Created
June 23, 2016 12:42
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name: "LogReg" | |
input: "data" | |
input_dim: 1 | |
input_dim: 2 | |
input_dim: 19 | |
input_dim: 19 | |
#this part should be the same in learning and prediction network | |
layers { | |
name: "conv1_7x7_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "data" | |
top: "conv2" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 7 | |
pad: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu2" | |
type: RELU | |
bottom: "conv2" | |
top: "conv2" | |
} | |
layers { | |
name: "conv2_5x5_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv2" | |
top: "conv3" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 5 | |
pad: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu3" | |
type: RELU | |
bottom: "conv3" | |
top: "conv3" | |
} | |
layers { | |
name: "conv3_5x5_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv3" | |
top: "conv4" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 5 | |
pad: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu4" | |
type: RELU | |
bottom: "conv4" | |
top: "conv4" | |
} | |
layers { | |
name: "conv4_5x5_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv4" | |
top: "conv5" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 5 | |
pad: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu5" | |
type: RELU | |
bottom: "conv5" | |
top: "conv5" | |
} | |
layers { | |
name: "conv5_5x5_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv5" | |
top: "conv6" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 5 | |
pad: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu6" | |
type: RELU | |
bottom: "conv6" | |
top: "conv6" | |
} | |
layers { | |
name: "conv6_5x5_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv6" | |
top: "conv7" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 5 | |
pad: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu7" | |
type: RELU | |
bottom: "conv7" | |
top: "conv7" | |
} | |
layers { | |
name: "conv7_5x5_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv7" | |
top: "conv8" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 5 | |
pad: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu8" | |
type: RELU | |
bottom: "conv8" | |
top: "conv8" | |
} | |
layers { | |
name: "conv8_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv8" | |
top: "conv9" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu9" | |
type: RELU | |
bottom: "conv9" | |
top: "conv9" | |
} | |
layers { | |
name: "conv9_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv9" | |
top: "conv10" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu10" | |
type: RELU | |
bottom: "conv10" | |
top: "conv10" | |
} | |
layers { | |
name: "conv10_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv10" | |
top: "conv11" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu11" | |
type: RELU | |
bottom: "conv11" | |
top: "conv11" | |
} | |
layers { | |
name: "conv11_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv11" | |
top: "conv12" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu12" | |
type: RELU | |
bottom: "conv12" | |
top: "conv12" | |
} | |
layers { | |
name: "conv12_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv12" | |
top: "conv13" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu13" | |
type: RELU | |
bottom: "conv13" | |
top: "conv13" | |
} | |
layers { | |
name: "conv13_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv13" | |
top: "conv14" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu14" | |
type: RELU | |
bottom: "conv14" | |
top: "conv14" | |
} | |
layers { | |
name: "conv14_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv14" | |
top: "conv15" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu15" | |
type: RELU | |
bottom: "conv15" | |
top: "conv15" | |
} | |
layers { | |
name: "conv15_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv15" | |
top: "conv16" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu16" | |
type: RELU | |
bottom: "conv16" | |
top: "conv16" | |
} | |
layers { | |
name: "conv16_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv16" | |
top: "conv17" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu17" | |
type: RELU | |
bottom: "conv17" | |
top: "conv17" | |
} | |
layers { | |
name: "conv17_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv17" | |
top: "conv18" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu18" | |
type: RELU | |
bottom: "conv18" | |
top: "conv18" | |
} | |
layers { | |
name: "conv18_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv18" | |
top: "conv19" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu19" | |
type: RELU | |
bottom: "conv19" | |
top: "conv19" | |
} | |
layers { | |
name: "conv19_3x3_128" | |
type: CONVOLUTION | |
blobs_lr: 1.0 | |
blobs_lr: 2.0 | |
bottom: "conv19" | |
top: "conv20" | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layers { | |
name: "relu20" | |
type: RELU | |
bottom: "conv20" | |
top: "conv20" | |
} | |
layers { | |
name: "ip" | |
type: INNER_PRODUCT | |
bottom: "conv20" | |
# I had to comment out that line to make it work | |
#top: "ip_zw" | |
inner_product_param { | |
num_output: 361 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
#layers { | |
# name: "flat" | |
# type: FLATTEN | |
# bottom: "conv8" | |
# top: "ip_zw" | |
#} | |
#only prediction | |
layers { | |
name: "softmax" | |
type: SOFTMAX | |
bottom: "ip_zw" | |
top: "ip" | |
} |
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