     Train net output #0: loss = 0.259529 (* 1 = 0.259529 loss)
I0121 19:05:19.343675  1741 sgd_solver.cpp:105] Iteration 10800, lr = 0.01
I0121 19:06:00.940517  1741 solver.cpp:218] Iteration 10900 (2.404 iter/s, 41.5974s/100 iters), loss = 0.189884
I0121 19:06:00.940693  1741 solver.cpp:237]     Train net output #0: loss = 0.189884 (* 1 = 0.189884 loss)
I0121 19:06:00.940713  1741 sgd_solver.cpp:105] Iteration 10900, lr = 0.01
I0121 19:06:14.675794  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:06:42.131989  1741 solver.cpp:330] Iteration 11000, Testing net (#0)
I0121 19:06:51.694697  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:06:51.909683  1741 solver.cpp:397]     Test net output #0: accuracy = 0.879556
I0121 19:06:51.909749  1741 solver.cpp:397]     Test net output #1: loss = 0.349222 (* 1 = 0.349222 loss)
I0121 19:06:52.325096  1741 solver.cpp:218] Iteration 11000 (1.94609 iter/s, 51.385s/100 iters), loss = 0.268353
I0121 19:06:52.325211  1741 solver.cpp:237]     Train net output #0: loss = 0.268353 (* 1 = 0.268353 loss)
I0121 19:06:52.325227  1741 sgd_solver.cpp:105] Iteration 11000, lr = 0.01
I0121 19:07:33.900969  1741 solver.cpp:218] Iteration 11100 (2.40522 iter/s, 41.5762s/100 iters), loss = 0.223137
I0121 19:07:33.901113  1741 solver.cpp:237]     Train net output #0: loss = 0.223137 (* 1 = 0.223137 loss)
I0121 19:07:33.901132  1741 sgd_solver.cpp:105] Iteration 11100, lr = 0.01
I0121 19:08:15.493058  1741 solver.cpp:218] Iteration 11200 (2.40428 iter/s, 41.5925s/100 iters), loss = 0.271219
I0121 19:08:15.493252  1741 solver.cpp:237]     Train net output #0: loss = 0.271219 (* 1 = 0.271219 loss)
I0121 19:08:15.493283  1741 sgd_solver.cpp:105] Iteration 11200, lr = 0.01
I0121 19:08:57.067176  1741 solver.cpp:218] Iteration 11300 (2.40533 iter/s, 41.5744s/100 iters), loss = 0.201089
I0121 19:08:57.067394  1741 solver.cpp:237]     Train net output #0: loss = 0.201089 (* 1 = 0.201089 loss)
I0121 19:08:57.067422  1741 sgd_solver.cpp:105] Iteration 11300, lr = 0.01
I0121 19:09:07.055799  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:09:38.669481  1741 solver.cpp:218] Iteration 11400 (2.4037 iter/s, 41.6026s/100 iters), loss = 0.291931
I0121 19:09:38.669656  1741 solver.cpp:237]     Train net output #0: loss = 0.291931 (* 1 = 0.291931 loss)
I0121 19:09:38.669682  1741 sgd_solver.cpp:105] Iteration 11400, lr = 0.01
I0121 19:10:20.249560  1741 solver.cpp:218] Iteration 11500 (2.40498 iter/s, 41.5804s/100 iters), loss = 0.185854
I0121 19:10:20.249740  1741 solver.cpp:237]     Train net output #0: loss = 0.185854 (* 1 = 0.185854 loss)
I0121 19:10:20.249769  1741 sgd_solver.cpp:105] Iteration 11500, lr = 0.01
I0121 19:11:01.833187  1741 solver.cpp:218] Iteration 11600 (2.40477 iter/s, 41.5839s/100 iters), loss = 0.170827
I0121 19:11:01.833380  1741 solver.cpp:237]     Train net output #0: loss = 0.170827 (* 1 = 0.170827 loss)
I0121 19:11:01.833410  1741 sgd_solver.cpp:105] Iteration 11600, lr = 0.01
I0121 19:11:43.396253  1741 solver.cpp:218] Iteration 11700 (2.40596 iter/s, 41.5634s/100 iters), loss = 0.196872
I0121 19:11:43.396409  1741 solver.cpp:237]     Train net output #0: loss = 0.196872 (* 1 = 0.196872 loss)
I0121 19:11:43.396423  1741 sgd_solver.cpp:105] Iteration 11700, lr = 0.01
I0121 19:11:49.212419  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:12:24.924895  1741 solver.cpp:218] Iteration 11800 (2.40796 iter/s, 41.529s/100 iters), loss = 0.152715
I0121 19:12:24.925086  1741 solver.cpp:237]     Train net output #0: loss = 0.152715 (* 1 = 0.152715 loss)
I0121 19:12:24.925102  1741 sgd_solver.cpp:105] Iteration 11800, lr = 0.01
I0121 19:13:06.471961  1741 solver.cpp:218] Iteration 11900 (2.40689 iter/s, 41.5474s/100 iters), loss = 0.130921
I0121 19:13:06.472144  1741 solver.cpp:237]     Train net output #0: loss = 0.130921 (* 1 = 0.130921 loss)
I0121 19:13:06.472160  1741 sgd_solver.cpp:105] Iteration 11900, lr = 0.01
I0121 19:13:47.600293  1741 solver.cpp:330] Iteration 12000, Testing net (#0)
I0121 19:13:57.133111  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:13:57.347553  1741 solver.cpp:397]     Test net output #0: accuracy = 0.886333
I0121 19:13:57.347628  1741 solver.cpp:397]     Test net output #1: loss = 0.345438 (* 1 = 0.345438 loss)
I0121 19:13:57.762140  1741 solver.cpp:218] Iteration 12000 (1.94967 iter/s, 51.2906s/100 iters), loss = 0.193493
I0121 19:13:57.762235  1741 solver.cpp:237]     Train net output #0: loss = 0.193493 (* 1 = 0.193493 loss)
I0121 19:13:57.762250  1741 sgd_solver.cpp:105] Iteration 12000, lr = 0.01
I0121 19:14:39.314338  1741 solver.cpp:218] Iteration 12100 (2.40659 iter/s, 41.5526s/100 iters), loss = 0.232431
I0121 19:14:39.314513  1741 solver.cpp:237]     Train net output #0: loss = 0.232431 (* 1 = 0.232431 loss)
I0121 19:14:39.314530  1741 sgd_solver.cpp:105] Iteration 12100, lr = 0.01
I0121 19:14:41.399808  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:15:20.836283  1741 solver.cpp:218] Iteration 12200 (2.40835 iter/s, 41.5223s/100 iters), loss = 0.112332
I0121 19:15:20.836468  1741 solver.cpp:237]     Train net output #0: loss = 0.112332 (* 1 = 0.112332 loss)
I0121 19:15:20.836485  1741 sgd_solver.cpp:105] Iteration 12200, lr = 0.01
I0121 19:16:02.330987  1741 solver.cpp:218] Iteration 12300 (2.40993 iter/s, 41.495s/100 iters), loss = 0.125394
I0121 19:16:02.331182  1741 solver.cpp:237]     Train net output #0: loss = 0.125394 (* 1 = 0.125394 loss)
I0121 19:16:02.331198  1741 sgd_solver.cpp:105] Iteration 12300, lr = 0.01
I0121 19:16:43.847290  1741 solver.cpp:218] Iteration 12400 (2.40867 iter/s, 41.5166s/100 iters), loss = 0.186593
I0121 19:16:43.847451  1741 solver.cpp:237]     Train net output #0: loss = 0.186593 (* 1 = 0.186593 loss)
I0121 19:16:43.847470  1741 sgd_solver.cpp:105] Iteration 12400, lr = 0.01
I0121 19:17:23.338224  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:17:25.410584  1741 solver.cpp:218] Iteration 12500 (2.40595 iter/s, 41.5636s/100 iters), loss = 0.182945
I0121 19:17:25.410671  1741 solver.cpp:237]     Train net output #0: loss = 0.182945 (* 1 = 0.182945 loss)
I0121 19:17:25.410686  1741 sgd_solver.cpp:105] Iteration 12500, lr = 0.01
I0121 19:18:06.964695  1741 solver.cpp:218] Iteration 12600 (2.40648 iter/s, 41.5545s/100 iters), loss = 0.0837846
I0121 19:18:06.964891  1741 solver.cpp:237]     Train net output #0: loss = 0.0837846 (* 1 = 0.0837846 loss)
I0121 19:18:06.964906  1741 sgd_solver.cpp:105] Iteration 12600, lr = 0.01
I0121 19:18:48.579041  1741 solver.cpp:218] Iteration 12700 (2.403 iter/s, 41.6147s/100 iters), loss = 0.114141
I0121 19:18:48.579217  1741 solver.cpp:237]     Train net output #0: loss = 0.114141 (* 1 = 0.114141 loss)
I0121 19:18:48.579237  1741 sgd_solver.cpp:105] Iteration 12700, lr = 0.01
I0121 19:19:30.179440  1741 solver.cpp:218] Iteration 12800 (2.4038 iter/s, 41.6007s/100 iters), loss = 0.0775963
I0121 19:19:30.179600  1741 solver.cpp:237]     Train net output #0: loss = 0.0775963 (* 1 = 0.0775963 loss)
I0121 19:19:30.179615  1741 sgd_solver.cpp:105] Iteration 12800, lr = 0.01
I0121 19:20:05.946691  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:20:11.762449  1741 solver.cpp:218] Iteration 12900 (2.40481 iter/s, 41.5834s/100 iters), loss = 0.145241
I0121 19:20:11.762542  1741 solver.cpp:237]     Train net output #0: loss = 0.145241 (* 1 = 0.145241 loss)
I0121 19:20:11.762557  1741 sgd_solver.cpp:105] Iteration 12900, lr = 0.01
I0121 19:20:52.902029  1741 solver.cpp:330] Iteration 13000, Testing net (#0)
I0121 19:21:02.443490  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:21:02.659811  1741 solver.cpp:397]     Test net output #0: accuracy = 0.884889
I0121 19:21:02.659891  1741 solver.cpp:397]     Test net output #1: loss = 0.356128 (* 1 = 0.356128 loss)
I0121 19:21:03.077149  1741 solver.cpp:218] Iteration 13000 (1.94874 iter/s, 51.3152s/100 iters), loss = 0.145049
I0121 19:21:03.077251  1741 solver.cpp:237]     Train net output #0: loss = 0.145049 (* 1 = 0.145049 loss)
I0121 19:21:03.077266  1741 sgd_solver.cpp:105] Iteration 13000, lr = 0.01
I0121 19:21:44.631330  1741 solver.cpp:218] Iteration 13100 (2.40647 iter/s, 41.5546s/100 iters), loss = 0.0846201
I0121 19:21:44.631523  1741 solver.cpp:237]     Train net output #0: loss = 0.0846201 (* 1 = 0.0846201 loss)
I0121 19:21:44.631539  1741 sgd_solver.cpp:105] Iteration 13100, lr = 0.01
I0121 19:22:26.202317  1741 solver.cpp:218] Iteration 13200 (2.40551 iter/s, 41.5713s/100 iters), loss = 0.131713
I0121 19:22:26.202507  1741 solver.cpp:237]     Train net output #0: loss = 0.131713 (* 1 = 0.131713 loss)
I0121 19:22:26.202529  1741 sgd_solver.cpp:105] Iteration 13200, lr = 0.01
I0121 19:22:58.205642  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:23:07.755313  1741 solver.cpp:218] Iteration 13300 (2.40655 iter/s, 41.5533s/100 iters), loss = 0.125141
I0121 19:23:07.755424  1741 solver.cpp:237]     Train net output #0: loss = 0.125141 (* 1 = 0.125141 loss)
I0121 19:23:07.755445  1741 sgd_solver.cpp:105] Iteration 13300, lr = 0.01
I0121 19:23:49.273421  1741 solver.cpp:218] Iteration 13400 (2.40857 iter/s, 41.5185s/100 iters), loss = 0.121517
I0121 19:23:49.273566  1741 solver.cpp:237]     Train net output #0: loss = 0.121517 (* 1 = 0.121517 loss)
I0121 19:23:49.273586  1741 sgd_solver.cpp:105] Iteration 13400, lr = 0.01
I0121 19:24:30.913887  1741 solver.cpp:218] Iteration 13500 (2.40149 iter/s, 41.6408s/100 iters), loss = 0.0554504
I0121 19:24:30.914058  1741 solver.cpp:237]     Train net output #0: loss = 0.0554504 (* 1 = 0.0554504 loss)
I0121 19:24:30.914078  1741 sgd_solver.cpp:105] Iteration 13500, lr = 0.01
I0121 19:25:12.523299  1741 solver.cpp:218] Iteration 13600 (2.40328 iter/s, 41.6098s/100 iters), loss = 0.120981
I0121 19:25:12.523442  1741 solver.cpp:237]     Train net output #0: loss = 0.120981 (* 1 = 0.120981 loss)
I0121 19:25:12.523461  1741 sgd_solver.cpp:105] Iteration 13600, lr = 0.01
I0121 19:25:40.376004  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:25:54.091928  1741 solver.cpp:218] Iteration 13700 (2.40564 iter/s, 41.569s/100 iters), loss = 0.0720138
I0121 19:25:54.092146  1741 solver.cpp:237]     Train net output #0: loss = 0.0720138 (* 1 = 0.0720138 loss)
I0121 19:25:54.092164  1741 sgd_solver.cpp:105] Iteration 13700, lr = 0.01
I0121 19:26:35.650858  1741 solver.cpp:218] Iteration 13800 (2.4062 iter/s, 41.5592s/100 iters), loss = 0.108627
I0121 19:26:35.651053  1741 solver.cpp:237]     Train net output #0: loss = 0.108627 (* 1 = 0.108627 loss)
I0121 19:26:35.651082  1741 sgd_solver.cpp:105] Iteration 13800, lr = 0.01
I0121 19:27:17.258064  1741 solver.cpp:218] Iteration 13900 (2.40341 iter/s, 41.6075s/100 iters), loss = 0.185608
I0121 19:27:17.258253  1741 solver.cpp:237]     Train net output #0: loss = 0.185608 (* 1 = 0.185608 loss)
I0121 19:27:17.258281  1741 sgd_solver.cpp:105] Iteration 13900, lr = 0.01
I0121 19:27:58.410447  1741 solver.cpp:330] Iteration 14000, Testing net (#0)
I0121 19:28:07.954744  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:28:08.170833  1741 solver.cpp:397]     Test net output #0: accuracy = 0.877778
I0121 19:28:08.170918  1741 solver.cpp:397]     Test net output #1: loss = 0.381788 (* 1 = 0.381788 loss)
I0121 19:28:08.589120  1741 solver.cpp:218] Iteration 14000 (1.94812 iter/s, 51.3315s/100 iters), loss = 0.0799966
I0121 19:28:08.589222  1741 solver.cpp:237]     Train net output #0: loss = 0.0799966 (* 1 = 0.0799966 loss)
I0121 19:28:08.589241  1741 sgd_solver.cpp:105] Iteration 14000, lr = 0.01
I0121 19:28:32.711732  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:28:50.155285  1741 solver.cpp:218] Iteration 14100 (2.40578 iter/s, 41.5665s/100 iters), loss = 0.107272
I0121 19:28:50.155382  1741 solver.cpp:237]     Train net output #0: loss = 0.107273 (* 1 = 0.107273 loss)
I0121 19:28:50.155400  1741 sgd_solver.cpp:105] Iteration 14100, lr = 0.01
I0121 19:29:31.735517  1741 solver.cpp:218] Iteration 14200 (2.40497 iter/s, 41.5806s/100 iters), loss = 0.0973852
I0121 19:29:31.735711  1741 solver.cpp:237]     Train net output #0: loss = 0.0973853 (* 1 = 0.0973853 loss)
I0121 19:29:31.735735  1741 sgd_solver.cpp:105] Iteration 14200, lr = 0.01
I0121 19:30:13.305457  1741 solver.cpp:218] Iteration 14300 (2.40557 iter/s, 41.5702s/100 iters), loss = 0.0969678
I0121 19:30:13.305625  1741 solver.cpp:237]     Train net output #0: loss = 0.0969678 (* 1 = 0.0969678 loss)
I0121 19:30:13.305640  1741 sgd_solver.cpp:105] Iteration 14300, lr = 0.01
I0121 19:30:54.897675  1741 solver.cpp:218] Iteration 14400 (2.40428 iter/s, 41.5925s/100 iters), loss = 0.0787849
I0121 19:30:54.897841  1741 solver.cpp:237]     Train net output #0: loss = 0.0787849 (* 1 = 0.0787849 loss)
I0121 19:30:54.897857  1741 sgd_solver.cpp:105] Iteration 14400, lr = 0.01
I0121 19:31:15.263496  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:31:36.467617  1741 solver.cpp:218] Iteration 14500 (2.40556 iter/s, 41.5703s/100 iters), loss = 0.115714
I0121 19:31:36.467799  1741 solver.cpp:237]     Train net output #0: loss = 0.115714 (* 1 = 0.115714 loss)
I0121 19:31:36.467815  1741 sgd_solver.cpp:105] Iteration 14500, lr = 0.01
I0121 19:32:18.048883  1741 solver.cpp:218] Iteration 14600 (2.40491 iter/s, 41.5816s/100 iters), loss = 0.0710719
I0121 19:32:18.049069  1741 solver.cpp:237]     Train net output #0: loss = 0.0710719 (* 1 = 0.0710719 loss)
I0121 19:32:18.049084  1741 sgd_solver.cpp:105] Iteration 14600, lr = 0.01
I0121 19:32:59.629634  1741 solver.cpp:218] Iteration 14700 (2.40494 iter/s, 41.5811s/100 iters), loss = 0.0553147
I0121 19:32:59.629824  1741 solver.cpp:237]     Train net output #0: loss = 0.0553147 (* 1 = 0.0553147 loss)
I0121 19:32:59.629839  1741 sgd_solver.cpp:105] Iteration 14700, lr = 0.01
I0121 19:33:41.230744  1741 solver.cpp:218] Iteration 14800 (2.40376 iter/s, 41.6014s/100 iters), loss = 0.182538
I0121 19:33:41.230927  1741 solver.cpp:237]     Train net output #0: loss = 0.182538 (* 1 = 0.182538 loss)
I0121 19:33:41.230945  1741 sgd_solver.cpp:105] Iteration 14800, lr = 0.01
I0121 19:33:57.451454  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:34:22.832129  1741 solver.cpp:218] Iteration 14900 (2.40375 iter/s, 41.6017s/100 iters), loss = 0.0962887
I0121 19:34:22.832352  1741 solver.cpp:237]     Train net output #0: loss = 0.0962888 (* 1 = 0.0962888 loss)
I0121 19:34:22.832383  1741 sgd_solver.cpp:105] Iteration 14900, lr = 0.01
I0121 19:35:03.995029  1741 solver.cpp:330] Iteration 15000, Testing net (#0)
I0121 19:35:13.517644  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:35:13.732064  1741 solver.cpp:397]     Test net output #0: accuracy = 0.880222
I0121 19:35:13.732136  1741 solver.cpp:397]     Test net output #1: loss = 0.385995 (* 1 = 0.385995 loss)
I0121 19:35:14.150358  1741 solver.cpp:218] Iteration 15000 (1.94861 iter/s, 51.3186s/100 iters), loss = 0.15401
I0121 19:35:14.150457  1741 solver.cpp:237]     Train net output #0: loss = 0.15401 (* 1 = 0.15401 loss)
I0121 19:35:14.150476  1741 sgd_solver.cpp:105] Iteration 15000, lr = 0.01
I0121 19:35:55.739250  1741 solver.cpp:218] Iteration 15100 (2.40446 iter/s, 41.5893s/100 iters), loss = 0.0830065
I0121 19:35:55.739428  1741 solver.cpp:237]     Train net output #0: loss = 0.0830066 (* 1 = 0.0830066 loss)
I0121 19:35:55.739447  1741 sgd_solver.cpp:105] Iteration 15100, lr = 0.01
I0121 19:36:37.342355  1741 solver.cpp:218] Iteration 15200 (2.40365 iter/s, 41.6034s/100 iters), loss = 0.0966766
I0121 19:36:37.342551  1741 solver.cpp:237]     Train net output #0: loss = 0.0966767 (* 1 = 0.0966767 loss)
I0121 19:36:37.342573  1741 sgd_solver.cpp:105] Iteration 15200, lr = 0.01
I0121 19:36:49.817095  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:37:18.903889  1741 solver.cpp:218] Iteration 15300 (2.40605 iter/s, 41.5619s/100 iters), loss = 0.18821
I0121 19:37:18.904067  1741 solver.cpp:237]     Train net output #0: loss = 0.18821 (* 1 = 0.18821 loss)
I0121 19:37:18.904094  1741 sgd_solver.cpp:105] Iteration 15300, lr = 0.01
I0121 19:38:00.472231  1741 solver.cpp:218] Iteration 15400 (2.40566 iter/s, 41.5687s/100 iters), loss = 0.0847323
I0121 19:38:00.472404  1741 solver.cpp:237]     Train net output #0: loss = 0.0847323 (* 1 = 0.0847323 loss)
I0121 19:38:00.472425  1741 sgd_solver.cpp:105] Iteration 15400, lr = 0.01
I0121 19:38:42.045403  1741 solver.cpp:218] Iteration 15500 (2.40538 iter/s, 41.5735s/100 iters), loss = 0.103621
I0121 19:38:42.045578  1741 solver.cpp:237]     Train net output #0: loss = 0.103621 (* 1 = 0.103621 loss)
I0121 19:38:42.045600  1741 sgd_solver.cpp:105] Iteration 15500, lr = 0.01
I0121 19:39:23.647564  1741 solver.cpp:218] Iteration 15600 (2.4037 iter/s, 41.6025s/100 iters), loss = 0.0933101
I0121 19:39:23.647702  1741 solver.cpp:237]     Train net output #0: loss = 0.0933102 (* 1 = 0.0933102 loss)
I0121 19:39:23.647722  1741 sgd_solver.cpp:105] Iteration 15600, lr = 0.01
I0121 19:39:31.978668  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:40:05.250474  1741 solver.cpp:218] Iteration 15700 (2.40366 iter/s, 41.6033s/100 iters), loss = 0.0897847
I0121 19:40:05.250633  1741 solver.cpp:237]     Train net output #0: loss = 0.0897847 (* 1 = 0.0897847 loss)
I0121 19:40:05.250651  1741 sgd_solver.cpp:105] Iteration 15700, lr = 0.01
I0121 19:40:46.845919  1741 solver.cpp:218] Iteration 15800 (2.40409 iter/s, 41.5958s/100 iters), loss = 0.0961236
I0121 19:40:46.846109  1741 solver.cpp:237]     Train net output #0: loss = 0.0961236 (* 1 = 0.0961236 loss)
I0121 19:40:46.846132  1741 sgd_solver.cpp:105] Iteration 15800, lr = 0.01
I0121 19:41:28.412163  1741 solver.cpp:218] Iteration 15900 (2.40578 iter/s, 41.5665s/100 iters), loss = 0.141141
I0121 19:41:28.412340  1741 solver.cpp:237]     Train net output #0: loss = 0.141141 (* 1 = 0.141141 loss)
I0121 19:41:28.412374  1741 sgd_solver.cpp:105] Iteration 15900, lr = 0.01
I0121 19:42:09.589191  1741 solver.cpp:330] Iteration 16000, Testing net (#0)
I0121 19:42:19.122828  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:42:19.339428  1741 solver.cpp:397]     Test net output #0: accuracy = 0.870555
I0121 19:42:19.339509  1741 solver.cpp:397]     Test net output #1: loss = 0.426338 (* 1 = 0.426338 loss)
I0121 19:42:19.752297  1741 solver.cpp:218] Iteration 16000 (1.94778 iter/s, 51.3406s/100 iters), loss = 0.139417
I0121 19:42:19.752405  1741 solver.cpp:237]     Train net output #0: loss = 0.139417 (* 1 = 0.139417 loss)
I0121 19:42:19.752424  1741 sgd_solver.cpp:105] Iteration 16000, lr = 0.01
I0121 19:42:24.327085  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:43:01.311652  1741 solver.cpp:218] Iteration 16100 (2.40617 iter/s, 41.5597s/100 iters), loss = 0.0948189
I0121 19:43:01.311861  1741 solver.cpp:237]     Train net output #0: loss = 0.094819 (* 1 = 0.094819 loss)
I0121 19:43:01.311882  1741 sgd_solver.cpp:105] Iteration 16100, lr = 0.01
I0121 19:43:42.910024  1741 solver.cpp:218] Iteration 16200 (2.40392 iter/s, 41.5987s/100 iters), loss = 0.107091
I0121 19:43:42.910212  1741 solver.cpp:237]     Train net output #0: loss = 0.107091 (* 1 = 0.107091 loss)
I0121 19:43:42.910241  1741 sgd_solver.cpp:105] Iteration 16200, lr = 0.01
I0121 19:44:24.463609  1741 solver.cpp:218] Iteration 16300 (2.40651 iter/s, 41.5539s/100 iters), loss = 0.0944435
I0121 19:44:24.463785  1741 solver.cpp:237]     Train net output #0: loss = 0.0944436 (* 1 = 0.0944436 loss)
I0121 19:44:24.463807  1741 sgd_solver.cpp:105] Iteration 16300, lr = 0.01
I0121 19:45:05.922215  1741 solver.cpp:218] Iteration 16400 (2.41202 iter/s, 41.4589s/100 iters), loss = 0.146863
I0121 19:45:05.922417  1741 solver.cpp:237]     Train net output #0: loss = 0.146863 (* 1 = 0.146863 loss)
I0121 19:45:05.922441  1741 sgd_solver.cpp:105] Iteration 16400, lr = 0.01
I0121 19:45:06.759212  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:45:47.483517  1741 solver.cpp:218] Iteration 16500 (2.40607 iter/s, 41.5616s/100 iters), loss = 0.0640304
I0121 19:45:47.483705  1741 solver.cpp:237]     Train net output #0: loss = 0.0640304 (* 1 = 0.0640304 loss)
I0121 19:45:47.483732  1741 sgd_solver.cpp:105] Iteration 16500, lr = 0.01
I0121 19:46:29.067126  1741 solver.cpp:218] Iteration 16600 (2.40478 iter/s, 41.5839s/100 iters), loss = 0.0791413
I0121 19:46:29.067318  1741 solver.cpp:237]     Train net output #0: loss = 0.0791413 (* 1 = 0.0791413 loss)
I0121 19:46:29.067339  1741 sgd_solver.cpp:105] Iteration 16600, lr = 0.01
I0121 19:47:10.656024  1741 solver.cpp:218] Iteration 16700 (2.40447 iter/s, 41.5892s/100 iters), loss = 0.0855462
I0121 19:47:10.656224  1741 solver.cpp:237]     Train net output #0: loss = 0.0855462 (* 1 = 0.0855462 loss)
I0121 19:47:10.656244  1741 sgd_solver.cpp:105] Iteration 16700, lr = 0.01
I0121 19:47:48.903340  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:47:52.230159  1741 solver.cpp:218] Iteration 16800 (2.40533 iter/s, 41.5744s/100 iters), loss = 0.173367
I0121 19:47:52.230254  1741 solver.cpp:237]     Train net output #0: loss = 0.173367 (* 1 = 0.173367 loss)
I0121 19:47:52.230269  1741 sgd_solver.cpp:105] Iteration 16800, lr = 0.01
I0121 19:48:33.809450  1741 solver.cpp:218] Iteration 16900 (2.40502 iter/s, 41.5797s/100 iters), loss = 0.115617
I0121 19:48:33.809628  1741 solver.cpp:237]     Train net output #0: loss = 0.115617 (* 1 = 0.115617 loss)
I0121 19:48:33.809643  1741 sgd_solver.cpp:105] Iteration 16900, lr = 0.01
I0121 19:49:14.972044  1741 solver.cpp:330] Iteration 17000, Testing net (#0)
I0121 19:49:24.507339  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:49:24.720865  1741 solver.cpp:397]     Test net output #0: accuracy = 0.876111
I0121 19:49:24.720935  1741 solver.cpp:397]     Test net output #1: loss = 0.406093 (* 1 = 0.406093 loss)
I0121 19:49:25.136008  1741 solver.cpp:218] Iteration 17000 (1.94829 iter/s, 51.327s/100 iters), loss = 0.060138
I0121 19:49:25.136102  1741 solver.cpp:237]     Train net output #0: loss = 0.060138 (* 1 = 0.060138 loss)
I0121 19:49:25.136118  1741 sgd_solver.cpp:105] Iteration 17000, lr = 0.01
I0121 19:50:06.728813  1741 solver.cpp:218] Iteration 17100 (2.40424 iter/s, 41.5932s/100 iters), loss = 0.163585
I0121 19:50:06.728984  1741 solver.cpp:237]     Train net output #0: loss = 0.163585 (* 1 = 0.163585 loss)
I0121 19:50:06.729001  1741 sgd_solver.cpp:105] Iteration 17100, lr = 0.01
I0121 19:50:41.213502  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:50:48.275943  1741 solver.cpp:218] Iteration 17200 (2.40689 iter/s, 41.5474s/100 iters), loss = 0.0907937
I0121 19:50:48.276037  1741 solver.cpp:237]     Train net output #0: loss = 0.0907937 (* 1 = 0.0907937 loss)
I0121 19:50:48.276052  1741 sgd_solver.cpp:105] Iteration 17200, lr = 0.01
I0121 19:51:29.794581  1741 solver.cpp:218] Iteration 17300 (2.40853 iter/s, 41.519s/100 iters), loss = 0.0735234
I0121 19:51:29.794760  1741 solver.cpp:237]     Train net output #0: loss = 0.0735234 (* 1 = 0.0735234 loss)
I0121 19:51:29.794775  1741 sgd_solver.cpp:105] Iteration 17300, lr = 0.01
I0121 19:52:11.363008  1741 solver.cpp:218] Iteration 17400 (2.40565 iter/s, 41.5688s/100 iters), loss = 0.136567
I0121 19:52:11.363193  1741 solver.cpp:237]     Train net output #0: loss = 0.136567 (* 1 = 0.136567 loss)
I0121 19:52:11.363209  1741 sgd_solver.cpp:105] Iteration 17400, lr = 0.01
I0121 19:52:52.960708  1741 solver.cpp:218] Iteration 17500 (2.40396 iter/s, 41.598s/100 iters), loss = 0.0847274
I0121 19:52:52.960839  1741 solver.cpp:237]     Train net output #0: loss = 0.0847274 (* 1 = 0.0847274 loss)
I0121 19:52:52.960856  1741 sgd_solver.cpp:105] Iteration 17500, lr = 0.01
I0121 19:53:23.738229  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:53:34.545876  1741 solver.cpp:218] Iteration 17600 (2.40468 iter/s, 41.5855s/100 iters), loss = 0.0630184
I0121 19:53:34.545974  1741 solver.cpp:237]     Train net output #0: loss = 0.0630184 (* 1 = 0.0630184 loss)
I0121 19:53:34.545989  1741 sgd_solver.cpp:105] Iteration 17600, lr = 0.01
I0121 19:54:16.142690  1741 solver.cpp:218] Iteration 17700 (2.40401 iter/s, 41.5972s/100 iters), loss = 0.10277
I0121 19:54:16.142817  1741 solver.cpp:237]     Train net output #0: loss = 0.10277 (* 1 = 0.10277 loss)
I0121 19:54:16.142833  1741 sgd_solver.cpp:105] Iteration 17700, lr = 0.01
I0121 19:54:57.747978  1741 solver.cpp:218] Iteration 17800 (2.40352 iter/s, 41.6057s/100 iters), loss = 0.122578
I0121 19:54:57.748169  1741 solver.cpp:237]     Train net output #0: loss = 0.122578 (* 1 = 0.122578 loss)
I0121 19:54:57.748184  1741 sgd_solver.cpp:105] Iteration 17800, lr = 0.01
I0121 19:55:39.355425  1741 solver.cpp:218] Iteration 17900 (2.4034 iter/s, 41.6077s/100 iters), loss = 0.0517816
I0121 19:55:39.355614  1741 solver.cpp:237]     Train net output #0: loss = 0.0517816 (* 1 = 0.0517816 loss)
I0121 19:55:39.355631  1741 sgd_solver.cpp:105] Iteration 17900, lr = 0.01
I0121 19:56:05.973006  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:56:20.539172  1741 solver.cpp:330] Iteration 18000, Testing net (#0)
I0121 19:56:30.104243  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:56:30.321223  1741 solver.cpp:397]     Test net output #0: accuracy = 0.871778
I0121 19:56:30.321310  1741 solver.cpp:397]     Test net output #1: loss = 0.41802 (* 1 = 0.41802 loss)
I0121 19:56:30.739387  1741 solver.cpp:218] Iteration 18000 (1.94612 iter/s, 51.3844s/100 iters), loss = 0.169593
I0121 19:56:30.739495  1741 solver.cpp:237]     Train net output #0: loss = 0.169593 (* 1 = 0.169593 loss)
I0121 19:56:30.739516  1741 sgd_solver.cpp:105] Iteration 18000, lr = 0.01
I0121 19:57:12.307428  1741 solver.cpp:218] Iteration 18100 (2.40567 iter/s, 41.5684s/100 iters), loss = 0.107608
I0121 19:57:12.307610  1741 solver.cpp:237]     Train net output #0: loss = 0.107608 (* 1 = 0.107608 loss)
I0121 19:57:12.307641  1741 sgd_solver.cpp:105] Iteration 18100, lr = 0.01
I0121 19:57:53.881384  1741 solver.cpp:218] Iteration 18200 (2.40533 iter/s, 41.5743s/100 iters), loss = 0.113704
I0121 19:57:53.881569  1741 solver.cpp:237]     Train net output #0: loss = 0.113704 (* 1 = 0.113704 loss)
I0121 19:57:53.881585  1741 sgd_solver.cpp:105] Iteration 18200, lr = 0.01
I0121 19:58:35.449620  1741 solver.cpp:218] Iteration 18300 (2.40567 iter/s, 41.5685s/100 iters), loss = 0.0847955
I0121 19:58:35.449813  1741 solver.cpp:237]     Train net output #0: loss = 0.0847955 (* 1 = 0.0847955 loss)
I0121 19:58:35.449829  1741 sgd_solver.cpp:105] Iteration 18300, lr = 0.01
I0121 19:58:58.343344  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 19:59:17.062768  1741 solver.cpp:218] Iteration 18400 (2.40307 iter/s, 41.6135s/100 iters), loss = 0.101585
I0121 19:59:17.062955  1741 solver.cpp:237]     Train net output #0: loss = 0.101585 (* 1 = 0.101585 loss)
I0121 19:59:17.062971  1741 sgd_solver.cpp:105] Iteration 18400, lr = 0.01
I0121 19:59:58.659837  1741 solver.cpp:218] Iteration 18500 (2.404 iter/s, 41.5974s/100 iters), loss = 0.111386
I0121 19:59:58.660032  1741 solver.cpp:237]     Train net output #0: loss = 0.111386 (* 1 = 0.111386 loss)
I0121 19:59:58.660048  1741 sgd_solver.cpp:105] Iteration 18500, lr = 0.01
I0121 20:00:40.224181  1741 solver.cpp:218] Iteration 18600 (2.40589 iter/s, 41.5646s/100 iters), loss = 0.110335
I0121 20:00:40.224372  1741 solver.cpp:237]     Train net output #0: loss = 0.110335 (* 1 = 0.110335 loss)
I0121 20:00:40.224390  1741 sgd_solver.cpp:105] Iteration 18600, lr = 0.01
I0121 20:01:21.810519  1741 solver.cpp:218] Iteration 18700 (2.40462 iter/s, 41.5867s/100 iters), loss = 0.12343
I0121 20:01:21.810709  1741 solver.cpp:237]     Train net output #0: loss = 0.12343 (* 1 = 0.12343 loss)
I0121 20:01:21.810731  1741 sgd_solver.cpp:105] Iteration 18700, lr = 0.01
I0121 20:01:40.522202  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:02:03.374085  1741 solver.cpp:218] Iteration 18800 (2.40594 iter/s, 41.5639s/100 iters), loss = 0.131511
I0121 20:02:03.374264  1741 solver.cpp:237]     Train net output #0: loss = 0.131511 (* 1 = 0.131511 loss)
I0121 20:02:03.374294  1741 sgd_solver.cpp:105] Iteration 18800, lr = 0.01
I0121 20:02:44.938328  1741 solver.cpp:218] Iteration 18900 (2.40589 iter/s, 41.5646s/100 iters), loss = 0.0807406
I0121 20:02:44.938485  1741 solver.cpp:237]     Train net output #0: loss = 0.0807406 (* 1 = 0.0807406 loss)
I0121 20:02:44.938504  1741 sgd_solver.cpp:105] Iteration 18900, lr = 0.01
I0121 20:03:26.064553  1741 solver.cpp:330] Iteration 19000, Testing net (#0)
I0121 20:03:35.575983  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:03:35.791064  1741 solver.cpp:397]     Test net output #0: accuracy = 0.872444
I0121 20:03:35.791128  1741 solver.cpp:397]     Test net output #1: loss = 0.423569 (* 1 = 0.423569 loss)
I0121 20:03:36.206111  1741 solver.cpp:218] Iteration 19000 (1.95053 iter/s, 51.2682s/100 iters), loss = 0.062351
I0121 20:03:36.206212  1741 solver.cpp:237]     Train net output #0: loss = 0.062351 (* 1 = 0.062351 loss)
I0121 20:03:36.206226  1741 sgd_solver.cpp:105] Iteration 19000, lr = 0.01
I0121 20:04:17.781245  1741 solver.cpp:218] Iteration 19100 (2.40526 iter/s, 41.5755s/100 iters), loss = 0.0594356
I0121 20:04:17.781435  1741 solver.cpp:237]     Train net output #0: loss = 0.0594356 (* 1 = 0.0594356 loss)
I0121 20:04:17.781457  1741 sgd_solver.cpp:105] Iteration 19100, lr = 0.01
I0121 20:04:32.755178  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:04:59.354094  1741 solver.cpp:218] Iteration 19200 (2.4054 iter/s, 41.5731s/100 iters), loss = 0.080567
I0121 20:04:59.354223  1741 solver.cpp:237]     Train net output #0: loss = 0.080567 (* 1 = 0.080567 loss)
I0121 20:04:59.354240  1741 sgd_solver.cpp:105] Iteration 19200, lr = 0.01
I0121 20:05:40.928697  1741 solver.cpp:218] Iteration 19300 (2.40529 iter/s, 41.575s/100 iters), loss = 0.0387918
I0121 20:05:40.928894  1741 solver.cpp:237]     Train net output #0: loss = 0.0387918 (* 1 = 0.0387918 loss)
I0121 20:05:40.928915  1741 sgd_solver.cpp:105] Iteration 19300, lr = 0.01
I0121 20:06:22.477360  1741 solver.cpp:218] Iteration 19400 (2.4068 iter/s, 41.5489s/100 iters), loss = 0.0560445
I0121 20:06:22.477598  1741 solver.cpp:237]     Train net output #0: loss = 0.0560445 (* 1 = 0.0560445 loss)
I0121 20:06:22.477620  1741 sgd_solver.cpp:105] Iteration 19400, lr = 0.01
I0121 20:07:03.953299  1741 solver.cpp:218] Iteration 19500 (2.41102 iter/s, 41.4762s/100 iters), loss = 0.0686756
I0121 20:07:03.953493  1741 solver.cpp:237]     Train net output #0: loss = 0.0686756 (* 1 = 0.0686756 loss)
I0121 20:07:03.953516  1741 sgd_solver.cpp:105] Iteration 19500, lr = 0.01
I0121 20:07:15.180624  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:07:45.504869  1741 solver.cpp:218] Iteration 19600 (2.40663 iter/s, 41.5519s/100 iters), loss = 0.133617
I0121 20:07:45.505038  1741 solver.cpp:237]     Train net output #0: loss = 0.133617 (* 1 = 0.133617 loss)
I0121 20:07:45.505057  1741 sgd_solver.cpp:105] Iteration 19600, lr = 0.01
I0121 20:08:27.099715  1741 solver.cpp:218] Iteration 19700 (2.40412 iter/s, 41.5952s/100 iters), loss = 0.0685938
I0121 20:08:27.099886  1741 solver.cpp:237]     Train net output #0: loss = 0.0685938 (* 1 = 0.0685938 loss)
I0121 20:08:27.099910  1741 sgd_solver.cpp:105] Iteration 19700, lr = 0.01
I0121 20:09:08.663058  1741 solver.cpp:218] Iteration 19800 (2.40595 iter/s, 41.5637s/100 iters), loss = 0.0578473
I0121 20:09:08.663189  1741 solver.cpp:237]     Train net output #0: loss = 0.0578473 (* 1 = 0.0578473 loss)
I0121 20:09:08.663213  1741 sgd_solver.cpp:105] Iteration 19800, lr = 0.01
I0121 20:09:50.247516  1741 solver.cpp:218] Iteration 19900 (2.40472 iter/s, 41.5848s/100 iters), loss = 0.117671
I0121 20:09:50.247640  1741 solver.cpp:237]     Train net output #0: loss = 0.117671 (* 1 = 0.117671 loss)
I0121 20:09:50.247656  1741 sgd_solver.cpp:105] Iteration 19900, lr = 0.01
I0121 20:09:57.319326  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:10:31.400357  1741 solver.cpp:447] Snapshotting to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_20000.caffemodel
I0121 20:10:31.420085  1741 sgd_solver.cpp:273] Snapshotting solver state to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_20000.solverstate
I0121 20:10:31.426203  1741 solver.cpp:330] Iteration 20000, Testing net (#0)
I0121 20:10:40.951871  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:10:41.166992  1741 solver.cpp:397]     Test net output #0: accuracy = 0.873444
I0121 20:10:41.167068  1741 solver.cpp:397]     Test net output #1: loss = 0.428603 (* 1 = 0.428603 loss)
I0121 20:10:41.582242  1741 solver.cpp:218] Iteration 20000 (1.94798 iter/s, 51.3352s/100 iters), loss = 0.0880837
I0121 20:10:41.582334  1741 solver.cpp:237]     Train net output #0: loss = 0.0880837 (* 1 = 0.0880837 loss)
I0121 20:10:41.582350  1741 sgd_solver.cpp:105] Iteration 20000, lr = 0.001
I0121 20:11:23.145100  1741 solver.cpp:218] Iteration 20100 (2.40597 iter/s, 41.5633s/100 iters), loss = 0.173139
I0121 20:11:23.145285  1741 solver.cpp:237]     Train net output #0: loss = 0.173139 (* 1 = 0.173139 loss)
I0121 20:11:23.145301  1741 sgd_solver.cpp:105] Iteration 20100, lr = 0.001
I0121 20:12:04.718915  1741 solver.cpp:218] Iteration 20200 (2.40534 iter/s, 41.5741s/100 iters), loss = 0.0840991
I0121 20:12:04.719097  1741 solver.cpp:237]     Train net output #0: loss = 0.0840991 (* 1 = 0.0840991 loss)
I0121 20:12:04.719118  1741 sgd_solver.cpp:105] Iteration 20200, lr = 0.001
I0121 20:12:46.240387  1741 solver.cpp:218] Iteration 20300 (2.40838 iter/s, 41.5218s/100 iters), loss = 0.0641609
I0121 20:12:46.240559  1741 solver.cpp:237]     Train net output #0: loss = 0.0641609 (* 1 = 0.0641609 loss)
I0121 20:12:46.240574  1741 sgd_solver.cpp:105] Iteration 20300, lr = 0.001
I0121 20:12:49.564828  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:13:27.756117  1741 solver.cpp:218] Iteration 20400 (2.40871 iter/s, 41.5161s/100 iters), loss = 0.0287477
I0121 20:13:27.756289  1741 solver.cpp:237]     Train net output #0: loss = 0.0287477 (* 1 = 0.0287477 loss)
I0121 20:13:27.756305  1741 sgd_solver.cpp:105] Iteration 20400, lr = 0.001
I0121 20:14:09.289880  1741 solver.cpp:218] Iteration 20500 (2.40766 iter/s, 41.5341s/100 iters), loss = 0.0319492
I0121 20:14:09.290108  1741 solver.cpp:237]     Train net output #0: loss = 0.0319492 (* 1 = 0.0319492 loss)
I0121 20:14:09.290132  1741 sgd_solver.cpp:105] Iteration 20500, lr = 0.001
I0121 20:14:50.818616  1741 solver.cpp:218] Iteration 20600 (2.40795 iter/s, 41.529s/100 iters), loss = 0.0352091
I0121 20:14:50.818816  1741 solver.cpp:237]     Train net output #0: loss = 0.0352091 (* 1 = 0.0352091 loss)
I0121 20:14:50.818846  1741 sgd_solver.cpp:105] Iteration 20600, lr = 0.001
I0121 20:15:31.940825  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:15:32.347767  1741 solver.cpp:218] Iteration 20700 (2.40793 iter/s, 41.5294s/100 iters), loss = 0.0164244
I0121 20:15:32.347868  1741 solver.cpp:237]     Train net output #0: loss = 0.0164244 (* 1 = 0.0164244 loss)
I0121 20:15:32.347887  1741 sgd_solver.cpp:105] Iteration 20700, lr = 0.001
I0121 20:16:13.883576  1741 solver.cpp:218] Iteration 20800 (2.40754 iter/s, 41.5362s/100 iters), loss = 0.0281479
I0121 20:16:13.883780  1741 solver.cpp:237]     Train net output #0: loss = 0.0281479 (* 1 = 0.0281479 loss)
I0121 20:16:13.883800  1741 sgd_solver.cpp:105] Iteration 20800, lr = 0.001
I0121 20:16:55.426928  1741 solver.cpp:218] Iteration 20900 (2.40711 iter/s, 41.5436s/100 iters), loss = 0.0284284
I0121 20:16:55.427119  1741 solver.cpp:237]     Train net output #0: loss = 0.0284284 (* 1 = 0.0284284 loss)
I0121 20:16:55.427139  1741 sgd_solver.cpp:105] Iteration 20900, lr = 0.001
I0121 20:17:36.533311  1741 solver.cpp:330] Iteration 21000, Testing net (#0)
I0121 20:17:46.039470  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:17:46.254037  1741 solver.cpp:397]     Test net output #0: accuracy = 0.892778
I0121 20:17:46.254094  1741 solver.cpp:397]     Test net output #1: loss = 0.349339 (* 1 = 0.349339 loss)
I0121 20:17:46.668624  1741 solver.cpp:218] Iteration 21000 (1.95152 iter/s, 51.2422s/100 iters), loss = 0.0545924
I0121 20:17:46.668689  1741 solver.cpp:237]     Train net output #0: loss = 0.0545924 (* 1 = 0.0545924 loss)
I0121 20:17:46.668707  1741 sgd_solver.cpp:105] Iteration 21000, lr = 0.001
I0121 20:18:23.627121  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:18:28.182768  1741 solver.cpp:218] Iteration 21100 (2.40879 iter/s, 41.5146s/100 iters), loss = 0.0200542
I0121 20:18:28.182883  1741 solver.cpp:237]     Train net output #0: loss = 0.0200542 (* 1 = 0.0200542 loss)
I0121 20:18:28.182902  1741 sgd_solver.cpp:105] Iteration 21100, lr = 0.001
I0121 20:19:09.732250  1741 solver.cpp:218] Iteration 21200 (2.40675 iter/s, 41.5499s/100 iters), loss = 0.0369195
I0121 20:19:09.732416  1741 solver.cpp:237]     Train net output #0: loss = 0.0369194 (* 1 = 0.0369194 loss)
I0121 20:19:09.732431  1741 sgd_solver.cpp:105] Iteration 21200, lr = 0.001
I0121 20:19:51.272595  1741 solver.cpp:218] Iteration 21300 (2.40728 iter/s, 41.5407s/100 iters), loss = 0.0317693
I0121 20:19:51.272758  1741 solver.cpp:237]     Train net output #0: loss = 0.0317693 (* 1 = 0.0317693 loss)
I0121 20:19:51.272774  1741 sgd_solver.cpp:105] Iteration 21300, lr = 0.001
I0121 20:20:32.821246  1741 solver.cpp:218] Iteration 21400 (2.4068 iter/s, 41.549s/100 iters), loss = 0.0256292
I0121 20:20:32.821435  1741 solver.cpp:237]     Train net output #0: loss = 0.0256292 (* 1 = 0.0256292 loss)
I0121 20:20:32.821451  1741 sgd_solver.cpp:105] Iteration 21400, lr = 0.001
I0121 20:21:06.094997  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:21:14.410573  1741 solver.cpp:218] Iteration 21500 (2.40445 iter/s, 41.5896s/100 iters), loss = 0.0157499
I0121 20:21:14.410671  1741 solver.cpp:237]     Train net output #0: loss = 0.0157499 (* 1 = 0.0157499 loss)
I0121 20:21:14.410686  1741 sgd_solver.cpp:105] Iteration 21500, lr = 0.001
I0121 20:21:56.013810  1741 solver.cpp:218] Iteration 21600 (2.40364 iter/s, 41.6036s/100 iters), loss = 0.0133527
I0121 20:21:56.013978  1741 solver.cpp:237]     Train net output #0: loss = 0.0133527 (* 1 = 0.0133527 loss)
I0121 20:21:56.013995  1741 sgd_solver.cpp:105] Iteration 21600, lr = 0.001
I0121 20:22:37.661301  1741 solver.cpp:218] Iteration 21700 (2.40109 iter/s, 41.6478s/100 iters), loss = 0.0246591
I0121 20:22:37.661479  1741 solver.cpp:237]     Train net output #0: loss = 0.0246591 (* 1 = 0.0246591 loss)
I0121 20:22:37.661494  1741 sgd_solver.cpp:105] Iteration 21700, lr = 0.001
I0121 20:23:19.266664  1741 solver.cpp:218] Iteration 21800 (2.40352 iter/s, 41.6057s/100 iters), loss = 0.0273032
I0121 20:23:19.266860  1741 solver.cpp:237]     Train net output #0: loss = 0.0273032 (* 1 = 0.0273032 loss)
I0121 20:23:19.266875  1741 sgd_solver.cpp:105] Iteration 21800, lr = 0.001
I0121 20:23:48.397994  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:24:00.883273  1741 solver.cpp:218] Iteration 21900 (2.40287 iter/s, 41.6169s/100 iters), loss = 0.0220712
I0121 20:24:00.883455  1741 solver.cpp:237]     Train net output #0: loss = 0.0220711 (* 1 = 0.0220711 loss)
I0121 20:24:00.883471  1741 sgd_solver.cpp:105] Iteration 21900, lr = 0.001
I0121 20:24:42.073487  1741 solver.cpp:330] Iteration 22000, Testing net (#0)
I0121 20:24:51.641206  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:24:51.856763  1741 solver.cpp:397]     Test net output #0: accuracy = 0.892333
I0121 20:24:51.856844  1741 solver.cpp:397]     Test net output #1: loss = 0.347882 (* 1 = 0.347882 loss)
I0121 20:24:52.272076  1741 solver.cpp:218] Iteration 22000 (1.94593 iter/s, 51.3893s/100 iters), loss = 0.0280041
I0121 20:24:52.272184  1741 solver.cpp:237]     Train net output #0: loss = 0.0280041 (* 1 = 0.0280041 loss)
I0121 20:24:52.272203  1741 sgd_solver.cpp:105] Iteration 22000, lr = 0.001
I0121 20:25:33.855665  1741 solver.cpp:218] Iteration 22100 (2.40477 iter/s, 41.584s/100 iters), loss = 0.0143319
I0121 20:25:33.855860  1741 solver.cpp:237]     Train net output #0: loss = 0.0143319 (* 1 = 0.0143319 loss)
I0121 20:25:33.855885  1741 sgd_solver.cpp:105] Iteration 22100, lr = 0.001
I0121 20:26:15.429641  1741 solver.cpp:218] Iteration 22200 (2.40533 iter/s, 41.5743s/100 iters), loss = 0.024039
I0121 20:26:15.429785  1741 solver.cpp:237]     Train net output #0: loss = 0.024039 (* 1 = 0.024039 loss)
I0121 20:26:15.429811  1741 sgd_solver.cpp:105] Iteration 22200, lr = 0.001
I0121 20:26:40.792541  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:26:56.995841  1741 solver.cpp:218] Iteration 22300 (2.40578 iter/s, 41.5666s/100 iters), loss = 0.0065451
I0121 20:26:56.996013  1741 solver.cpp:237]     Train net output #0: loss = 0.00654509 (* 1 = 0.00654509 loss)
I0121 20:26:56.996029  1741 sgd_solver.cpp:105] Iteration 22300, lr = 0.001
I0121 20:27:38.575585  1741 solver.cpp:218] Iteration 22400 (2.405 iter/s, 41.5801s/100 iters), loss = 0.0189579
I0121 20:27:38.575758  1741 solver.cpp:237]     Train net output #0: loss = 0.0189579 (* 1 = 0.0189579 loss)
I0121 20:27:38.575774  1741 sgd_solver.cpp:105] Iteration 22400, lr = 0.001
I0121 20:28:20.070449  1741 solver.cpp:218] Iteration 22500 (2.40992 iter/s, 41.4952s/100 iters), loss = 0.0190772
I0121 20:28:20.070634  1741 solver.cpp:237]     Train net output #0: loss = 0.0190772 (* 1 = 0.0190772 loss)
I0121 20:28:20.070652  1741 sgd_solver.cpp:105] Iteration 22500, lr = 0.001
I0121 20:29:01.516351  1741 solver.cpp:218] Iteration 22600 (2.41277 iter/s, 41.4462s/100 iters), loss = 0.0244769
I0121 20:29:01.516518  1741 solver.cpp:237]     Train net output #0: loss = 0.0244769 (* 1 = 0.0244769 loss)
I0121 20:29:01.516535  1741 sgd_solver.cpp:105] Iteration 22600, lr = 0.001
I0121 20:29:23.138139  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:29:43.060844  1741 solver.cpp:218] Iteration 22700 (2.40704 iter/s, 41.5448s/100 iters), loss = 0.0121038
I0121 20:29:43.061022  1741 solver.cpp:237]     Train net output #0: loss = 0.0121038 (* 1 = 0.0121038 loss)
I0121 20:29:43.061038  1741 sgd_solver.cpp:105] Iteration 22700, lr = 0.001
I0121 20:30:24.633242  1741 solver.cpp:218] Iteration 22800 (2.40542 iter/s, 41.5727s/100 iters), loss = 0.00978502
I0121 20:30:24.633486  1741 solver.cpp:237]     Train net output #0: loss = 0.00978501 (* 1 = 0.00978501 loss)
I0121 20:30:24.633507  1741 sgd_solver.cpp:105] Iteration 22800, lr = 0.001
I0121 20:31:06.155118  1741 solver.cpp:218] Iteration 22900 (2.40835 iter/s, 41.5222s/100 iters), loss = 0.0166294
I0121 20:31:06.155282  1741 solver.cpp:237]     Train net output #0: loss = 0.0166294 (* 1 = 0.0166294 loss)
I0121 20:31:06.155297  1741 sgd_solver.cpp:105] Iteration 22900, lr = 0.001
I0121 20:31:47.263378  1741 solver.cpp:330] Iteration 23000, Testing net (#0)
I0121 20:31:56.778431  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:31:56.994558  1741 solver.cpp:397]     Test net output #0: accuracy = 0.896444
I0121 20:31:56.994637  1741 solver.cpp:397]     Test net output #1: loss = 0.345895 (* 1 = 0.345895 loss)
I0121 20:31:57.409821  1741 solver.cpp:218] Iteration 23000 (1.95102 iter/s, 51.2551s/100 iters), loss = 0.0160283
I0121 20:31:57.409898  1741 solver.cpp:237]     Train net output #0: loss = 0.0160283 (* 1 = 0.0160283 loss)
I0121 20:31:57.409911  1741 sgd_solver.cpp:105] Iteration 23000, lr = 0.001
I0121 20:32:14.845847  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:32:38.892163  1741 solver.cpp:218] Iteration 23100 (2.41064 iter/s, 41.4828s/100 iters), loss = 0.0220436
I0121 20:32:38.892290  1741 solver.cpp:237]     Train net output #0: loss = 0.0220436 (* 1 = 0.0220436 loss)
I0121 20:32:38.892307  1741 sgd_solver.cpp:105] Iteration 23100, lr = 0.001
I0121 20:33:20.387789  1741 solver.cpp:218] Iteration 23200 (2.40987 iter/s, 41.496s/100 iters), loss = 0.0111246
I0121 20:33:20.387975  1741 solver.cpp:237]     Train net output #0: loss = 0.0111246 (* 1 = 0.0111246 loss)
I0121 20:33:20.387992  1741 sgd_solver.cpp:105] Iteration 23200, lr = 0.001
I0121 20:34:01.901001  1741 solver.cpp:218] Iteration 23300 (2.40885 iter/s, 41.5135s/100 iters), loss = 0.0170159
I0121 20:34:01.901186  1741 solver.cpp:237]     Train net output #0: loss = 0.0170159 (* 1 = 0.0170159 loss)
I0121 20:34:01.901202  1741 sgd_solver.cpp:105] Iteration 23300, lr = 0.001
I0121 20:34:43.397609  1741 solver.cpp:218] Iteration 23400 (2.40982 iter/s, 41.4969s/100 iters), loss = 0.00940975
I0121 20:34:43.397773  1741 solver.cpp:237]     Train net output #0: loss = 0.00940974 (* 1 = 0.00940974 loss)
I0121 20:34:43.397789  1741 sgd_solver.cpp:105] Iteration 23400, lr = 0.001
I0121 20:34:57.097740  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:35:24.871628  1741 solver.cpp:218] Iteration 23500 (2.41113 iter/s, 41.4743s/100 iters), loss = 0.00999167
I0121 20:35:24.871827  1741 solver.cpp:237]     Train net output #0: loss = 0.00999166 (* 1 = 0.00999166 loss)
I0121 20:35:24.871845  1741 sgd_solver.cpp:105] Iteration 23500, lr = 0.001
I0121 20:36:06.370555  1741 solver.cpp:218] Iteration 23600 (2.40968 iter/s, 41.4992s/100 iters), loss = 0.014759
I0121 20:36:06.370692  1741 solver.cpp:237]     Train net output #0: loss = 0.014759 (* 1 = 0.014759 loss)
I0121 20:36:06.370708  1741 sgd_solver.cpp:105] Iteration 23600, lr = 0.001
I0121 20:36:47.861831  1741 solver.cpp:218] Iteration 23700 (2.41012 iter/s, 41.4916s/100 iters), loss = 0.0277306
I0121 20:36:47.862026  1741 solver.cpp:237]     Train net output #0: loss = 0.0277306 (* 1 = 0.0277306 loss)
I0121 20:36:47.862043  1741 sgd_solver.cpp:105] Iteration 23700, lr = 0.001
I0121 20:37:29.345890  1741 solver.cpp:218] Iteration 23800 (2.41055 iter/s, 41.4844s/100 iters), loss = 0.00787218
I0121 20:37:29.346050  1741 solver.cpp:237]     Train net output #0: loss = 0.00787217 (* 1 = 0.00787217 loss)
I0121 20:37:29.346063  1741 sgd_solver.cpp:105] Iteration 23800, lr = 0.001
I0121 20:37:39.324463  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:38:10.879065  1741 solver.cpp:218] Iteration 23900 (2.4077 iter/s, 41.5335s/100 iters), loss = 0.0151252
I0121 20:38:10.879216  1741 solver.cpp:237]     Train net output #0: loss = 0.0151252 (* 1 = 0.0151252 loss)
I0121 20:38:10.879232  1741 sgd_solver.cpp:105] Iteration 23900, lr = 0.001
I0121 20:38:51.975898  1741 solver.cpp:330] Iteration 24000, Testing net (#0)
I0121 20:39:01.495039  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:39:01.711222  1741 solver.cpp:397]     Test net output #0: accuracy = 0.894444
I0121 20:39:01.711302  1741 solver.cpp:397]     Test net output #1: loss = 0.348949 (* 1 = 0.348949 loss)
I0121 20:39:02.124626  1741 solver.cpp:218] Iteration 24000 (1.95137 iter/s, 51.246s/100 iters), loss = 0.0189219
I0121 20:39:02.124724  1741 solver.cpp:237]     Train net output #0: loss = 0.0189219 (* 1 = 0.0189219 loss)
I0121 20:39:02.124739  1741 sgd_solver.cpp:105] Iteration 24000, lr = 0.001
I0121 20:39:43.658790  1741 solver.cpp:218] Iteration 24100 (2.40763 iter/s, 41.5346s/100 iters), loss = 0.0118546
I0121 20:39:43.658948  1741 solver.cpp:237]     Train net output #0: loss = 0.0118546 (* 1 = 0.0118546 loss)
I0121 20:39:43.658963  1741 sgd_solver.cpp:105] Iteration 24100, lr = 0.001
I0121 20:40:25.213407  1741 solver.cpp:218] Iteration 24200 (2.40645 iter/s, 41.555s/100 iters), loss = 0.0117563
I0121 20:40:25.213589  1741 solver.cpp:237]     Train net output #0: loss = 0.0117563 (* 1 = 0.0117563 loss)
I0121 20:40:25.213606  1741 sgd_solver.cpp:105] Iteration 24200, lr = 0.001
I0121 20:40:31.032054  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:41:06.762984  1741 solver.cpp:218] Iteration 24300 (2.40675 iter/s, 41.5499s/100 iters), loss = 0.0150742
I0121 20:41:06.763114  1741 solver.cpp:237]     Train net output #0: loss = 0.0150741 (* 1 = 0.0150741 loss)
I0121 20:41:06.763131  1741 sgd_solver.cpp:105] Iteration 24300, lr = 0.001
I0121 20:41:48.307895  1741 solver.cpp:218] Iteration 24400 (2.40701 iter/s, 41.5453s/100 iters), loss = 0.0236839
I0121 20:41:48.308020  1741 solver.cpp:237]     Train net output #0: loss = 0.0236839 (* 1 = 0.0236839 loss)
I0121 20:41:48.308037  1741 sgd_solver.cpp:105] Iteration 24400, lr = 0.001
I0121 20:42:29.853052  1741 solver.cpp:218] Iteration 24500 (2.407 iter/s, 41.5455s/100 iters), loss = 0.0182942
I0121 20:42:29.853173  1741 solver.cpp:237]     Train net output #0: loss = 0.0182942 (* 1 = 0.0182942 loss)
I0121 20:42:29.853188  1741 sgd_solver.cpp:105] Iteration 24500, lr = 0.001
I0121 20:43:11.401819  1741 solver.cpp:218] Iteration 24600 (2.40679 iter/s, 41.5492s/100 iters), loss = 0.0148342
I0121 20:43:11.402007  1741 solver.cpp:237]     Train net output #0: loss = 0.0148342 (* 1 = 0.0148342 loss)
I0121 20:43:11.402024  1741 sgd_solver.cpp:105] Iteration 24600, lr = 0.001
I0121 20:43:13.487817  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:43:52.965658  1741 solver.cpp:218] Iteration 24700 (2.40592 iter/s, 41.5641s/100 iters), loss = 0.0169539
I0121 20:43:52.965840  1741 solver.cpp:237]     Train net output #0: loss = 0.0169538 (* 1 = 0.0169538 loss)
I0121 20:43:52.965857  1741 sgd_solver.cpp:105] Iteration 24700, lr = 0.001
I0121 20:44:34.506577  1741 solver.cpp:218] Iteration 24800 (2.40725 iter/s, 41.5412s/100 iters), loss = 0.0151219
I0121 20:44:34.506767  1741 solver.cpp:237]     Train net output #0: loss = 0.0151219 (* 1 = 0.0151219 loss)
I0121 20:44:34.506783  1741 sgd_solver.cpp:105] Iteration 24800, lr = 0.001
I0121 20:45:16.058301  1741 solver.cpp:218] Iteration 24900 (2.40662 iter/s, 41.552s/100 iters), loss = 0.0178902
I0121 20:45:16.058475  1741 solver.cpp:237]     Train net output #0: loss = 0.0178902 (* 1 = 0.0178902 loss)
I0121 20:45:16.058490  1741 sgd_solver.cpp:105] Iteration 24900, lr = 0.001
I0121 20:45:55.519343  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:45:57.173898  1741 solver.cpp:330] Iteration 25000, Testing net (#0)
I0121 20:46:06.691285  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:46:06.906603  1741 solver.cpp:397]     Test net output #0: accuracy = 0.894889
I0121 20:46:06.906672  1741 solver.cpp:397]     Test net output #1: loss = 0.34662 (* 1 = 0.34662 loss)
I0121 20:46:07.322430  1741 solver.cpp:218] Iteration 25000 (1.95066 iter/s, 51.2646s/100 iters), loss = 0.0114254
I0121 20:46:07.322520  1741 solver.cpp:237]     Train net output #0: loss = 0.0114254 (* 1 = 0.0114254 loss)
I0121 20:46:07.322535  1741 sgd_solver.cpp:105] Iteration 25000, lr = 0.001
I0121 20:46:48.902081  1741 solver.cpp:218] Iteration 25100 (2.405 iter/s, 41.5801s/100 iters), loss = 0.00898316
I0121 20:46:48.902281  1741 solver.cpp:237]     Train net output #0: loss = 0.00898315 (* 1 = 0.00898315 loss)
I0121 20:46:48.902297  1741 sgd_solver.cpp:105] Iteration 25100, lr = 0.001
I0121 20:47:30.464340  1741 solver.cpp:218] Iteration 25200 (2.40601 iter/s, 41.5626s/100 iters), loss = 0.0182723
I0121 20:47:30.464545  1741 solver.cpp:237]     Train net output #0: loss = 0.0182722 (* 1 = 0.0182722 loss)
I0121 20:47:30.464567  1741 sgd_solver.cpp:105] Iteration 25200, lr = 0.001
I0121 20:48:12.012287  1741 solver.cpp:218] Iteration 25300 (2.40684 iter/s, 41.5482s/100 iters), loss = 0.0114379
I0121 20:48:12.012462  1741 solver.cpp:237]     Train net output #0: loss = 0.0114379 (* 1 = 0.0114379 loss)
I0121 20:48:12.012480  1741 sgd_solver.cpp:105] Iteration 25300, lr = 0.001
I0121 20:48:47.743036  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:48:53.549028  1741 solver.cpp:218] Iteration 25400 (2.40749 iter/s, 41.5371s/100 iters), loss = 0.010939
I0121 20:48:53.549129  1741 solver.cpp:237]     Train net output #0: loss = 0.010939 (* 1 = 0.010939 loss)
I0121 20:48:53.549144  1741 sgd_solver.cpp:105] Iteration 25400, lr = 0.001
I0121 20:49:35.126636  1741 solver.cpp:218] Iteration 25500 (2.40512 iter/s, 41.578s/100 iters), loss = 0.0157442
I0121 20:49:35.126765  1741 solver.cpp:237]     Train net output #0: loss = 0.0157442 (* 1 = 0.0157442 loss)
I0121 20:49:35.126781  1741 sgd_solver.cpp:105] Iteration 25500, lr = 0.001
I0121 20:50:16.598548  1741 solver.cpp:218] Iteration 25600 (2.41125 iter/s, 41.4723s/100 iters), loss = 0.0107165
I0121 20:50:16.598676  1741 solver.cpp:237]     Train net output #0: loss = 0.0107165 (* 1 = 0.0107165 loss)
I0121 20:50:16.598691  1741 sgd_solver.cpp:105] Iteration 25600, lr = 0.001
I0121 20:50:58.177222  1741 solver.cpp:218] Iteration 25700 (2.40506 iter/s, 41.579s/100 iters), loss = 0.0142064
I0121 20:50:58.177363  1741 solver.cpp:237]     Train net output #0: loss = 0.0142064 (* 1 = 0.0142064 loss)
I0121 20:50:58.177382  1741 sgd_solver.cpp:105] Iteration 25700, lr = 0.001
I0121 20:51:30.171646  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:51:39.726660  1741 solver.cpp:218] Iteration 25800 (2.40675 iter/s, 41.5498s/100 iters), loss = 0.00977039
I0121 20:51:39.726752  1741 solver.cpp:237]     Train net output #0: loss = 0.00977038 (* 1 = 0.00977038 loss)
I0121 20:51:39.726768  1741 sgd_solver.cpp:105] Iteration 25800, lr = 0.001
I0121 20:52:21.306282  1741 solver.cpp:218] Iteration 25900 (2.405 iter/s, 41.5801s/100 iters), loss = 0.00958947
I0121 20:52:21.306468  1741 solver.cpp:237]     Train net output #0: loss = 0.00958946 (* 1 = 0.00958946 loss)
I0121 20:52:21.306485  1741 sgd_solver.cpp:105] Iteration 25900, lr = 0.001
I0121 20:53:02.501065  1741 solver.cpp:330] Iteration 26000, Testing net (#0)
I0121 20:53:12.028666  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:53:12.244371  1741 solver.cpp:397]     Test net output #0: accuracy = 0.894555
I0121 20:53:12.244446  1741 solver.cpp:397]     Test net output #1: loss = 0.347748 (* 1 = 0.347748 loss)
I0121 20:53:12.658375  1741 solver.cpp:218] Iteration 26000 (1.94732 iter/s, 51.3525s/100 iters), loss = 0.0101033
I0121 20:53:12.658473  1741 solver.cpp:237]     Train net output #0: loss = 0.0101033 (* 1 = 0.0101033 loss)
I0121 20:53:12.658488  1741 sgd_solver.cpp:105] Iteration 26000, lr = 0.001
I0121 20:53:54.256213  1741 solver.cpp:218] Iteration 26100 (2.40395 iter/s, 41.5983s/100 iters), loss = 0.0156041
I0121 20:53:54.256400  1741 solver.cpp:237]     Train net output #0: loss = 0.0156041 (* 1 = 0.0156041 loss)
I0121 20:53:54.256417  1741 sgd_solver.cpp:105] Iteration 26100, lr = 0.001
I0121 20:54:22.136144  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:54:35.848610  1741 solver.cpp:218] Iteration 26200 (2.40427 iter/s, 41.5927s/100 iters), loss = 0.00794353
I0121 20:54:35.848834  1741 solver.cpp:237]     Train net output #0: loss = 0.00794352 (* 1 = 0.00794352 loss)
I0121 20:54:35.848852  1741 sgd_solver.cpp:105] Iteration 26200, lr = 0.001
I0121 20:55:17.415558  1741 solver.cpp:218] Iteration 26300 (2.40574 iter/s, 41.5672s/100 iters), loss = 0.0105112
I0121 20:55:17.415752  1741 solver.cpp:237]     Train net output #0: loss = 0.0105112 (* 1 = 0.0105112 loss)
I0121 20:55:17.415767  1741 sgd_solver.cpp:105] Iteration 26300, lr = 0.001
I0121 20:55:59.017459  1741 solver.cpp:218] Iteration 26400 (2.40372 iter/s, 41.6022s/100 iters), loss = 0.0168728
I0121 20:55:59.017633  1741 solver.cpp:237]     Train net output #0: loss = 0.0168728 (* 1 = 0.0168728 loss)
I0121 20:55:59.017650  1741 sgd_solver.cpp:105] Iteration 26400, lr = 0.001
I0121 20:56:40.575904  1741 solver.cpp:218] Iteration 26500 (2.40623 iter/s, 41.5588s/100 iters), loss = 0.0105675
I0121 20:56:40.576093  1741 solver.cpp:237]     Train net output #0: loss = 0.0105675 (* 1 = 0.0105675 loss)
I0121 20:56:40.576110  1741 sgd_solver.cpp:105] Iteration 26500, lr = 0.001
I0121 20:57:04.670159  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 20:57:22.113787  1741 solver.cpp:218] Iteration 26600 (2.40742 iter/s, 41.5382s/100 iters), loss = 0.0106902
I0121 20:57:22.113975  1741 solver.cpp:237]     Train net output #0: loss = 0.0106901 (* 1 = 0.0106901 loss)
I0121 20:57:22.113991  1741 sgd_solver.cpp:105] Iteration 26600, lr = 0.001
I0121 20:58:03.636804  1741 solver.cpp:218] Iteration 26700 (2.40828 iter/s, 41.5233s/100 iters), loss = 0.00732538
I0121 20:58:03.636991  1741 solver.cpp:237]     Train net output #0: loss = 0.00732537 (* 1 = 0.00732537 loss)
I0121 20:58:03.637006  1741 sgd_solver.cpp:105] Iteration 26700, lr = 0.001
I0121 20:58:45.197504  1741 solver.cpp:218] Iteration 26800 (2.4061 iter/s, 41.561s/100 iters), loss = 0.00740138
I0121 20:58:45.197701  1741 solver.cpp:237]     Train net output #0: loss = 0.00740137 (* 1 = 0.00740137 loss)
I0121 20:58:45.197717  1741 sgd_solver.cpp:105] Iteration 26800, lr = 0.001
I0121 20:59:26.812696  1741 solver.cpp:218] Iteration 26900 (2.40295 iter/s, 41.6155s/100 iters), loss = 0.0117204
I0121 20:59:26.812885  1741 solver.cpp:237]     Train net output #0: loss = 0.0117204 (* 1 = 0.0117204 loss)
I0121 20:59:26.812902  1741 sgd_solver.cpp:105] Iteration 26900, lr = 0.001
I0121 20:59:47.190572  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:00:07.958626  1741 solver.cpp:330] Iteration 27000, Testing net (#0)
I0121 21:00:17.481273  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:00:17.695410  1741 solver.cpp:397]     Test net output #0: accuracy = 0.894888
I0121 21:00:17.695482  1741 solver.cpp:397]     Test net output #1: loss = 0.349464 (* 1 = 0.349464 loss)
I0121 21:00:18.110888  1741 solver.cpp:218] Iteration 27000 (1.94937 iter/s, 51.2986s/100 iters), loss = 0.0109797
I0121 21:00:18.110980  1741 solver.cpp:237]     Train net output #0: loss = 0.0109797 (* 1 = 0.0109797 loss)
I0121 21:00:18.110996  1741 sgd_solver.cpp:105] Iteration 27000, lr = 0.001
I0121 21:00:59.639426  1741 solver.cpp:218] Iteration 27100 (2.40796 iter/s, 41.5289s/100 iters), loss = 0.0100466
I0121 21:00:59.639629  1741 solver.cpp:237]     Train net output #0: loss = 0.0100466 (* 1 = 0.0100466 loss)
I0121 21:00:59.639645  1741 sgd_solver.cpp:105] Iteration 27100, lr = 0.001
I0121 21:01:41.168012  1741 solver.cpp:218] Iteration 27200 (2.40796 iter/s, 41.5289s/100 iters), loss = 0.0120323
I0121 21:01:41.168176  1741 solver.cpp:237]     Train net output #0: loss = 0.0120323 (* 1 = 0.0120323 loss)
I0121 21:01:41.168192  1741 sgd_solver.cpp:105] Iteration 27200, lr = 0.001
I0121 21:02:22.731165  1741 solver.cpp:218] Iteration 27300 (2.40596 iter/s, 41.5635s/100 iters), loss = 0.0092206
I0121 21:02:22.731392  1741 solver.cpp:237]     Train net output #0: loss = 0.00922059 (* 1 = 0.00922059 loss)
I0121 21:02:22.731408  1741 sgd_solver.cpp:105] Iteration 27300, lr = 0.001
I0121 21:02:38.940672  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:03:04.280208  1741 solver.cpp:218] Iteration 27400 (2.40678 iter/s, 41.5493s/100 iters), loss = 0.0110877
I0121 21:03:04.280400  1741 solver.cpp:237]     Train net output #0: loss = 0.0110877 (* 1 = 0.0110877 loss)
I0121 21:03:04.280416  1741 sgd_solver.cpp:105] Iteration 27400, lr = 0.001
I0121 21:03:45.794283  1741 solver.cpp:218] Iteration 27500 (2.4088 iter/s, 41.5144s/100 iters), loss = 0.0137132
I0121 21:03:45.794453  1741 solver.cpp:237]     Train net output #0: loss = 0.0137132 (* 1 = 0.0137132 loss)
I0121 21:03:45.794471  1741 sgd_solver.cpp:105] Iteration 27500, lr = 0.001
I0121 21:04:27.301813  1741 solver.cpp:218] Iteration 27600 (2.40918 iter/s, 41.5079s/100 iters), loss = 0.00906712
I0121 21:04:27.301935  1741 solver.cpp:237]     Train net output #0: loss = 0.00906711 (* 1 = 0.00906711 loss)
I0121 21:04:27.301954  1741 sgd_solver.cpp:105] Iteration 27600, lr = 0.001
I0121 21:05:08.845399  1741 solver.cpp:218] Iteration 27700 (2.40709 iter/s, 41.544s/100 iters), loss = 0.0185494
I0121 21:05:08.845594  1741 solver.cpp:237]     Train net output #0: loss = 0.0185494 (* 1 = 0.0185494 loss)
I0121 21:05:08.845612  1741 sgd_solver.cpp:105] Iteration 27700, lr = 0.001
I0121 21:05:21.303673  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:05:50.371330  1741 solver.cpp:218] Iteration 27800 (2.40812 iter/s, 41.5262s/100 iters), loss = 0.010844
I0121 21:05:50.371513  1741 solver.cpp:237]     Train net output #0: loss = 0.010844 (* 1 = 0.010844 loss)
I0121 21:05:50.371531  1741 sgd_solver.cpp:105] Iteration 27800, lr = 0.001
I0121 21:06:31.907001  1741 solver.cpp:218] Iteration 27900 (2.40755 iter/s, 41.536s/100 iters), loss = 0.00942492
I0121 21:06:31.907186  1741 solver.cpp:237]     Train net output #0: loss = 0.00942491 (* 1 = 0.00942491 loss)
I0121 21:06:31.907207  1741 sgd_solver.cpp:105] Iteration 27900, lr = 0.001
I0121 21:07:13.004294  1741 solver.cpp:330] Iteration 28000, Testing net (#0)
I0121 21:07:22.527246  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:07:22.740046  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895889
I0121 21:07:22.740104  1741 solver.cpp:397]     Test net output #1: loss = 0.348195 (* 1 = 0.348195 loss)
I0121 21:07:23.156525  1741 solver.cpp:218] Iteration 28000 (1.95122 iter/s, 51.25s/100 iters), loss = 0.0106123
I0121 21:07:23.156607  1741 solver.cpp:237]     Train net output #0: loss = 0.0106123 (* 1 = 0.0106123 loss)
I0121 21:07:23.156622  1741 sgd_solver.cpp:105] Iteration 28000, lr = 0.001
I0121 21:08:04.702394  1741 solver.cpp:218] Iteration 28100 (2.40695 iter/s, 41.5463s/100 iters), loss = 0.0104757
I0121 21:08:04.702584  1741 solver.cpp:237]     Train net output #0: loss = 0.0104757 (* 1 = 0.0104757 loss)
I0121 21:08:04.702600  1741 sgd_solver.cpp:105] Iteration 28100, lr = 0.001
I0121 21:08:13.016438  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:08:46.255666  1741 solver.cpp:218] Iteration 28200 (2.40653 iter/s, 41.5536s/100 iters), loss = 0.0105936
I0121 21:08:46.255856  1741 solver.cpp:237]     Train net output #0: loss = 0.0105936 (* 1 = 0.0105936 loss)
I0121 21:08:46.255872  1741 sgd_solver.cpp:105] Iteration 28200, lr = 0.001
I0121 21:09:27.796358  1741 solver.cpp:218] Iteration 28300 (2.40726 iter/s, 41.541s/100 iters), loss = 0.0105794
I0121 21:09:27.796514  1741 solver.cpp:237]     Train net output #0: loss = 0.0105794 (* 1 = 0.0105794 loss)
I0121 21:09:27.796530  1741 sgd_solver.cpp:105] Iteration 28300, lr = 0.001
I0121 21:10:09.345049  1741 solver.cpp:218] Iteration 28400 (2.40679 iter/s, 41.549s/100 iters), loss = 0.00911416
I0121 21:10:09.345232  1741 solver.cpp:237]     Train net output #0: loss = 0.00911415 (* 1 = 0.00911415 loss)
I0121 21:10:09.345247  1741 sgd_solver.cpp:105] Iteration 28400, lr = 0.001
I0121 21:10:50.878131  1741 solver.cpp:218] Iteration 28500 (2.4077 iter/s, 41.5334s/100 iters), loss = 0.00693965
I0121 21:10:50.878365  1741 solver.cpp:237]     Train net output #0: loss = 0.00693965 (* 1 = 0.00693965 loss)
I0121 21:10:50.878383  1741 sgd_solver.cpp:105] Iteration 28500, lr = 0.001
I0121 21:10:55.464146  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:11:32.338919  1741 solver.cpp:218] Iteration 28600 (2.4119 iter/s, 41.4611s/100 iters), loss = 0.00710901
I0121 21:11:32.339109  1741 solver.cpp:237]     Train net output #0: loss = 0.007109 (* 1 = 0.007109 loss)
I0121 21:11:32.339135  1741 sgd_solver.cpp:105] Iteration 28600, lr = 0.001
I0121 21:12:13.871748  1741 solver.cpp:218] Iteration 28700 (2.40772 iter/s, 41.5331s/100 iters), loss = 0.00999688
I0121 21:12:13.871924  1741 solver.cpp:237]     Train net output #0: loss = 0.00999688 (* 1 = 0.00999688 loss)
I0121 21:12:13.871939  1741 sgd_solver.cpp:105] Iteration 28700, lr = 0.001
I0121 21:12:55.404554  1741 solver.cpp:218] Iteration 28800 (2.40771 iter/s, 41.5332s/100 iters), loss = 0.0102406
I0121 21:12:55.404747  1741 solver.cpp:237]     Train net output #0: loss = 0.0102406 (* 1 = 0.0102406 loss)
I0121 21:12:55.404768  1741 sgd_solver.cpp:105] Iteration 28800, lr = 0.001
I0121 21:13:36.930948  1741 solver.cpp:218] Iteration 28900 (2.40809 iter/s, 41.5267s/100 iters), loss = 0.0143568
I0121 21:13:36.931129  1741 solver.cpp:237]     Train net output #0: loss = 0.0143568 (* 1 = 0.0143568 loss)
I0121 21:13:36.931149  1741 sgd_solver.cpp:105] Iteration 28900, lr = 0.001
I0121 21:13:37.763865  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:14:18.056011  1741 solver.cpp:330] Iteration 29000, Testing net (#0)
I0121 21:14:27.593911  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:14:27.809926  1741 solver.cpp:397]     Test net output #0: accuracy = 0.894777
I0121 21:14:27.809993  1741 solver.cpp:397]     Test net output #1: loss = 0.348497 (* 1 = 0.348497 loss)
I0121 21:14:28.223945  1741 solver.cpp:218] Iteration 29000 (1.94957 iter/s, 51.2935s/100 iters), loss = 0.0108864
I0121 21:14:28.224046  1741 solver.cpp:237]     Train net output #0: loss = 0.0108864 (* 1 = 0.0108864 loss)
I0121 21:14:28.224061  1741 sgd_solver.cpp:105] Iteration 29000, lr = 0.001
I0121 21:15:09.816110  1741 solver.cpp:218] Iteration 29100 (2.40428 iter/s, 41.5926s/100 iters), loss = 0.0106003
I0121 21:15:09.816308  1741 solver.cpp:237]     Train net output #0: loss = 0.0106003 (* 1 = 0.0106003 loss)
I0121 21:15:09.816334  1741 sgd_solver.cpp:105] Iteration 29100, lr = 0.001
I0121 21:15:51.373827  1741 solver.cpp:218] Iteration 29200 (2.40627 iter/s, 41.558s/100 iters), loss = 0.0137871
I0121 21:15:51.374029  1741 solver.cpp:237]     Train net output #0: loss = 0.013787 (* 1 = 0.013787 loss)
I0121 21:15:51.374053  1741 sgd_solver.cpp:105] Iteration 29200, lr = 0.001
I0121 21:16:29.636143  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:16:32.953284  1741 solver.cpp:218] Iteration 29300 (2.40502 iter/s, 41.5798s/100 iters), loss = 0.00982904
I0121 21:16:32.953392  1741 solver.cpp:237]     Train net output #0: loss = 0.00982904 (* 1 = 0.00982904 loss)
I0121 21:16:32.953406  1741 sgd_solver.cpp:105] Iteration 29300, lr = 0.001
I0121 21:17:14.542066  1741 solver.cpp:218] Iteration 29400 (2.40447 iter/s, 41.5892s/100 iters), loss = 0.00833203
I0121 21:17:14.542192  1741 solver.cpp:237]     Train net output #0: loss = 0.00833202 (* 1 = 0.00833202 loss)
I0121 21:17:14.542207  1741 sgd_solver.cpp:105] Iteration 29400, lr = 0.001
I0121 21:17:56.189098  1741 solver.cpp:218] Iteration 29500 (2.40111 iter/s, 41.6474s/100 iters), loss = 0.0066406
I0121 21:17:56.189297  1741 solver.cpp:237]     Train net output #0: loss = 0.0066406 (* 1 = 0.0066406 loss)
I0121 21:17:56.189318  1741 sgd_solver.cpp:105] Iteration 29500, lr = 0.001
I0121 21:18:37.870323  1741 solver.cpp:218] Iteration 29600 (2.39914 iter/s, 41.6815s/100 iters), loss = 0.0136756
I0121 21:18:37.870523  1741 solver.cpp:237]     Train net output #0: loss = 0.0136756 (* 1 = 0.0136756 loss)
I0121 21:18:37.870544  1741 sgd_solver.cpp:105] Iteration 29600, lr = 0.001
I0121 21:19:12.452920  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:19:19.528581  1741 solver.cpp:218] Iteration 29700 (2.40046 iter/s, 41.6586s/100 iters), loss = 0.00993399
I0121 21:19:19.528684  1741 solver.cpp:237]     Train net output #0: loss = 0.00993398 (* 1 = 0.00993398 loss)
I0121 21:19:19.528704  1741 sgd_solver.cpp:105] Iteration 29700, lr = 0.001
I0121 21:20:01.154563  1741 solver.cpp:218] Iteration 29800 (2.40232 iter/s, 41.6264s/100 iters), loss = 0.0130873
I0121 21:20:01.154765  1741 solver.cpp:237]     Train net output #0: loss = 0.0130873 (* 1 = 0.0130873 loss)
I0121 21:20:01.154785  1741 sgd_solver.cpp:105] Iteration 29800, lr = 0.001
I0121 21:20:42.809271  1741 solver.cpp:218] Iteration 29900 (2.40067 iter/s, 41.6551s/100 iters), loss = 0.0101049
I0121 21:20:42.809461  1741 solver.cpp:237]     Train net output #0: loss = 0.0101049 (* 1 = 0.0101049 loss)
I0121 21:20:42.809484  1741 sgd_solver.cpp:105] Iteration 29900, lr = 0.001
I0121 21:21:24.083248  1741 solver.cpp:447] Snapshotting to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_30000.caffemodel
I0121 21:21:24.104560  1741 sgd_solver.cpp:273] Snapshotting solver state to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_30000.solverstate
I0121 21:21:24.111426  1741 solver.cpp:330] Iteration 30000, Testing net (#0)
I0121 21:21:33.696815  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:21:33.912894  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895
I0121 21:21:33.912968  1741 solver.cpp:397]     Test net output #1: loss = 0.346639 (* 1 = 0.346639 loss)
I0121 21:21:34.334141  1741 solver.cpp:218] Iteration 30000 (1.94079 iter/s, 51.5253s/100 iters), loss = 0.00542565
I0121 21:21:34.334242  1741 solver.cpp:237]     Train net output #0: loss = 0.00542565 (* 1 = 0.00542565 loss)
I0121 21:21:34.334257  1741 sgd_solver.cpp:105] Iteration 30000, lr = 0.0001
I0121 21:22:05.161747  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:22:15.996923  1741 solver.cpp:218] Iteration 30100 (2.4002 iter/s, 41.6632s/100 iters), loss = 0.00555655
I0121 21:22:15.997016  1741 solver.cpp:237]     Train net output #0: loss = 0.00555654 (* 1 = 0.00555654 loss)
I0121 21:22:15.997032  1741 sgd_solver.cpp:105] Iteration 30100, lr = 0.0001
I0121 21:22:57.750516  1741 solver.cpp:218] Iteration 30200 (2.39498 iter/s, 41.754s/100 iters), loss = 0.0113376
I0121 21:22:57.750685  1741 solver.cpp:237]     Train net output #0: loss = 0.0113376 (* 1 = 0.0113376 loss)
I0121 21:22:57.750702  1741 sgd_solver.cpp:105] Iteration 30200, lr = 0.0001
I0121 21:23:39.433637  1741 solver.cpp:218] Iteration 30300 (2.39903 iter/s, 41.6835s/100 iters), loss = 0.00611343
I0121 21:23:39.433782  1741 solver.cpp:237]     Train net output #0: loss = 0.00611343 (* 1 = 0.00611343 loss)
I0121 21:23:39.433800  1741 sgd_solver.cpp:105] Iteration 30300, lr = 0.0001
I0121 21:24:21.128824  1741 solver.cpp:218] Iteration 30400 (2.39834 iter/s, 41.6956s/100 iters), loss = 0.00775273
I0121 21:24:21.128959  1741 solver.cpp:237]     Train net output #0: loss = 0.00775273 (* 1 = 0.00775273 loss)
I0121 21:24:21.128976  1741 sgd_solver.cpp:105] Iteration 30400, lr = 0.0001
I0121 21:24:47.878652  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:25:02.892216  1741 solver.cpp:218] Iteration 30500 (2.39442 iter/s, 41.7638s/100 iters), loss = 0.00944009
I0121 21:25:02.892406  1741 solver.cpp:237]     Train net output #0: loss = 0.00944009 (* 1 = 0.00944009 loss)
I0121 21:25:02.892423  1741 sgd_solver.cpp:105] Iteration 30500, lr = 0.0001
I0121 21:25:44.588977  1741 solver.cpp:218] Iteration 30600 (2.39825 iter/s, 41.6971s/100 iters), loss = 0.00866554
I0121 21:25:44.589166  1741 solver.cpp:237]     Train net output #0: loss = 0.00866553 (* 1 = 0.00866553 loss)
I0121 21:25:44.589182  1741 sgd_solver.cpp:105] Iteration 30600, lr = 0.0001
I0121 21:26:26.219839  1741 solver.cpp:218] Iteration 30700 (2.40205 iter/s, 41.6312s/100 iters), loss = 0.00780767
I0121 21:26:26.220057  1741 solver.cpp:237]     Train net output #0: loss = 0.00780767 (* 1 = 0.00780767 loss)
I0121 21:26:26.220073  1741 sgd_solver.cpp:105] Iteration 30700, lr = 0.0001
I0121 21:27:07.836272  1741 solver.cpp:218] Iteration 30800 (2.40288 iter/s, 41.6168s/100 iters), loss = 0.0129564
I0121 21:27:07.836432  1741 solver.cpp:237]     Train net output #0: loss = 0.0129564 (* 1 = 0.0129564 loss)
I0121 21:27:07.836448  1741 sgd_solver.cpp:105] Iteration 30800, lr = 0.0001
I0121 21:27:30.720094  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:27:49.446559  1741 solver.cpp:218] Iteration 30900 (2.40323 iter/s, 41.6106s/100 iters), loss = 0.0066659
I0121 21:27:49.446677  1741 solver.cpp:237]     Train net output #0: loss = 0.00666589 (* 1 = 0.00666589 loss)
I0121 21:27:49.446697  1741 sgd_solver.cpp:105] Iteration 30900, lr = 0.0001
I0121 21:28:30.635097  1741 solver.cpp:330] Iteration 31000, Testing net (#0)
I0121 21:28:40.191759  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:28:40.408804  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895222
I0121 21:28:40.408881  1741 solver.cpp:397]     Test net output #1: loss = 0.34652 (* 1 = 0.34652 loss)
I0121 21:28:40.822288  1741 solver.cpp:218] Iteration 31000 (1.94642 iter/s, 51.3763s/100 iters), loss = 0.0101422
I0121 21:28:40.822386  1741 solver.cpp:237]     Train net output #0: loss = 0.0101422 (* 1 = 0.0101422 loss)
I0121 21:28:40.822402  1741 sgd_solver.cpp:105] Iteration 31000, lr = 0.0001
I0121 21:29:22.439864  1741 solver.cpp:218] Iteration 31100 (2.40281 iter/s, 41.618s/100 iters), loss = 0.00960192
I0121 21:29:22.440030  1741 solver.cpp:237]     Train net output #0: loss = 0.00960192 (* 1 = 0.00960192 loss)
I0121 21:29:22.440047  1741 sgd_solver.cpp:105] Iteration 31100, lr = 0.0001
I0121 21:30:04.058810  1741 solver.cpp:218] Iteration 31200 (2.40273 iter/s, 41.6193s/100 iters), loss = 0.00751778
I0121 21:30:04.058938  1741 solver.cpp:237]     Train net output #0: loss = 0.00751778 (* 1 = 0.00751778 loss)
I0121 21:30:04.058953  1741 sgd_solver.cpp:105] Iteration 31200, lr = 0.0001
I0121 21:30:22.800081  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:30:45.678669  1741 solver.cpp:218] Iteration 31300 (2.40268 iter/s, 41.6203s/100 iters), loss = 0.00663344
I0121 21:30:45.678835  1741 solver.cpp:237]     Train net output #0: loss = 0.00663344 (* 1 = 0.00663344 loss)
I0121 21:30:45.678851  1741 sgd_solver.cpp:105] Iteration 31300, lr = 0.0001
I0121 21:31:27.342908  1741 solver.cpp:218] Iteration 31400 (2.40012 iter/s, 41.6646s/100 iters), loss = 0.00987788
I0121 21:31:27.343086  1741 solver.cpp:237]     Train net output #0: loss = 0.00987788 (* 1 = 0.00987788 loss)
I0121 21:31:27.343102  1741 sgd_solver.cpp:105] Iteration 31400, lr = 0.0001
I0121 21:32:08.987262  1741 solver.cpp:218] Iteration 31500 (2.40127 iter/s, 41.6447s/100 iters), loss = 0.00744178
I0121 21:32:08.987376  1741 solver.cpp:237]     Train net output #0: loss = 0.00744178 (* 1 = 0.00744178 loss)
I0121 21:32:08.987392  1741 sgd_solver.cpp:105] Iteration 31500, lr = 0.0001
I0121 21:32:50.601501  1741 solver.cpp:218] Iteration 31600 (2.403 iter/s, 41.6147s/100 iters), loss = 0.00550998
I0121 21:32:50.601651  1741 solver.cpp:237]     Train net output #0: loss = 0.00550998 (* 1 = 0.00550998 loss)
I0121 21:32:50.601666  1741 sgd_solver.cpp:105] Iteration 31600, lr = 0.0001
I0121 21:33:05.560776  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:33:32.206220  1741 solver.cpp:218] Iteration 31700 (2.40355 iter/s, 41.6051s/100 iters), loss = 0.00676373
I0121 21:33:32.206336  1741 solver.cpp:237]     Train net output #0: loss = 0.00676373 (* 1 = 0.00676373 loss)
I0121 21:33:32.206352  1741 sgd_solver.cpp:105] Iteration 31700, lr = 0.0001
I0121 21:34:13.861001  1741 solver.cpp:218] Iteration 31800 (2.40066 iter/s, 41.6552s/100 iters), loss = 0.0124069
I0121 21:34:13.861227  1741 solver.cpp:237]     Train net output #0: loss = 0.0124069 (* 1 = 0.0124069 loss)
I0121 21:34:13.861244  1741 sgd_solver.cpp:105] Iteration 31800, lr = 0.0001
I0121 21:34:55.596552  1741 solver.cpp:218] Iteration 31900 (2.39602 iter/s, 41.7358s/100 iters), loss = 0.0116604
I0121 21:34:55.596727  1741 solver.cpp:237]     Train net output #0: loss = 0.0116604 (* 1 = 0.0116604 loss)
I0121 21:34:55.596745  1741 sgd_solver.cpp:105] Iteration 31900, lr = 0.0001
I0121 21:35:36.876508  1741 solver.cpp:330] Iteration 32000, Testing net (#0)
I0121 21:35:46.443275  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:35:46.657785  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895
I0121 21:35:46.657840  1741 solver.cpp:397]     Test net output #1: loss = 0.34619 (* 1 = 0.34619 loss)
I0121 21:35:47.075157  1741 solver.cpp:218] Iteration 32000 (1.94254 iter/s, 51.4791s/100 iters), loss = 0.00495708
I0121 21:35:47.075223  1741 solver.cpp:237]     Train net output #0: loss = 0.00495708 (* 1 = 0.00495708 loss)
I0121 21:35:47.075238  1741 sgd_solver.cpp:105] Iteration 32000, lr = 0.0001
I0121 21:35:58.313699  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:36:28.702725  1741 solver.cpp:218] Iteration 32100 (2.40223 iter/s, 41.628s/100 iters), loss = 0.012873
I0121 21:36:28.702885  1741 solver.cpp:237]     Train net output #0: loss = 0.012873 (* 1 = 0.012873 loss)
I0121 21:36:28.702903  1741 sgd_solver.cpp:105] Iteration 32100, lr = 0.0001
I0121 21:37:10.330663  1741 solver.cpp:218] Iteration 32200 (2.40221 iter/s, 41.6283s/100 iters), loss = 0.00952953
I0121 21:37:10.330811  1741 solver.cpp:237]     Train net output #0: loss = 0.00952953 (* 1 = 0.00952953 loss)
I0121 21:37:10.330826  1741 sgd_solver.cpp:105] Iteration 32200, lr = 0.0001
I0121 21:37:51.961957  1741 solver.cpp:218] Iteration 32300 (2.40202 iter/s, 41.6317s/100 iters), loss = 0.00818177
I0121 21:37:51.962127  1741 solver.cpp:237]     Train net output #0: loss = 0.00818177 (* 1 = 0.00818177 loss)
I0121 21:37:51.962142  1741 sgd_solver.cpp:105] Iteration 32300, lr = 0.0001
I0121 21:38:33.594987  1741 solver.cpp:218] Iteration 32400 (2.40192 iter/s, 41.6334s/100 iters), loss = 0.0072501
I0121 21:38:33.595156  1741 solver.cpp:237]     Train net output #0: loss = 0.0072501 (* 1 = 0.0072501 loss)
I0121 21:38:33.595173  1741 sgd_solver.cpp:105] Iteration 32400, lr = 0.0001
I0121 21:38:40.672415  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:39:15.239722  1741 solver.cpp:218] Iteration 32500 (2.40124 iter/s, 41.6451s/100 iters), loss = 0.00886301
I0121 21:39:15.239890  1741 solver.cpp:237]     Train net output #0: loss = 0.00886301 (* 1 = 0.00886301 loss)
I0121 21:39:15.239905  1741 sgd_solver.cpp:105] Iteration 32500, lr = 0.0001
I0121 21:39:56.889569  1741 solver.cpp:218] Iteration 32600 (2.40095 iter/s, 41.6502s/100 iters), loss = 0.0138659
I0121 21:39:56.889745  1741 solver.cpp:237]     Train net output #0: loss = 0.0138659 (* 1 = 0.0138659 loss)
I0121 21:39:56.889765  1741 sgd_solver.cpp:105] Iteration 32600, lr = 0.0001
I0121 21:40:38.517622  1741 solver.cpp:218] Iteration 32700 (2.40221 iter/s, 41.6284s/100 iters), loss = 0.00792371
I0121 21:40:38.517812  1741 solver.cpp:237]     Train net output #0: loss = 0.00792371 (* 1 = 0.00792371 loss)
I0121 21:40:38.517828  1741 sgd_solver.cpp:105] Iteration 32700, lr = 0.0001
I0121 21:41:20.153695  1741 solver.cpp:218] Iteration 32800 (2.40175 iter/s, 41.6364s/100 iters), loss = 0.01176
I0121 21:41:20.153877  1741 solver.cpp:237]     Train net output #0: loss = 0.01176 (* 1 = 0.01176 loss)
I0121 21:41:20.153893  1741 sgd_solver.cpp:105] Iteration 32800, lr = 0.0001
I0121 21:41:23.484551  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:42:01.795351  1741 solver.cpp:218] Iteration 32900 (2.40142 iter/s, 41.642s/100 iters), loss = 0.00814549
I0121 21:42:01.795584  1741 solver.cpp:237]     Train net output #0: loss = 0.00814549 (* 1 = 0.00814549 loss)
I0121 21:42:01.795601  1741 sgd_solver.cpp:105] Iteration 32900, lr = 0.0001
I0121 21:42:43.023339  1741 solver.cpp:330] Iteration 33000, Testing net (#0)
I0121 21:42:52.568751  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:42:52.783177  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895444
I0121 21:42:52.783229  1741 solver.cpp:397]     Test net output #1: loss = 0.346457 (* 1 = 0.346457 loss)
I0121 21:42:53.198880  1741 solver.cpp:218] Iteration 33000 (1.94538 iter/s, 51.4039s/100 iters), loss = 0.00976386
I0121 21:42:53.198969  1741 solver.cpp:237]     Train net output #0: loss = 0.00976386 (* 1 = 0.00976386 loss)
I0121 21:42:53.198984  1741 sgd_solver.cpp:105] Iteration 33000, lr = 0.0001
I0121 21:43:34.826892  1741 solver.cpp:218] Iteration 33100 (2.4022 iter/s, 41.6284s/100 iters), loss = 0.0111998
I0121 21:43:34.827075  1741 solver.cpp:237]     Train net output #0: loss = 0.0111998 (* 1 = 0.0111998 loss)
I0121 21:43:34.827091  1741 sgd_solver.cpp:105] Iteration 33100, lr = 0.0001
I0121 21:44:16.020064  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:44:16.431869  1741 solver.cpp:218] Iteration 33200 (2.40354 iter/s, 41.6053s/100 iters), loss = 0.0152387
I0121 21:44:16.431962  1741 solver.cpp:237]     Train net output #0: loss = 0.0152387 (* 1 = 0.0152387 loss)
I0121 21:44:16.431977  1741 sgd_solver.cpp:105] Iteration 33200, lr = 0.0001
I0121 21:44:58.043130  1741 solver.cpp:218] Iteration 33300 (2.40317 iter/s, 41.6117s/100 iters), loss = 0.0123976
I0121 21:44:58.043303  1741 solver.cpp:237]     Train net output #0: loss = 0.0123976 (* 1 = 0.0123976 loss)
I0121 21:44:58.043319  1741 sgd_solver.cpp:105] Iteration 33300, lr = 0.0001
I0121 21:45:39.632472  1741 solver.cpp:218] Iteration 33400 (2.40444 iter/s, 41.5897s/100 iters), loss = 0.0165487
I0121 21:45:39.632658  1741 solver.cpp:237]     Train net output #0: loss = 0.0165487 (* 1 = 0.0165487 loss)
I0121 21:45:39.632678  1741 sgd_solver.cpp:105] Iteration 33400, lr = 0.0001
I0121 21:46:21.235085  1741 solver.cpp:218] Iteration 33500 (2.40368 iter/s, 41.6029s/100 iters), loss = 0.0090369
I0121 21:46:21.235285  1741 solver.cpp:237]     Train net output #0: loss = 0.0090369 (* 1 = 0.0090369 loss)
I0121 21:46:21.235308  1741 sgd_solver.cpp:105] Iteration 33500, lr = 0.0001
I0121 21:46:58.251945  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:47:02.823567  1741 solver.cpp:218] Iteration 33600 (2.40449 iter/s, 41.5888s/100 iters), loss = 0.0106132
I0121 21:47:02.823664  1741 solver.cpp:237]     Train net output #0: loss = 0.0106132 (* 1 = 0.0106132 loss)
I0121 21:47:02.823680  1741 sgd_solver.cpp:105] Iteration 33600, lr = 0.0001
I0121 21:47:44.430160  1741 solver.cpp:218] Iteration 33700 (2.40344 iter/s, 41.607s/100 iters), loss = 0.00915787
I0121 21:47:44.430346  1741 solver.cpp:237]     Train net output #0: loss = 0.00915787 (* 1 = 0.00915787 loss)
I0121 21:47:44.430364  1741 sgd_solver.cpp:105] Iteration 33700, lr = 0.0001
I0121 21:48:26.025254  1741 solver.cpp:218] Iteration 33800 (2.40411 iter/s, 41.5954s/100 iters), loss = 0.0109555
I0121 21:48:26.025420  1741 solver.cpp:237]     Train net output #0: loss = 0.0109555 (* 1 = 0.0109555 loss)
I0121 21:48:26.025436  1741 sgd_solver.cpp:105] Iteration 33800, lr = 0.0001
I0121 21:49:07.635850  1741 solver.cpp:218] Iteration 33900 (2.40321 iter/s, 41.6109s/100 iters), loss = 0.00891923
I0121 21:49:07.636044  1741 solver.cpp:237]     Train net output #0: loss = 0.00891923 (* 1 = 0.00891923 loss)
I0121 21:49:07.636060  1741 sgd_solver.cpp:105] Iteration 33900, lr = 0.0001
I0121 21:49:40.927124  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:49:48.828425  1741 solver.cpp:330] Iteration 34000, Testing net (#0)
I0121 21:49:58.378285  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:49:58.592952  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895778
I0121 21:49:58.593025  1741 solver.cpp:397]     Test net output #1: loss = 0.346473 (* 1 = 0.346473 loss)
I0121 21:49:59.010198  1741 solver.cpp:218] Iteration 34000 (1.94648 iter/s, 51.3748s/100 iters), loss = 0.00674987
I0121 21:49:59.010274  1741 solver.cpp:237]     Train net output #0: loss = 0.00674987 (* 1 = 0.00674987 loss)
I0121 21:49:59.010288  1741 sgd_solver.cpp:105] Iteration 34000, lr = 0.0001
I0121 21:50:40.630311  1741 solver.cpp:218] Iteration 34100 (2.40266 iter/s, 41.6205s/100 iters), loss = 0.00884215
I0121 21:50:40.630550  1741 solver.cpp:237]     Train net output #0: loss = 0.00884215 (* 1 = 0.00884215 loss)
I0121 21:50:40.630569  1741 sgd_solver.cpp:105] Iteration 34100, lr = 0.0001
I0121 21:51:22.227762  1741 solver.cpp:218] Iteration 34200 (2.40398 iter/s, 41.5977s/100 iters), loss = 0.0107262
I0121 21:51:22.227939  1741 solver.cpp:237]     Train net output #0: loss = 0.0107262 (* 1 = 0.0107262 loss)
I0121 21:51:22.227958  1741 sgd_solver.cpp:105] Iteration 34200, lr = 0.0001
I0121 21:52:03.867553  1741 solver.cpp:218] Iteration 34300 (2.40153 iter/s, 41.6401s/100 iters), loss = 0.0148086
I0121 21:52:03.867741  1741 solver.cpp:237]     Train net output #0: loss = 0.0148086 (* 1 = 0.0148086 loss)
I0121 21:52:03.867759  1741 sgd_solver.cpp:105] Iteration 34300, lr = 0.0001
I0121 21:52:33.026334  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:52:45.514720  1741 solver.cpp:218] Iteration 34400 (2.40111 iter/s, 41.6475s/100 iters), loss = 0.0131859
I0121 21:52:45.514847  1741 solver.cpp:237]     Train net output #0: loss = 0.0131859 (* 1 = 0.0131859 loss)
I0121 21:52:45.514863  1741 sgd_solver.cpp:105] Iteration 34400, lr = 0.0001
I0121 21:53:27.197823  1741 solver.cpp:218] Iteration 34500 (2.39903 iter/s, 41.6835s/100 iters), loss = 0.00997038
I0121 21:53:27.198014  1741 solver.cpp:237]     Train net output #0: loss = 0.00997038 (* 1 = 0.00997038 loss)
I0121 21:53:27.198030  1741 sgd_solver.cpp:105] Iteration 34500, lr = 0.0001
I0121 21:54:08.877099  1741 solver.cpp:218] Iteration 34600 (2.39926 iter/s, 41.6796s/100 iters), loss = 0.00892996
I0121 21:54:08.877229  1741 solver.cpp:237]     Train net output #0: loss = 0.00892996 (* 1 = 0.00892996 loss)
I0121 21:54:08.877245  1741 sgd_solver.cpp:105] Iteration 34600, lr = 0.0001
I0121 21:54:50.514639  1741 solver.cpp:218] Iteration 34700 (2.40166 iter/s, 41.6379s/100 iters), loss = 0.00727224
I0121 21:54:50.514775  1741 solver.cpp:237]     Train net output #0: loss = 0.00727224 (* 1 = 0.00727224 loss)
I0121 21:54:50.514791  1741 sgd_solver.cpp:105] Iteration 34700, lr = 0.0001
I0121 21:55:15.836906  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:55:32.057320  1741 solver.cpp:218] Iteration 34800 (2.40714 iter/s, 41.5431s/100 iters), loss = 0.00527153
I0121 21:55:32.057494  1741 solver.cpp:237]     Train net output #0: loss = 0.00527153 (* 1 = 0.00527153 loss)
I0121 21:55:32.057512  1741 sgd_solver.cpp:105] Iteration 34800, lr = 0.0001
I0121 21:56:13.716950  1741 solver.cpp:218] Iteration 34900 (2.40039 iter/s, 41.66s/100 iters), loss = 0.0096564
I0121 21:56:13.717133  1741 solver.cpp:237]     Train net output #0: loss = 0.0096564 (* 1 = 0.0096564 loss)
I0121 21:56:13.717150  1741 sgd_solver.cpp:105] Iteration 34900, lr = 0.0001
I0121 21:56:54.936677  1741 solver.cpp:330] Iteration 35000, Testing net (#0)
I0121 21:57:04.503154  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:57:04.717624  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895222
I0121 21:57:04.717695  1741 solver.cpp:397]     Test net output #1: loss = 0.346456 (* 1 = 0.346456 loss)
I0121 21:57:05.136677  1741 solver.cpp:218] Iteration 35000 (1.94476 iter/s, 51.4202s/100 iters), loss = 0.0131256
I0121 21:57:05.136772  1741 solver.cpp:237]     Train net output #0: loss = 0.0131256 (* 1 = 0.0131256 loss)
I0121 21:57:05.136787  1741 sgd_solver.cpp:105] Iteration 35000, lr = 0.0001
I0121 21:57:46.815127  1741 solver.cpp:218] Iteration 35100 (2.3993 iter/s, 41.6789s/100 iters), loss = 0.0093389
I0121 21:57:46.815280  1741 solver.cpp:237]     Train net output #0: loss = 0.0093389 (* 1 = 0.0093389 loss)
I0121 21:57:46.815297  1741 sgd_solver.cpp:105] Iteration 35100, lr = 0.0001
I0121 21:58:08.490449  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 21:58:28.454224  1741 solver.cpp:218] Iteration 35200 (2.40157 iter/s, 41.6395s/100 iters), loss = 0.00613869
I0121 21:58:28.454427  1741 solver.cpp:237]     Train net output #0: loss = 0.00613869 (* 1 = 0.00613869 loss)
I0121 21:58:28.454443  1741 sgd_solver.cpp:105] Iteration 35200, lr = 0.0001
I0121 21:59:10.104009  1741 solver.cpp:218] Iteration 35300 (2.40095 iter/s, 41.6501s/100 iters), loss = 0.00651503
I0121 21:59:10.104188  1741 solver.cpp:237]     Train net output #0: loss = 0.00651503 (* 1 = 0.00651503 loss)
I0121 21:59:10.104207  1741 sgd_solver.cpp:105] Iteration 35300, lr = 0.0001
I0121 21:59:51.730110  1741 solver.cpp:218] Iteration 35400 (2.40232 iter/s, 41.6264s/100 iters), loss = 0.0167341
I0121 21:59:51.730315  1741 solver.cpp:237]     Train net output #0: loss = 0.0167341 (* 1 = 0.0167341 loss)
I0121 21:59:51.730345  1741 sgd_solver.cpp:105] Iteration 35400, lr = 0.0001
I0121 22:00:33.344091  1741 solver.cpp:218] Iteration 35500 (2.40302 iter/s, 41.6143s/100 iters), loss = 0.00920336
I0121 22:00:33.344216  1741 solver.cpp:237]     Train net output #0: loss = 0.00920336 (* 1 = 0.00920336 loss)
I0121 22:00:33.344238  1741 sgd_solver.cpp:105] Iteration 35500, lr = 0.0001
I0121 22:00:50.831930  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:01:14.968827  1741 solver.cpp:218] Iteration 35600 (2.4024 iter/s, 41.6251s/100 iters), loss = 0.0135252
I0121 22:01:14.968963  1741 solver.cpp:237]     Train net output #0: loss = 0.0135252 (* 1 = 0.0135252 loss)
I0121 22:01:14.968984  1741 sgd_solver.cpp:105] Iteration 35600, lr = 0.0001
I0121 22:01:56.596421  1741 solver.cpp:218] Iteration 35700 (2.40223 iter/s, 41.628s/100 iters), loss = 0.0113667
I0121 22:01:56.596612  1741 solver.cpp:237]     Train net output #0: loss = 0.0113667 (* 1 = 0.0113667 loss)
I0121 22:01:56.596635  1741 sgd_solver.cpp:105] Iteration 35700, lr = 0.0001
I0121 22:02:38.204704  1741 solver.cpp:218] Iteration 35800 (2.40335 iter/s, 41.6087s/100 iters), loss = 0.0155489
I0121 22:02:38.204814  1741 solver.cpp:237]     Train net output #0: loss = 0.0155489 (* 1 = 0.0155489 loss)
I0121 22:02:38.204834  1741 sgd_solver.cpp:105] Iteration 35800, lr = 0.0001
I0121 22:03:19.813436  1741 solver.cpp:218] Iteration 35900 (2.40332 iter/s, 41.6091s/100 iters), loss = 0.00690969
I0121 22:03:19.813632  1741 solver.cpp:237]     Train net output #0: loss = 0.00690969 (* 1 = 0.00690969 loss)
I0121 22:03:19.813660  1741 sgd_solver.cpp:105] Iteration 35900, lr = 0.0001
I0121 22:03:33.549098  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:04:01.026600  1741 solver.cpp:330] Iteration 36000, Testing net (#0)
I0121 22:04:10.578871  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:04:10.794111  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895778
I0121 22:04:10.794186  1741 solver.cpp:397]     Test net output #1: loss = 0.346033 (* 1 = 0.346033 loss)
I0121 22:04:11.209934  1741 solver.cpp:218] Iteration 36000 (1.94564 iter/s, 51.397s/100 iters), loss = 0.00982381
I0121 22:04:11.210034  1741 solver.cpp:237]     Train net output #0: loss = 0.00982381 (* 1 = 0.00982381 loss)
I0121 22:04:11.210053  1741 sgd_solver.cpp:105] Iteration 36000, lr = 0.0001
I0121 22:04:52.816494  1741 solver.cpp:218] Iteration 36100 (2.40344 iter/s, 41.607s/100 iters), loss = 0.00969326
I0121 22:04:52.816654  1741 solver.cpp:237]     Train net output #0: loss = 0.00969326 (* 1 = 0.00969326 loss)
I0121 22:04:52.816674  1741 sgd_solver.cpp:105] Iteration 36100, lr = 0.0001
I0121 22:05:34.416431  1741 solver.cpp:218] Iteration 36200 (2.40383 iter/s, 41.6003s/100 iters), loss = 0.00832922
I0121 22:05:34.416596  1741 solver.cpp:237]     Train net output #0: loss = 0.00832922 (* 1 = 0.00832922 loss)
I0121 22:05:34.416617  1741 sgd_solver.cpp:105] Iteration 36200, lr = 0.0001
I0121 22:06:16.045274  1741 solver.cpp:218] Iteration 36300 (2.40216 iter/s, 41.6292s/100 iters), loss = 0.0117484
I0121 22:06:16.045431  1741 solver.cpp:237]     Train net output #0: loss = 0.0117484 (* 1 = 0.0117484 loss)
I0121 22:06:16.045452  1741 sgd_solver.cpp:105] Iteration 36300, lr = 0.0001
I0121 22:06:26.040230  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:06:57.678681  1741 solver.cpp:218] Iteration 36400 (2.4019 iter/s, 41.6338s/100 iters), loss = 0.0115027
I0121 22:06:57.678886  1741 solver.cpp:237]     Train net output #0: loss = 0.0115027 (* 1 = 0.0115027 loss)
I0121 22:06:57.678916  1741 sgd_solver.cpp:105] Iteration 36400, lr = 0.0001
I0121 22:07:39.314824  1741 solver.cpp:218] Iteration 36500 (2.40174 iter/s, 41.6365s/100 iters), loss = 0.00692285
I0121 22:07:39.315026  1741 solver.cpp:237]     Train net output #0: loss = 0.00692284 (* 1 = 0.00692284 loss)
I0121 22:07:39.315048  1741 sgd_solver.cpp:105] Iteration 36500, lr = 0.0001
I0121 22:08:21.004818  1741 solver.cpp:218] Iteration 36600 (2.39864 iter/s, 41.6903s/100 iters), loss = 0.00940163
I0121 22:08:21.005015  1741 solver.cpp:237]     Train net output #0: loss = 0.00940163 (* 1 = 0.00940163 loss)
I0121 22:08:21.005041  1741 sgd_solver.cpp:105] Iteration 36600, lr = 0.0001
I0121 22:09:02.689450  1741 solver.cpp:218] Iteration 36700 (2.39895 iter/s, 41.6849s/100 iters), loss = 0.00774674
I0121 22:09:02.689646  1741 solver.cpp:237]     Train net output #0: loss = 0.00774674 (* 1 = 0.00774674 loss)
I0121 22:09:02.689667  1741 sgd_solver.cpp:105] Iteration 36700, lr = 0.0001
I0121 22:09:08.527772  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:09:44.337069  1741 solver.cpp:218] Iteration 36800 (2.40108 iter/s, 41.648s/100 iters), loss = 0.00772086
I0121 22:09:44.337237  1741 solver.cpp:237]     Train net output #0: loss = 0.00772086 (* 1 = 0.00772086 loss)
I0121 22:09:44.337255  1741 sgd_solver.cpp:105] Iteration 36800, lr = 0.0001
I0121 22:10:25.974891  1741 solver.cpp:218] Iteration 36900 (2.40164 iter/s, 41.6381s/100 iters), loss = 0.0149785
I0121 22:10:25.975092  1741 solver.cpp:237]     Train net output #0: loss = 0.0149785 (* 1 = 0.0149785 loss)
I0121 22:10:25.975114  1741 sgd_solver.cpp:105] Iteration 36900, lr = 0.0001
I0121 22:11:07.223392  1741 solver.cpp:330] Iteration 37000, Testing net (#0)
I0121 22:11:16.791283  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:11:17.007977  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895667
I0121 22:11:17.008054  1741 solver.cpp:397]     Test net output #1: loss = 0.346189 (* 1 = 0.346189 loss)
I0121 22:11:17.426375  1741 solver.cpp:218] Iteration 37000 (1.94356 iter/s, 51.4519s/100 iters), loss = 0.0143812
I0121 22:11:17.426482  1741 solver.cpp:237]     Train net output #0: loss = 0.0143811 (* 1 = 0.0143811 loss)
I0121 22:11:17.426502  1741 sgd_solver.cpp:105] Iteration 37000, lr = 0.0001
I0121 22:11:59.036741  1741 solver.cpp:218] Iteration 37100 (2.40322 iter/s, 41.6108s/100 iters), loss = 0.00747499
I0121 22:11:59.036880  1741 solver.cpp:237]     Train net output #0: loss = 0.00747498 (* 1 = 0.00747498 loss)
I0121 22:11:59.036903  1741 sgd_solver.cpp:105] Iteration 37100, lr = 0.0001
I0121 22:12:01.123919  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:12:40.686208  1741 solver.cpp:218] Iteration 37200 (2.40097 iter/s, 41.6498s/100 iters), loss = 0.0100741
I0121 22:12:40.686394  1741 solver.cpp:237]     Train net output #0: loss = 0.0100741 (* 1 = 0.0100741 loss)
I0121 22:12:40.686415  1741 sgd_solver.cpp:105] Iteration 37200, lr = 0.0001
I0121 22:13:22.318590  1741 solver.cpp:218] Iteration 37300 (2.40196 iter/s, 41.6327s/100 iters), loss = 0.00774739
I0121 22:13:22.318717  1741 solver.cpp:237]     Train net output #0: loss = 0.00774738 (* 1 = 0.00774738 loss)
I0121 22:13:22.318738  1741 sgd_solver.cpp:105] Iteration 37300, lr = 0.0001
I0121 22:14:03.991668  1741 solver.cpp:218] Iteration 37400 (2.39961 iter/s, 41.6735s/100 iters), loss = 0.00684818
I0121 22:14:03.991842  1741 solver.cpp:237]     Train net output #0: loss = 0.00684818 (* 1 = 0.00684818 loss)
I0121 22:14:03.991860  1741 sgd_solver.cpp:105] Iteration 37400, lr = 0.0001
I0121 22:14:43.599633  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:14:45.676386  1741 solver.cpp:218] Iteration 37500 (2.39894 iter/s, 41.6851s/100 iters), loss = 0.00992124
I0121 22:14:45.676481  1741 solver.cpp:237]     Train net output #0: loss = 0.00992123 (* 1 = 0.00992123 loss)
I0121 22:14:45.676497  1741 sgd_solver.cpp:105] Iteration 37500, lr = 0.0001
I0121 22:15:27.321645  1741 solver.cpp:218] Iteration 37600 (2.40121 iter/s, 41.6457s/100 iters), loss = 0.00766205
I0121 22:15:27.321808  1741 solver.cpp:237]     Train net output #0: loss = 0.00766205 (* 1 = 0.00766205 loss)
I0121 22:15:27.321825  1741 sgd_solver.cpp:105] Iteration 37600, lr = 0.0001
I0121 22:16:08.971243  1741 solver.cpp:218] Iteration 37700 (2.40096 iter/s, 41.6499s/100 iters), loss = 0.0095385
I0121 22:16:08.971410  1741 solver.cpp:237]     Train net output #0: loss = 0.0095385 (* 1 = 0.0095385 loss)
I0121 22:16:08.971426  1741 sgd_solver.cpp:105] Iteration 37700, lr = 0.0001
I0121 22:16:50.544900  1741 solver.cpp:218] Iteration 37800 (2.40535 iter/s, 41.574s/100 iters), loss = 0.00644527
I0121 22:16:50.545068  1741 solver.cpp:237]     Train net output #0: loss = 0.00644526 (* 1 = 0.00644526 loss)
I0121 22:16:50.545084  1741 sgd_solver.cpp:105] Iteration 37800, lr = 0.0001
I0121 22:17:26.387179  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:17:32.217844  1741 solver.cpp:218] Iteration 37900 (2.39962 iter/s, 41.6733s/100 iters), loss = 0.0113792
I0121 22:17:32.217936  1741 solver.cpp:237]     Train net output #0: loss = 0.0113792 (* 1 = 0.0113792 loss)
I0121 22:17:32.217952  1741 sgd_solver.cpp:105] Iteration 37900, lr = 0.0001
I0121 22:18:13.439965  1741 solver.cpp:330] Iteration 38000, Testing net (#0)
I0121 22:18:23.006728  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:18:23.222801  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895333
I0121 22:18:23.222873  1741 solver.cpp:397]     Test net output #1: loss = 0.346499 (* 1 = 0.346499 loss)
I0121 22:18:23.639278  1741 solver.cpp:218] Iteration 38000 (1.94469 iter/s, 51.422s/100 iters), loss = 0.00762575
I0121 22:18:23.639374  1741 solver.cpp:237]     Train net output #0: loss = 0.00762574 (* 1 = 0.00762574 loss)
I0121 22:18:23.639390  1741 sgd_solver.cpp:105] Iteration 38000, lr = 0.0001
I0121 22:19:05.254904  1741 solver.cpp:218] Iteration 38100 (2.40292 iter/s, 41.6161s/100 iters), loss = 0.00568373
I0121 22:19:05.255053  1741 solver.cpp:237]     Train net output #0: loss = 0.00568372 (* 1 = 0.00568372 loss)
I0121 22:19:05.255067  1741 sgd_solver.cpp:105] Iteration 38100, lr = 0.0001
I0121 22:19:46.858742  1741 solver.cpp:218] Iteration 38200 (2.4036 iter/s, 41.6042s/100 iters), loss = 0.00871203
I0121 22:19:46.858870  1741 solver.cpp:237]     Train net output #0: loss = 0.00871203 (* 1 = 0.00871203 loss)
I0121 22:19:46.858887  1741 sgd_solver.cpp:105] Iteration 38200, lr = 0.0001
I0121 22:20:18.949955  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:20:28.526497  1741 solver.cpp:218] Iteration 38300 (2.39991 iter/s, 41.6682s/100 iters), loss = 0.0107746
I0121 22:20:28.526589  1741 solver.cpp:237]     Train net output #0: loss = 0.0107746 (* 1 = 0.0107746 loss)
I0121 22:20:28.526604  1741 sgd_solver.cpp:105] Iteration 38300, lr = 0.0001
I0121 22:21:10.223119  1741 solver.cpp:218] Iteration 38400 (2.39825 iter/s, 41.697s/100 iters), loss = 0.00708728
I0121 22:21:10.223305  1741 solver.cpp:237]     Train net output #0: loss = 0.00708728 (* 1 = 0.00708728 loss)
I0121 22:21:10.223322  1741 sgd_solver.cpp:105] Iteration 38400, lr = 0.0001
I0121 22:21:51.875238  1741 solver.cpp:218] Iteration 38500 (2.40082 iter/s, 41.6525s/100 iters), loss = 0.00701208
I0121 22:21:51.875363  1741 solver.cpp:237]     Train net output #0: loss = 0.00701208 (* 1 = 0.00701208 loss)
I0121 22:21:51.875381  1741 sgd_solver.cpp:105] Iteration 38500, lr = 0.0001
I0121 22:22:33.576205  1741 solver.cpp:218] Iteration 38600 (2.398 iter/s, 41.7014s/100 iters), loss = 0.0108814
I0121 22:22:33.576431  1741 solver.cpp:237]     Train net output #0: loss = 0.0108814 (* 1 = 0.0108814 loss)
I0121 22:22:33.576447  1741 sgd_solver.cpp:105] Iteration 38600, lr = 0.0001
I0121 22:23:01.538293  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:23:15.287297  1741 solver.cpp:218] Iteration 38700 (2.39743 iter/s, 41.7114s/100 iters), loss = 0.00519064
I0121 22:23:15.287478  1741 solver.cpp:237]     Train net output #0: loss = 0.00519064 (* 1 = 0.00519064 loss)
I0121 22:23:15.287494  1741 sgd_solver.cpp:105] Iteration 38700, lr = 0.0001
I0121 22:23:56.970810  1741 solver.cpp:218] Iteration 38800 (2.39901 iter/s, 41.6838s/100 iters), loss = 0.0059158
I0121 22:23:56.971004  1741 solver.cpp:237]     Train net output #0: loss = 0.0059158 (* 1 = 0.0059158 loss)
I0121 22:23:56.971020  1741 sgd_solver.cpp:105] Iteration 38800, lr = 0.0001
I0121 22:24:38.655761  1741 solver.cpp:218] Iteration 38900 (2.39893 iter/s, 41.6853s/100 iters), loss = 0.0151
I0121 22:24:38.655936  1741 solver.cpp:237]     Train net output #0: loss = 0.0151 (* 1 = 0.0151 loss)
I0121 22:24:38.655951  1741 sgd_solver.cpp:105] Iteration 38900, lr = 0.0001
I0121 22:25:19.947542  1741 solver.cpp:330] Iteration 39000, Testing net (#0)
I0121 22:25:29.517644  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:25:29.732615  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895667
I0121 22:25:29.732693  1741 solver.cpp:397]     Test net output #1: loss = 0.346137 (* 1 = 0.346137 loss)
I0121 22:25:30.148308  1741 solver.cpp:218] Iteration 39000 (1.94201 iter/s, 51.493s/100 iters), loss = 0.00804616
I0121 22:25:30.148402  1741 solver.cpp:237]     Train net output #0: loss = 0.00804615 (* 1 = 0.00804615 loss)
I0121 22:25:30.148419  1741 sgd_solver.cpp:105] Iteration 39000, lr = 0.0001
I0121 22:25:54.322968  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:26:11.810218  1741 solver.cpp:218] Iteration 39100 (2.40025 iter/s, 41.6623s/100 iters), loss = 0.0133393
I0121 22:26:11.810313  1741 solver.cpp:237]     Train net output #0: loss = 0.0133393 (* 1 = 0.0133393 loss)
I0121 22:26:11.810330  1741 sgd_solver.cpp:105] Iteration 39100, lr = 0.0001
I0121 22:26:53.474606  1741 solver.cpp:218] Iteration 39200 (2.40011 iter/s, 41.6648s/100 iters), loss = 0.00648233
I0121 22:26:53.474728  1741 solver.cpp:237]     Train net output #0: loss = 0.00648233 (* 1 = 0.00648233 loss)
I0121 22:26:53.474745  1741 sgd_solver.cpp:105] Iteration 39200, lr = 0.0001
I0121 22:27:35.139837  1741 solver.cpp:218] Iteration 39300 (2.40006 iter/s, 41.6656s/100 iters), loss = 0.00764456
I0121 22:27:35.139967  1741 solver.cpp:237]     Train net output #0: loss = 0.00764456 (* 1 = 0.00764456 loss)
I0121 22:27:35.139983  1741 sgd_solver.cpp:105] Iteration 39300, lr = 0.0001
I0121 22:28:16.800843  1741 solver.cpp:218] Iteration 39400 (2.40031 iter/s, 41.6614s/100 iters), loss = 0.0086681
I0121 22:28:16.800972  1741 solver.cpp:237]     Train net output #0: loss = 0.0086681 (* 1 = 0.0086681 loss)
I0121 22:28:16.800988  1741 sgd_solver.cpp:105] Iteration 39400, lr = 0.0001
I0121 22:28:37.210599  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:28:58.465466  1741 solver.cpp:218] Iteration 39500 (2.40009 iter/s, 41.665s/100 iters), loss = 0.0122663
I0121 22:28:58.465591  1741 solver.cpp:237]     Train net output #0: loss = 0.0122663 (* 1 = 0.0122663 loss)
I0121 22:28:58.465607  1741 sgd_solver.cpp:105] Iteration 39500, lr = 0.0001
I0121 22:29:40.125291  1741 solver.cpp:218] Iteration 39600 (2.40037 iter/s, 41.6602s/100 iters), loss = 0.00736525
I0121 22:29:40.125476  1741 solver.cpp:237]     Train net output #0: loss = 0.00736525 (* 1 = 0.00736525 loss)
I0121 22:29:40.125494  1741 sgd_solver.cpp:105] Iteration 39600, lr = 0.0001
I0121 22:30:21.822207  1741 solver.cpp:218] Iteration 39700 (2.39824 iter/s, 41.6972s/100 iters), loss = 0.00848885
I0121 22:30:21.822414  1741 solver.cpp:237]     Train net output #0: loss = 0.00848885 (* 1 = 0.00848885 loss)
I0121 22:30:21.822435  1741 sgd_solver.cpp:105] Iteration 39700, lr = 0.0001
I0121 22:31:03.489190  1741 solver.cpp:218] Iteration 39800 (2.39996 iter/s, 41.6673s/100 iters), loss = 0.0107135
I0121 22:31:03.489424  1741 solver.cpp:237]     Train net output #0: loss = 0.0107135 (* 1 = 0.0107135 loss)
I0121 22:31:03.489446  1741 sgd_solver.cpp:105] Iteration 39800, lr = 0.0001
I0121 22:31:19.755210  1757 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:31:45.173458  1741 solver.cpp:218] Iteration 39900 (2.39897 iter/s, 41.6845s/100 iters), loss = 0.0052094
I0121 22:31:45.173660  1741 solver.cpp:237]     Train net output #0: loss = 0.0052094 (* 1 = 0.0052094 loss)
I0121 22:31:45.173676  1741 sgd_solver.cpp:105] Iteration 39900, lr = 0.0001
I0121 22:32:26.445495  1741 solver.cpp:447] Snapshotting to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_40000.caffemodel
I0121 22:32:26.474074  1741 sgd_solver.cpp:273] Snapshotting solver state to binary proto file cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_40000.solverstate
I0121 22:32:26.594830  1741 solver.cpp:310] Iteration 40000, loss = 0.0100259
I0121 22:32:26.594892  1741 solver.cpp:330] Iteration 40000, Testing net (#0)
I0121 22:32:36.175549  1758 data_layer.cpp:73] Restarting data prefetching from start.
I0121 22:32:36.391412  1741 solver.cpp:397]     Test net output #0: accuracy = 0.895778
I0121 22:32:36.391484  1741 solver.cpp:397]     Test net output #1: loss = 0.346221 (* 1 = 0.346221 loss)
I0121 22:32:36.391494  1741 solver.cpp:315] Optimization Done.
I0121 22:32:36.391499  1741 caffe.cpp:259] Optimization Done.
TRAINING WITH CAFFE


('Elapsed time for Caffe training (s): ', 17042.850067)


PRINT CNN BLOCK DIAGRAM
Drawing net to /home/ubuntu/ML/cifar10/caffe/models/miniGoogleNet/m3/bd_3_miniGoogleNet.png
PLOT LEARNING CURVERS
/bin/sh: 1: /home/ubuntu/caffe_tools/BVLC1v0-Caffe/tools/extra/parse_log.sh: not found
Traceback (most recent call last):
  File "/home/ubuntu/ML/cifar10/caffe/code/5_plot_learning_curve.py", line 50, in <module>
    train_log = pd.read_csv(train_log_path, delim_whitespace=True)
  File "/home/ubuntu/anaconda3/envs/caffe_p27/lib/python2.7/site-packages/pandas/io/parsers.py", line 709, in parser_f
    return _read(filepath_or_buffer, kwds)
  File "/home/ubuntu/anaconda3/envs/caffe_p27/lib/python2.7/site-packages/pandas/io/parsers.py", line 449, in _read
    parser = TextFileReader(filepath_or_buffer, **kwds)
  File "/home/ubuntu/anaconda3/envs/caffe_p27/lib/python2.7/site-packages/pandas/io/parsers.py", line 818, in __init__
    self._make_engine(self.engine)
  File "/home/ubuntu/anaconda3/envs/caffe_p27/lib/python2.7/site-packages/pandas/io/parsers.py", line 1049, in _make_engine
    self._engine = CParserWrapper(self.f, **self.options)
  File "/home/ubuntu/anaconda3/envs/caffe_p27/lib/python2.7/site-packages/pandas/io/parsers.py", line 1695, in __init__
    self._reader = parsers.TextReader(src, **kwds)
  File "pandas/_libs/parsers.pyx", line 402, in pandas._libs.parsers.TextReader.__cinit__
  File "pandas/_libs/parsers.pyx", line 718, in pandas._libs.parsers.TextReader._setup_parser_source
IOError: File /home/ubuntu/ML/cifar10/caffe/models/miniGoogleNet/m3/logfile_3_miniGoogleNet.log.train does not exist
COMPUTE PREDICTIONS
WARNING: Logging before InitGoogleLogging() is written to STDERR
W0121 22:32:42.504050  1946 _caffe.cpp:139] DEPRECATION WARNING - deprecated use of Python interface
W0121 22:32:42.504101  1946 _caffe.cpp:140] Use this instead (with the named "weights" parameter):
W0121 22:32:42.504109  1946 _caffe.cpp:142] Net('cifar10/caffe/models/miniGoogleNet/m3/deploy_3_miniGoogleNet.prototxt', 1, weights='cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_40000.caffemodel')
I0121 22:32:42.510231  1946 upgrade_proto.cpp:77] Attempting to upgrade batch norm layers using deprecated params: cifar10/caffe/models/miniGoogleNet/m3/deploy_3_miniGoogleNet.prototxt
I0121 22:32:42.510263  1946 upgrade_proto.cpp:80] Successfully upgraded batch norm layers using deprecated params.
I0121 22:32:42.511936  1946 net.cpp:51] Initializing net from parameters: 
name: "miniGoogleNet"
state {
  phase: TEST
  level: 0
}
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 32
      dim: 32
    }
  }
}
layer {
  name: "conv1/3x3_s1"
  type: "Convolution"
  bottom: "data"
  top: "conv1/3x3_s1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/bn1"
  type: "BatchNorm"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "conv1/scale1"
  type: "Scale"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv1/relu1"
  type: "ReLU"
  bottom: "conv1/3x3_s1"
  top: "conv1/3x3_s1"
}
layer {
  name: "inception_2a/1x1"
  type: "Convolution"
  bottom: "conv1/3x3_s1"
  top: "inception_2a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_2a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_2a/1x1/scale1"
  type: "Scale"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_2a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_2a/1x1"
  top: "inception_2a/1x1"
}
layer {
  name: "inception_2a/3x3"
  type: "Convolution"
  bottom: "conv1/3x3_s1"
  top: "inception_2a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_2a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_2a/3x3/scale1"
  type: "Scale"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_2a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_2a/3x3"
  top: "inception_2a/3x3"
}
layer {
  name: "inception_2a/output"
  type: "Concat"
  bottom: "inception_2a/1x1"
  bottom: "inception_2a/3x3"
  top: "inception_2a/output"
}
layer {
  name: "inception_3a/1x1"
  type: "Convolution"
  bottom: "inception_2a/output"
  top: "inception_3a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_3a/1x1/scale1"
  type: "Scale"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_3a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_3a/1x1"
  top: "inception_3a/1x1"
}
layer {
  name: "inception_3a/3x3"
  type: "Convolution"
  bottom: "inception_2a/output"
  top: "inception_3a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_3a/3x3/scale1"
  type: "Scale"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_3a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_3a/3x3"
  top: "inception_3a/3x3"
}
layer {
  name: "inception_3a/output"
  type: "Concat"
  bottom: "inception_3a/1x1"
  bottom: "inception_3a/3x3"
  top: "inception_3a/output"
}
layer {
  name: "downsample_4/3x3_s2"
  type: "Convolution"
  bottom: "inception_3a/output"
  top: "downsample_4/3x3_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "downsample_4/3x3_s2/bn1"
  type: "BatchNorm"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "downsample_4/3x3_s2/scale1"
  type: "Scale"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "downsample_4/3x3_s2/relu1"
  type: "ReLU"
  bottom: "downsample_4/3x3_s2"
  top: "downsample_4/3x3_s2"
}
layer {
  name: "downsample_4/pool_s2"
  type: "Pooling"
  bottom: "inception_3a/output"
  top: "downsample_4/pool_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "downsample_4/output"
  type: "Concat"
  bottom: "downsample_4/3x3_s2"
  bottom: "downsample_4/pool_s2"
  top: "downsample_4/output"
}
layer {
  name: "inception_5a/1x1"
  type: "Convolution"
  bottom: "downsample_4/output"
  top: "inception_5a/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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_5a/1x1/scale1"
  type: "Scale"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_5a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_5a/1x1"
  top: "inception_5a/1x1"
}
layer {
  name: "inception_5a/3x3"
  type: "Convolution"
  bottom: "downsample_4/output"
  top: "inception_5a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_5a/3x3/scale1"
  type: "Scale"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_5a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_5a/3x3"
  top: "inception_5a/3x3"
}
layer {
  name: "inception_5a/output"
  type: "Concat"
  bottom: "inception_5a/1x1"
  bottom: "inception_5a/3x3"
  top: "inception_5a/output"
}
layer {
  name: "inception_6a/1x1"
  type: "Convolution"
  bottom: "inception_5a/output"
  top: "inception_6a/1x1"
  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"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_6a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_6a/1x1/scale1"
  type: "Scale"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_6a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_6a/1x1"
  top: "inception_6a/1x1"
}
layer {
  name: "inception_6a/3x3"
  type: "Convolution"
  bottom: "inception_5a/output"
  top: "inception_6a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_6a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_6a/3x3/scale1"
  type: "Scale"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_6a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_6a/3x3"
  top: "inception_6a/3x3"
}
layer {
  name: "inception_6a/output"
  type: "Concat"
  bottom: "inception_6a/1x1"
  bottom: "inception_6a/3x3"
  top: "inception_6a/output"
}
layer {
  name: "inception_7a/1x1"
  type: "Convolution"
  bottom: "inception_6a/output"
  top: "inception_7a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_7a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_7a/1x1/scale1"
  type: "Scale"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_7a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_7a/1x1"
  top: "inception_7a/1x1"
}
layer {
  name: "inception_7a/3x3"
  type: "Convolution"
  bottom: "inception_6a/output"
  top: "inception_7a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_7a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_7a/3x3/scale1"
  type: "Scale"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_7a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_7a/3x3"
  top: "inception_7a/3x3"
}
layer {
  name: "inception_7a/output"
  type: "Concat"
  bottom: "inception_7a/1x1"
  bottom: "inception_7a/3x3"
  top: "inception_7a/output"
}
layer {
  name: "inception_8a/1x1"
  type: "Convolution"
  bottom: "inception_7a/output"
  top: "inception_8a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_8a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_8a/1x1/scale1"
  type: "Scale"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_8a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_8a/1x1"
  top: "inception_8a/1x1"
}
layer {
  name: "inception_8a/3x3"
  type: "Convolution"
  bottom: "inception_7a/output"
  top: "inception_8a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_8a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_8a/3x3/scale1"
  type: "Scale"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_8a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_8a/3x3"
  top: "inception_8a/3x3"
}
layer {
  name: "inception_8a/output"
  type: "Concat"
  bottom: "inception_8a/1x1"
  bottom: "inception_8a/3x3"
  top: "inception_8a/output"
}
layer {
  name: "downsample_9/3x3_s2"
  type: "Convolution"
  bottom: "inception_8a/output"
  top: "downsample_9/3x3_s2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "downsample_9/3x3_s2/bn1"
  type: "BatchNorm"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "downsample_9/3x3_s2/scale1"
  type: "Scale"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "downsample_9/3x3_s2/relu1"
  type: "ReLU"
  bottom: "downsample_9/3x3_s2"
  top: "downsample_9/3x3_s2"
}
layer {
  name: "downsample_9/pool_s2"
  type: "Pooling"
  bottom: "inception_8a/output"
  top: "downsample_9/pool_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "downsample_9/output"
  type: "Concat"
  bottom: "downsample_9/3x3_s2"
  bottom: "downsample_9/pool_s2"
  top: "downsample_9/output"
}
layer {
  name: "inception_10a/1x1"
  type: "Convolution"
  bottom: "downsample_9/output"
  top: "inception_10a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 176
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_10a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_10a/1x1/scale1"
  type: "Scale"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_10a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_10a/1x1"
  top: "inception_10a/1x1"
}
layer {
  name: "inception_10a/3x3"
  type: "Convolution"
  bottom: "downsample_9/output"
  top: "inception_10a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_10a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_10a/3x3/scale1"
  type: "Scale"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_10a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_10a/3x3"
  top: "inception_10a/3x3"
}
layer {
  name: "inception_10a/output"
  type: "Concat"
  bottom: "inception_10a/1x1"
  bottom: "inception_10a/3x3"
  top: "inception_10a/output"
}
layer {
  name: "inception_11a/1x1"
  type: "Convolution"
  bottom: "inception_10a/output"
  top: "inception_11a/1x1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 176
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_11a/1x1/bn1"
  type: "BatchNorm"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_11a/1x1/scale1"
  type: "Scale"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_11a/1x1/relu1"
  type: "ReLU"
  bottom: "inception_11a/1x1"
  top: "inception_11a/1x1"
}
layer {
  name: "inception_11a/3x3"
  type: "Convolution"
  bottom: "inception_10a/output"
  top: "inception_11a/3x3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_11a/3x3/bn1"
  type: "BatchNorm"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "inception_11a/3x3/scale1"
  type: "Scale"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "inception_11a/3x3/relu1"
  type: "ReLU"
  bottom: "inception_11a/3x3"
  top: "inception_11a/3x3"
}
layer {
  name: "inception_11a/output"
  type: "Concat"
  bottom: "inception_11a/1x1"
  bottom: "inception_11a/3x3"
  top: "inception_11a/output"
}
layer {
  name: "avg_pool_12/8x8_s1"
  type: "Pooling"
  bottom: "inception_11a/output"
  top: "avg_pool_12/8x8_s1"
  pooling_param {
    pool: AVE
    kernel_size: 8
    stride: 1
  }
}
layer {
  name: "drop_8x8_s1"
  type: "Dropout"
  bottom: "avg_pool_12/8x8_s1"
  top: "avg_pool_12/8x8_s1"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "loss/classifier"
  type: "InnerProduct"
  bottom: "avg_pool_12/8x8_s1"
  top: "loss/classifier"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 10
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "prob"
  type: "Softmax"
  bottom: "loss/classifier"
  top: "prob"
}
I0121 22:32:42.513691  1946 layer_factory.hpp:77] Creating layer data
I0121 22:32:42.513813  1946 net.cpp:84] Creating Layer data
I0121 22:32:42.513825  1946 net.cpp:380] data -> data
I0121 22:32:42.546743  1946 net.cpp:122] Setting up data
I0121 22:32:42.546777  1946 net.cpp:129] Top shape: 1 3 32 32 (3072)
I0121 22:32:42.546782  1946 net.cpp:137] Memory required for data: 12288
I0121 22:32:42.546788  1946 layer_factory.hpp:77] Creating layer conv1/3x3_s1
I0121 22:32:42.546808  1946 net.cpp:84] Creating Layer conv1/3x3_s1
I0121 22:32:42.546816  1946 net.cpp:406] conv1/3x3_s1 <- data
I0121 22:32:42.546826  1946 net.cpp:380] conv1/3x3_s1 -> conv1/3x3_s1
I0121 22:32:42.975030  1946 net.cpp:122] Setting up conv1/3x3_s1
I0121 22:32:42.975085  1946 net.cpp:129] Top shape: 1 96 32 32 (98304)
I0121 22:32:42.975090  1946 net.cpp:137] Memory required for data: 405504
I0121 22:32:42.975111  1946 layer_factory.hpp:77] Creating layer conv1/bn1
I0121 22:32:42.975134  1946 net.cpp:84] Creating Layer conv1/bn1
I0121 22:32:42.975152  1946 net.cpp:406] conv1/bn1 <- conv1/3x3_s1
I0121 22:32:42.975164  1946 net.cpp:367] conv1/bn1 -> conv1/3x3_s1 (in-place)
I0121 22:32:42.975430  1946 net.cpp:122] Setting up conv1/bn1
I0121 22:32:42.975453  1946 net.cpp:129] Top shape: 1 96 32 32 (98304)
I0121 22:32:42.975461  1946 net.cpp:137] Memory required for data: 798720
I0121 22:32:42.975483  1946 layer_factory.hpp:77] Creating layer conv1/scale1
I0121 22:32:42.976831  1946 net.cpp:84] Creating Layer conv1/scale1
I0121 22:32:42.976850  1946 net.cpp:406] conv1/scale1 <- conv1/3x3_s1
I0121 22:32:42.976861  1946 net.cpp:367] conv1/scale1 -> conv1/3x3_s1 (in-place)
I0121 22:32:42.976928  1946 layer_factory.hpp:77] Creating layer conv1/scale1
I0121 22:32:42.978009  1946 net.cpp:122] Setting up conv1/scale1
I0121 22:32:42.978034  1946 net.cpp:129] Top shape: 1 96 32 32 (98304)
I0121 22:32:42.978042  1946 net.cpp:137] Memory required for data: 1191936
I0121 22:32:42.978055  1946 layer_factory.hpp:77] Creating layer conv1/relu1
I0121 22:32:42.978068  1946 net.cpp:84] Creating Layer conv1/relu1
I0121 22:32:42.978076  1946 net.cpp:406] conv1/relu1 <- conv1/3x3_s1
I0121 22:32:42.978085  1946 net.cpp:367] conv1/relu1 -> conv1/3x3_s1 (in-place)
I0121 22:32:42.979233  1946 net.cpp:122] Setting up conv1/relu1
I0121 22:32:42.979254  1946 net.cpp:129] Top shape: 1 96 32 32 (98304)
I0121 22:32:42.979264  1946 net.cpp:137] Memory required for data: 1585152
I0121 22:32:42.979270  1946 layer_factory.hpp:77] Creating layer conv1/3x3_s1_conv1/relu1_0_split
I0121 22:32:42.980008  1946 net.cpp:84] Creating Layer conv1/3x3_s1_conv1/relu1_0_split
I0121 22:32:42.980026  1946 net.cpp:406] conv1/3x3_s1_conv1/relu1_0_split <- conv1/3x3_s1
I0121 22:32:42.980037  1946 net.cpp:380] conv1/3x3_s1_conv1/relu1_0_split -> conv1/3x3_s1_conv1/relu1_0_split_0
I0121 22:32:42.980051  1946 net.cpp:380] conv1/3x3_s1_conv1/relu1_0_split -> conv1/3x3_s1_conv1/relu1_0_split_1
I0121 22:32:42.980113  1946 net.cpp:122] Setting up conv1/3x3_s1_conv1/relu1_0_split
I0121 22:32:42.980134  1946 net.cpp:129] Top shape: 1 96 32 32 (98304)
I0121 22:32:42.980144  1946 net.cpp:129] Top shape: 1 96 32 32 (98304)
I0121 22:32:42.980165  1946 net.cpp:137] Memory required for data: 2371584
I0121 22:32:42.980171  1946 layer_factory.hpp:77] Creating layer inception_2a/1x1
I0121 22:32:42.980190  1946 net.cpp:84] Creating Layer inception_2a/1x1
I0121 22:32:42.980197  1946 net.cpp:406] inception_2a/1x1 <- conv1/3x3_s1_conv1/relu1_0_split_0
I0121 22:32:42.980208  1946 net.cpp:380] inception_2a/1x1 -> inception_2a/1x1
I0121 22:32:42.981261  1946 net.cpp:122] Setting up inception_2a/1x1
I0121 22:32:42.981290  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.981298  1946 net.cpp:137] Memory required for data: 2502656
I0121 22:32:42.981317  1946 layer_factory.hpp:77] Creating layer inception_2a/1x1/bn1
I0121 22:32:42.981329  1946 net.cpp:84] Creating Layer inception_2a/1x1/bn1
I0121 22:32:42.981338  1946 net.cpp:406] inception_2a/1x1/bn1 <- inception_2a/1x1
I0121 22:32:42.981348  1946 net.cpp:367] inception_2a/1x1/bn1 -> inception_2a/1x1 (in-place)
I0121 22:32:42.981552  1946 net.cpp:122] Setting up inception_2a/1x1/bn1
I0121 22:32:42.981572  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.981580  1946 net.cpp:137] Memory required for data: 2633728
I0121 22:32:42.981593  1946 layer_factory.hpp:77] Creating layer inception_2a/1x1/scale1
I0121 22:32:42.981607  1946 net.cpp:84] Creating Layer inception_2a/1x1/scale1
I0121 22:32:42.981616  1946 net.cpp:406] inception_2a/1x1/scale1 <- inception_2a/1x1
I0121 22:32:42.981624  1946 net.cpp:367] inception_2a/1x1/scale1 -> inception_2a/1x1 (in-place)
I0121 22:32:42.981685  1946 layer_factory.hpp:77] Creating layer inception_2a/1x1/scale1
I0121 22:32:42.981883  1946 net.cpp:122] Setting up inception_2a/1x1/scale1
I0121 22:32:42.981904  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.981910  1946 net.cpp:137] Memory required for data: 2764800
I0121 22:32:42.981923  1946 layer_factory.hpp:77] Creating layer inception_2a/1x1/relu1
I0121 22:32:42.981941  1946 net.cpp:84] Creating Layer inception_2a/1x1/relu1
I0121 22:32:42.981948  1946 net.cpp:406] inception_2a/1x1/relu1 <- inception_2a/1x1
I0121 22:32:42.981957  1946 net.cpp:367] inception_2a/1x1/relu1 -> inception_2a/1x1 (in-place)
I0121 22:32:42.982265  1946 net.cpp:122] Setting up inception_2a/1x1/relu1
I0121 22:32:42.982292  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.982300  1946 net.cpp:137] Memory required for data: 2895872
I0121 22:32:42.982307  1946 layer_factory.hpp:77] Creating layer inception_2a/3x3
I0121 22:32:42.982323  1946 net.cpp:84] Creating Layer inception_2a/3x3
I0121 22:32:42.982336  1946 net.cpp:406] inception_2a/3x3 <- conv1/3x3_s1_conv1/relu1_0_split_1
I0121 22:32:42.982347  1946 net.cpp:380] inception_2a/3x3 -> inception_2a/3x3
I0121 22:32:42.984076  1946 net.cpp:122] Setting up inception_2a/3x3
I0121 22:32:42.984104  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.984110  1946 net.cpp:137] Memory required for data: 3026944
I0121 22:32:42.984119  1946 layer_factory.hpp:77] Creating layer inception_2a/3x3/bn1
I0121 22:32:42.984128  1946 net.cpp:84] Creating Layer inception_2a/3x3/bn1
I0121 22:32:42.984133  1946 net.cpp:406] inception_2a/3x3/bn1 <- inception_2a/3x3
I0121 22:32:42.984140  1946 net.cpp:367] inception_2a/3x3/bn1 -> inception_2a/3x3 (in-place)
I0121 22:32:42.984349  1946 net.cpp:122] Setting up inception_2a/3x3/bn1
I0121 22:32:42.984365  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.984370  1946 net.cpp:137] Memory required for data: 3158016
I0121 22:32:42.984383  1946 layer_factory.hpp:77] Creating layer inception_2a/3x3/scale1
I0121 22:32:42.984395  1946 net.cpp:84] Creating Layer inception_2a/3x3/scale1
I0121 22:32:42.984398  1946 net.cpp:406] inception_2a/3x3/scale1 <- inception_2a/3x3
I0121 22:32:42.984406  1946 net.cpp:367] inception_2a/3x3/scale1 -> inception_2a/3x3 (in-place)
I0121 22:32:42.984469  1946 layer_factory.hpp:77] Creating layer inception_2a/3x3/scale1
I0121 22:32:42.984591  1946 net.cpp:122] Setting up inception_2a/3x3/scale1
I0121 22:32:42.984601  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.984604  1946 net.cpp:137] Memory required for data: 3289088
I0121 22:32:42.984612  1946 layer_factory.hpp:77] Creating layer inception_2a/3x3/relu1
I0121 22:32:42.984621  1946 net.cpp:84] Creating Layer inception_2a/3x3/relu1
I0121 22:32:42.984624  1946 net.cpp:406] inception_2a/3x3/relu1 <- inception_2a/3x3
I0121 22:32:42.984629  1946 net.cpp:367] inception_2a/3x3/relu1 -> inception_2a/3x3 (in-place)
I0121 22:32:42.984755  1946 net.cpp:122] Setting up inception_2a/3x3/relu1
I0121 22:32:42.984766  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.984769  1946 net.cpp:137] Memory required for data: 3420160
I0121 22:32:42.984773  1946 layer_factory.hpp:77] Creating layer inception_2a/output
I0121 22:32:42.984782  1946 net.cpp:84] Creating Layer inception_2a/output
I0121 22:32:42.984786  1946 net.cpp:406] inception_2a/output <- inception_2a/1x1
I0121 22:32:42.984791  1946 net.cpp:406] inception_2a/output <- inception_2a/3x3
I0121 22:32:42.984797  1946 net.cpp:380] inception_2a/output -> inception_2a/output
I0121 22:32:42.984829  1946 net.cpp:122] Setting up inception_2a/output
I0121 22:32:42.984838  1946 net.cpp:129] Top shape: 1 64 32 32 (65536)
I0121 22:32:42.984841  1946 net.cpp:137] Memory required for data: 3682304
I0121 22:32:42.984845  1946 layer_factory.hpp:77] Creating layer inception_2a/output_inception_2a/output_0_split
I0121 22:32:42.984853  1946 net.cpp:84] Creating Layer inception_2a/output_inception_2a/output_0_split
I0121 22:32:42.984856  1946 net.cpp:406] inception_2a/output_inception_2a/output_0_split <- inception_2a/output
I0121 22:32:42.984861  1946 net.cpp:380] inception_2a/output_inception_2a/output_0_split -> inception_2a/output_inception_2a/output_0_split_0
I0121 22:32:42.984867  1946 net.cpp:380] inception_2a/output_inception_2a/output_0_split -> inception_2a/output_inception_2a/output_0_split_1
I0121 22:32:42.984902  1946 net.cpp:122] Setting up inception_2a/output_inception_2a/output_0_split
I0121 22:32:42.984910  1946 net.cpp:129] Top shape: 1 64 32 32 (65536)
I0121 22:32:42.984915  1946 net.cpp:129] Top shape: 1 64 32 32 (65536)
I0121 22:32:42.984918  1946 net.cpp:137] Memory required for data: 4206592
I0121 22:32:42.984922  1946 layer_factory.hpp:77] Creating layer inception_3a/1x1
I0121 22:32:42.984933  1946 net.cpp:84] Creating Layer inception_3a/1x1
I0121 22:32:42.984938  1946 net.cpp:406] inception_3a/1x1 <- inception_2a/output_inception_2a/output_0_split_0
I0121 22:32:42.984944  1946 net.cpp:380] inception_3a/1x1 -> inception_3a/1x1
I0121 22:32:42.985961  1946 net.cpp:122] Setting up inception_3a/1x1
I0121 22:32:42.985991  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.985996  1946 net.cpp:137] Memory required for data: 4337664
I0121 22:32:42.986006  1946 layer_factory.hpp:77] Creating layer inception_3a/1x1/bn1
I0121 22:32:42.986014  1946 net.cpp:84] Creating Layer inception_3a/1x1/bn1
I0121 22:32:42.986022  1946 net.cpp:406] inception_3a/1x1/bn1 <- inception_3a/1x1
I0121 22:32:42.986037  1946 net.cpp:367] inception_3a/1x1/bn1 -> inception_3a/1x1 (in-place)
I0121 22:32:42.986281  1946 net.cpp:122] Setting up inception_3a/1x1/bn1
I0121 22:32:42.986302  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.986306  1946 net.cpp:137] Memory required for data: 4468736
I0121 22:32:42.986316  1946 layer_factory.hpp:77] Creating layer inception_3a/1x1/scale1
I0121 22:32:42.986325  1946 net.cpp:84] Creating Layer inception_3a/1x1/scale1
I0121 22:32:42.986331  1946 net.cpp:406] inception_3a/1x1/scale1 <- inception_3a/1x1
I0121 22:32:42.986340  1946 net.cpp:367] inception_3a/1x1/scale1 -> inception_3a/1x1 (in-place)
I0121 22:32:42.986410  1946 layer_factory.hpp:77] Creating layer inception_3a/1x1/scale1
I0121 22:32:42.986572  1946 net.cpp:122] Setting up inception_3a/1x1/scale1
I0121 22:32:42.986594  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.986601  1946 net.cpp:137] Memory required for data: 4599808
I0121 22:32:42.986613  1946 layer_factory.hpp:77] Creating layer inception_3a/1x1/relu1
I0121 22:32:42.986635  1946 net.cpp:84] Creating Layer inception_3a/1x1/relu1
I0121 22:32:42.986644  1946 net.cpp:406] inception_3a/1x1/relu1 <- inception_3a/1x1
I0121 22:32:42.986660  1946 net.cpp:367] inception_3a/1x1/relu1 -> inception_3a/1x1 (in-place)
I0121 22:32:42.986944  1946 net.cpp:122] Setting up inception_3a/1x1/relu1
I0121 22:32:42.986971  1946 net.cpp:129] Top shape: 1 32 32 32 (32768)
I0121 22:32:42.986979  1946 net.cpp:137] Memory required for data: 4730880
I0121 22:32:42.986986  1946 layer_factory.hpp:77] Creating layer inception_3a/3x3
I0121 22:32:42.987007  1946 net.cpp:84] Creating Layer inception_3a/3x3
I0121 22:32:42.987020  1946 net.cpp:406] inception_3a/3x3 <- inception_2a/output_inception_2a/output_0_split_1
I0121 22:32:42.987033  1946 net.cpp:380] inception_3a/3x3 -> inception_3a/3x3
I0121 22:32:42.988108  1946 net.cpp:122] Setting up inception_3a/3x3
I0121 22:32:42.988137  1946 net.cpp:129] Top shape: 1 48 32 32 (49152)
I0121 22:32:42.988147  1946 net.cpp:137] Memory required for data: 4927488
I0121 22:32:42.988158  1946 layer_factory.hpp:77] Creating layer inception_3a/3x3/bn1
I0121 22:32:42.988175  1946 net.cpp:84] Creating Layer inception_3a/3x3/bn1
I0121 22:32:42.988190  1946 net.cpp:406] inception_3a/3x3/bn1 <- inception_3a/3x3
I0121 22:32:42.988203  1946 net.cpp:367] inception_3a/3x3/bn1 -> inception_3a/3x3 (in-place)
I0121 22:32:42.988420  1946 net.cpp:122] Setting up inception_3a/3x3/bn1
I0121 22:32:42.988440  1946 net.cpp:129] Top shape: 1 48 32 32 (49152)
I0121 22:32:42.988446  1946 net.cpp:137] Memory required for data: 5124096
I0121 22:32:42.988466  1946 layer_factory.hpp:77] Creating layer inception_3a/3x3/scale1
I0121 22:32:42.988488  1946 net.cpp:84] Creating Layer inception_3a/3x3/scale1
I0121 22:32:42.988497  1946 net.cpp:406] inception_3a/3x3/scale1 <- inception_3a/3x3
I0121 22:32:42.988507  1946 net.cpp:367] inception_3a/3x3/scale1 -> inception_3a/3x3 (in-place)
I0121 22:32:42.988569  1946 layer_factory.hpp:77] Creating layer inception_3a/3x3/scale1
I0121 22:32:42.988708  1946 net.cpp:122] Setting up inception_3a/3x3/scale1
I0121 22:32:42.988728  1946 net.cpp:129] Top shape: 1 48 32 32 (49152)
I0121 22:32:42.988734  1946 net.cpp:137] Memory required for data: 5320704
I0121 22:32:42.988745  1946 layer_factory.hpp:77] Creating layer inception_3a/3x3/relu1
I0121 22:32:42.988765  1946 net.cpp:84] Creating Layer inception_3a/3x3/relu1
I0121 22:32:42.988772  1946 net.cpp:406] inception_3a/3x3/relu1 <- inception_3a/3x3
I0121 22:32:42.988780  1946 net.cpp:367] inception_3a/3x3/relu1 -> inception_3a/3x3 (in-place)
I0121 22:32:42.988942  1946 net.cpp:122] Setting up inception_3a/3x3/relu1
I0121 22:32:42.988966  1946 net.cpp:129] Top shape: 1 48 32 32 (49152)
I0121 22:32:42.988973  1946 net.cpp:137] Memory required for data: 5517312
I0121 22:32:42.988981  1946 layer_factory.hpp:77] Creating layer inception_3a/output
I0121 22:32:42.988991  1946 net.cpp:84] Creating Layer inception_3a/output
I0121 22:32:42.989003  1946 net.cpp:406] inception_3a/output <- inception_3a/1x1
I0121 22:32:42.989013  1946 net.cpp:406] inception_3a/output <- inception_3a/3x3
I0121 22:32:42.989027  1946 net.cpp:380] inception_3a/output -> inception_3a/output
I0121 22:32:42.989073  1946 net.cpp:122] Setting up inception_3a/output
I0121 22:32:42.989095  1946 net.cpp:129] Top shape: 1 80 32 32 (81920)
I0121 22:32:42.989104  1946 net.cpp:137] Memory required for data: 5844992
I0121 22:32:42.989109  1946 layer_factory.hpp:77] Creating layer inception_3a/output_inception_3a/output_0_split
I0121 22:32:42.989120  1946 net.cpp:84] Creating Layer inception_3a/output_inception_3a/output_0_split
I0121 22:32:42.989126  1946 net.cpp:406] inception_3a/output_inception_3a/output_0_split <- inception_3a/output
I0121 22:32:42.989135  1946 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_0
I0121 22:32:42.989145  1946 net.cpp:380] inception_3a/output_inception_3a/output_0_split -> inception_3a/output_inception_3a/output_0_split_1
I0121 22:32:42.989209  1946 net.cpp:122] Setting up inception_3a/output_inception_3a/output_0_split
I0121 22:32:42.989229  1946 net.cpp:129] Top shape: 1 80 32 32 (81920)
I0121 22:32:42.989238  1946 net.cpp:129] Top shape: 1 80 32 32 (81920)
I0121 22:32:42.989243  1946 net.cpp:137] Memory required for data: 6500352
I0121 22:32:42.989250  1946 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2
I0121 22:32:42.989269  1946 net.cpp:84] Creating Layer downsample_4/3x3_s2
I0121 22:32:42.989284  1946 net.cpp:406] downsample_4/3x3_s2 <- inception_3a/output_inception_3a/output_0_split_0
I0121 22:32:42.989300  1946 net.cpp:380] downsample_4/3x3_s2 -> downsample_4/3x3_s2
I0121 22:32:42.990542  1946 net.cpp:122] Setting up downsample_4/3x3_s2
I0121 22:32:42.990572  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:42.990581  1946 net.cpp:137] Memory required for data: 6582272
I0121 22:32:42.990593  1946 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/bn1
I0121 22:32:42.990610  1946 net.cpp:84] Creating Layer downsample_4/3x3_s2/bn1
I0121 22:32:42.990625  1946 net.cpp:406] downsample_4/3x3_s2/bn1 <- downsample_4/3x3_s2
I0121 22:32:42.990638  1946 net.cpp:367] downsample_4/3x3_s2/bn1 -> downsample_4/3x3_s2 (in-place)
I0121 22:32:42.990860  1946 net.cpp:122] Setting up downsample_4/3x3_s2/bn1
I0121 22:32:42.990880  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:42.990888  1946 net.cpp:137] Memory required for data: 6664192
I0121 22:32:42.990902  1946 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/scale1
I0121 22:32:42.990919  1946 net.cpp:84] Creating Layer downsample_4/3x3_s2/scale1
I0121 22:32:42.990927  1946 net.cpp:406] downsample_4/3x3_s2/scale1 <- downsample_4/3x3_s2
I0121 22:32:42.990937  1946 net.cpp:367] downsample_4/3x3_s2/scale1 -> downsample_4/3x3_s2 (in-place)
I0121 22:32:42.990999  1946 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/scale1
I0121 22:32:42.991142  1946 net.cpp:122] Setting up downsample_4/3x3_s2/scale1
I0121 22:32:42.991160  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:42.991168  1946 net.cpp:137] Memory required for data: 6746112
I0121 22:32:42.991180  1946 layer_factory.hpp:77] Creating layer downsample_4/3x3_s2/relu1
I0121 22:32:42.991197  1946 net.cpp:84] Creating Layer downsample_4/3x3_s2/relu1
I0121 22:32:42.991205  1946 net.cpp:406] downsample_4/3x3_s2/relu1 <- downsample_4/3x3_s2
I0121 22:32:42.991217  1946 net.cpp:367] downsample_4/3x3_s2/relu1 -> downsample_4/3x3_s2 (in-place)
I0121 22:32:42.991509  1946 net.cpp:122] Setting up downsample_4/3x3_s2/relu1
I0121 22:32:42.991535  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:42.991544  1946 net.cpp:137] Memory required for data: 6828032
I0121 22:32:42.991550  1946 layer_factory.hpp:77] Creating layer downsample_4/pool_s2
I0121 22:32:42.991564  1946 net.cpp:84] Creating Layer downsample_4/pool_s2
I0121 22:32:42.991577  1946 net.cpp:406] downsample_4/pool_s2 <- inception_3a/output_inception_3a/output_0_split_1
I0121 22:32:42.991592  1946 net.cpp:380] downsample_4/pool_s2 -> downsample_4/pool_s2
I0121 22:32:42.991662  1946 net.cpp:122] Setting up downsample_4/pool_s2
I0121 22:32:42.991683  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:42.991689  1946 net.cpp:137] Memory required for data: 6909952
I0121 22:32:42.991695  1946 layer_factory.hpp:77] Creating layer downsample_4/output
I0121 22:32:42.991706  1946 net.cpp:84] Creating Layer downsample_4/output
I0121 22:32:42.991719  1946 net.cpp:406] downsample_4/output <- downsample_4/3x3_s2
I0121 22:32:42.991729  1946 net.cpp:406] downsample_4/output <- downsample_4/pool_s2
I0121 22:32:42.991740  1946 net.cpp:380] downsample_4/output -> downsample_4/output
I0121 22:32:42.991793  1946 net.cpp:122] Setting up downsample_4/output
I0121 22:32:42.991811  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:42.991818  1946 net.cpp:137] Memory required for data: 7073792
I0121 22:32:42.991824  1946 layer_factory.hpp:77] Creating layer downsample_4/output_downsample_4/output_0_split
I0121 22:32:42.991842  1946 net.cpp:84] Creating Layer downsample_4/output_downsample_4/output_0_split
I0121 22:32:42.991854  1946 net.cpp:406] downsample_4/output_downsample_4/output_0_split <- downsample_4/output
I0121 22:32:42.991865  1946 net.cpp:380] downsample_4/output_downsample_4/output_0_split -> downsample_4/output_downsample_4/output_0_split_0
I0121 22:32:42.991875  1946 net.cpp:380] downsample_4/output_downsample_4/output_0_split -> downsample_4/output_downsample_4/output_0_split_1
I0121 22:32:42.991941  1946 net.cpp:122] Setting up downsample_4/output_downsample_4/output_0_split
I0121 22:32:42.991961  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:42.991969  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:42.991976  1946 net.cpp:137] Memory required for data: 7401472
I0121 22:32:42.991982  1946 layer_factory.hpp:77] Creating layer inception_5a/1x1
I0121 22:32:42.992007  1946 net.cpp:84] Creating Layer inception_5a/1x1
I0121 22:32:42.992022  1946 net.cpp:406] inception_5a/1x1 <- downsample_4/output_downsample_4/output_0_split_0
I0121 22:32:42.992034  1946 net.cpp:380] inception_5a/1x1 -> inception_5a/1x1
I0121 22:32:42.993083  1946 net.cpp:122] Setting up inception_5a/1x1
I0121 22:32:42.993111  1946 net.cpp:129] Top shape: 1 112 16 16 (28672)
I0121 22:32:42.993119  1946 net.cpp:137] Memory required for data: 7516160
I0121 22:32:42.993132  1946 layer_factory.hpp:77] Creating layer inception_5a/1x1/bn1
I0121 22:32:42.993149  1946 net.cpp:84] Creating Layer inception_5a/1x1/bn1
I0121 22:32:42.993163  1946 net.cpp:406] inception_5a/1x1/bn1 <- inception_5a/1x1
I0121 22:32:42.993180  1946 net.cpp:367] inception_5a/1x1/bn1 -> inception_5a/1x1 (in-place)
I0121 22:32:42.993393  1946 net.cpp:122] Setting up inception_5a/1x1/bn1
I0121 22:32:42.993414  1946 net.cpp:129] Top shape: 1 112 16 16 (28672)
I0121 22:32:42.993422  1946 net.cpp:137] Memory required for data: 7630848
I0121 22:32:42.993434  1946 layer_factory.hpp:77] Creating layer inception_5a/1x1/scale1
I0121 22:32:42.993458  1946 net.cpp:84] Creating Layer inception_5a/1x1/scale1
I0121 22:32:42.993466  1946 net.cpp:406] inception_5a/1x1/scale1 <- inception_5a/1x1
I0121 22:32:42.993475  1946 net.cpp:367] inception_5a/1x1/scale1 -> inception_5a/1x1 (in-place)
I0121 22:32:42.993544  1946 layer_factory.hpp:77] Creating layer inception_5a/1x1/scale1
I0121 22:32:42.993687  1946 net.cpp:122] Setting up inception_5a/1x1/scale1
I0121 22:32:42.993707  1946 net.cpp:129] Top shape: 1 112 16 16 (28672)
I0121 22:32:42.993715  1946 net.cpp:137] Memory required for data: 7745536
I0121 22:32:42.993726  1946 layer_factory.hpp:77] Creating layer inception_5a/1x1/relu1
I0121 22:32:42.993746  1946 net.cpp:84] Creating Layer inception_5a/1x1/relu1
I0121 22:32:42.993754  1946 net.cpp:406] inception_5a/1x1/relu1 <- inception_5a/1x1
I0121 22:32:42.993785  1946 net.cpp:367] inception_5a/1x1/relu1 -> inception_5a/1x1 (in-place)
I0121 22:32:42.993943  1946 net.cpp:122] Setting up inception_5a/1x1/relu1
I0121 22:32:42.993966  1946 net.cpp:129] Top shape: 1 112 16 16 (28672)
I0121 22:32:42.993974  1946 net.cpp:137] Memory required for data: 7860224
I0121 22:32:42.993981  1946 layer_factory.hpp:77] Creating layer inception_5a/3x3
I0121 22:32:42.994000  1946 net.cpp:84] Creating Layer inception_5a/3x3
I0121 22:32:42.994014  1946 net.cpp:406] inception_5a/3x3 <- downsample_4/output_downsample_4/output_0_split_1
I0121 22:32:42.994029  1946 net.cpp:380] inception_5a/3x3 -> inception_5a/3x3
I0121 22:32:42.996016  1946 net.cpp:122] Setting up inception_5a/3x3
I0121 22:32:42.996047  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:42.996055  1946 net.cpp:137] Memory required for data: 7909376
I0121 22:32:42.996068  1946 layer_factory.hpp:77] Creating layer inception_5a/3x3/bn1
I0121 22:32:42.996081  1946 net.cpp:84] Creating Layer inception_5a/3x3/bn1
I0121 22:32:42.996096  1946 net.cpp:406] inception_5a/3x3/bn1 <- inception_5a/3x3
I0121 22:32:42.996112  1946 net.cpp:367] inception_5a/3x3/bn1 -> inception_5a/3x3 (in-place)
I0121 22:32:42.996342  1946 net.cpp:122] Setting up inception_5a/3x3/bn1
I0121 22:32:42.996363  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:42.996371  1946 net.cpp:137] Memory required for data: 7958528
I0121 22:32:42.996385  1946 layer_factory.hpp:77] Creating layer inception_5a/3x3/scale1
I0121 22:32:42.996405  1946 net.cpp:84] Creating Layer inception_5a/3x3/scale1
I0121 22:32:42.996412  1946 net.cpp:406] inception_5a/3x3/scale1 <- inception_5a/3x3
I0121 22:32:42.996421  1946 net.cpp:367] inception_5a/3x3/scale1 -> inception_5a/3x3 (in-place)
I0121 22:32:42.996487  1946 layer_factory.hpp:77] Creating layer inception_5a/3x3/scale1
I0121 22:32:42.996632  1946 net.cpp:122] Setting up inception_5a/3x3/scale1
I0121 22:32:42.996655  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:42.996662  1946 net.cpp:137] Memory required for data: 8007680
I0121 22:32:42.996675  1946 layer_factory.hpp:77] Creating layer inception_5a/3x3/relu1
I0121 22:32:42.996691  1946 net.cpp:84] Creating Layer inception_5a/3x3/relu1
I0121 22:32:42.996700  1946 net.cpp:406] inception_5a/3x3/relu1 <- inception_5a/3x3
I0121 22:32:42.996707  1946 net.cpp:367] inception_5a/3x3/relu1 -> inception_5a/3x3 (in-place)
I0121 22:32:42.997123  1946 net.cpp:122] Setting up inception_5a/3x3/relu1
I0121 22:32:42.997150  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:42.997162  1946 net.cpp:137] Memory required for data: 8056832
I0121 22:32:42.997169  1946 layer_factory.hpp:77] Creating layer inception_5a/output
I0121 22:32:42.997179  1946 net.cpp:84] Creating Layer inception_5a/output
I0121 22:32:42.997195  1946 net.cpp:406] inception_5a/output <- inception_5a/1x1
I0121 22:32:42.997205  1946 net.cpp:406] inception_5a/output <- inception_5a/3x3
I0121 22:32:42.997213  1946 net.cpp:380] inception_5a/output -> inception_5a/output
I0121 22:32:42.997261  1946 net.cpp:122] Setting up inception_5a/output
I0121 22:32:42.997284  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:42.997292  1946 net.cpp:137] Memory required for data: 8220672
I0121 22:32:42.997298  1946 layer_factory.hpp:77] Creating layer inception_5a/output_inception_5a/output_0_split
I0121 22:32:42.997316  1946 net.cpp:84] Creating Layer inception_5a/output_inception_5a/output_0_split
I0121 22:32:42.997324  1946 net.cpp:406] inception_5a/output_inception_5a/output_0_split <- inception_5a/output
I0121 22:32:42.997334  1946 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_0
I0121 22:32:42.997354  1946 net.cpp:380] inception_5a/output_inception_5a/output_0_split -> inception_5a/output_inception_5a/output_0_split_1
I0121 22:32:42.997418  1946 net.cpp:122] Setting up inception_5a/output_inception_5a/output_0_split
I0121 22:32:42.997437  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:42.997447  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:42.997452  1946 net.cpp:137] Memory required for data: 8548352
I0121 22:32:42.997459  1946 layer_factory.hpp:77] Creating layer inception_6a/1x1
I0121 22:32:42.997483  1946 net.cpp:84] Creating Layer inception_6a/1x1
I0121 22:32:42.997493  1946 net.cpp:406] inception_6a/1x1 <- inception_5a/output_inception_5a/output_0_split_0
I0121 22:32:42.997514  1946 net.cpp:380] inception_6a/1x1 -> inception_6a/1x1
I0121 22:32:42.999172  1946 net.cpp:122] Setting up inception_6a/1x1
I0121 22:32:42.999202  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:42.999212  1946 net.cpp:137] Memory required for data: 8646656
I0121 22:32:42.999223  1946 layer_factory.hpp:77] Creating layer inception_6a/1x1/bn1
I0121 22:32:42.999243  1946 net.cpp:84] Creating Layer inception_6a/1x1/bn1
I0121 22:32:42.999258  1946 net.cpp:406] inception_6a/1x1/bn1 <- inception_6a/1x1
I0121 22:32:42.999269  1946 net.cpp:367] inception_6a/1x1/bn1 -> inception_6a/1x1 (in-place)
I0121 22:32:42.999497  1946 net.cpp:122] Setting up inception_6a/1x1/bn1
I0121 22:32:42.999517  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:42.999526  1946 net.cpp:137] Memory required for data: 8744960
I0121 22:32:42.999539  1946 layer_factory.hpp:77] Creating layer inception_6a/1x1/scale1
I0121 22:32:42.999557  1946 net.cpp:84] Creating Layer inception_6a/1x1/scale1
I0121 22:32:42.999564  1946 net.cpp:406] inception_6a/1x1/scale1 <- inception_6a/1x1
I0121 22:32:42.999583  1946 net.cpp:367] inception_6a/1x1/scale1 -> inception_6a/1x1 (in-place)
I0121 22:32:42.999652  1946 layer_factory.hpp:77] Creating layer inception_6a/1x1/scale1
I0121 22:32:42.999802  1946 net.cpp:122] Setting up inception_6a/1x1/scale1
I0121 22:32:42.999821  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:42.999828  1946 net.cpp:137] Memory required for data: 8843264
I0121 22:32:42.999840  1946 layer_factory.hpp:77] Creating layer inception_6a/1x1/relu1
I0121 22:32:42.999857  1946 net.cpp:84] Creating Layer inception_6a/1x1/relu1
I0121 22:32:42.999866  1946 net.cpp:406] inception_6a/1x1/relu1 <- inception_6a/1x1
I0121 22:32:42.999878  1946 net.cpp:367] inception_6a/1x1/relu1 -> inception_6a/1x1 (in-place)
I0121 22:32:43.000161  1946 net.cpp:122] Setting up inception_6a/1x1/relu1
I0121 22:32:43.000188  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:43.000195  1946 net.cpp:137] Memory required for data: 8941568
I0121 22:32:43.000202  1946 layer_factory.hpp:77] Creating layer inception_6a/3x3
I0121 22:32:43.000221  1946 net.cpp:84] Creating Layer inception_6a/3x3
I0121 22:32:43.000236  1946 net.cpp:406] inception_6a/3x3 <- inception_5a/output_inception_5a/output_0_split_1
I0121 22:32:43.000252  1946 net.cpp:380] inception_6a/3x3 -> inception_6a/3x3
I0121 22:32:43.001678  1946 net.cpp:122] Setting up inception_6a/3x3
I0121 22:32:43.001708  1946 net.cpp:129] Top shape: 1 64 16 16 (16384)
I0121 22:32:43.001715  1946 net.cpp:137] Memory required for data: 9007104
I0121 22:32:43.001744  1946 layer_factory.hpp:77] Creating layer inception_6a/3x3/bn1
I0121 22:32:43.001806  1946 net.cpp:84] Creating Layer inception_6a/3x3/bn1
I0121 22:32:43.001819  1946 net.cpp:406] inception_6a/3x3/bn1 <- inception_6a/3x3
I0121 22:32:43.001837  1946 net.cpp:367] inception_6a/3x3/bn1 -> inception_6a/3x3 (in-place)
I0121 22:32:43.002050  1946 net.cpp:122] Setting up inception_6a/3x3/bn1
I0121 22:32:43.002060  1946 net.cpp:129] Top shape: 1 64 16 16 (16384)
I0121 22:32:43.002064  1946 net.cpp:137] Memory required for data: 9072640
I0121 22:32:43.002074  1946 layer_factory.hpp:77] Creating layer inception_6a/3x3/scale1
I0121 22:32:43.002081  1946 net.cpp:84] Creating Layer inception_6a/3x3/scale1
I0121 22:32:43.002086  1946 net.cpp:406] inception_6a/3x3/scale1 <- inception_6a/3x3
I0121 22:32:43.002094  1946 net.cpp:367] inception_6a/3x3/scale1 -> inception_6a/3x3 (in-place)
I0121 22:32:43.002135  1946 layer_factory.hpp:77] Creating layer inception_6a/3x3/scale1
I0121 22:32:43.002251  1946 net.cpp:122] Setting up inception_6a/3x3/scale1
I0121 22:32:43.002260  1946 net.cpp:129] Top shape: 1 64 16 16 (16384)
I0121 22:32:43.002264  1946 net.cpp:137] Memory required for data: 9138176
I0121 22:32:43.002270  1946 layer_factory.hpp:77] Creating layer inception_6a/3x3/relu1
I0121 22:32:43.002277  1946 net.cpp:84] Creating Layer inception_6a/3x3/relu1
I0121 22:32:43.002281  1946 net.cpp:406] inception_6a/3x3/relu1 <- inception_6a/3x3
I0121 22:32:43.002288  1946 net.cpp:367] inception_6a/3x3/relu1 -> inception_6a/3x3 (in-place)
I0121 22:32:43.002434  1946 net.cpp:122] Setting up inception_6a/3x3/relu1
I0121 22:32:43.002445  1946 net.cpp:129] Top shape: 1 64 16 16 (16384)
I0121 22:32:43.002449  1946 net.cpp:137] Memory required for data: 9203712
I0121 22:32:43.002454  1946 layer_factory.hpp:77] Creating layer inception_6a/output
I0121 22:32:43.002460  1946 net.cpp:84] Creating Layer inception_6a/output
I0121 22:32:43.002465  1946 net.cpp:406] inception_6a/output <- inception_6a/1x1
I0121 22:32:43.002470  1946 net.cpp:406] inception_6a/output <- inception_6a/3x3
I0121 22:32:43.002480  1946 net.cpp:380] inception_6a/output -> inception_6a/output
I0121 22:32:43.002506  1946 net.cpp:122] Setting up inception_6a/output
I0121 22:32:43.002513  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:43.002517  1946 net.cpp:137] Memory required for data: 9367552
I0121 22:32:43.002521  1946 layer_factory.hpp:77] Creating layer inception_6a/output_inception_6a/output_0_split
I0121 22:32:43.002527  1946 net.cpp:84] Creating Layer inception_6a/output_inception_6a/output_0_split
I0121 22:32:43.002532  1946 net.cpp:406] inception_6a/output_inception_6a/output_0_split <- inception_6a/output
I0121 22:32:43.002537  1946 net.cpp:380] inception_6a/output_inception_6a/output_0_split -> inception_6a/output_inception_6a/output_0_split_0
I0121 22:32:43.002543  1946 net.cpp:380] inception_6a/output_inception_6a/output_0_split -> inception_6a/output_inception_6a/output_0_split_1
I0121 22:32:43.002583  1946 net.cpp:122] Setting up inception_6a/output_inception_6a/output_0_split
I0121 22:32:43.002590  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:43.002595  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:43.002599  1946 net.cpp:137] Memory required for data: 9695232
I0121 22:32:43.002604  1946 layer_factory.hpp:77] Creating layer inception_7a/1x1
I0121 22:32:43.002614  1946 net.cpp:84] Creating Layer inception_7a/1x1
I0121 22:32:43.002619  1946 net.cpp:406] inception_7a/1x1 <- inception_6a/output_inception_6a/output_0_split_0
I0121 22:32:43.002627  1946 net.cpp:380] inception_7a/1x1 -> inception_7a/1x1
I0121 22:32:43.003701  1946 net.cpp:122] Setting up inception_7a/1x1
I0121 22:32:43.003731  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.003736  1946 net.cpp:137] Memory required for data: 9777152
I0121 22:32:43.003746  1946 layer_factory.hpp:77] Creating layer inception_7a/1x1/bn1
I0121 22:32:43.003754  1946 net.cpp:84] Creating Layer inception_7a/1x1/bn1
I0121 22:32:43.003762  1946 net.cpp:406] inception_7a/1x1/bn1 <- inception_7a/1x1
I0121 22:32:43.003777  1946 net.cpp:367] inception_7a/1x1/bn1 -> inception_7a/1x1 (in-place)
I0121 22:32:43.004026  1946 net.cpp:122] Setting up inception_7a/1x1/bn1
I0121 22:32:43.004045  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.004050  1946 net.cpp:137] Memory required for data: 9859072
I0121 22:32:43.004060  1946 layer_factory.hpp:77] Creating layer inception_7a/1x1/scale1
I0121 22:32:43.004066  1946 net.cpp:84] Creating Layer inception_7a/1x1/scale1
I0121 22:32:43.004073  1946 net.cpp:406] inception_7a/1x1/scale1 <- inception_7a/1x1
I0121 22:32:43.004079  1946 net.cpp:367] inception_7a/1x1/scale1 -> inception_7a/1x1 (in-place)
I0121 22:32:43.004144  1946 layer_factory.hpp:77] Creating layer inception_7a/1x1/scale1
I0121 22:32:43.004297  1946 net.cpp:122] Setting up inception_7a/1x1/scale1
I0121 22:32:43.004315  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.004319  1946 net.cpp:137] Memory required for data: 9940992
I0121 22:32:43.004328  1946 layer_factory.hpp:77] Creating layer inception_7a/1x1/relu1
I0121 22:32:43.004338  1946 net.cpp:84] Creating Layer inception_7a/1x1/relu1
I0121 22:32:43.004353  1946 net.cpp:406] inception_7a/1x1/relu1 <- inception_7a/1x1
I0121 22:32:43.004362  1946 net.cpp:367] inception_7a/1x1/relu1 -> inception_7a/1x1 (in-place)
I0121 22:32:43.004657  1946 net.cpp:122] Setting up inception_7a/1x1/relu1
I0121 22:32:43.004680  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.004684  1946 net.cpp:137] Memory required for data: 10022912
I0121 22:32:43.004689  1946 layer_factory.hpp:77] Creating layer inception_7a/3x3
I0121 22:32:43.004704  1946 net.cpp:84] Creating Layer inception_7a/3x3
I0121 22:32:43.004711  1946 net.cpp:406] inception_7a/3x3 <- inception_6a/output_inception_6a/output_0_split_1
I0121 22:32:43.004727  1946 net.cpp:380] inception_7a/3x3 -> inception_7a/3x3
I0121 22:32:43.007040  1946 net.cpp:122] Setting up inception_7a/3x3
I0121 22:32:43.007068  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.007073  1946 net.cpp:137] Memory required for data: 10104832
I0121 22:32:43.007081  1946 layer_factory.hpp:77] Creating layer inception_7a/3x3/bn1
I0121 22:32:43.007097  1946 net.cpp:84] Creating Layer inception_7a/3x3/bn1
I0121 22:32:43.007114  1946 net.cpp:406] inception_7a/3x3/bn1 <- inception_7a/3x3
I0121 22:32:43.007127  1946 net.cpp:367] inception_7a/3x3/bn1 -> inception_7a/3x3 (in-place)
I0121 22:32:43.007354  1946 net.cpp:122] Setting up inception_7a/3x3/bn1
I0121 22:32:43.007371  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.007376  1946 net.cpp:137] Memory required for data: 10186752
I0121 22:32:43.007385  1946 layer_factory.hpp:77] Creating layer inception_7a/3x3/scale1
I0121 22:32:43.007395  1946 net.cpp:84] Creating Layer inception_7a/3x3/scale1
I0121 22:32:43.007400  1946 net.cpp:406] inception_7a/3x3/scale1 <- inception_7a/3x3
I0121 22:32:43.007411  1946 net.cpp:367] inception_7a/3x3/scale1 -> inception_7a/3x3 (in-place)
I0121 22:32:43.007484  1946 layer_factory.hpp:77] Creating layer inception_7a/3x3/scale1
I0121 22:32:43.007637  1946 net.cpp:122] Setting up inception_7a/3x3/scale1
I0121 22:32:43.007654  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.007658  1946 net.cpp:137] Memory required for data: 10268672
I0121 22:32:43.007666  1946 layer_factory.hpp:77] Creating layer inception_7a/3x3/relu1
I0121 22:32:43.007674  1946 net.cpp:84] Creating Layer inception_7a/3x3/relu1
I0121 22:32:43.007680  1946 net.cpp:406] inception_7a/3x3/relu1 <- inception_7a/3x3
I0121 22:32:43.007686  1946 net.cpp:367] inception_7a/3x3/relu1 -> inception_7a/3x3 (in-place)
I0121 22:32:43.007848  1946 net.cpp:122] Setting up inception_7a/3x3/relu1
I0121 22:32:43.007869  1946 net.cpp:129] Top shape: 1 80 16 16 (20480)
I0121 22:32:43.007872  1946 net.cpp:137] Memory required for data: 10350592
I0121 22:32:43.007877  1946 layer_factory.hpp:77] Creating layer inception_7a/output
I0121 22:32:43.007885  1946 net.cpp:84] Creating Layer inception_7a/output
I0121 22:32:43.007891  1946 net.cpp:406] inception_7a/output <- inception_7a/1x1
I0121 22:32:43.007896  1946 net.cpp:406] inception_7a/output <- inception_7a/3x3
I0121 22:32:43.007910  1946 net.cpp:380] inception_7a/output -> inception_7a/output
I0121 22:32:43.007952  1946 net.cpp:122] Setting up inception_7a/output
I0121 22:32:43.007968  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:43.007974  1946 net.cpp:137] Memory required for data: 10514432
I0121 22:32:43.007982  1946 layer_factory.hpp:77] Creating layer inception_7a/output_inception_7a/output_0_split
I0121 22:32:43.007990  1946 net.cpp:84] Creating Layer inception_7a/output_inception_7a/output_0_split
I0121 22:32:43.008004  1946 net.cpp:406] inception_7a/output_inception_7a/output_0_split <- inception_7a/output
I0121 22:32:43.008011  1946 net.cpp:380] inception_7a/output_inception_7a/output_0_split -> inception_7a/output_inception_7a/output_0_split_0
I0121 22:32:43.008054  1946 net.cpp:380] inception_7a/output_inception_7a/output_0_split -> inception_7a/output_inception_7a/output_0_split_1
I0121 22:32:43.008155  1946 net.cpp:122] Setting up inception_7a/output_inception_7a/output_0_split
I0121 22:32:43.008177  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:43.008186  1946 net.cpp:129] Top shape: 1 160 16 16 (40960)
I0121 22:32:43.008193  1946 net.cpp:137] Memory required for data: 10842112
I0121 22:32:43.008199  1946 layer_factory.hpp:77] Creating layer inception_8a/1x1
I0121 22:32:43.008217  1946 net.cpp:84] Creating Layer inception_8a/1x1
I0121 22:32:43.008232  1946 net.cpp:406] inception_8a/1x1 <- inception_7a/output_inception_7a/output_0_split_0
I0121 22:32:43.008247  1946 net.cpp:380] inception_8a/1x1 -> inception_8a/1x1
I0121 22:32:43.009275  1946 net.cpp:122] Setting up inception_8a/1x1
I0121 22:32:43.009302  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:43.009308  1946 net.cpp:137] Memory required for data: 10891264
I0121 22:32:43.009320  1946 layer_factory.hpp:77] Creating layer inception_8a/1x1/bn1
I0121 22:32:43.009356  1946 net.cpp:84] Creating Layer inception_8a/1x1/bn1
I0121 22:32:43.009372  1946 net.cpp:406] inception_8a/1x1/bn1 <- inception_8a/1x1
I0121 22:32:43.009383  1946 net.cpp:367] inception_8a/1x1/bn1 -> inception_8a/1x1 (in-place)
I0121 22:32:43.009613  1946 net.cpp:122] Setting up inception_8a/1x1/bn1
I0121 22:32:43.009631  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:43.009635  1946 net.cpp:137] Memory required for data: 10940416
I0121 22:32:43.009645  1946 layer_factory.hpp:77] Creating layer inception_8a/1x1/scale1
I0121 22:32:43.009660  1946 net.cpp:84] Creating Layer inception_8a/1x1/scale1
I0121 22:32:43.009688  1946 net.cpp:406] inception_8a/1x1/scale1 <- inception_8a/1x1
I0121 22:32:43.009706  1946 net.cpp:367] inception_8a/1x1/scale1 -> inception_8a/1x1 (in-place)
I0121 22:32:43.009816  1946 layer_factory.hpp:77] Creating layer inception_8a/1x1/scale1
I0121 22:32:43.009990  1946 net.cpp:122] Setting up inception_8a/1x1/scale1
I0121 22:32:43.010010  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:43.010017  1946 net.cpp:137] Memory required for data: 10989568
I0121 22:32:43.010028  1946 layer_factory.hpp:77] Creating layer inception_8a/1x1/relu1
I0121 22:32:43.010057  1946 net.cpp:84] Creating Layer inception_8a/1x1/relu1
I0121 22:32:43.010066  1946 net.cpp:406] inception_8a/1x1/relu1 <- inception_8a/1x1
I0121 22:32:43.010076  1946 net.cpp:367] inception_8a/1x1/relu1 -> inception_8a/1x1 (in-place)
I0121 22:32:43.010398  1946 net.cpp:122] Setting up inception_8a/1x1/relu1
I0121 22:32:43.010423  1946 net.cpp:129] Top shape: 1 48 16 16 (12288)
I0121 22:32:43.010428  1946 net.cpp:137] Memory required for data: 11038720
I0121 22:32:43.010433  1946 layer_factory.hpp:77] Creating layer inception_8a/3x3
I0121 22:32:43.010444  1946 net.cpp:84] Creating Layer inception_8a/3x3
I0121 22:32:43.010452  1946 net.cpp:406] inception_8a/3x3 <- inception_7a/output_inception_7a/output_0_split_1
I0121 22:32:43.010465  1946 net.cpp:380] inception_8a/3x3 -> inception_8a/3x3
I0121 22:32:43.012161  1946 net.cpp:122] Setting up inception_8a/3x3
I0121 22:32:43.012187  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:43.012192  1946 net.cpp:137] Memory required for data: 11137024
I0121 22:32:43.012202  1946 layer_factory.hpp:77] Creating layer inception_8a/3x3/bn1
I0121 22:32:43.012210  1946 net.cpp:84] Creating Layer inception_8a/3x3/bn1
I0121 22:32:43.012217  1946 net.cpp:406] inception_8a/3x3/bn1 <- inception_8a/3x3
I0121 22:32:43.012230  1946 net.cpp:367] inception_8a/3x3/bn1 -> inception_8a/3x3 (in-place)
I0121 22:32:43.012465  1946 net.cpp:122] Setting up inception_8a/3x3/bn1
I0121 22:32:43.012483  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:43.012488  1946 net.cpp:137] Memory required for data: 11235328
I0121 22:32:43.012498  1946 layer_factory.hpp:77] Creating layer inception_8a/3x3/scale1
I0121 22:32:43.012506  1946 net.cpp:84] Creating Layer inception_8a/3x3/scale1
I0121 22:32:43.012511  1946 net.cpp:406] inception_8a/3x3/scale1 <- inception_8a/3x3
I0121 22:32:43.012518  1946 net.cpp:367] inception_8a/3x3/scale1 -> inception_8a/3x3 (in-place)
I0121 22:32:43.012591  1946 layer_factory.hpp:77] Creating layer inception_8a/3x3/scale1
I0121 22:32:43.012760  1946 net.cpp:122] Setting up inception_8a/3x3/scale1
I0121 22:32:43.012781  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:43.012786  1946 net.cpp:137] Memory required for data: 11333632
I0121 22:32:43.012794  1946 layer_factory.hpp:77] Creating layer inception_8a/3x3/relu1
I0121 22:32:43.012801  1946 net.cpp:84] Creating Layer inception_8a/3x3/relu1
I0121 22:32:43.012806  1946 net.cpp:406] inception_8a/3x3/relu1 <- inception_8a/3x3
I0121 22:32:43.012811  1946 net.cpp:367] inception_8a/3x3/relu1 -> inception_8a/3x3 (in-place)
I0121 22:32:43.012977  1946 net.cpp:122] Setting up inception_8a/3x3/relu1
I0121 22:32:43.012998  1946 net.cpp:129] Top shape: 1 96 16 16 (24576)
I0121 22:32:43.013002  1946 net.cpp:137] Memory required for data: 11431936
I0121 22:32:43.013007  1946 layer_factory.hpp:77] Creating layer inception_8a/output
I0121 22:32:43.013015  1946 net.cpp:84] Creating Layer inception_8a/output
I0121 22:32:43.013020  1946 net.cpp:406] inception_8a/output <- inception_8a/1x1
I0121 22:32:43.013026  1946 net.cpp:406] inception_8a/output <- inception_8a/3x3
I0121 22:32:43.013034  1946 net.cpp:380] inception_8a/output -> inception_8a/output
I0121 22:32:43.013075  1946 net.cpp:122] Setting up inception_8a/output
I0121 22:32:43.013094  1946 net.cpp:129] Top shape: 1 144 16 16 (36864)
I0121 22:32:43.013098  1946 net.cpp:137] Memory required for data: 11579392
I0121 22:32:43.013103  1946 layer_factory.hpp:77] Creating layer inception_8a/output_inception_8a/output_0_split
I0121 22:32:43.013111  1946 net.cpp:84] Creating Layer inception_8a/output_inception_8a/output_0_split
I0121 22:32:43.013115  1946 net.cpp:406] inception_8a/output_inception_8a/output_0_split <- inception_8a/output
I0121 22:32:43.013123  1946 net.cpp:380] inception_8a/output_inception_8a/output_0_split -> inception_8a/output_inception_8a/output_0_split_0
I0121 22:32:43.013134  1946 net.cpp:380] inception_8a/output_inception_8a/output_0_split -> inception_8a/output_inception_8a/output_0_split_1
I0121 22:32:43.013197  1946 net.cpp:122] Setting up inception_8a/output_inception_8a/output_0_split
I0121 22:32:43.013213  1946 net.cpp:129] Top shape: 1 144 16 16 (36864)
I0121 22:32:43.013219  1946 net.cpp:129] Top shape: 1 144 16 16 (36864)
I0121 22:32:43.013223  1946 net.cpp:137] Memory required for data: 11874304
I0121 22:32:43.013227  1946 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2
I0121 22:32:43.013242  1946 net.cpp:84] Creating Layer downsample_9/3x3_s2
I0121 22:32:43.013255  1946 net.cpp:406] downsample_9/3x3_s2 <- inception_8a/output_inception_8a/output_0_split_0
I0121 22:32:43.013268  1946 net.cpp:380] downsample_9/3x3_s2 -> downsample_9/3x3_s2
I0121 22:32:43.015815  1946 net.cpp:122] Setting up downsample_9/3x3_s2
I0121 22:32:43.015843  1946 net.cpp:129] Top shape: 1 96 8 8 (6144)
I0121 22:32:43.015848  1946 net.cpp:137] Memory required for data: 11898880
I0121 22:32:43.015857  1946 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/bn1
I0121 22:32:43.015871  1946 net.cpp:84] Creating Layer downsample_9/3x3_s2/bn1
I0121 22:32:43.015887  1946 net.cpp:406] downsample_9/3x3_s2/bn1 <- downsample_9/3x3_s2
I0121 22:32:43.015898  1946 net.cpp:367] downsample_9/3x3_s2/bn1 -> downsample_9/3x3_s2 (in-place)
I0121 22:32:43.016149  1946 net.cpp:122] Setting up downsample_9/3x3_s2/bn1
I0121 22:32:43.016167  1946 net.cpp:129] Top shape: 1 96 8 8 (6144)
I0121 22:32:43.016172  1946 net.cpp:137] Memory required for data: 11923456
I0121 22:32:43.016182  1946 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/scale1
I0121 22:32:43.016189  1946 net.cpp:84] Creating Layer downsample_9/3x3_s2/scale1
I0121 22:32:43.016196  1946 net.cpp:406] downsample_9/3x3_s2/scale1 <- downsample_9/3x3_s2
I0121 22:32:43.016203  1946 net.cpp:367] downsample_9/3x3_s2/scale1 -> downsample_9/3x3_s2 (in-place)
I0121 22:32:43.016280  1946 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/scale1
I0121 22:32:43.016458  1946 net.cpp:122] Setting up downsample_9/3x3_s2/scale1
I0121 22:32:43.016477  1946 net.cpp:129] Top shape: 1 96 8 8 (6144)
I0121 22:32:43.016484  1946 net.cpp:137] Memory required for data: 11948032
I0121 22:32:43.016496  1946 layer_factory.hpp:77] Creating layer downsample_9/3x3_s2/relu1
I0121 22:32:43.016515  1946 net.cpp:84] Creating Layer downsample_9/3x3_s2/relu1
I0121 22:32:43.016523  1946 net.cpp:406] downsample_9/3x3_s2/relu1 <- downsample_9/3x3_s2
I0121 22:32:43.016532  1946 net.cpp:367] downsample_9/3x3_s2/relu1 -> downsample_9/3x3_s2 (in-place)
I0121 22:32:43.016840  1946 net.cpp:122] Setting up downsample_9/3x3_s2/relu1
I0121 22:32:43.016871  1946 net.cpp:129] Top shape: 1 96 8 8 (6144)
I0121 22:32:43.016880  1946 net.cpp:137] Memory required for data: 11972608
I0121 22:32:43.016886  1946 layer_factory.hpp:77] Creating layer downsample_9/pool_s2
I0121 22:32:43.016897  1946 net.cpp:84] Creating Layer downsample_9/pool_s2
I0121 22:32:43.016912  1946 net.cpp:406] downsample_9/pool_s2 <- inception_8a/output_inception_8a/output_0_split_1
I0121 22:32:43.016925  1946 net.cpp:380] downsample_9/pool_s2 -> downsample_9/pool_s2
I0121 22:32:43.017009  1946 net.cpp:122] Setting up downsample_9/pool_s2
I0121 22:32:43.017030  1946 net.cpp:129] Top shape: 1 144 8 8 (9216)
I0121 22:32:43.017036  1946 net.cpp:137] Memory required for data: 12009472
I0121 22:32:43.017043  1946 layer_factory.hpp:77] Creating layer downsample_9/output
I0121 22:32:43.017056  1946 net.cpp:84] Creating Layer downsample_9/output
I0121 22:32:43.017069  1946 net.cpp:406] downsample_9/output <- downsample_9/3x3_s2
I0121 22:32:43.017079  1946 net.cpp:406] downsample_9/output <- downsample_9/pool_s2
I0121 22:32:43.017088  1946 net.cpp:380] downsample_9/output -> downsample_9/output
I0121 22:32:43.017139  1946 net.cpp:122] Setting up downsample_9/output
I0121 22:32:43.017160  1946 net.cpp:129] Top shape: 1 240 8 8 (15360)
I0121 22:32:43.017168  1946 net.cpp:137] Memory required for data: 12070912
I0121 22:32:43.017174  1946 layer_factory.hpp:77] Creating layer downsample_9/output_downsample_9/output_0_split
I0121 22:32:43.017184  1946 net.cpp:84] Creating Layer downsample_9/output_downsample_9/output_0_split
I0121 22:32:43.017196  1946 net.cpp:406] downsample_9/output_downsample_9/output_0_split <- downsample_9/output
I0121 22:32:43.017210  1946 net.cpp:380] downsample_9/output_downsample_9/output_0_split -> downsample_9/output_downsample_9/output_0_split_0
I0121 22:32:43.017222  1946 net.cpp:380] downsample_9/output_downsample_9/output_0_split -> downsample_9/output_downsample_9/output_0_split_1
I0121 22:32:43.017287  1946 net.cpp:122] Setting up downsample_9/output_downsample_9/output_0_split
I0121 22:32:43.017304  1946 net.cpp:129] Top shape: 1 240 8 8 (15360)
I0121 22:32:43.017313  1946 net.cpp:129] Top shape: 1 240 8 8 (15360)
I0121 22:32:43.017319  1946 net.cpp:137] Memory required for data: 12193792
I0121 22:32:43.017325  1946 layer_factory.hpp:77] Creating layer inception_10a/1x1
I0121 22:32:43.017349  1946 net.cpp:84] Creating Layer inception_10a/1x1
I0121 22:32:43.017365  1946 net.cpp:406] inception_10a/1x1 <- downsample_9/output_downsample_9/output_0_split_0
I0121 22:32:43.017387  1946 net.cpp:380] inception_10a/1x1 -> inception_10a/1x1
I0121 22:32:43.018718  1946 net.cpp:122] Setting up inception_10a/1x1
I0121 22:32:43.018745  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.018750  1946 net.cpp:137] Memory required for data: 12238848
I0121 22:32:43.018761  1946 layer_factory.hpp:77] Creating layer inception_10a/1x1/bn1
I0121 22:32:43.018777  1946 net.cpp:84] Creating Layer inception_10a/1x1/bn1
I0121 22:32:43.018788  1946 net.cpp:406] inception_10a/1x1/bn1 <- inception_10a/1x1
I0121 22:32:43.018801  1946 net.cpp:367] inception_10a/1x1/bn1 -> inception_10a/1x1 (in-place)
I0121 22:32:43.019068  1946 net.cpp:122] Setting up inception_10a/1x1/bn1
I0121 22:32:43.019089  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.019096  1946 net.cpp:137] Memory required for data: 12283904
I0121 22:32:43.019110  1946 layer_factory.hpp:77] Creating layer inception_10a/1x1/scale1
I0121 22:32:43.019132  1946 net.cpp:84] Creating Layer inception_10a/1x1/scale1
I0121 22:32:43.019141  1946 net.cpp:406] inception_10a/1x1/scale1 <- inception_10a/1x1
I0121 22:32:43.019150  1946 net.cpp:367] inception_10a/1x1/scale1 -> inception_10a/1x1 (in-place)
I0121 22:32:43.019217  1946 layer_factory.hpp:77] Creating layer inception_10a/1x1/scale1
I0121 22:32:43.019381  1946 net.cpp:122] Setting up inception_10a/1x1/scale1
I0121 22:32:43.019402  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.019408  1946 net.cpp:137] Memory required for data: 12328960
I0121 22:32:43.019420  1946 layer_factory.hpp:77] Creating layer inception_10a/1x1/relu1
I0121 22:32:43.019444  1946 net.cpp:84] Creating Layer inception_10a/1x1/relu1
I0121 22:32:43.019454  1946 net.cpp:406] inception_10a/1x1/relu1 <- inception_10a/1x1
I0121 22:32:43.019469  1946 net.cpp:367] inception_10a/1x1/relu1 -> inception_10a/1x1 (in-place)
I0121 22:32:43.019886  1946 net.cpp:122] Setting up inception_10a/1x1/relu1
I0121 22:32:43.019913  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.019922  1946 net.cpp:137] Memory required for data: 12374016
I0121 22:32:43.019927  1946 layer_factory.hpp:77] Creating layer inception_10a/3x3
I0121 22:32:43.019948  1946 net.cpp:84] Creating Layer inception_10a/3x3
I0121 22:32:43.019963  1946 net.cpp:406] inception_10a/3x3 <- downsample_9/output_downsample_9/output_0_split_1
I0121 22:32:43.019976  1946 net.cpp:380] inception_10a/3x3 -> inception_10a/3x3
I0121 22:32:43.023948  1946 net.cpp:122] Setting up inception_10a/3x3
I0121 22:32:43.023977  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.023983  1946 net.cpp:137] Memory required for data: 12414976
I0121 22:32:43.023993  1946 layer_factory.hpp:77] Creating layer inception_10a/3x3/bn1
I0121 22:32:43.024016  1946 net.cpp:84] Creating Layer inception_10a/3x3/bn1
I0121 22:32:43.024034  1946 net.cpp:406] inception_10a/3x3/bn1 <- inception_10a/3x3
I0121 22:32:43.024049  1946 net.cpp:367] inception_10a/3x3/bn1 -> inception_10a/3x3 (in-place)
I0121 22:32:43.024387  1946 net.cpp:122] Setting up inception_10a/3x3/bn1
I0121 22:32:43.024407  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.024411  1946 net.cpp:137] Memory required for data: 12455936
I0121 22:32:43.024425  1946 layer_factory.hpp:77] Creating layer inception_10a/3x3/scale1
I0121 22:32:43.024451  1946 net.cpp:84] Creating Layer inception_10a/3x3/scale1
I0121 22:32:43.024487  1946 net.cpp:406] inception_10a/3x3/scale1 <- inception_10a/3x3
I0121 22:32:43.024507  1946 net.cpp:367] inception_10a/3x3/scale1 -> inception_10a/3x3 (in-place)
I0121 22:32:43.024595  1946 layer_factory.hpp:77] Creating layer inception_10a/3x3/scale1
I0121 22:32:43.024770  1946 net.cpp:122] Setting up inception_10a/3x3/scale1
I0121 22:32:43.024791  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.024797  1946 net.cpp:137] Memory required for data: 12496896
I0121 22:32:43.024811  1946 layer_factory.hpp:77] Creating layer inception_10a/3x3/relu1
I0121 22:32:43.024832  1946 net.cpp:84] Creating Layer inception_10a/3x3/relu1
I0121 22:32:43.024839  1946 net.cpp:406] inception_10a/3x3/relu1 <- inception_10a/3x3
I0121 22:32:43.024847  1946 net.cpp:367] inception_10a/3x3/relu1 -> inception_10a/3x3 (in-place)
I0121 22:32:43.025017  1946 net.cpp:122] Setting up inception_10a/3x3/relu1
I0121 22:32:43.025039  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.025046  1946 net.cpp:137] Memory required for data: 12537856
I0121 22:32:43.025053  1946 layer_factory.hpp:77] Creating layer inception_10a/output
I0121 22:32:43.025071  1946 net.cpp:84] Creating Layer inception_10a/output
I0121 22:32:43.025084  1946 net.cpp:406] inception_10a/output <- inception_10a/1x1
I0121 22:32:43.025094  1946 net.cpp:406] inception_10a/output <- inception_10a/3x3
I0121 22:32:43.025104  1946 net.cpp:380] inception_10a/output -> inception_10a/output
I0121 22:32:43.025151  1946 net.cpp:122] Setting up inception_10a/output
I0121 22:32:43.025171  1946 net.cpp:129] Top shape: 1 336 8 8 (21504)
I0121 22:32:43.025177  1946 net.cpp:137] Memory required for data: 12623872
I0121 22:32:43.025183  1946 layer_factory.hpp:77] Creating layer inception_10a/output_inception_10a/output_0_split
I0121 22:32:43.025193  1946 net.cpp:84] Creating Layer inception_10a/output_inception_10a/output_0_split
I0121 22:32:43.025207  1946 net.cpp:406] inception_10a/output_inception_10a/output_0_split <- inception_10a/output
I0121 22:32:43.025221  1946 net.cpp:380] inception_10a/output_inception_10a/output_0_split -> inception_10a/output_inception_10a/output_0_split_0
I0121 22:32:43.025233  1946 net.cpp:380] inception_10a/output_inception_10a/output_0_split -> inception_10a/output_inception_10a/output_0_split_1
I0121 22:32:43.025303  1946 net.cpp:122] Setting up inception_10a/output_inception_10a/output_0_split
I0121 22:32:43.025328  1946 net.cpp:129] Top shape: 1 336 8 8 (21504)
I0121 22:32:43.025334  1946 net.cpp:129] Top shape: 1 336 8 8 (21504)
I0121 22:32:43.025339  1946 net.cpp:137] Memory required for data: 12795904
I0121 22:32:43.025346  1946 layer_factory.hpp:77] Creating layer inception_11a/1x1
I0121 22:32:43.025377  1946 net.cpp:84] Creating Layer inception_11a/1x1
I0121 22:32:43.025393  1946 net.cpp:406] inception_11a/1x1 <- inception_10a/output_inception_10a/output_0_split_0
I0121 22:32:43.025403  1946 net.cpp:380] inception_11a/1x1 -> inception_11a/1x1
I0121 22:32:43.026823  1946 net.cpp:122] Setting up inception_11a/1x1
I0121 22:32:43.026851  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.026856  1946 net.cpp:137] Memory required for data: 12840960
I0121 22:32:43.026865  1946 layer_factory.hpp:77] Creating layer inception_11a/1x1/bn1
I0121 22:32:43.026877  1946 net.cpp:84] Creating Layer inception_11a/1x1/bn1
I0121 22:32:43.026893  1946 net.cpp:406] inception_11a/1x1/bn1 <- inception_11a/1x1
I0121 22:32:43.026909  1946 net.cpp:367] inception_11a/1x1/bn1 -> inception_11a/1x1 (in-place)
I0121 22:32:43.027254  1946 net.cpp:122] Setting up inception_11a/1x1/bn1
I0121 22:32:43.027276  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.027281  1946 net.cpp:137] Memory required for data: 12886016
I0121 22:32:43.027292  1946 layer_factory.hpp:77] Creating layer inception_11a/1x1/scale1
I0121 22:32:43.027300  1946 net.cpp:84] Creating Layer inception_11a/1x1/scale1
I0121 22:32:43.027308  1946 net.cpp:406] inception_11a/1x1/scale1 <- inception_11a/1x1
I0121 22:32:43.027318  1946 net.cpp:367] inception_11a/1x1/scale1 -> inception_11a/1x1 (in-place)
I0121 22:32:43.027402  1946 layer_factory.hpp:77] Creating layer inception_11a/1x1/scale1
I0121 22:32:43.027604  1946 net.cpp:122] Setting up inception_11a/1x1/scale1
I0121 22:32:43.027624  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.027629  1946 net.cpp:137] Memory required for data: 12931072
I0121 22:32:43.027637  1946 layer_factory.hpp:77] Creating layer inception_11a/1x1/relu1
I0121 22:32:43.027647  1946 net.cpp:84] Creating Layer inception_11a/1x1/relu1
I0121 22:32:43.027653  1946 net.cpp:406] inception_11a/1x1/relu1 <- inception_11a/1x1
I0121 22:32:43.027669  1946 net.cpp:367] inception_11a/1x1/relu1 -> inception_11a/1x1 (in-place)
I0121 22:32:43.027978  1946 net.cpp:122] Setting up inception_11a/1x1/relu1
I0121 22:32:43.028003  1946 net.cpp:129] Top shape: 1 176 8 8 (11264)
I0121 22:32:43.028008  1946 net.cpp:137] Memory required for data: 12976128
I0121 22:32:43.028013  1946 layer_factory.hpp:77] Creating layer inception_11a/3x3
I0121 22:32:43.028026  1946 net.cpp:84] Creating Layer inception_11a/3x3
I0121 22:32:43.028039  1946 net.cpp:406] inception_11a/3x3 <- inception_10a/output_inception_10a/output_0_split_1
I0121 22:32:43.028057  1946 net.cpp:380] inception_11a/3x3 -> inception_11a/3x3
I0121 22:32:43.033043  1946 net.cpp:122] Setting up inception_11a/3x3
I0121 22:32:43.033074  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.033082  1946 net.cpp:137] Memory required for data: 13017088
I0121 22:32:43.033100  1946 layer_factory.hpp:77] Creating layer inception_11a/3x3/bn1
I0121 22:32:43.033118  1946 net.cpp:84] Creating Layer inception_11a/3x3/bn1
I0121 22:32:43.033133  1946 net.cpp:406] inception_11a/3x3/bn1 <- inception_11a/3x3
I0121 22:32:43.033149  1946 net.cpp:367] inception_11a/3x3/bn1 -> inception_11a/3x3 (in-place)
I0121 22:32:43.033402  1946 net.cpp:122] Setting up inception_11a/3x3/bn1
I0121 22:32:43.033422  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.033429  1946 net.cpp:137] Memory required for data: 13058048
I0121 22:32:43.033468  1946 layer_factory.hpp:77] Creating layer inception_11a/3x3/scale1
I0121 22:32:43.033489  1946 net.cpp:84] Creating Layer inception_11a/3x3/scale1
I0121 22:32:43.033498  1946 net.cpp:406] inception_11a/3x3/scale1 <- inception_11a/3x3
I0121 22:32:43.033527  1946 net.cpp:367] inception_11a/3x3/scale1 -> inception_11a/3x3 (in-place)
I0121 22:32:43.033619  1946 layer_factory.hpp:77] Creating layer inception_11a/3x3/scale1
I0121 22:32:43.033843  1946 net.cpp:122] Setting up inception_11a/3x3/scale1
I0121 22:32:43.033865  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.033872  1946 net.cpp:137] Memory required for data: 13099008
I0121 22:32:43.033885  1946 layer_factory.hpp:77] Creating layer inception_11a/3x3/relu1
I0121 22:32:43.033905  1946 net.cpp:84] Creating Layer inception_11a/3x3/relu1
I0121 22:32:43.033913  1946 net.cpp:406] inception_11a/3x3/relu1 <- inception_11a/3x3
I0121 22:32:43.033921  1946 net.cpp:367] inception_11a/3x3/relu1 -> inception_11a/3x3 (in-place)
I0121 22:32:43.034095  1946 net.cpp:122] Setting up inception_11a/3x3/relu1
I0121 22:32:43.034117  1946 net.cpp:129] Top shape: 1 160 8 8 (10240)
I0121 22:32:43.034124  1946 net.cpp:137] Memory required for data: 13139968
I0121 22:32:43.034132  1946 layer_factory.hpp:77] Creating layer inception_11a/output
I0121 22:32:43.034140  1946 net.cpp:84] Creating Layer inception_11a/output
I0121 22:32:43.034154  1946 net.cpp:406] inception_11a/output <- inception_11a/1x1
I0121 22:32:43.034163  1946 net.cpp:406] inception_11a/output <- inception_11a/3x3
I0121 22:32:43.034173  1946 net.cpp:380] inception_11a/output -> inception_11a/output
I0121 22:32:43.034229  1946 net.cpp:122] Setting up inception_11a/output
I0121 22:32:43.034248  1946 net.cpp:129] Top shape: 1 336 8 8 (21504)
I0121 22:32:43.034255  1946 net.cpp:137] Memory required for data: 13225984
I0121 22:32:43.034261  1946 layer_factory.hpp:77] Creating layer avg_pool_12/8x8_s1
I0121 22:32:43.034276  1946 net.cpp:84] Creating Layer avg_pool_12/8x8_s1
I0121 22:32:43.034283  1946 net.cpp:406] avg_pool_12/8x8_s1 <- inception_11a/output
I0121 22:32:43.034308  1946 net.cpp:380] avg_pool_12/8x8_s1 -> avg_pool_12/8x8_s1
I0121 22:32:43.034658  1946 net.cpp:122] Setting up avg_pool_12/8x8_s1
I0121 22:32:43.034685  1946 net.cpp:129] Top shape: 1 336 1 1 (336)
I0121 22:32:43.034694  1946 net.cpp:137] Memory required for data: 13227328
I0121 22:32:43.034700  1946 layer_factory.hpp:77] Creating layer drop_8x8_s1
I0121 22:32:43.034715  1946 net.cpp:84] Creating Layer drop_8x8_s1
I0121 22:32:43.034729  1946 net.cpp:406] drop_8x8_s1 <- avg_pool_12/8x8_s1
I0121 22:32:43.034741  1946 net.cpp:367] drop_8x8_s1 -> avg_pool_12/8x8_s1 (in-place)
I0121 22:32:43.034790  1946 net.cpp:122] Setting up drop_8x8_s1
I0121 22:32:43.034808  1946 net.cpp:129] Top shape: 1 336 1 1 (336)
I0121 22:32:43.034816  1946 net.cpp:137] Memory required for data: 13228672
I0121 22:32:43.034821  1946 layer_factory.hpp:77] Creating layer loss/classifier
I0121 22:32:43.034835  1946 net.cpp:84] Creating Layer loss/classifier
I0121 22:32:43.034847  1946 net.cpp:406] loss/classifier <- avg_pool_12/8x8_s1
I0121 22:32:43.034863  1946 net.cpp:380] loss/classifier -> loss/classifier
I0121 22:32:43.035038  1946 net.cpp:122] Setting up loss/classifier
I0121 22:32:43.035058  1946 net.cpp:129] Top shape: 1 10 (10)
I0121 22:32:43.035064  1946 net.cpp:137] Memory required for data: 13228712
I0121 22:32:43.035076  1946 layer_factory.hpp:77] Creating layer prob
I0121 22:32:43.035095  1946 net.cpp:84] Creating Layer prob
I0121 22:32:43.035104  1946 net.cpp:406] prob <- loss/classifier
I0121 22:32:43.035111  1946 net.cpp:380] prob -> prob
I0121 22:32:43.035343  1946 net.cpp:122] Setting up prob
I0121 22:32:43.035369  1946 net.cpp:129] Top shape: 1 10 (10)
I0121 22:32:43.035377  1946 net.cpp:137] Memory required for data: 13228752
I0121 22:32:43.035384  1946 net.cpp:200] prob does not need backward computation.
I0121 22:32:43.035392  1946 net.cpp:200] loss/classifier does not need backward computation.
I0121 22:32:43.035398  1946 net.cpp:200] drop_8x8_s1 does not need backward computation.
I0121 22:32:43.035403  1946 net.cpp:200] avg_pool_12/8x8_s1 does not need backward computation.
I0121 22:32:43.035409  1946 net.cpp:200] inception_11a/output does not need backward computation.
I0121 22:32:43.035423  1946 net.cpp:200] inception_11a/3x3/relu1 does not need backward computation.
I0121 22:32:43.035431  1946 net.cpp:200] inception_11a/3x3/scale1 does not need backward computation.
I0121 22:32:43.035437  1946 net.cpp:200] inception_11a/3x3/bn1 does not need backward computation.
I0121 22:32:43.035442  1946 net.cpp:200] inception_11a/3x3 does not need backward computation.
I0121 22:32:43.035466  1946 net.cpp:200] inception_11a/1x1/relu1 does not need backward computation.
I0121 22:32:43.035482  1946 net.cpp:200] inception_11a/1x1/scale1 does not need backward computation.
I0121 22:32:43.035490  1946 net.cpp:200] inception_11a/1x1/bn1 does not need backward computation.
I0121 22:32:43.035495  1946 net.cpp:200] inception_11a/1x1 does not need backward computation.
I0121 22:32:43.035501  1946 net.cpp:200] inception_10a/output_inception_10a/output_0_split does not need backward computation.
I0121 22:32:43.035517  1946 net.cpp:200] inception_10a/output does not need backward computation.
I0121 22:32:43.035526  1946 net.cpp:200] inception_10a/3x3/relu1 does not need backward computation.
I0121 22:32:43.035531  1946 net.cpp:200] inception_10a/3x3/scale1 does not need backward computation.
I0121 22:32:43.035537  1946 net.cpp:200] inception_10a/3x3/bn1 does not need backward computation.
I0121 22:32:43.035543  1946 net.cpp:200] inception_10a/3x3 does not need backward computation.
I0121 22:32:43.035549  1946 net.cpp:200] inception_10a/1x1/relu1 does not need backward computation.
I0121 22:32:43.035555  1946 net.cpp:200] inception_10a/1x1/scale1 does not need backward computation.
I0121 22:32:43.035562  1946 net.cpp:200] inception_10a/1x1/bn1 does not need backward computation.
I0121 22:32:43.035567  1946 net.cpp:200] inception_10a/1x1 does not need backward computation.
I0121 22:32:43.035573  1946 net.cpp:200] downsample_9/output_downsample_9/output_0_split does not need backward computation.
I0121 22:32:43.035580  1946 net.cpp:200] downsample_9/output does not need backward computation.
I0121 22:32:43.035589  1946 net.cpp:200] downsample_9/pool_s2 does not need backward computation.
I0121 22:32:43.035596  1946 net.cpp:200] downsample_9/3x3_s2/relu1 does not need backward computation.
I0121 22:32:43.035601  1946 net.cpp:200] downsample_9/3x3_s2/scale1 does not need backward computation.
I0121 22:32:43.035607  1946 net.cpp:200] downsample_9/3x3_s2/bn1 does not need backward computation.
I0121 22:32:43.035612  1946 net.cpp:200] downsample_9/3x3_s2 does not need backward computation.
I0121 22:32:43.035619  1946 net.cpp:200] inception_8a/output_inception_8a/output_0_split does not need backward computation.
I0121 22:32:43.035625  1946 net.cpp:200] inception_8a/output does not need backward computation.
I0121 22:32:43.035634  1946 net.cpp:200] inception_8a/3x3/relu1 does not need backward computation.
I0121 22:32:43.035641  1946 net.cpp:200] inception_8a/3x3/scale1 does not need backward computation.
I0121 22:32:43.035647  1946 net.cpp:200] inception_8a/3x3/bn1 does not need backward computation.
I0121 22:32:43.035652  1946 net.cpp:200] inception_8a/3x3 does not need backward computation.
I0121 22:32:43.035658  1946 net.cpp:200] inception_8a/1x1/relu1 does not need backward computation.
I0121 22:32:43.035665  1946 net.cpp:200] inception_8a/1x1/scale1 does not need backward computation.
I0121 22:32:43.035672  1946 net.cpp:200] inception_8a/1x1/bn1 does not need backward computation.
I0121 22:32:43.035678  1946 net.cpp:200] inception_8a/1x1 does not need backward computation.
I0121 22:32:43.035684  1946 net.cpp:200] inception_7a/output_inception_7a/output_0_split does not need backward computation.
I0121 22:32:43.035692  1946 net.cpp:200] inception_7a/output does not need backward computation.
I0121 22:32:43.035701  1946 net.cpp:200] inception_7a/3x3/relu1 does not need backward computation.
I0121 22:32:43.035733  1946 net.cpp:200] inception_7a/3x3/scale1 does not need backward computation.
I0121 22:32:43.035748  1946 net.cpp:200] inception_7a/3x3/bn1 does not need backward computation.
I0121 22:32:43.035754  1946 net.cpp:200] inception_7a/3x3 does not need backward computation.
I0121 22:32:43.035761  1946 net.cpp:200] inception_7a/1x1/relu1 does not need backward computation.
I0121 22:32:43.035768  1946 net.cpp:200] inception_7a/1x1/scale1 does not need backward computation.
I0121 22:32:43.035773  1946 net.cpp:200] inception_7a/1x1/bn1 does not need backward computation.
I0121 22:32:43.035799  1946 net.cpp:200] inception_7a/1x1 does not need backward computation.
I0121 22:32:43.035828  1946 net.cpp:200] inception_6a/output_inception_6a/output_0_split does not need backward computation.
I0121 22:32:43.035851  1946 net.cpp:200] inception_6a/output does not need backward computation.
I0121 22:32:43.035868  1946 net.cpp:200] inception_6a/3x3/relu1 does not need backward computation.
I0121 22:32:43.035876  1946 net.cpp:200] inception_6a/3x3/scale1 does not need backward computation.
I0121 22:32:43.035879  1946 net.cpp:200] inception_6a/3x3/bn1 does not need backward computation.
I0121 22:32:43.035883  1946 net.cpp:200] inception_6a/3x3 does not need backward computation.
I0121 22:32:43.035887  1946 net.cpp:200] inception_6a/1x1/relu1 does not need backward computation.
I0121 22:32:43.035892  1946 net.cpp:200] inception_6a/1x1/scale1 does not need backward computation.
I0121 22:32:43.035898  1946 net.cpp:200] inception_6a/1x1/bn1 does not need backward computation.
I0121 22:32:43.035905  1946 net.cpp:200] inception_6a/1x1 does not need backward computation.
I0121 22:32:43.035914  1946 net.cpp:200] inception_5a/output_inception_5a/output_0_split does not need backward computation.
I0121 22:32:43.035921  1946 net.cpp:200] inception_5a/output does not need backward computation.
I0121 22:32:43.035928  1946 net.cpp:200] inception_5a/3x3/relu1 does not need backward computation.
I0121 22:32:43.035936  1946 net.cpp:200] inception_5a/3x3/scale1 does not need backward computation.
I0121 22:32:43.035943  1946 net.cpp:200] inception_5a/3x3/bn1 does not need backward computation.
I0121 22:32:43.035948  1946 net.cpp:200] inception_5a/3x3 does not need backward computation.
I0121 22:32:43.035959  1946 net.cpp:200] inception_5a/1x1/relu1 does not need backward computation.
I0121 22:32:43.035965  1946 net.cpp:200] inception_5a/1x1/scale1 does not need backward computation.
I0121 22:32:43.035971  1946 net.cpp:200] inception_5a/1x1/bn1 does not need backward computation.
I0121 22:32:43.035979  1946 net.cpp:200] inception_5a/1x1 does not need backward computation.
I0121 22:32:43.035986  1946 net.cpp:200] downsample_4/output_downsample_4/output_0_split does not need backward computation.
I0121 22:32:43.035993  1946 net.cpp:200] downsample_4/output does not need backward computation.
I0121 22:32:43.036002  1946 net.cpp:200] downsample_4/pool_s2 does not need backward computation.
I0121 22:32:43.036008  1946 net.cpp:200] downsample_4/3x3_s2/relu1 does not need backward computation.
I0121 22:32:43.036015  1946 net.cpp:200] downsample_4/3x3_s2/scale1 does not need backward computation.
I0121 22:32:43.036018  1946 net.cpp:200] downsample_4/3x3_s2/bn1 does not need backward computation.
I0121 22:32:43.036023  1946 net.cpp:200] downsample_4/3x3_s2 does not need backward computation.
I0121 22:32:43.036033  1946 net.cpp:200] inception_3a/output_inception_3a/output_0_split does not need backward computation.
I0121 22:32:43.036041  1946 net.cpp:200] inception_3a/output does not need backward computation.
I0121 22:32:43.036047  1946 net.cpp:200] inception_3a/3x3/relu1 does not need backward computation.
I0121 22:32:43.036056  1946 net.cpp:200] inception_3a/3x3/scale1 does not need backward computation.
I0121 22:32:43.036062  1946 net.cpp:200] inception_3a/3x3/bn1 does not need backward computation.
I0121 22:32:43.036069  1946 net.cpp:200] inception_3a/3x3 does not need backward computation.
I0121 22:32:43.036075  1946 net.cpp:200] inception_3a/1x1/relu1 does not need backward computation.
I0121 22:32:43.036082  1946 net.cpp:200] inception_3a/1x1/scale1 does not need backward computation.
I0121 22:32:43.036089  1946 net.cpp:200] inception_3a/1x1/bn1 does not need backward computation.
I0121 22:32:43.036096  1946 net.cpp:200] inception_3a/1x1 does not need backward computation.
I0121 22:32:43.036104  1946 net.cpp:200] inception_2a/output_inception_2a/output_0_split does not need backward computation.
I0121 22:32:43.036110  1946 net.cpp:200] inception_2a/output does not need backward computation.
I0121 22:32:43.036118  1946 net.cpp:200] inception_2a/3x3/relu1 does not need backward computation.
I0121 22:32:43.036125  1946 net.cpp:200] inception_2a/3x3/scale1 does not need backward computation.
I0121 22:32:43.036132  1946 net.cpp:200] inception_2a/3x3/bn1 does not need backward computation.
I0121 22:32:43.036140  1946 net.cpp:200] inception_2a/3x3 does not need backward computation.
I0121 22:32:43.036146  1946 net.cpp:200] inception_2a/1x1/relu1 does not need backward computation.
I0121 22:32:43.036155  1946 net.cpp:200] inception_2a/1x1/scale1 does not need backward computation.
I0121 22:32:43.036161  1946 net.cpp:200] inception_2a/1x1/bn1 does not need backward computation.
I0121 22:32:43.036165  1946 net.cpp:200] inception_2a/1x1 does not need backward computation.
I0121 22:32:43.036170  1946 net.cpp:200] conv1/3x3_s1_conv1/relu1_0_split does not need backward computation.
I0121 22:32:43.036177  1946 net.cpp:200] conv1/relu1 does not need backward computation.
I0121 22:32:43.036183  1946 net.cpp:200] conv1/scale1 does not need backward computation.
I0121 22:32:43.036192  1946 net.cpp:200] conv1/bn1 does not need backward computation.
I0121 22:32:43.036198  1946 net.cpp:200] conv1/3x3_s1 does not need backward computation.
I0121 22:32:43.036206  1946 net.cpp:200] data does not need backward computation.
I0121 22:32:43.036213  1946 net.cpp:242] This network produces output prob
I0121 22:32:43.036309  1946 net.cpp:255] Network initialization done.
I0121 22:32:43.042788  1946 upgrade_proto.cpp:77] Attempting to upgrade batch norm layers using deprecated params: cifar10/caffe/models/miniGoogleNet/m3/snapshot_3_miniGoogleNet__iter_40000.caffemodel
I0121 22:32:43.042826  1946 upgrade_proto.cpp:80] Successfully upgraded batch norm layers using deprecated params.
I0121 22:32:43.043913  1946 net.cpp:744] Ignoring source layer loss
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00044.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00004.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00059.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00055.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00068.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00079.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00038.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00039.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00064.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00013.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00002.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00081.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00072.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00078.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00035.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00054.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00085.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00021.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00080.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00093.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00026.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00067.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00018.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00096.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00010.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00039.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00022.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00042.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00009.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00054.jpg
PREDICTED: 8
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00002.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00047.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00029.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00005.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00066.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00064.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00063.jpg
PREDICTED: 0
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00002.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00065.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00100.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00034.jpg
PREDICTED: 8
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00011.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00057.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00078.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00087.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00094.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00098.jpg
PREDICTED: 6
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00094.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00029.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00059.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00070.jpg
PREDICTED: 7
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00063.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00059.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00051.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00067.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00069.jpg
PREDICTED: 8
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00087.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00095.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00009.jpg
PREDICTED: 4
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00092.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00055.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00074.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00078.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00082.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00058.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00096.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00002.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00017.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00091.jpg
PREDICTED: 5
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00035.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00028.jpg
PREDICTED: 8
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00047.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00075.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00088.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00062.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00018.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00081.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00003.jpg
PREDICTED: 9
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00073.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00086.jpg
PREDICTED: 3
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00019.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00067.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00012.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00047.jpg
PREDICTED: 0
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00082.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00050.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00040.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00075.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00092.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00089.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00044.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00031.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00010.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00043.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00029.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00086.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00011.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00085.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00006.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00081.jpg
PREDICTED: 3
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00006.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00059.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00048.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00092.jpg
PREDICTED: 8
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00029.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00037.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00091.jpg
PREDICTED: 0
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00059.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00068.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00073.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00026.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00044.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00072.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00035.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00004.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00048.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00099.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00079.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00053.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00046.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00058.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00060.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00073.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00097.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00035.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00061.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00046.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00070.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00059.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00002.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00008.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00034.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00098.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00004.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00070.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00017.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00074.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00094.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00018.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00051.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00037.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00042.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00087.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00011.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00008.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00066.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00097.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00051.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00063.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00091.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00080.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00032.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00096.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00069.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00077.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00027.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00080.jpg
PREDICTED: 3
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00019.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00020.jpg
PREDICTED: 3
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00038.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00003.jpg
PREDICTED: 4
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00001.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00033.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00057.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00051.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00010.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00086.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00081.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00065.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00090.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00054.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00006.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00029.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00098.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00020.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00064.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00079.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00066.jpg
PREDICTED: 3
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00086.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00034.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00090.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00077.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00085.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00061.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00054.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00094.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00044.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00030.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00050.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00016.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00094.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00058.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00076.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00065.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00062.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00032.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00097.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00054.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00060.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00029.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00065.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00065.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00079.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00100.jpg
PREDICTED: 3
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00031.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00053.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00073.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00015.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00028.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00068.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00028.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00047.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00019.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00053.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00045.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00081.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00100.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00087.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00035.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00033.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00036.jpg
PREDICTED: 2
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00069.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00049.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00036.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00100.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00093.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00040.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00031.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00049.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00069.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00001.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00094.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00031.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00001.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00071.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00036.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00012.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00075.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00055.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00095.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00090.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00051.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00058.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00052.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00007.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00039.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00028.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00008.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00070.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00044.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00003.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00053.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00029.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00071.jpg
PREDICTED: 0
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00050.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00084.jpg
PREDICTED: 3
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00032.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00088.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00026.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00044.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00060.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00021.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00064.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00009.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00084.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00072.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00032.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00011.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00094.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00023.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00086.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00022.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00021.jpg
PREDICTED: 0
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00090.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00045.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00078.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00076.jpg
PREDICTED: 2
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00093.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00099.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00019.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00013.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00082.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00100.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00074.jpg
PREDICTED: 0
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00025.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00031.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00061.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00041.jpg
PREDICTED: 6
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00048.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00049.jpg
PREDICTED: 3
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00074.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00097.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00064.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00088.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00040.jpg
PREDICTED: 0
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00083.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00041.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00013.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00022.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00027.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00086.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00048.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00086.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00034.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00099.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00053.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00035.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00068.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00002.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00073.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00074.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00038.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00001.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00046.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00010.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00014.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00015.jpg
PREDICTED: 6
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00094.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00026.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00083.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00002.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00032.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00036.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00046.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00087.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00083.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00082.jpg
PREDICTED: 3
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00095.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00010.jpg
PREDICTED: 3
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00037.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00060.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00031.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00015.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00011.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00024.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00005.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00038.jpg
PREDICTED: 9
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00092.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00043.jpg
PREDICTED: 8
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00067.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00010.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00096.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00089.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00073.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00085.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00045.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00004.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00004.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00084.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00041.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00099.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00057.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00098.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00095.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00072.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00068.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00009.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00005.jpg
PREDICTED: 5
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00093.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00026.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00099.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00036.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00053.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00080.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00061.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00082.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00008.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00099.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00026.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00033.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00007.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00069.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00026.jpg
PREDICTED: 9
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00079.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00021.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00018.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00026.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00084.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00070.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00056.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00093.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00020.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00026.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00041.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00087.jpg
PREDICTED: 1
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00019.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00006.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00028.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00010.jpg
PREDICTED: 3
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00046.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00008.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00021.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00007.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00077.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00014.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00072.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00089.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00048.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00003.jpg
PREDICTED: 6
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00049.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00095.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00096.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00082.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00098.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00016.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00069.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00064.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00084.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00083.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00055.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00035.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00005.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00082.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00043.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00019.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00022.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00016.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00088.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00045.jpg
PREDICTED: 3
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00056.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00080.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00021.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00009.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00073.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00037.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00067.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00097.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00015.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00014.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00061.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00091.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00056.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00011.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00048.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00037.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00008.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00015.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00018.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00002.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00058.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00043.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00034.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00091.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00020.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00060.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00007.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00064.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00069.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00082.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00009.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00059.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00088.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00078.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00031.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00006.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00007.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00023.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00004.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00003.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00075.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00006.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00085.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00100.jpg
PREDICTED: 4
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00033.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00053.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00095.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00059.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00090.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00053.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00036.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00090.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00083.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00056.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00054.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00039.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00007.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00006.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00076.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00027.jpg
PREDICTED: 3
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00030.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00083.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00085.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00047.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00005.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00023.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00092.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00076.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00042.jpg
PREDICTED: 2
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00088.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00050.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00071.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00074.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00058.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00057.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00068.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00087.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00049.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00073.jpg
PREDICTED: 4
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00023.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00055.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00030.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00016.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00086.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00060.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00039.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00063.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00056.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00025.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00033.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00021.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00033.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00042.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00080.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00041.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00012.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00033.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00096.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00092.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00039.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00020.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00100.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00084.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00081.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00088.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00084.jpg
PREDICTED: 0
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00020.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00007.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00078.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00041.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00012.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00044.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00099.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00098.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00028.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00062.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00081.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00097.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00031.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00060.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00068.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00065.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00045.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00053.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00074.jpg
PREDICTED: 5
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00063.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00033.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00038.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00006.jpg
PREDICTED: 5
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00017.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00043.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00097.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00022.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00062.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00085.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00025.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00091.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00043.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00056.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00013.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00036.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00030.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00079.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00023.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00045.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00013.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00013.jpg
PREDICTED: 5
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00080.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00075.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00034.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00027.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00011.jpg
PREDICTED: 6
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00052.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00017.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00049.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00014.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00018.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00063.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00080.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00095.jpg
PREDICTED: 4
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00066.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00055.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00005.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00096.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00099.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00064.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00018.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00080.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00098.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00062.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00008.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00057.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00028.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00085.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00061.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00088.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00005.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00090.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00077.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00035.jpg
PREDICTED: 1
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00015.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00022.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00009.jpg
PREDICTED: 7
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00039.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00066.jpg
PREDICTED: 2
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00023.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00051.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00063.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00074.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00041.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00072.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00055.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00076.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00058.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00017.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00038.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00079.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00040.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00018.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00018.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00048.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00027.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00024.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00070.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00076.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00071.jpg
PREDICTED: 0
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00023.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00045.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00015.jpg
PREDICTED: 3
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00071.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00044.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00056.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00015.jpg
PREDICTED: 2
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00016.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00076.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00022.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00014.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00027.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00077.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00098.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00005.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00077.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00100.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00013.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00068.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00010.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00075.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00042.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00100.jpg
PREDICTED: 2
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00052.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00061.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00042.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00019.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00014.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00095.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00056.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00040.jpg
PREDICTED: 5
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00094.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00050.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00074.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00055.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00061.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00085.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00013.jpg
PREDICTED: 2
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00016.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00078.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00067.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00071.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00016.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00075.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00015.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00020.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00012.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00047.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00001.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00059.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00021.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00097.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00081.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00072.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00068.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00040.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00058.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00042.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00022.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00091.jpg
PREDICTED: 2
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00046.jpg
PREDICTED: 4
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00092.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00075.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00008.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00027.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00064.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00001.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00096.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00009.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00089.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00098.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00006.jpg
PREDICTED: 7
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00098.jpg
PREDICTED: 7
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00042.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00028.jpg
PREDICTED: 0
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00091.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00051.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00047.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00070.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00025.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00081.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00009.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00030.jpg
PREDICTED: 3
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00008.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00050.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00025.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00043.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00017.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00004.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00024.jpg
PREDICTED: 3
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00029.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00051.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00100.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00030.jpg
PREDICTED: 5
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00014.jpg
PREDICTED: 3
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00076.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00025.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00031.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00069.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00040.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00066.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00028.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00041.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00034.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00073.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00008.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00085.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00025.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00042.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00087.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00050.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00040.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00079.jpg
PREDICTED: 5
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00045.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00060.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00027.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00084.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00030.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00038.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00072.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00058.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00093.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00059.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00039.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00038.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00070.jpg
PREDICTED: 0
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00092.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00062.jpg
PREDICTED: 3
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00078.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00062.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00088.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00027.jpg
PREDICTED: 2
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00032.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00025.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00065.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00071.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00065.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00079.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00093.jpg
PREDICTED: 3
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00025.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00077.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00047.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00025.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00011.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00091.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00019.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00076.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00041.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00006.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00077.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00048.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00062.jpg
PREDICTED: 3
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00099.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00012.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00022.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00077.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00003.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00007.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00063.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00051.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00026.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00070.jpg
PREDICTED: 0
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00093.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00079.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00052.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00024.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00054.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00003.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00017.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00030.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00007.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00086.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00097.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00046.jpg
PREDICTED: 3
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00095.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00016.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00082.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00044.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00027.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00071.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00029.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00002.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00036.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00040.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00063.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00072.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00067.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00012.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00037.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00083.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00050.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00075.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00096.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00007.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00024.jpg
PREDICTED: 9
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00083.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00024.jpg
PREDICTED: 3
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00035.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00078.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00062.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00089.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00011.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00062.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00092.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00034.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00050.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00014.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00055.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00018.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00073.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00034.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00033.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00010.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00046.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00069.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00034.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00061.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00049.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00049.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00054.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00039.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00097.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00082.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00089.jpg
PREDICTED: 9
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00038.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00021.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00092.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00043.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00093.jpg
PREDICTED: 7
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00071.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00087.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00081.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00060.jpg
PREDICTED: 4
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00086.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00032.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00042.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00012.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00024.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00056.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00041.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00024.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00038.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00003.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00037.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00061.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00083.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00052.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00050.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00013.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00017.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00001.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00037.jpg
PREDICTED: 5
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00075.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00084.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00009.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00054.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00024.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00044.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00013.jpg
PREDICTED: 3
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00083.jpg
PREDICTED: 3
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00005.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00037.jpg
PREDICTED: 5
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00090.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00068.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00070.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00030.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00020.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00037.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00084.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00028.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00094.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00023.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00077.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00078.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00014.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00066.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00024.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00089.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00014.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00036.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00057.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00043.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00020.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00021.jpg
PREDICTED: 4
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00015.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00048.jpg
PREDICTED: 0
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00030.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00003.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00049.jpg
PREDICTED: 5
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00017.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00035.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00010.jpg
PREDICTED: 6
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00067.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00020.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00004.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00045.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00069.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00090.jpg
PREDICTED: 3
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00048.jpg
PREDICTED: 8
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00023.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00045.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00065.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00039.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00055.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00040.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00046.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00019.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00046.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00060.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00063.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00057.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00067.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00066.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00052.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00029.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00016.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00052.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00033.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00074.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00052.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00057.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00011.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00032.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00022.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00072.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00065.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00005.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00047.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00058.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00043.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00066.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00089.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00093.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00090.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00047.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00054.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00017.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00049.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00056.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00012.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00071.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00036.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00012.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00004.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00001.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00099.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00080.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00016.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00066.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00051.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00002.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00004.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00052.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/truck_00032.jpg
PREDICTED: 9
EXPECTED : 9
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00089.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00089.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00087.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00057.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00023.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/deer_00057.jpg
PREDICTED: 4
EXPECTED : 4
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00001.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00052.jpg
PREDICTED: 1
EXPECTED : 1
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/ship_00076.jpg
PREDICTED: 8
EXPECTED : 8
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/frog_00019.jpg
PREDICTED: 6
EXPECTED : 6
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00088.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00001.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00064.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00091.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/bird_00053.jpg
PREDICTED: 2
EXPECTED : 2
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/dog_00032.jpg
PREDICTED: 5
EXPECTED : 5
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00003.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/cat_00096.jpg
PREDICTED: 3
EXPECTED : 3
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/airplane_00067.jpg
PREDICTED: 0
EXPECTED : 0
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/horse_00095.jpg
PREDICTED: 7
EXPECTED : 7
-------
IMAGE: /home/ubuntu/ML/cifar10/input/cifar10_jpg/test/automobile_00031.jpg
PREDICTED: 1
EXPECTED : 1
-------
              precision    recall  f1-score   support

    airplane       0.87      0.86      0.86       100
  automobile       0.98      0.96      0.97       100
        bird       0.91      0.87      0.89       100
         cat       0.77      0.83      0.80       100
        deer       0.92      0.94      0.93       100
         dog       0.89      0.88      0.88       100
        frog       0.94      0.90      0.92       100
       horse       0.95      0.97      0.96       100
        ship       0.93      0.93      0.93       100
       truck       0.95      0.95      0.95       100

   micro avg       0.91      0.91      0.91      1000
   macro avg       0.91      0.91      0.91      1000
weighted avg       0.91      0.91      0.91      1000

SKLEARN Accuracy = 0.91


TOP-5 ACCURACY                    = 1.00 
TOP-5 FALSE                       =  0
TOP-5 TRUE                        =  1000


TOTAL NUMBER OF TRUE  PREDICTIONS =  909
TOTAL NUMBER OF FALSE PREDICTIONS =  91
MANUALLY COMPUTED RECALL = 0.91