Created
December 1, 2016 16:53
-
-
Save chuckcho/7d78212896951f558407386dbf489089 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
name: "c3d_ucf101" | |
input: "data" | |
input_shape { | |
dim: 1 | |
dim: 3 | |
dim: 16 | |
dim: 112 | |
dim: 112 | |
} | |
# ----- 1st group ----- | |
layer { | |
name: "conv1a" | |
type: "NdConvolution" | |
bottom: "data" | |
top: "conv1a" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_shape { dim: 3 dim: 3 dim: 3 } | |
stride_shape { dim: 1 dim: 1 dim: 1 } | |
pad_shape { dim: 1 dim: 1 dim: 1 } | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1a" | |
type: "ReLU" | |
bottom: "conv1a" | |
top: "conv1a-relu" | |
} | |
layer { | |
name: "pool1" | |
type: "NdPooling" | |
bottom: "conv1a-relu" | |
top: "pool1" | |
pooling_param { | |
pool: MAX | |
kernel_shape { dim: 1 dim: 2 dim: 2 } | |
stride_shape { dim: 1 dim: 2 dim: 2 } | |
} | |
} | |
# ----- 2nd group ----- | |
layer { | |
name: "conv2a" | |
type: "NdConvolution" | |
bottom: "pool1" | |
top: "conv2a" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_shape { dim: 3 dim: 3 dim: 3 } | |
stride_shape { dim: 1 dim: 1 dim: 1 } | |
pad_shape { dim: 1 dim: 1 dim: 1 } | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layer { | |
name: "relu2a" | |
type: "ReLU" | |
bottom: "conv2a" | |
top: "conv2a-relu" | |
} | |
layer { | |
name: "pool2" | |
type: "NdPooling" | |
bottom: "conv2a-relu" | |
top: "pool2" | |
pooling_param { | |
pool: MAX | |
kernel_shape { dim: 2 dim: 2 dim: 2 } | |
stride_shape { dim: 2 dim: 2 dim: 2 } | |
} | |
} | |
# ----- 3rd group ----- | |
layer { | |
name: "conv3a" | |
type: "NdConvolution" | |
bottom: "pool2" | |
top: "conv3a" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_shape { dim: 3 dim: 3 dim: 3 } | |
stride_shape { dim: 1 dim: 1 dim: 1 } | |
pad_shape { dim: 1 dim: 1 dim: 1 } | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layer { | |
name: "relu3a" | |
type: "ReLU" | |
bottom: "conv3a" | |
top: "conv3a-relu" | |
} | |
layer { | |
name: "pool3" | |
type: "NdPooling" | |
bottom: "conv3a-relu" | |
top: "pool3" | |
pooling_param { | |
pool: MAX | |
kernel_shape { dim: 2 dim: 2 dim: 2 } | |
stride_shape { dim: 2 dim: 2 dim: 2 } | |
} | |
} | |
# ----- 4th group ----- | |
layer { | |
name: "conv4a" | |
type: "NdConvolution" | |
bottom: "pool3" | |
top: "conv4a" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_shape { dim: 3 dim: 3 dim: 3 } | |
stride_shape { dim: 1 dim: 1 dim: 1 } | |
pad_shape { dim: 1 dim: 1 dim: 1 } | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layer { | |
name: "relu4a" | |
type: "ReLU" | |
bottom: "conv4a" | |
top: "conv4a-relu" | |
} | |
layer { | |
name: "pool4" | |
type: "NdPooling" | |
bottom: "conv4a-relu" | |
top: "pool4" | |
pooling_param { | |
pool: MAX | |
kernel_shape { dim: 2 dim: 2 dim: 2 } | |
stride_shape { dim: 2 dim: 2 dim: 2 } | |
} | |
} | |
# ----- 5th group ----- | |
layer { | |
name: "conv5a" | |
type: "NdConvolution" | |
bottom: "pool4" | |
top: "conv5a" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_shape { dim: 3 dim: 3 dim: 3 } | |
stride_shape { dim: 1 dim: 1 dim: 1 } | |
pad_shape { dim: 1 dim: 1 dim: 1 } | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layer { | |
name: "relu5a" | |
type: "ReLU" | |
bottom: "conv5a" | |
top: "conv5a-relu" | |
} | |
layer { | |
name: "pool5" | |
type: "NdPooling" | |
bottom: "conv5a-relu" | |
top: "pool5" | |
pooling_param { | |
pool: MAX | |
kernel_shape { dim: 2 dim: 2 dim: 2 } | |
stride_shape { dim: 2 dim: 2 dim: 2 } | |
} | |
} | |
# ----- 1st fc group ----- | |
layer { | |
name: "fc6" | |
type: "InnerProduct" | |
bottom: "pool5" | |
top: "fc6" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 2048 | |
weight_filler { | |
type: "gaussian" | |
std: 0.005 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layer { | |
name: "relu6" | |
type: "ReLU" | |
bottom: "fc6" | |
top: "fc6-relu" | |
} | |
layer { | |
name: "drop6" | |
type: "Dropout" | |
bottom: "fc6-relu" | |
top: "fc6-drop" | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
# ----- 2nd fc group ----- | |
layer { | |
name: "fc7" | |
type: "InnerProduct" | |
bottom: "fc6-drop" | |
top: "fc7" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 2048 | |
weight_filler { | |
type: "gaussian" | |
std: 0.005 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layer { | |
name: "relu7" | |
type: "ReLU" | |
bottom: "fc7" | |
top: "fc7-relu" | |
} | |
layer { | |
name: "drop7" | |
type: "Dropout" | |
bottom: "fc7-relu" | |
top: "fc7-drop" | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
# ----- 3rd fc group ----- | |
layer { | |
name: "fc8" | |
type: "InnerProduct" | |
bottom: "fc7-drop" | |
top: "fc8" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 101 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "prob" | |
type: "Softmax" | |
bottom: "fc8" | |
top: "prob" | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment