Skip to content

Instantly share code, notes, and snippets.

@mgolub2

mgolub2/wrn.prototxt

Last active August 21, 2018 02:49
Show Gist options
  • Save mgolub2/629a44d8666cd07e4bd68f8e5a27ee2f to your computer and use it in GitHub Desktop.
Save mgolub2/629a44d8666cd07e4bd68f8e5a27ee2f to your computer and use it in GitHub Desktop.
Download ZIP
wrn_real
Raw
wrn.prototxt
name: "wrn"
layer {
name: "data"
type: "Input"
top: "data"
input_param { shape: { dim: 1 dim: 3 dim: 32 dim: 32 } }
}
layer {
type: "Convolution"
name: "Convolution2DFunction-0-1"
bottom: "data"
top: "Convolution2DFunction-0-1"
convolution_param {
num_output: 16
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-1-1_bn"
bottom: "Convolution2DFunction-0-1"
top: "FixedBatchNormalization-1-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-1-1"
bottom: "FixedBatchNormalization-1-1_bn"
top: "FixedBatchNormalization-1-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-2-1"
bottom: "FixedBatchNormalization-1-1"
top: "ReLU-2-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-3-1"
bottom: "ReLU-2-1"
top: "Convolution2DFunction-3-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 0
pad_h: 0
stride_w: 1
stride_h: 1
kernel_w: 1
kernel_h: 1
}
}
layer {
type: "Convolution"
name: "Convolution2DFunction-3-2"
bottom: "ReLU-2-1"
top: "Convolution2DFunction-3-2"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-4-1_bn"
bottom: "Convolution2DFunction-3-2"
top: "FixedBatchNormalization-4-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-4-1"
bottom: "FixedBatchNormalization-4-1_bn"
top: "FixedBatchNormalization-4-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-5-1"
bottom: "FixedBatchNormalization-4-1"
top: "ReLU-5-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-6-1"
bottom: "ReLU-5-1"
top: "Convolution2DFunction-6-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-7-1"
bottom: "Convolution2DFunction-6-1"
bottom: "Convolution2DFunction-3-1"
top: "_ + _-7-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-8-1_bn"
bottom: "_ + _-7-1"
top: "FixedBatchNormalization-8-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-8-1"
bottom: "FixedBatchNormalization-8-1_bn"
top: "FixedBatchNormalization-8-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-9-1"
bottom: "FixedBatchNormalization-8-1"
top: "ReLU-9-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-10-1"
bottom: "ReLU-9-1"
top: "Convolution2DFunction-10-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-11-1_bn"
bottom: "Convolution2DFunction-10-1"
top: "FixedBatchNormalization-11-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-11-1"
bottom: "FixedBatchNormalization-11-1_bn"
top: "FixedBatchNormalization-11-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-12-1"
bottom: "FixedBatchNormalization-11-1"
top: "ReLU-12-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-13-1"
bottom: "ReLU-12-1"
top: "Convolution2DFunction-13-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-14-1"
bottom: "Convolution2DFunction-13-1"
bottom: "ReLU-9-1"
top: "_ + _-14-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-15-1_bn"
bottom: "_ + _-14-1"
top: "FixedBatchNormalization-15-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-15-1"
bottom: "FixedBatchNormalization-15-1_bn"
top: "FixedBatchNormalization-15-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-16-1"
bottom: "FixedBatchNormalization-15-1"
top: "ReLU-16-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-17-1"
bottom: "ReLU-16-1"
top: "Convolution2DFunction-17-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-18-1_bn"
bottom: "Convolution2DFunction-17-1"
top: "FixedBatchNormalization-18-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-18-1"
bottom: "FixedBatchNormalization-18-1_bn"
top: "FixedBatchNormalization-18-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-19-1"
bottom: "FixedBatchNormalization-18-1"
top: "ReLU-19-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-20-1"
bottom: "ReLU-19-1"
top: "Convolution2DFunction-20-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-21-1"
bottom: "Convolution2DFunction-20-1"
bottom: "ReLU-16-1"
top: "_ + _-21-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-22-1_bn"
bottom: "_ + _-21-1"
top: "FixedBatchNormalization-22-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-22-1"
bottom: "FixedBatchNormalization-22-1_bn"
top: "FixedBatchNormalization-22-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-23-1"
bottom: "FixedBatchNormalization-22-1"
top: "ReLU-23-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-24-1"
bottom: "ReLU-23-1"
top: "Convolution2DFunction-24-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-25-1_bn"
bottom: "Convolution2DFunction-24-1"
top: "FixedBatchNormalization-25-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-25-1"
bottom: "FixedBatchNormalization-25-1_bn"
top: "FixedBatchNormalization-25-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-26-1"
bottom: "FixedBatchNormalization-25-1"
top: "ReLU-26-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-27-1"
bottom: "ReLU-26-1"
top: "Convolution2DFunction-27-1"
convolution_param {
num_output: 160
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-28-1"
bottom: "Convolution2DFunction-27-1"
bottom: "ReLU-23-1"
top: "_ + _-28-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-29-1_bn"
bottom: "_ + _-28-1"
top: "FixedBatchNormalization-29-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-29-1"
bottom: "FixedBatchNormalization-29-1_bn"
top: "FixedBatchNormalization-29-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-30-1"
bottom: "FixedBatchNormalization-29-1"
top: "ReLU-30-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-31-1"
bottom: "ReLU-30-1"
top: "Convolution2DFunction-31-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 0
pad_h: 0
stride_w: 2
stride_h: 2
kernel_w: 1
kernel_h: 1
}
}
layer {
type: "Convolution"
name: "Convolution2DFunction-31-2"
bottom: "ReLU-30-1"
top: "Convolution2DFunction-31-2"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 2
stride_h: 2
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-32-1_bn"
bottom: "Convolution2DFunction-31-2"
top: "FixedBatchNormalization-32-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-32-1"
bottom: "FixedBatchNormalization-32-1_bn"
top: "FixedBatchNormalization-32-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-33-1"
bottom: "FixedBatchNormalization-32-1"
top: "ReLU-33-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-34-1"
bottom: "ReLU-33-1"
top: "Convolution2DFunction-34-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-35-1"
bottom: "Convolution2DFunction-34-1"
bottom: "Convolution2DFunction-31-1"
top: "_ + _-35-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-36-1_bn"
bottom: "_ + _-35-1"
top: "FixedBatchNormalization-36-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-36-1"
bottom: "FixedBatchNormalization-36-1_bn"
top: "FixedBatchNormalization-36-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-37-1"
bottom: "FixedBatchNormalization-36-1"
top: "ReLU-37-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-38-1"
bottom: "ReLU-37-1"
top: "Convolution2DFunction-38-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-39-1_bn"
bottom: "Convolution2DFunction-38-1"
top: "FixedBatchNormalization-39-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-39-1"
bottom: "FixedBatchNormalization-39-1_bn"
top: "FixedBatchNormalization-39-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-40-1"
bottom: "FixedBatchNormalization-39-1"
top: "ReLU-40-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-41-1"
bottom: "ReLU-40-1"
top: "Convolution2DFunction-41-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-42-1"
bottom: "Convolution2DFunction-41-1"
bottom: "ReLU-37-1"
top: "_ + _-42-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-43-1_bn"
bottom: "_ + _-42-1"
top: "FixedBatchNormalization-43-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-43-1"
bottom: "FixedBatchNormalization-43-1_bn"
top: "FixedBatchNormalization-43-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-44-1"
bottom: "FixedBatchNormalization-43-1"
top: "ReLU-44-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-45-1"
bottom: "ReLU-44-1"
top: "Convolution2DFunction-45-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-46-1_bn"
bottom: "Convolution2DFunction-45-1"
top: "FixedBatchNormalization-46-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-46-1"
bottom: "FixedBatchNormalization-46-1_bn"
top: "FixedBatchNormalization-46-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-47-1"
bottom: "FixedBatchNormalization-46-1"
top: "ReLU-47-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-48-1"
bottom: "ReLU-47-1"
top: "Convolution2DFunction-48-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-49-1"
bottom: "Convolution2DFunction-48-1"
bottom: "ReLU-44-1"
top: "_ + _-49-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-50-1_bn"
bottom: "_ + _-49-1"
top: "FixedBatchNormalization-50-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-50-1"
bottom: "FixedBatchNormalization-50-1_bn"
top: "FixedBatchNormalization-50-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-51-1"
bottom: "FixedBatchNormalization-50-1"
top: "ReLU-51-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-52-1"
bottom: "ReLU-51-1"
top: "Convolution2DFunction-52-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-53-1_bn"
bottom: "Convolution2DFunction-52-1"
top: "FixedBatchNormalization-53-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-53-1"
bottom: "FixedBatchNormalization-53-1_bn"
top: "FixedBatchNormalization-53-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-54-1"
bottom: "FixedBatchNormalization-53-1"
top: "ReLU-54-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-55-1"
bottom: "ReLU-54-1"
top: "Convolution2DFunction-55-1"
convolution_param {
num_output: 320
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-56-1"
bottom: "Convolution2DFunction-55-1"
bottom: "ReLU-51-1"
top: "_ + _-56-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-57-1_bn"
bottom: "_ + _-56-1"
top: "FixedBatchNormalization-57-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-57-1"
bottom: "FixedBatchNormalization-57-1_bn"
top: "FixedBatchNormalization-57-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-58-1"
bottom: "FixedBatchNormalization-57-1"
top: "ReLU-58-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-59-1"
bottom: "ReLU-58-1"
top: "Convolution2DFunction-59-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 0
pad_h: 0
stride_w: 2
stride_h: 2
kernel_w: 1
kernel_h: 1
}
}
layer {
type: "Convolution"
name: "Convolution2DFunction-59-2"
bottom: "ReLU-58-1"
top: "Convolution2DFunction-59-2"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 2
stride_h: 2
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-60-1_bn"
bottom: "Convolution2DFunction-59-2"
top: "FixedBatchNormalization-60-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-60-1"
bottom: "FixedBatchNormalization-60-1_bn"
top: "FixedBatchNormalization-60-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-61-1"
bottom: "FixedBatchNormalization-60-1"
top: "ReLU-61-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-62-1"
bottom: "ReLU-61-1"
top: "Convolution2DFunction-62-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-63-1"
bottom: "Convolution2DFunction-62-1"
bottom: "Convolution2DFunction-59-1"
top: "_ + _-63-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-64-1_bn"
bottom: "_ + _-63-1"
top: "FixedBatchNormalization-64-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-64-1"
bottom: "FixedBatchNormalization-64-1_bn"
top: "FixedBatchNormalization-64-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-65-1"
bottom: "FixedBatchNormalization-64-1"
top: "ReLU-65-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-66-1"
bottom: "ReLU-65-1"
top: "Convolution2DFunction-66-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-67-1_bn"
bottom: "Convolution2DFunction-66-1"
top: "FixedBatchNormalization-67-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-67-1"
bottom: "FixedBatchNormalization-67-1_bn"
top: "FixedBatchNormalization-67-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-68-1"
bottom: "FixedBatchNormalization-67-1"
top: "ReLU-68-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-69-1"
bottom: "ReLU-68-1"
top: "Convolution2DFunction-69-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-70-1"
bottom: "Convolution2DFunction-69-1"
bottom: "ReLU-65-1"
top: "_ + _-70-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-71-1_bn"
bottom: "_ + _-70-1"
top: "FixedBatchNormalization-71-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-71-1"
bottom: "FixedBatchNormalization-71-1_bn"
top: "FixedBatchNormalization-71-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-72-1"
bottom: "FixedBatchNormalization-71-1"
top: "ReLU-72-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-73-1"
bottom: "ReLU-72-1"
top: "Convolution2DFunction-73-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-74-1_bn"
bottom: "Convolution2DFunction-73-1"
top: "FixedBatchNormalization-74-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-74-1"
bottom: "FixedBatchNormalization-74-1_bn"
top: "FixedBatchNormalization-74-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-75-1"
bottom: "FixedBatchNormalization-74-1"
top: "ReLU-75-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-76-1"
bottom: "ReLU-75-1"
top: "Convolution2DFunction-76-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-77-1"
bottom: "Convolution2DFunction-76-1"
bottom: "ReLU-72-1"
top: "_ + _-77-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-78-1_bn"
bottom: "_ + _-77-1"
top: "FixedBatchNormalization-78-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-78-1"
bottom: "FixedBatchNormalization-78-1_bn"
top: "FixedBatchNormalization-78-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-79-1"
bottom: "FixedBatchNormalization-78-1"
top: "ReLU-79-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-80-1"
bottom: "ReLU-79-1"
top: "Convolution2DFunction-80-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-81-1_bn"
bottom: "Convolution2DFunction-80-1"
top: "FixedBatchNormalization-81-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-81-1"
bottom: "FixedBatchNormalization-81-1_bn"
top: "FixedBatchNormalization-81-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-82-1"
bottom: "FixedBatchNormalization-81-1"
top: "ReLU-82-1"
}
layer {
type: "Convolution"
name: "Convolution2DFunction-83-1"
bottom: "ReLU-82-1"
top: "Convolution2DFunction-83-1"
convolution_param {
num_output: 640
bias_term: false
pad_w: 1
pad_h: 1
stride_w: 1
stride_h: 1
kernel_w: 3
kernel_h: 3
}
}
layer {
type: "Eltwise"
name: "_ + _-84-1"
bottom: "Convolution2DFunction-83-1"
bottom: "ReLU-79-1"
top: "_ + _-84-1"
}
layer {
type: "BatchNorm"
name: "FixedBatchNormalization-85-1_bn"
bottom: "_ + _-84-1"
top: "FixedBatchNormalization-85-1_bn"
batch_norm_param {
use_global_stats: true
eps: 2e-05
}
}
layer {
type: "Scale"
name: "FixedBatchNormalization-85-1"
bottom: "FixedBatchNormalization-85-1_bn"
top: "FixedBatchNormalization-85-1"
scale_param {
axis: 1
bias_term: true
}
}
layer {
type: "ReLU"
name: "ReLU-86-1"
bottom: "FixedBatchNormalization-85-1"
top: "ReLU-86-1"
}
layer {
type: "Pooling"
name: "AveragePooling2D-87-1"
bottom: "ReLU-86-1"
top: "AveragePooling2D-87-1"
pooling_param {
pool: AVE
pad_w: 0
pad_h: 0
stride_w: 8
stride_h: 8
kernel_w: 8
kernel_h: 8
}
}
layer {
type: "Reshape"
name: "Reshape-88-1"
bottom: "AveragePooling2D-87-1"
top: "Reshape-88-1"
reshape_param {
shape {
dim: 1
dim: -1
}
}
}
layer {
type: "InnerProduct"
name: "LinearFunction-89-1"
bottom: "Reshape-88-1"
top: "LinearFunction-89-1"
inner_product_param {
num_output: 10
bias_term: true
}
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment