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cifar10_full.prototxt
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cifar10_full.prototxt
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name: "CIFAR10_full_deploy"
# N.B. input image must be in CIFAR-10 format
# as described at http://www.cs.toronto.edu/~kriz/cifar.html
input: "data"
input_dim: 1
input_dim: 3
input_dim: 32
input_dim: 32
layers {
name: "conv1"
type: CONVOLUTION
bottom: "data"
top: "conv1"
blobs_lr: 1
blobs_lr: 2
convolution_param {
num_output: 32
pad: 2
kernel_size: 5
stride: 1
}
}
layers {
name: "pool1"
type: POOLING
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layers {
name: "relu1"
type: RELU
bottom: "pool1"
top: "pool1"
}
layers {
name: "norm1"
type: LRN
bottom: "pool1"
top: "norm1"
lrn_param {
norm_region: WITHIN_CHANNEL
local_size: 3
alpha: 5e-05
beta: 0.75
}
}
layers {
name: "conv2"
type: CONVOLUTION
bottom: "norm1"
top: "conv2"
blobs_lr: 1
blobs_lr: 2
convolution_param {
num_output: 32
pad: 2
kernel_size: 5
stride: 1
}
}
layers {
name: "relu2"
type: RELU
bottom: "conv2"
top: "conv2"
}
layers {
name: "pool2"
type: POOLING
bottom: "conv2"
top: "pool2"
pooling_param {
pool: AVE
kernel_size: 3
stride: 2
}
}
layers {
name: "norm2"
type: LRN
bottom: "pool2"
top: "norm2"
lrn_param {
norm_region: WITHIN_CHANNEL
local_size: 3
alpha: 5e-05
beta: 0.75
}
}
layers {
name: "conv3"
type: CONVOLUTION
bottom: "norm2"
top: "conv3"
convolution_param {
num_output: 64
pad: 2
kernel_size: 5
stride: 1
}
}
layers {
name: "relu3"
type: RELU
bottom: "conv3"
top: "conv3"
}
layers {
name: "pool3"
type: POOLING
bottom: "conv3"
top: "pool3"
pooling_param {
pool: AVE
kernel_size: 3
stride: 2
}
}
layers {
name: "ip1"
type: INNER_PRODUCT
bottom: "pool3"
top: "ip1"
blobs_lr: 1
blobs_lr: 2
weight_decay: 250
weight_decay: 0
inner_product_param {
num_output: 10
}
}
layers {
name: "prob"
type: SOFTMAX
bottom: "ip1"
top: "prob"
}