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| name: "FractalNet-34" | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 224 | |
| input_dim: 224 | |
| # Input size: 32 | |
| layer { | |
| bottom: "data" | |
| top: "conv2_0" | |
| name: "conv2_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_0" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_0_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_0" | |
| type: "Dropout" | |
| bottom: "conv2_0" | |
| top: "conv2_0" | |
| dropout_param { | |
| dropout_ratio: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_0" | |
| type: "BatchNorm" | |
| bottom: "conv2_0" | |
| top: "conv2_0" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_0" | |
| type: "ReLU" | |
| bottom: "conv2_0" | |
| top: "conv2_0" | |
| } | |
| layer { | |
| bottom: "conv2_0" | |
| top: "conv2_1" | |
| name: "conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_1" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_1_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_1" | |
| type: "Dropout" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| dropout_param { | |
| dropout_ratio: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_1" | |
| type: "BatchNorm" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_1" | |
| type: "ReLU" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| } | |
| layer { | |
| bottom: "data" | |
| top: "conv1_0" | |
| name: "conv1_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_0" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_0_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_0" | |
| type: "Dropout" | |
| bottom: "conv1_0" | |
| top: "conv1_0" | |
| dropout_param { | |
| dropout_ratio: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_0" | |
| type: "BatchNorm" | |
| bottom: "conv1_0" | |
| top: "conv1_0" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_0" | |
| type: "ReLU" | |
| bottom: "conv1_0" | |
| top: "conv1_0" | |
| } | |
| layer { | |
| name: "join_conv2_1_plus" | |
| type: "Concat" | |
| bottom: "conv1_0" | |
| bottom: "conv2_1" | |
| top: "conv2_1_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_1_plus" | |
| top: "conv2_2" | |
| name: "conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_2" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_2_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_2" | |
| type: "Dropout" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| dropout_param { | |
| dropout_ratio: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_2" | |
| type: "BatchNorm" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_2" | |
| type: "ReLU" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| } | |
| layer { | |
| bottom: "conv2_2" | |
| top: "conv2_3" | |
| name: "conv2_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_3" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_3_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_3" | |
| type: "Dropout" | |
| bottom: "conv2_3" | |
| top: "conv2_3" | |
| dropout_param { | |
| dropout_ratio: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_3" | |
| type: "BatchNorm" | |
| bottom: "conv2_3" | |
| top: "conv2_3" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_3" | |
| type: "ReLU" | |
| bottom: "conv2_3" | |
| top: "conv2_3" | |
| } | |
| layer { | |
| bottom: "conv2_1_plus" | |
| top: "conv1_1" | |
| name: "conv1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_1" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_1_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_1" | |
| type: "Dropout" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| dropout_param { | |
| dropout_ratio: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_1" | |
| type: "BatchNorm" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_1" | |
| type: "ReLU" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| } | |
| layer { | |
| bottom: "data" | |
| top: "conv0_0" | |
| name: "conv0_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv0_0" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv0_0_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv0_0" | |
| type: "Dropout" | |
| bottom: "conv0_0" | |
| top: "conv0_0" | |
| dropout_param { | |
| dropout_ratio: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv0_0" | |
| type: "BatchNorm" | |
| bottom: "conv0_0" | |
| top: "conv0_0" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv0_0" | |
| type: "ReLU" | |
| bottom: "conv0_0" | |
| top: "conv0_0" | |
| } | |
| layer { | |
| bottom: "conv0_0" | |
| top: "pool0_0" | |
| name: "pool0_0" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1_1" | |
| top: "pool1_1" | |
| name: "pool1_1" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_3" | |
| top: "pool2_3" | |
| name: "pool2_3" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "join_pool2_3_plus" | |
| type: "Concat" | |
| bottom: "pool0_0" | |
| bottom: "pool1_1" | |
| bottom: "pool2_3" | |
| top: "pool2_3_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| # Reduction: 1, spatial size: 16 | |
| layer { | |
| bottom: "pool2_3_plus" | |
| top: "conv2_4" | |
| name: "conv2_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_4" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_4_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_4" | |
| type: "Dropout" | |
| bottom: "conv2_4" | |
| top: "conv2_4" | |
| dropout_param { | |
| dropout_ratio: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_4" | |
| type: "BatchNorm" | |
| bottom: "conv2_4" | |
| top: "conv2_4" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_4" | |
| type: "ReLU" | |
| bottom: "conv2_4" | |
| top: "conv2_4" | |
| } | |
| layer { | |
| bottom: "conv2_4" | |
| top: "conv2_5" | |
| name: "conv2_5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_5" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_5_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_5" | |
| type: "Dropout" | |
| bottom: "conv2_5" | |
| top: "conv2_5" | |
| dropout_param { | |
| dropout_ratio: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_5" | |
| type: "BatchNorm" | |
| bottom: "conv2_5" | |
| top: "conv2_5" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_5" | |
| type: "ReLU" | |
| bottom: "conv2_5" | |
| top: "conv2_5" | |
| } | |
| layer { | |
| bottom: "pool2_3_plus" | |
| top: "conv1_2" | |
| name: "conv1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_2" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_2_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_2" | |
| type: "Dropout" | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| dropout_param { | |
| dropout_ratio: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_2" | |
| type: "BatchNorm" | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_2" | |
| type: "ReLU" | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| } | |
| layer { | |
| name: "join_conv2_5_plus" | |
| type: "Concat" | |
| bottom: "conv1_2" | |
| bottom: "conv2_5" | |
| top: "conv2_5_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_5_plus" | |
| top: "conv2_6" | |
| name: "conv2_6" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_6" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_6_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_6" | |
| type: "Dropout" | |
| bottom: "conv2_6" | |
| top: "conv2_6" | |
| dropout_param { | |
| dropout_ratio: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_6" | |
| type: "BatchNorm" | |
| bottom: "conv2_6" | |
| top: "conv2_6" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_6" | |
| type: "ReLU" | |
| bottom: "conv2_6" | |
| top: "conv2_6" | |
| } | |
| layer { | |
| bottom: "conv2_6" | |
| top: "conv2_7" | |
| name: "conv2_7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_7" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_7_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_7" | |
| type: "Dropout" | |
| bottom: "conv2_7" | |
| top: "conv2_7" | |
| dropout_param { | |
| dropout_ratio: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_7" | |
| type: "BatchNorm" | |
| bottom: "conv2_7" | |
| top: "conv2_7" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_7" | |
| type: "ReLU" | |
| bottom: "conv2_7" | |
| top: "conv2_7" | |
| } | |
| layer { | |
| bottom: "conv2_5_plus" | |
| top: "conv1_3" | |
| name: "conv1_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_3" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_3_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_3" | |
| type: "Dropout" | |
| bottom: "conv1_3" | |
| top: "conv1_3" | |
| dropout_param { | |
| dropout_ratio: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_3" | |
| type: "BatchNorm" | |
| bottom: "conv1_3" | |
| top: "conv1_3" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_3" | |
| type: "ReLU" | |
| bottom: "conv1_3" | |
| top: "conv1_3" | |
| } | |
| layer { | |
| bottom: "pool2_3_plus" | |
| top: "conv0_1" | |
| name: "conv0_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv0_1" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv0_1_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv0_1" | |
| type: "Dropout" | |
| bottom: "conv0_1" | |
| top: "conv0_1" | |
| dropout_param { | |
| dropout_ratio: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv0_1" | |
| type: "BatchNorm" | |
| bottom: "conv0_1" | |
| top: "conv0_1" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv0_1" | |
| type: "ReLU" | |
| bottom: "conv0_1" | |
| top: "conv0_1" | |
| } | |
| layer { | |
| bottom: "conv0_1" | |
| top: "pool0_1" | |
| name: "pool0_1" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1_3" | |
| top: "pool1_3" | |
| name: "pool1_3" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_7" | |
| top: "pool2_7" | |
| name: "pool2_7" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "join_pool2_7_plus" | |
| type: "Concat" | |
| bottom: "pool0_1" | |
| bottom: "pool1_3" | |
| bottom: "pool2_7" | |
| top: "pool2_7_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| # Reduction: 2, spatial size: 8 | |
| layer { | |
| bottom: "pool2_7_plus" | |
| top: "conv2_8" | |
| name: "conv2_8" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_8" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_8_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_8" | |
| type: "Dropout" | |
| bottom: "conv2_8" | |
| top: "conv2_8" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_8" | |
| type: "BatchNorm" | |
| bottom: "conv2_8" | |
| top: "conv2_8" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_8" | |
| type: "ReLU" | |
| bottom: "conv2_8" | |
| top: "conv2_8" | |
| } | |
| layer { | |
| bottom: "conv2_8" | |
| top: "conv2_9" | |
| name: "conv2_9" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_9" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_9_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_9" | |
| type: "Dropout" | |
| bottom: "conv2_9" | |
| top: "conv2_9" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_9" | |
| type: "BatchNorm" | |
| bottom: "conv2_9" | |
| top: "conv2_9" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_9" | |
| type: "ReLU" | |
| bottom: "conv2_9" | |
| top: "conv2_9" | |
| } | |
| layer { | |
| bottom: "pool2_7_plus" | |
| top: "conv1_4" | |
| name: "conv1_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_4" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_4_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_4" | |
| type: "Dropout" | |
| bottom: "conv1_4" | |
| top: "conv1_4" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_4" | |
| type: "BatchNorm" | |
| bottom: "conv1_4" | |
| top: "conv1_4" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_4" | |
| type: "ReLU" | |
| bottom: "conv1_4" | |
| top: "conv1_4" | |
| } | |
| layer { | |
| name: "join_conv2_9_plus" | |
| type: "Concat" | |
| bottom: "conv1_4" | |
| bottom: "conv2_9" | |
| top: "conv2_9_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_9_plus" | |
| top: "conv2_10" | |
| name: "conv2_10" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_10" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_10_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_10" | |
| type: "Dropout" | |
| bottom: "conv2_10" | |
| top: "conv2_10" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_10" | |
| type: "BatchNorm" | |
| bottom: "conv2_10" | |
| top: "conv2_10" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_10" | |
| type: "ReLU" | |
| bottom: "conv2_10" | |
| top: "conv2_10" | |
| } | |
| layer { | |
| bottom: "conv2_10" | |
| top: "conv2_11" | |
| name: "conv2_11" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_11" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_11_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_11" | |
| type: "Dropout" | |
| bottom: "conv2_11" | |
| top: "conv2_11" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_11" | |
| type: "BatchNorm" | |
| bottom: "conv2_11" | |
| top: "conv2_11" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_11" | |
| type: "ReLU" | |
| bottom: "conv2_11" | |
| top: "conv2_11" | |
| } | |
| layer { | |
| bottom: "conv2_9_plus" | |
| top: "conv1_5" | |
| name: "conv1_5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_5" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_5_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_5" | |
| type: "Dropout" | |
| bottom: "conv1_5" | |
| top: "conv1_5" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_5" | |
| type: "BatchNorm" | |
| bottom: "conv1_5" | |
| top: "conv1_5" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_5" | |
| type: "ReLU" | |
| bottom: "conv1_5" | |
| top: "conv1_5" | |
| } | |
| layer { | |
| bottom: "pool2_7_plus" | |
| top: "conv0_2" | |
| name: "conv0_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv0_2" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv0_2_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv0_2" | |
| type: "Dropout" | |
| bottom: "conv0_2" | |
| top: "conv0_2" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv0_2" | |
| type: "BatchNorm" | |
| bottom: "conv0_2" | |
| top: "conv0_2" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv0_2" | |
| type: "ReLU" | |
| bottom: "conv0_2" | |
| top: "conv0_2" | |
| } | |
| layer { | |
| bottom: "conv0_2" | |
| top: "pool0_2" | |
| name: "pool0_2" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1_5" | |
| top: "pool1_5" | |
| name: "pool1_5" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_11" | |
| top: "pool2_11" | |
| name: "pool2_11" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "join_pool2_11_plus" | |
| type: "Concat" | |
| bottom: "pool0_2" | |
| bottom: "pool1_5" | |
| bottom: "pool2_11" | |
| top: "pool2_11_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| # Reduction: 3, spatial size: 4 | |
| layer { | |
| bottom: "pool2_11_plus" | |
| top: "conv2_12" | |
| name: "conv2_12" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_12" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_12_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_12" | |
| type: "Dropout" | |
| bottom: "conv2_12" | |
| top: "conv2_12" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_12" | |
| type: "BatchNorm" | |
| bottom: "conv2_12" | |
| top: "conv2_12" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_12" | |
| type: "ReLU" | |
| bottom: "conv2_12" | |
| top: "conv2_12" | |
| } | |
| layer { | |
| bottom: "conv2_12" | |
| top: "conv2_13" | |
| name: "conv2_13" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_13" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_13_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_13" | |
| type: "Dropout" | |
| bottom: "conv2_13" | |
| top: "conv2_13" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_13" | |
| type: "BatchNorm" | |
| bottom: "conv2_13" | |
| top: "conv2_13" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_13" | |
| type: "ReLU" | |
| bottom: "conv2_13" | |
| top: "conv2_13" | |
| } | |
| layer { | |
| bottom: "pool2_11_plus" | |
| top: "conv1_6" | |
| name: "conv1_6" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_6" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_6_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_6" | |
| type: "Dropout" | |
| bottom: "conv1_6" | |
| top: "conv1_6" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_6" | |
| type: "BatchNorm" | |
| bottom: "conv1_6" | |
| top: "conv1_6" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_6" | |
| type: "ReLU" | |
| bottom: "conv1_6" | |
| top: "conv1_6" | |
| } | |
| layer { | |
| name: "join_conv2_13_plus" | |
| type: "Concat" | |
| bottom: "conv1_6" | |
| bottom: "conv2_13" | |
| top: "conv2_13_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_13_plus" | |
| top: "conv2_14" | |
| name: "conv2_14" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_14" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_14_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_14" | |
| type: "Dropout" | |
| bottom: "conv2_14" | |
| top: "conv2_14" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_14" | |
| type: "BatchNorm" | |
| bottom: "conv2_14" | |
| top: "conv2_14" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_14" | |
| type: "ReLU" | |
| bottom: "conv2_14" | |
| top: "conv2_14" | |
| } | |
| layer { | |
| bottom: "conv2_14" | |
| top: "conv2_15" | |
| name: "conv2_15" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_15" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_15_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_15" | |
| type: "Dropout" | |
| bottom: "conv2_15" | |
| top: "conv2_15" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_15" | |
| type: "BatchNorm" | |
| bottom: "conv2_15" | |
| top: "conv2_15" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_15" | |
| type: "ReLU" | |
| bottom: "conv2_15" | |
| top: "conv2_15" | |
| } | |
| layer { | |
| bottom: "conv2_13_plus" | |
| top: "conv1_7" | |
| name: "conv1_7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_7" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_7_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_7" | |
| type: "Dropout" | |
| bottom: "conv1_7" | |
| top: "conv1_7" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_7" | |
| type: "BatchNorm" | |
| bottom: "conv1_7" | |
| top: "conv1_7" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_7" | |
| type: "ReLU" | |
| bottom: "conv1_7" | |
| top: "conv1_7" | |
| } | |
| layer { | |
| bottom: "pool2_11_plus" | |
| top: "conv0_3" | |
| name: "conv0_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv0_3" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv0_3_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv0_3" | |
| type: "Dropout" | |
| bottom: "conv0_3" | |
| top: "conv0_3" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv0_3" | |
| type: "BatchNorm" | |
| bottom: "conv0_3" | |
| top: "conv0_3" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv0_3" | |
| type: "ReLU" | |
| bottom: "conv0_3" | |
| top: "conv0_3" | |
| } | |
| layer { | |
| bottom: "conv0_3" | |
| top: "pool0_3" | |
| name: "pool0_3" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1_7" | |
| top: "pool1_7" | |
| name: "pool1_7" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_15" | |
| top: "pool2_15" | |
| name: "pool2_15" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "join_pool2_15_plus" | |
| type: "Concat" | |
| bottom: "pool0_3" | |
| bottom: "pool1_7" | |
| bottom: "pool2_15" | |
| top: "pool2_15_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| # Reduction: 4, spatial size: 2 | |
| layer { | |
| bottom: "pool2_15_plus" | |
| top: "conv2_16" | |
| name: "conv2_16" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_16" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_16_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_16" | |
| type: "Dropout" | |
| bottom: "conv2_16" | |
| top: "conv2_16" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_16" | |
| type: "BatchNorm" | |
| bottom: "conv2_16" | |
| top: "conv2_16" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_16" | |
| type: "ReLU" | |
| bottom: "conv2_16" | |
| top: "conv2_16" | |
| } | |
| layer { | |
| bottom: "conv2_16" | |
| top: "conv2_17" | |
| name: "conv2_17" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_17" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_17_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_17" | |
| type: "Dropout" | |
| bottom: "conv2_17" | |
| top: "conv2_17" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_17" | |
| type: "BatchNorm" | |
| bottom: "conv2_17" | |
| top: "conv2_17" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_17" | |
| type: "ReLU" | |
| bottom: "conv2_17" | |
| top: "conv2_17" | |
| } | |
| layer { | |
| bottom: "pool2_15_plus" | |
| top: "conv1_8" | |
| name: "conv1_8" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_8" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_8_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_8" | |
| type: "Dropout" | |
| bottom: "conv1_8" | |
| top: "conv1_8" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_8" | |
| type: "BatchNorm" | |
| bottom: "conv1_8" | |
| top: "conv1_8" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_8" | |
| type: "ReLU" | |
| bottom: "conv1_8" | |
| top: "conv1_8" | |
| } | |
| layer { | |
| name: "join_conv2_17_plus" | |
| type: "Concat" | |
| bottom: "conv1_8" | |
| bottom: "conv2_17" | |
| top: "conv2_17_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_17_plus" | |
| top: "conv2_18" | |
| name: "conv2_18" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_18" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_18_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_18" | |
| type: "Dropout" | |
| bottom: "conv2_18" | |
| top: "conv2_18" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_18" | |
| type: "BatchNorm" | |
| bottom: "conv2_18" | |
| top: "conv2_18" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_18" | |
| type: "ReLU" | |
| bottom: "conv2_18" | |
| top: "conv2_18" | |
| } | |
| layer { | |
| bottom: "conv2_18" | |
| top: "conv2_19" | |
| name: "conv2_19" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv2_19" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv2_19_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv2_19" | |
| type: "Dropout" | |
| bottom: "conv2_19" | |
| top: "conv2_19" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv2_19" | |
| type: "BatchNorm" | |
| bottom: "conv2_19" | |
| top: "conv2_19" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv2_19" | |
| type: "ReLU" | |
| bottom: "conv2_19" | |
| top: "conv2_19" | |
| } | |
| layer { | |
| bottom: "conv2_17_plus" | |
| top: "conv1_9" | |
| name: "conv1_9" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv1_9" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv1_9_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv1_9" | |
| type: "Dropout" | |
| bottom: "conv1_9" | |
| top: "conv1_9" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv1_9" | |
| type: "BatchNorm" | |
| bottom: "conv1_9" | |
| top: "conv1_9" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv1_9" | |
| type: "ReLU" | |
| bottom: "conv1_9" | |
| top: "conv1_9" | |
| } | |
| layer { | |
| bottom: "pool2_15_plus" | |
| top: "conv0_4" | |
| name: "conv0_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "conv0_4" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "conv0_4_b" | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "dropout_conv0_4" | |
| type: "Dropout" | |
| bottom: "conv0_4" | |
| top: "conv0_4" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "batch_conv0_4" | |
| type: "BatchNorm" | |
| bottom: "conv0_4" | |
| top: "conv0_4" | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| param { lr_mult: 0 } | |
| } | |
| layer { | |
| name: "relu_conv0_4" | |
| type: "ReLU" | |
| bottom: "conv0_4" | |
| top: "conv0_4" | |
| } | |
| layer { | |
| bottom: "conv0_4" | |
| top: "pool0_4" | |
| name: "pool0_4" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1_9" | |
| top: "pool1_9" | |
| name: "pool1_9" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_19" | |
| top: "pool2_19" | |
| name: "pool2_19" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "join_pool2_19_plus" | |
| type: "Concat" | |
| bottom: "pool0_4" | |
| bottom: "pool1_9" | |
| bottom: "pool2_19" | |
| top: "pool2_19_plus" | |
| fractal_join_param { | |
| drop_path_ratio: 0.15 | |
| } | |
| } | |
| # Reduction: 5, spatial size: 1 | |
| layer { | |
| name: "prediction0" | |
| type: "InnerProduct" | |
| bottom: "pool2_19_plus" | |
| top: "prediction0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| name: "prediction0" | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| name: "prediction0_b" | |
| } | |
| inner_product_param { | |
| num_output: 10 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss0" | |
| type: "SoftmaxWithLoss" | |
| bottom: "prediction0" | |
| bottom: "label" | |
| top: "loss0" | |
| loss_weight: 1.0 | |
| include: { phase: TRAIN } | |
| } | |
| layer { | |
| name: "accuracy_loss0" | |
| type: "Accuracy" | |
| bottom: "prediction0" | |
| bottom: "label" | |
| top: "accuracy_loss0" | |
| include: { phase: TEST } | |
| } |
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This prototxt is incorrect. As FractalNet uses some custom layers that aren't available yet in netscope, I replaced them just for visualization, like "FractalJoin" by "Concat".