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getResNetProtoTxt.py
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4969 lines (4864 loc) · 93.5 KB
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def getResNet50Init():
string = '\
layer {\n\
bottom: "image"\n\
top: "conv1"\n\
name: "conv1"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 64\n\
kernel_size: 7\n\
pad: 3\n\
stride: 2\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "conv1"\n\
top: "conv1"\n\
name: "bn_conv1"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "conv1"\n\
top: "conv1"\n\
name: "scale_conv1"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "conv1"\n\
top: "conv1"\n\
name: "conv1_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "conv1"\n\
top: "pool1"\n\
name: "pool1"\n\
type: "Pooling"\n\
pooling_param {\n\
kernel_size: 3\n\
stride: 2\n\
pool: MAX\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "pool1"\n\
top: "res2a_branch1"\n\
name: "res2a_branch1"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 256\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch1"\n\
top: "res2a_branch1"\n\
name: "bn2a_branch1"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch1"\n\
top: "res2a_branch1"\n\
name: "scale2a_branch1"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "pool1"\n\
top: "res2a_branch2a"\n\
name: "res2a_branch2a"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 64\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2a"\n\
top: "res2a_branch2a"\n\
name: "bn2a_branch2a"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2a"\n\
top: "res2a_branch2a"\n\
name: "scale2a_branch2a"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2a"\n\
top: "res2a_branch2a"\n\
name: "res2a_branch2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2a"\n\
top: "res2a_branch2b"\n\
name: "res2a_branch2b"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 64\n\
kernel_size: 3\n\
pad: 1\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2b"\n\
top: "res2a_branch2b"\n\
name: "bn2a_branch2b"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2b"\n\
top: "res2a_branch2b"\n\
name: "scale2a_branch2b"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2b"\n\
top: "res2a_branch2b"\n\
name: "res2a_branch2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2b"\n\
top: "res2a_branch2c"\n\
name: "res2a_branch2c"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 256\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2c"\n\
top: "res2a_branch2c"\n\
name: "bn2a_branch2c"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch2c"\n\
top: "res2a_branch2c"\n\
name: "scale2a_branch2c"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a_branch1"\n\
bottom: "res2a_branch2c"\n\
top: "res2a"\n\
name: "res2a"\n\
type: "Eltwise"\n\
}\n\
\n\
layer {\n\
bottom: "res2a"\n\
top: "res2a"\n\
name: "res2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2a"\n\
top: "res2b_branch2a"\n\
name: "res2b_branch2a"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 64\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2a"\n\
top: "res2b_branch2a"\n\
name: "bn2b_branch2a"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2a"\n\
top: "res2b_branch2a"\n\
name: "scale2b_branch2a"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2a"\n\
top: "res2b_branch2a"\n\
name: "res2b_branch2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2a"\n\
top: "res2b_branch2b"\n\
name: "res2b_branch2b"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 64\n\
kernel_size: 3\n\
pad: 1\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2b"\n\
top: "res2b_branch2b"\n\
name: "bn2b_branch2b"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2b"\n\
top: "res2b_branch2b"\n\
name: "scale2b_branch2b"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2b"\n\
top: "res2b_branch2b"\n\
name: "res2b_branch2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2b"\n\
top: "res2b_branch2c"\n\
name: "res2b_branch2c"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 256\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2c"\n\
top: "res2b_branch2c"\n\
name: "bn2b_branch2c"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b_branch2c"\n\
top: "res2b_branch2c"\n\
name: "scale2b_branch2c"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2a"\n\
bottom: "res2b_branch2c"\n\
top: "res2b"\n\
name: "res2b"\n\
type: "Eltwise"\n\
}\n\
\n\
layer {\n\
bottom: "res2b"\n\
top: "res2b"\n\
name: "res2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2b"\n\
top: "res2c_branch2a"\n\
name: "res2c_branch2a"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 64\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2a"\n\
top: "res2c_branch2a"\n\
name: "bn2c_branch2a"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2a"\n\
top: "res2c_branch2a"\n\
name: "scale2c_branch2a"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2a"\n\
top: "res2c_branch2a"\n\
name: "res2c_branch2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2a"\n\
top: "res2c_branch2b"\n\
name: "res2c_branch2b"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 64\n\
kernel_size: 3\n\
pad: 1\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2b"\n\
top: "res2c_branch2b"\n\
name: "bn2c_branch2b"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2b"\n\
top: "res2c_branch2b"\n\
name: "scale2c_branch2b"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2b"\n\
top: "res2c_branch2b"\n\
name: "res2c_branch2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2b"\n\
top: "res2c_branch2c"\n\
name: "res2c_branch2c"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 256\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2c"\n\
top: "res2c_branch2c"\n\
name: "bn2c_branch2c"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c_branch2c"\n\
top: "res2c_branch2c"\n\
name: "scale2c_branch2c"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2b"\n\
bottom: "res2c_branch2c"\n\
top: "res2c"\n\
name: "res2c"\n\
type: "Eltwise"\n\
}\n\
\n\
layer {\n\
bottom: "res2c"\n\
top: "res2c"\n\
name: "res2c_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res2c"\n\
top: "res3a_branch1"\n\
name: "res3a_branch1"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 512\n\
kernel_size: 1\n\
pad: 0\n\
stride: 2\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch1"\n\
top: "res3a_branch1"\n\
name: "bn3a_branch1"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch1"\n\
top: "res3a_branch1"\n\
name: "scale3a_branch1"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res2c"\n\
top: "res3a_branch2a"\n\
name: "res3a_branch2a"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 1\n\
pad: 0\n\
stride: 2\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2a"\n\
top: "res3a_branch2a"\n\
name: "bn3a_branch2a"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2a"\n\
top: "res3a_branch2a"\n\
name: "scale3a_branch2a"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2a"\n\
top: "res3a_branch2a"\n\
name: "res3a_branch2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2a"\n\
top: "res3a_branch2b"\n\
name: "res3a_branch2b"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 3\n\
pad: 1\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2b"\n\
top: "res3a_branch2b"\n\
name: "bn3a_branch2b"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2b"\n\
top: "res3a_branch2b"\n\
name: "scale3a_branch2b"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2b"\n\
top: "res3a_branch2b"\n\
name: "res3a_branch2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2b"\n\
top: "res3a_branch2c"\n\
name: "res3a_branch2c"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 512\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2c"\n\
top: "res3a_branch2c"\n\
name: "bn3a_branch2c"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch2c"\n\
top: "res3a_branch2c"\n\
name: "scale3a_branch2c"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a_branch1"\n\
bottom: "res3a_branch2c"\n\
top: "res3a"\n\
name: "res3a"\n\
type: "Eltwise"\n\
}\n\
\n\
layer {\n\
bottom: "res3a"\n\
top: "res3a"\n\
name: "res3a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3a"\n\
top: "res3b_branch2a"\n\
name: "res3b_branch2a"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2a"\n\
top: "res3b_branch2a"\n\
name: "bn3b_branch2a"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2a"\n\
top: "res3b_branch2a"\n\
name: "scale3b_branch2a"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2a"\n\
top: "res3b_branch2a"\n\
name: "res3b_branch2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2a"\n\
top: "res3b_branch2b"\n\
name: "res3b_branch2b"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 3\n\
pad: 1\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2b"\n\
top: "res3b_branch2b"\n\
name: "bn3b_branch2b"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2b"\n\
top: "res3b_branch2b"\n\
name: "scale3b_branch2b"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2b"\n\
top: "res3b_branch2b"\n\
name: "res3b_branch2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2b"\n\
top: "res3b_branch2c"\n\
name: "res3b_branch2c"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 512\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2c"\n\
top: "res3b_branch2c"\n\
name: "bn3b_branch2c"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b_branch2c"\n\
top: "res3b_branch2c"\n\
name: "scale3b_branch2c"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3a"\n\
bottom: "res3b_branch2c"\n\
top: "res3b"\n\
name: "res3b"\n\
type: "Eltwise"\n\
}\n\
\n\
layer {\n\
bottom: "res3b"\n\
top: "res3b"\n\
name: "res3b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3b"\n\
top: "res3c_branch2a"\n\
name: "res3c_branch2a"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2a"\n\
top: "res3c_branch2a"\n\
name: "bn3c_branch2a"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2a"\n\
top: "res3c_branch2a"\n\
name: "scale3c_branch2a"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2a"\n\
top: "res3c_branch2a"\n\
name: "res3c_branch2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2a"\n\
top: "res3c_branch2b"\n\
name: "res3c_branch2b"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 3\n\
pad: 1\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2b"\n\
top: "res3c_branch2b"\n\
name: "bn3c_branch2b"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2b"\n\
top: "res3c_branch2b"\n\
name: "scale3c_branch2b"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2b"\n\
top: "res3c_branch2b"\n\
name: "res3c_branch2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2b"\n\
top: "res3c_branch2c"\n\
name: "res3c_branch2c"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 512\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2c"\n\
top: "res3c_branch2c"\n\
name: "bn3c_branch2c"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3c_branch2c"\n\
top: "res3c_branch2c"\n\
name: "scale3c_branch2c"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3b"\n\
bottom: "res3c_branch2c"\n\
top: "res3c"\n\
name: "res3c"\n\
type: "Eltwise"\n\
}\n\
\n\
layer {\n\
bottom: "res3c"\n\
top: "res3c"\n\
name: "res3c_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3c"\n\
top: "res3d_branch2a"\n\
name: "res3d_branch2a"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2a"\n\
top: "res3d_branch2a"\n\
name: "bn3d_branch2a"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2a"\n\
top: "res3d_branch2a"\n\
name: "scale3d_branch2a"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2a"\n\
top: "res3d_branch2a"\n\
name: "res3d_branch2a_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2a"\n\
top: "res3d_branch2b"\n\
name: "res3d_branch2b"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 128\n\
kernel_size: 3\n\
pad: 1\n\
stride: 1\n\
bias_term: false\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2b"\n\
top: "res3d_branch2b"\n\
name: "bn3d_branch2b"\n\
type: "BatchNorm"\n\
batch_norm_param {\n\
use_global_stats: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2b"\n\
top: "res3d_branch2b"\n\
name: "scale3d_branch2b"\n\
type: "Scale"\n\
scale_param {\n\
bias_term: true\n\
}\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2b"\n\
top: "res3d_branch2b"\n\
name: "res3d_branch2b_relu"\n\
type: "ReLU"\n\
}\n\
\n\
layer {\n\
bottom: "res3d_branch2b"\n\
top: "res3d_branch2c"\n\
name: "res3d_branch2c"\n\
type: "Convolution"\n\
convolution_param {\n\
num_output: 512\n\
kernel_size: 1\n\
pad: 0\n\
stride: 1\n\