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| # refer: https://github.com/TimoSaemann/ENet/blob/master/prototxts/enet_train_encoder.prototxt | |
| # graph: http://ethereon.github.io/netscope/#/gist/ccac19b9c4f5cb39d76495e32e964bdf | |
| name: "ENet" | |
| layer { | |
| name: "data" | |
| type: "DenseImageData" | |
| top: "data" | |
| top: "label" | |
| dense_image_data_param { | |
| source: "ENet/dataset/train_fine_2columns.txt" | |
| batch_size: 4 | |
| shuffle: true | |
| new_height: 512 | |
| new_width: 1024 | |
| label_divide_factor: 8 | |
| } | |
| } | |
| layer { | |
| name: "conv0_1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv0_1" | |
| convolution_param { | |
| num_output: 13 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "pool0_1" | |
| type: "Pooling" | |
| bottom: "data" | |
| top: "pool0_1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "concat0_1" | |
| type: "Concat" | |
| bottom: "conv0_1" | |
| bottom: "pool0_1" | |
| top: "concat0_1" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "bn0_1" | |
| type: "BN" | |
| bottom: "concat0_1" | |
| top: "bn0_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu0_1" | |
| type: "PReLU" | |
| bottom: "bn0_1" | |
| top: "prelu0_1" | |
| } | |
| layer { | |
| name: "conv1_0_0" | |
| type: "Convolution" | |
| bottom: "prelu0_1" | |
| top: "conv1_0_0" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 2 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_0_0" | |
| type: "BN" | |
| bottom: "conv1_0_0" | |
| top: "bn1_0_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_0_0" | |
| type: "PReLU" | |
| bottom: "bn1_0_0" | |
| top: "prelu1_0_0" | |
| } | |
| layer { | |
| name: "conv1_0_1" | |
| type: "Convolution" | |
| bottom: "prelu1_0_0" | |
| top: "conv1_0_1" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_0_1" | |
| type: "BN" | |
| bottom: "conv1_0_1" | |
| top: "bn1_0_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_0_1" | |
| type: "PReLU" | |
| bottom: "bn1_0_1" | |
| top: "prelu1_0_1" | |
| } | |
| layer { | |
| name: "conv1_0_2" | |
| type: "Convolution" | |
| bottom: "prelu1_0_1" | |
| top: "conv1_0_2" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_0_2" | |
| type: "BN" | |
| bottom: "conv1_0_2" | |
| top: "bn1_0_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop1_0_3" | |
| type: "Python" | |
| bottom: "bn1_0_2" | |
| top: "drop1_0_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.01\'}" | |
| } | |
| } | |
| layer { | |
| name: "pool1_0_4" | |
| type: "Pooling" | |
| bottom: "prelu0_1" | |
| top: "pool1_0_4" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv1_0_4" | |
| type: "Convolution" | |
| bottom: "pool1_0_4" | |
| top: "conv1_0_4" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_0_4" | |
| type: "BN" | |
| bottom: "conv1_0_4" | |
| top: "bn1_0_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "eltwise1_0_4" | |
| type: "Eltwise" | |
| bottom: "drop1_0_3" | |
| bottom: "bn1_0_4" | |
| top: "eltwise1_0_4" | |
| } | |
| layer { | |
| name: "prelu1_0_4" | |
| type: "PReLU" | |
| bottom: "eltwise1_0_4" | |
| top: "prelu1_0_4" | |
| } | |
| layer { | |
| name: "conv1_1_0" | |
| type: "Convolution" | |
| bottom: "prelu1_0_4" | |
| top: "conv1_1_0" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_1_0" | |
| type: "BN" | |
| bottom: "conv1_1_0" | |
| top: "bn1_1_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_1_0" | |
| type: "PReLU" | |
| bottom: "bn1_1_0" | |
| top: "prelu1_1_0" | |
| } | |
| layer { | |
| name: "conv1_1_1" | |
| type: "Convolution" | |
| bottom: "prelu1_1_0" | |
| top: "conv1_1_1" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_1_1" | |
| type: "BN" | |
| bottom: "conv1_1_1" | |
| top: "bn1_1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_1_1" | |
| type: "PReLU" | |
| bottom: "bn1_1_1" | |
| top: "prelu1_1_1" | |
| } | |
| layer { | |
| name: "conv1_1_2" | |
| type: "Convolution" | |
| bottom: "prelu1_1_1" | |
| top: "conv1_1_2" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_1_2" | |
| type: "BN" | |
| bottom: "conv1_1_2" | |
| top: "bn1_1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop1_1_3" | |
| type: "Python" | |
| bottom: "bn1_1_2" | |
| top: "drop1_1_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.01\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise1_1_4" | |
| type: "Eltwise" | |
| bottom: "drop1_1_3" | |
| bottom: "prelu1_0_4" | |
| top: "eltwise1_1_4" | |
| } | |
| layer { | |
| name: "prelu1_1_4" | |
| type: "PReLU" | |
| bottom: "eltwise1_1_4" | |
| top: "prelu1_1_4" | |
| } | |
| layer { | |
| name: "conv1_2_0" | |
| type: "Convolution" | |
| bottom: "prelu1_1_4" | |
| top: "conv1_2_0" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_2_0" | |
| type: "BN" | |
| bottom: "conv1_2_0" | |
| top: "bn1_2_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_2_0" | |
| type: "PReLU" | |
| bottom: "bn1_2_0" | |
| top: "prelu1_2_0" | |
| } | |
| layer { | |
| name: "conv1_2_1" | |
| type: "Convolution" | |
| bottom: "prelu1_2_0" | |
| top: "conv1_2_1" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_2_1" | |
| type: "BN" | |
| bottom: "conv1_2_1" | |
| top: "bn1_2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_2_1" | |
| type: "PReLU" | |
| bottom: "bn1_2_1" | |
| top: "prelu1_2_1" | |
| } | |
| layer { | |
| name: "conv1_2_2" | |
| type: "Convolution" | |
| bottom: "prelu1_2_1" | |
| top: "conv1_2_2" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_2_2" | |
| type: "BN" | |
| bottom: "conv1_2_2" | |
| top: "bn1_2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop1_2_3" | |
| type: "Python" | |
| bottom: "bn1_2_2" | |
| top: "drop1_2_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.01\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise1_2_4" | |
| type: "Eltwise" | |
| bottom: "drop1_2_3" | |
| bottom: "prelu1_1_4" | |
| top: "eltwise1_2_4" | |
| } | |
| layer { | |
| name: "prelu1_2_4" | |
| type: "PReLU" | |
| bottom: "eltwise1_2_4" | |
| top: "prelu1_2_4" | |
| } | |
| layer { | |
| name: "conv1_3_0" | |
| type: "Convolution" | |
| bottom: "prelu1_2_4" | |
| top: "conv1_3_0" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_3_0" | |
| type: "BN" | |
| bottom: "conv1_3_0" | |
| top: "bn1_3_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_3_0" | |
| type: "PReLU" | |
| bottom: "bn1_3_0" | |
| top: "prelu1_3_0" | |
| } | |
| layer { | |
| name: "conv1_3_1" | |
| type: "Convolution" | |
| bottom: "prelu1_3_0" | |
| top: "conv1_3_1" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_3_1" | |
| type: "BN" | |
| bottom: "conv1_3_1" | |
| top: "bn1_3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_3_1" | |
| type: "PReLU" | |
| bottom: "bn1_3_1" | |
| top: "prelu1_3_1" | |
| } | |
| layer { | |
| name: "conv1_3_2" | |
| type: "Convolution" | |
| bottom: "prelu1_3_1" | |
| top: "conv1_3_2" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_3_2" | |
| type: "BN" | |
| bottom: "conv1_3_2" | |
| top: "bn1_3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop1_3_3" | |
| type: "Python" | |
| bottom: "bn1_3_2" | |
| top: "drop1_3_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.01\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise1_3_4" | |
| type: "Eltwise" | |
| bottom: "drop1_3_3" | |
| bottom: "prelu1_2_4" | |
| top: "eltwise1_3_4" | |
| } | |
| layer { | |
| name: "prelu1_3_4" | |
| type: "PReLU" | |
| bottom: "eltwise1_3_4" | |
| top: "prelu1_3_4" | |
| } | |
| layer { | |
| name: "conv1_4_0" | |
| type: "Convolution" | |
| bottom: "prelu1_3_4" | |
| top: "conv1_4_0" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_4_0" | |
| type: "BN" | |
| bottom: "conv1_4_0" | |
| top: "bn1_4_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_4_0" | |
| type: "PReLU" | |
| bottom: "bn1_4_0" | |
| top: "prelu1_4_0" | |
| } | |
| layer { | |
| name: "conv1_4_1" | |
| type: "Convolution" | |
| bottom: "prelu1_4_0" | |
| top: "conv1_4_1" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_4_1" | |
| type: "BN" | |
| bottom: "conv1_4_1" | |
| top: "bn1_4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu1_4_1" | |
| type: "PReLU" | |
| bottom: "bn1_4_1" | |
| top: "prelu1_4_1" | |
| } | |
| layer { | |
| name: "conv1_4_2" | |
| type: "Convolution" | |
| bottom: "prelu1_4_1" | |
| top: "conv1_4_2" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_4_2" | |
| type: "BN" | |
| bottom: "conv1_4_2" | |
| top: "bn1_4_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop1_4_3" | |
| type: "Python" | |
| bottom: "bn1_4_2" | |
| top: "drop1_4_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.01\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise1_4_4" | |
| type: "Eltwise" | |
| bottom: "drop1_4_3" | |
| bottom: "prelu1_3_4" | |
| top: "eltwise1_4_4" | |
| } | |
| layer { | |
| name: "prelu1_4_4" | |
| type: "PReLU" | |
| bottom: "eltwise1_4_4" | |
| top: "prelu1_4_4" | |
| } | |
| layer { | |
| name: "conv2_0_0" | |
| type: "Convolution" | |
| bottom: "prelu1_4_4" | |
| top: "conv2_0_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 2 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_0_0" | |
| type: "BN" | |
| bottom: "conv2_0_0" | |
| top: "bn2_0_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_0_0" | |
| type: "PReLU" | |
| bottom: "bn2_0_0" | |
| top: "prelu2_0_0" | |
| } | |
| layer { | |
| name: "conv2_0_1" | |
| type: "Convolution" | |
| bottom: "prelu2_0_0" | |
| top: "conv2_0_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_0_1" | |
| type: "BN" | |
| bottom: "conv2_0_1" | |
| top: "bn2_0_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_0_1" | |
| type: "PReLU" | |
| bottom: "bn2_0_1" | |
| top: "prelu2_0_1" | |
| } | |
| layer { | |
| name: "conv2_0_2" | |
| type: "Convolution" | |
| bottom: "prelu2_0_1" | |
| top: "conv2_0_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_0_2" | |
| type: "BN" | |
| bottom: "conv2_0_2" | |
| top: "bn2_0_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_0_3" | |
| type: "Python" | |
| bottom: "bn2_0_2" | |
| top: "drop2_0_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "pool2_0_4" | |
| type: "Pooling" | |
| bottom: "prelu1_4_4" | |
| top: "pool2_0_4" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv2_0_4" | |
| type: "Convolution" | |
| bottom: "pool2_0_4" | |
| top: "conv2_0_4" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_0_4" | |
| type: "BN" | |
| bottom: "conv2_0_4" | |
| top: "bn2_0_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_0_4" | |
| type: "Eltwise" | |
| bottom: "drop2_0_3" | |
| bottom: "bn2_0_4" | |
| top: "eltwise2_0_4" | |
| } | |
| layer { | |
| name: "prelu2_0_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_0_4" | |
| top: "prelu2_0_4" | |
| } | |
| layer { | |
| name: "conv2_1_0" | |
| type: "Convolution" | |
| bottom: "prelu2_0_4" | |
| top: "conv2_1_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_1_0" | |
| type: "BN" | |
| bottom: "conv2_1_0" | |
| top: "bn2_1_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_1_0" | |
| type: "PReLU" | |
| bottom: "bn2_1_0" | |
| top: "prelu2_1_0" | |
| } | |
| layer { | |
| name: "conv2_1_1" | |
| type: "Convolution" | |
| bottom: "prelu2_1_0" | |
| top: "conv2_1_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_1_1" | |
| type: "BN" | |
| bottom: "conv2_1_1" | |
| top: "bn2_1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_1_1" | |
| type: "PReLU" | |
| bottom: "bn2_1_1" | |
| top: "prelu2_1_1" | |
| } | |
| layer { | |
| name: "conv2_1_2" | |
| type: "Convolution" | |
| bottom: "prelu2_1_1" | |
| top: "conv2_1_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_1_2" | |
| type: "BN" | |
| bottom: "conv2_1_2" | |
| top: "bn2_1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_1_3" | |
| type: "Python" | |
| bottom: "bn2_1_2" | |
| top: "drop2_1_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_1_4" | |
| type: "Eltwise" | |
| bottom: "drop2_1_3" | |
| bottom: "prelu2_0_4" | |
| top: "eltwise2_1_4" | |
| } | |
| layer { | |
| name: "prelu2_1_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_1_4" | |
| top: "prelu2_1_4" | |
| } | |
| layer { | |
| name: "conv2_2_0" | |
| type: "Convolution" | |
| bottom: "prelu2_1_4" | |
| top: "conv2_2_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_2_0" | |
| type: "BN" | |
| bottom: "conv2_2_0" | |
| top: "bn2_2_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_2_0" | |
| type: "PReLU" | |
| bottom: "bn2_2_0" | |
| top: "prelu2_2_0" | |
| } | |
| layer { | |
| name: "conv2_2_1" | |
| type: "Convolution" | |
| bottom: "prelu2_2_0" | |
| top: "conv2_2_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "bn2_2_1" | |
| type: "BN" | |
| bottom: "conv2_2_1" | |
| top: "bn2_2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_2_1" | |
| type: "PReLU" | |
| bottom: "bn2_2_1" | |
| top: "prelu2_2_1" | |
| } | |
| layer { | |
| name: "conv2_2_2" | |
| type: "Convolution" | |
| bottom: "prelu2_2_1" | |
| top: "conv2_2_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_2_2" | |
| type: "BN" | |
| bottom: "conv2_2_2" | |
| top: "bn2_2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_2_3" | |
| type: "Python" | |
| bottom: "bn2_2_2" | |
| top: "drop2_2_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_2_4" | |
| type: "Eltwise" | |
| bottom: "drop2_2_3" | |
| bottom: "prelu2_1_4" | |
| top: "eltwise2_2_4" | |
| } | |
| layer { | |
| name: "prelu2_2_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_2_4" | |
| top: "prelu2_2_4" | |
| } | |
| layer { | |
| name: "conv2_3_0" | |
| type: "Convolution" | |
| bottom: "prelu2_2_4" | |
| top: "conv2_3_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_3_0" | |
| type: "BN" | |
| bottom: "conv2_3_0" | |
| top: "bn2_3_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_3_0" | |
| type: "PReLU" | |
| bottom: "bn2_3_0" | |
| top: "prelu2_3_0" | |
| } | |
| layer { | |
| name: "conv2_3_1_a" | |
| type: "Convolution" | |
| bottom: "prelu2_3_0" | |
| top: "conv2_3_1_a" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 5 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3_1" | |
| type: "Convolution" | |
| bottom: "conv2_3_1_a" | |
| top: "conv2_3_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 1 | |
| kernel_w: 5 | |
| } | |
| } | |
| layer { | |
| name: "bn2_3_1" | |
| type: "BN" | |
| bottom: "conv2_3_1" | |
| top: "bn2_3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_3_1" | |
| type: "PReLU" | |
| bottom: "bn2_3_1" | |
| top: "prelu2_3_1" | |
| } | |
| layer { | |
| name: "conv2_3_2" | |
| type: "Convolution" | |
| bottom: "prelu2_3_1" | |
| top: "conv2_3_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_3_2" | |
| type: "BN" | |
| bottom: "conv2_3_2" | |
| top: "bn2_3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_3_3" | |
| type: "Python" | |
| bottom: "bn2_3_2" | |
| top: "drop2_3_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_3_4" | |
| type: "Eltwise" | |
| bottom: "drop2_3_3" | |
| bottom: "prelu2_2_4" | |
| top: "eltwise2_3_4" | |
| } | |
| layer { | |
| name: "prelu2_3_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_3_4" | |
| top: "prelu2_3_4" | |
| } | |
| layer { | |
| name: "conv2_4_0" | |
| type: "Convolution" | |
| bottom: "prelu2_3_4" | |
| top: "conv2_4_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_4_0" | |
| type: "BN" | |
| bottom: "conv2_4_0" | |
| top: "bn2_4_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_4_0" | |
| type: "PReLU" | |
| bottom: "bn2_4_0" | |
| top: "prelu2_4_0" | |
| } | |
| layer { | |
| name: "conv2_4_1" | |
| type: "Convolution" | |
| bottom: "prelu2_4_0" | |
| top: "conv2_4_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 4 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 4 | |
| } | |
| } | |
| layer { | |
| name: "bn2_4_1" | |
| type: "BN" | |
| bottom: "conv2_4_1" | |
| top: "bn2_4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_4_1" | |
| type: "PReLU" | |
| bottom: "bn2_4_1" | |
| top: "prelu2_4_1" | |
| } | |
| layer { | |
| name: "conv2_4_2" | |
| type: "Convolution" | |
| bottom: "prelu2_4_1" | |
| top: "conv2_4_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_4_2" | |
| type: "BN" | |
| bottom: "conv2_4_2" | |
| top: "bn2_4_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_4_3" | |
| type: "Python" | |
| bottom: "bn2_4_2" | |
| top: "drop2_4_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_4_4" | |
| type: "Eltwise" | |
| bottom: "drop2_4_3" | |
| bottom: "prelu2_3_4" | |
| top: "eltwise2_4_4" | |
| } | |
| layer { | |
| name: "prelu2_4_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_4_4" | |
| top: "prelu2_4_4" | |
| } | |
| layer { | |
| name: "conv2_5_0" | |
| type: "Convolution" | |
| bottom: "prelu2_4_4" | |
| top: "conv2_5_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_5_0" | |
| type: "BN" | |
| bottom: "conv2_5_0" | |
| top: "bn2_5_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_5_0" | |
| type: "PReLU" | |
| bottom: "bn2_5_0" | |
| top: "prelu2_5_0" | |
| } | |
| layer { | |
| name: "conv2_5_1" | |
| type: "Convolution" | |
| bottom: "prelu2_5_0" | |
| top: "conv2_5_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_5_1" | |
| type: "BN" | |
| bottom: "conv2_5_1" | |
| top: "bn2_5_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_5_1" | |
| type: "PReLU" | |
| bottom: "bn2_5_1" | |
| top: "prelu2_5_1" | |
| } | |
| layer { | |
| name: "conv2_5_2" | |
| type: "Convolution" | |
| bottom: "prelu2_5_1" | |
| top: "conv2_5_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_5_2" | |
| type: "BN" | |
| bottom: "conv2_5_2" | |
| top: "bn2_5_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_5_3" | |
| type: "Python" | |
| bottom: "bn2_5_2" | |
| top: "drop2_5_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_5_4" | |
| type: "Eltwise" | |
| bottom: "drop2_5_3" | |
| bottom: "prelu2_4_4" | |
| top: "eltwise2_5_4" | |
| } | |
| layer { | |
| name: "prelu2_5_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_5_4" | |
| top: "prelu2_5_4" | |
| } | |
| layer { | |
| name: "conv2_6_0" | |
| type: "Convolution" | |
| bottom: "prelu2_5_4" | |
| top: "conv2_6_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_6_0" | |
| type: "BN" | |
| bottom: "conv2_6_0" | |
| top: "bn2_6_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_6_0" | |
| type: "PReLU" | |
| bottom: "bn2_6_0" | |
| top: "prelu2_6_0" | |
| } | |
| layer { | |
| name: "conv2_6_1" | |
| type: "Convolution" | |
| bottom: "prelu2_6_0" | |
| top: "conv2_6_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 8 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 8 | |
| } | |
| } | |
| layer { | |
| name: "bn2_6_1" | |
| type: "BN" | |
| bottom: "conv2_6_1" | |
| top: "bn2_6_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_6_1" | |
| type: "PReLU" | |
| bottom: "bn2_6_1" | |
| top: "prelu2_6_1" | |
| } | |
| layer { | |
| name: "conv2_6_2" | |
| type: "Convolution" | |
| bottom: "prelu2_6_1" | |
| top: "conv2_6_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_6_2" | |
| type: "BN" | |
| bottom: "conv2_6_2" | |
| top: "bn2_6_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_6_3" | |
| type: "Python" | |
| bottom: "bn2_6_2" | |
| top: "drop2_6_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_6_4" | |
| type: "Eltwise" | |
| bottom: "drop2_6_3" | |
| bottom: "prelu2_5_4" | |
| top: "eltwise2_6_4" | |
| } | |
| layer { | |
| name: "prelu2_6_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_6_4" | |
| top: "prelu2_6_4" | |
| } | |
| layer { | |
| name: "conv2_7_0" | |
| type: "Convolution" | |
| bottom: "prelu2_6_4" | |
| top: "conv2_7_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_7_0" | |
| type: "BN" | |
| bottom: "conv2_7_0" | |
| top: "bn2_7_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_7_0" | |
| type: "PReLU" | |
| bottom: "bn2_7_0" | |
| top: "prelu2_7_0" | |
| } | |
| layer { | |
| name: "conv2_7_1_a" | |
| type: "Convolution" | |
| bottom: "prelu2_7_0" | |
| top: "conv2_7_1_a" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 5 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_7_1" | |
| type: "Convolution" | |
| bottom: "conv2_7_1_a" | |
| top: "conv2_7_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 1 | |
| kernel_w: 5 | |
| } | |
| } | |
| layer { | |
| name: "bn2_7_1" | |
| type: "BN" | |
| bottom: "conv2_7_1" | |
| top: "bn2_7_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_7_1" | |
| type: "PReLU" | |
| bottom: "bn2_7_1" | |
| top: "prelu2_7_1" | |
| } | |
| layer { | |
| name: "conv2_7_2" | |
| type: "Convolution" | |
| bottom: "prelu2_7_1" | |
| top: "conv2_7_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_7_2" | |
| type: "BN" | |
| bottom: "conv2_7_2" | |
| top: "bn2_7_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_7_3" | |
| type: "Python" | |
| bottom: "bn2_7_2" | |
| top: "drop2_7_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_7_4" | |
| type: "Eltwise" | |
| bottom: "drop2_7_3" | |
| bottom: "prelu2_6_4" | |
| top: "eltwise2_7_4" | |
| } | |
| layer { | |
| name: "prelu2_7_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_7_4" | |
| top: "prelu2_7_4" | |
| } | |
| layer { | |
| name: "conv2_8_0" | |
| type: "Convolution" | |
| bottom: "prelu2_7_4" | |
| top: "conv2_8_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_8_0" | |
| type: "BN" | |
| bottom: "conv2_8_0" | |
| top: "bn2_8_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_8_0" | |
| type: "PReLU" | |
| bottom: "bn2_8_0" | |
| top: "prelu2_8_0" | |
| } | |
| layer { | |
| name: "conv2_8_1" | |
| type: "Convolution" | |
| bottom: "prelu2_8_0" | |
| top: "conv2_8_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 16 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 16 | |
| } | |
| } | |
| layer { | |
| name: "bn2_8_1" | |
| type: "BN" | |
| bottom: "conv2_8_1" | |
| top: "bn2_8_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu2_8_1" | |
| type: "PReLU" | |
| bottom: "bn2_8_1" | |
| top: "prelu2_8_1" | |
| } | |
| layer { | |
| name: "conv2_8_2" | |
| type: "Convolution" | |
| bottom: "prelu2_8_1" | |
| top: "conv2_8_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_8_2" | |
| type: "BN" | |
| bottom: "conv2_8_2" | |
| top: "bn2_8_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop2_8_3" | |
| type: "Python" | |
| bottom: "bn2_8_2" | |
| top: "drop2_8_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise2_8_4" | |
| type: "Eltwise" | |
| bottom: "drop2_8_3" | |
| bottom: "prelu2_7_4" | |
| top: "eltwise2_8_4" | |
| } | |
| layer { | |
| name: "prelu2_8_4" | |
| type: "PReLU" | |
| bottom: "eltwise2_8_4" | |
| top: "prelu2_8_4" | |
| } | |
| layer { | |
| name: "conv3_1_0" | |
| type: "Convolution" | |
| bottom: "prelu2_8_4" | |
| top: "conv3_1_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_1_0" | |
| type: "BN" | |
| bottom: "conv3_1_0" | |
| top: "bn3_1_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_1_0" | |
| type: "PReLU" | |
| bottom: "bn3_1_0" | |
| top: "prelu3_1_0" | |
| } | |
| layer { | |
| name: "conv3_1_1" | |
| type: "Convolution" | |
| bottom: "prelu3_1_0" | |
| top: "conv3_1_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_1_1" | |
| type: "BN" | |
| bottom: "conv3_1_1" | |
| top: "bn3_1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_1_1" | |
| type: "PReLU" | |
| bottom: "bn3_1_1" | |
| top: "prelu3_1_1" | |
| } | |
| layer { | |
| name: "conv3_1_2" | |
| type: "Convolution" | |
| bottom: "prelu3_1_1" | |
| top: "conv3_1_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_1_2" | |
| type: "BN" | |
| bottom: "conv3_1_2" | |
| top: "bn3_1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_1_3" | |
| type: "Python" | |
| bottom: "bn3_1_2" | |
| top: "drop3_1_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_1_4" | |
| type: "Eltwise" | |
| bottom: "drop3_1_3" | |
| bottom: "prelu2_8_4" | |
| top: "eltwise3_1_4" | |
| } | |
| layer { | |
| name: "prelu3_1_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_1_4" | |
| top: "prelu3_1_4" | |
| } | |
| layer { | |
| name: "conv3_2_0" | |
| type: "Convolution" | |
| bottom: "prelu3_1_4" | |
| top: "conv3_2_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_2_0" | |
| type: "BN" | |
| bottom: "conv3_2_0" | |
| top: "bn3_2_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_2_0" | |
| type: "PReLU" | |
| bottom: "bn3_2_0" | |
| top: "prelu3_2_0" | |
| } | |
| layer { | |
| name: "conv3_2_1" | |
| type: "Convolution" | |
| bottom: "prelu3_2_0" | |
| top: "conv3_2_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "bn3_2_1" | |
| type: "BN" | |
| bottom: "conv3_2_1" | |
| top: "bn3_2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_2_1" | |
| type: "PReLU" | |
| bottom: "bn3_2_1" | |
| top: "prelu3_2_1" | |
| } | |
| layer { | |
| name: "conv3_2_2" | |
| type: "Convolution" | |
| bottom: "prelu3_2_1" | |
| top: "conv3_2_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_2_2" | |
| type: "BN" | |
| bottom: "conv3_2_2" | |
| top: "bn3_2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_2_3" | |
| type: "Python" | |
| bottom: "bn3_2_2" | |
| top: "drop3_2_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_2_4" | |
| type: "Eltwise" | |
| bottom: "drop3_2_3" | |
| bottom: "prelu3_1_4" | |
| top: "eltwise3_2_4" | |
| } | |
| layer { | |
| name: "prelu3_2_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_2_4" | |
| top: "prelu3_2_4" | |
| } | |
| layer { | |
| name: "conv3_3_0" | |
| type: "Convolution" | |
| bottom: "prelu3_2_4" | |
| top: "conv3_3_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_3_0" | |
| type: "BN" | |
| bottom: "conv3_3_0" | |
| top: "bn3_3_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_3_0" | |
| type: "PReLU" | |
| bottom: "bn3_3_0" | |
| top: "prelu3_3_0" | |
| } | |
| layer { | |
| name: "conv3_3_1_a" | |
| type: "Convolution" | |
| bottom: "prelu3_3_0" | |
| top: "conv3_3_1_a" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 5 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3_1" | |
| type: "Convolution" | |
| bottom: "conv3_3_1_a" | |
| top: "conv3_3_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 1 | |
| kernel_w: 5 | |
| } | |
| } | |
| layer { | |
| name: "bn3_3_1" | |
| type: "BN" | |
| bottom: "conv3_3_1" | |
| top: "bn3_3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_3_1" | |
| type: "PReLU" | |
| bottom: "bn3_3_1" | |
| top: "prelu3_3_1" | |
| } | |
| layer { | |
| name: "conv3_3_2" | |
| type: "Convolution" | |
| bottom: "prelu3_3_1" | |
| top: "conv3_3_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_3_2" | |
| type: "BN" | |
| bottom: "conv3_3_2" | |
| top: "bn3_3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_3_3" | |
| type: "Python" | |
| bottom: "bn3_3_2" | |
| top: "drop3_3_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_3_4" | |
| type: "Eltwise" | |
| bottom: "drop3_3_3" | |
| bottom: "prelu3_2_4" | |
| top: "eltwise3_3_4" | |
| } | |
| layer { | |
| name: "prelu3_3_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_3_4" | |
| top: "prelu3_3_4" | |
| } | |
| layer { | |
| name: "conv3_4_0" | |
| type: "Convolution" | |
| bottom: "prelu3_3_4" | |
| top: "conv3_4_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_4_0" | |
| type: "BN" | |
| bottom: "conv3_4_0" | |
| top: "bn3_4_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_4_0" | |
| type: "PReLU" | |
| bottom: "bn3_4_0" | |
| top: "prelu3_4_0" | |
| } | |
| layer { | |
| name: "conv3_4_1" | |
| type: "Convolution" | |
| bottom: "prelu3_4_0" | |
| top: "conv3_4_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 4 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 4 | |
| } | |
| } | |
| layer { | |
| name: "bn3_4_1" | |
| type: "BN" | |
| bottom: "conv3_4_1" | |
| top: "bn3_4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_4_1" | |
| type: "PReLU" | |
| bottom: "bn3_4_1" | |
| top: "prelu3_4_1" | |
| } | |
| layer { | |
| name: "conv3_4_2" | |
| type: "Convolution" | |
| bottom: "prelu3_4_1" | |
| top: "conv3_4_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_4_2" | |
| type: "BN" | |
| bottom: "conv3_4_2" | |
| top: "bn3_4_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_4_3" | |
| type: "Python" | |
| bottom: "bn3_4_2" | |
| top: "drop3_4_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_4_4" | |
| type: "Eltwise" | |
| bottom: "drop3_4_3" | |
| bottom: "prelu3_3_4" | |
| top: "eltwise3_4_4" | |
| } | |
| layer { | |
| name: "prelu3_4_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_4_4" | |
| top: "prelu3_4_4" | |
| } | |
| layer { | |
| name: "conv3_5_0" | |
| type: "Convolution" | |
| bottom: "prelu3_4_4" | |
| top: "conv3_5_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_5_0" | |
| type: "BN" | |
| bottom: "conv3_5_0" | |
| top: "bn3_5_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_5_0" | |
| type: "PReLU" | |
| bottom: "bn3_5_0" | |
| top: "prelu3_5_0" | |
| } | |
| layer { | |
| name: "conv3_5_1" | |
| type: "Convolution" | |
| bottom: "prelu3_5_0" | |
| top: "conv3_5_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_5_1" | |
| type: "BN" | |
| bottom: "conv3_5_1" | |
| top: "bn3_5_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_5_1" | |
| type: "PReLU" | |
| bottom: "bn3_5_1" | |
| top: "prelu3_5_1" | |
| } | |
| layer { | |
| name: "conv3_5_2" | |
| type: "Convolution" | |
| bottom: "prelu3_5_1" | |
| top: "conv3_5_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_5_2" | |
| type: "BN" | |
| bottom: "conv3_5_2" | |
| top: "bn3_5_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_5_3" | |
| type: "Python" | |
| bottom: "bn3_5_2" | |
| top: "drop3_5_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_5_4" | |
| type: "Eltwise" | |
| bottom: "drop3_5_3" | |
| bottom: "prelu3_4_4" | |
| top: "eltwise3_5_4" | |
| } | |
| layer { | |
| name: "prelu3_5_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_5_4" | |
| top: "prelu3_5_4" | |
| } | |
| layer { | |
| name: "conv3_6_0" | |
| type: "Convolution" | |
| bottom: "prelu3_5_4" | |
| top: "conv3_6_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_6_0" | |
| type: "BN" | |
| bottom: "conv3_6_0" | |
| top: "bn3_6_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_6_0" | |
| type: "PReLU" | |
| bottom: "bn3_6_0" | |
| top: "prelu3_6_0" | |
| } | |
| layer { | |
| name: "conv3_6_1" | |
| type: "Convolution" | |
| bottom: "prelu3_6_0" | |
| top: "conv3_6_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 8 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 8 | |
| } | |
| } | |
| layer { | |
| name: "bn3_6_1" | |
| type: "BN" | |
| bottom: "conv3_6_1" | |
| top: "bn3_6_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_6_1" | |
| type: "PReLU" | |
| bottom: "bn3_6_1" | |
| top: "prelu3_6_1" | |
| } | |
| layer { | |
| name: "conv3_6_2" | |
| type: "Convolution" | |
| bottom: "prelu3_6_1" | |
| top: "conv3_6_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_6_2" | |
| type: "BN" | |
| bottom: "conv3_6_2" | |
| top: "bn3_6_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_6_3" | |
| type: "Python" | |
| bottom: "bn3_6_2" | |
| top: "drop3_6_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_6_4" | |
| type: "Eltwise" | |
| bottom: "drop3_6_3" | |
| bottom: "prelu3_5_4" | |
| top: "eltwise3_6_4" | |
| } | |
| layer { | |
| name: "prelu3_6_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_6_4" | |
| top: "prelu3_6_4" | |
| } | |
| layer { | |
| name: "conv3_7_0" | |
| type: "Convolution" | |
| bottom: "prelu3_6_4" | |
| top: "conv3_7_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_7_0" | |
| type: "BN" | |
| bottom: "conv3_7_0" | |
| top: "bn3_7_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_7_0" | |
| type: "PReLU" | |
| bottom: "bn3_7_0" | |
| top: "prelu3_7_0" | |
| } | |
| layer { | |
| name: "conv3_7_1_a" | |
| type: "Convolution" | |
| bottom: "prelu3_7_0" | |
| top: "conv3_7_1_a" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 5 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_7_1" | |
| type: "Convolution" | |
| bottom: "conv3_7_1_a" | |
| top: "conv3_7_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| kernel_h: 1 | |
| kernel_w: 5 | |
| } | |
| } | |
| layer { | |
| name: "bn3_7_1" | |
| type: "BN" | |
| bottom: "conv3_7_1" | |
| top: "bn3_7_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_7_1" | |
| type: "PReLU" | |
| bottom: "bn3_7_1" | |
| top: "prelu3_7_1" | |
| } | |
| layer { | |
| name: "conv3_7_2" | |
| type: "Convolution" | |
| bottom: "prelu3_7_1" | |
| top: "conv3_7_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_7_2" | |
| type: "BN" | |
| bottom: "conv3_7_2" | |
| top: "bn3_7_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_7_3" | |
| type: "Python" | |
| bottom: "bn3_7_2" | |
| top: "drop3_7_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_7_4" | |
| type: "Eltwise" | |
| bottom: "drop3_7_3" | |
| bottom: "prelu3_6_4" | |
| top: "eltwise3_7_4" | |
| } | |
| layer { | |
| name: "prelu3_7_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_7_4" | |
| top: "prelu3_7_4" | |
| } | |
| layer { | |
| name: "conv3_8_0" | |
| type: "Convolution" | |
| bottom: "prelu3_7_4" | |
| top: "conv3_8_0" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_8_0" | |
| type: "BN" | |
| bottom: "conv3_8_0" | |
| top: "bn3_8_0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_8_0" | |
| type: "PReLU" | |
| bottom: "bn3_8_0" | |
| top: "prelu3_8_0" | |
| } | |
| layer { | |
| name: "conv3_8_1" | |
| type: "Convolution" | |
| bottom: "prelu3_8_0" | |
| top: "conv3_8_1" | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 16 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 16 | |
| } | |
| } | |
| layer { | |
| name: "bn3_8_1" | |
| type: "BN" | |
| bottom: "conv3_8_1" | |
| top: "bn3_8_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "prelu3_8_1" | |
| type: "PReLU" | |
| bottom: "bn3_8_1" | |
| top: "prelu3_8_1" | |
| } | |
| layer { | |
| name: "conv3_8_2" | |
| type: "Convolution" | |
| bottom: "prelu3_8_1" | |
| top: "conv3_8_2" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_8_2" | |
| type: "BN" | |
| bottom: "conv3_8_2" | |
| top: "bn3_8_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| bn_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| shift_filler { | |
| type: "constant" | |
| value: 0.001 | |
| } | |
| bn_mode: LEARN | |
| } | |
| } | |
| layer { | |
| name: "drop3_8_3" | |
| type: "Python" | |
| bottom: "bn3_8_2" | |
| top: "drop3_8_3" | |
| python_param { | |
| module: "spatial_dropout" | |
| layer: "SpatialDropoutLayer" | |
| param_str: "{\'phase\': \'TRAIN\', \'p\': \'0.1\'}" | |
| } | |
| } | |
| layer { | |
| name: "eltwise3_8_4" | |
| type: "Eltwise" | |
| bottom: "drop3_8_3" | |
| bottom: "prelu3_7_4" | |
| top: "eltwise3_8_4" | |
| } | |
| layer { | |
| name: "prelu3_8_4" | |
| type: "PReLU" | |
| bottom: "eltwise3_8_4" | |
| top: "prelu3_8_4" | |
| } | |
| layer { | |
| name: "deconv_encoder6_0_0" | |
| type: "Deconvolution" | |
| bottom: "prelu3_8_4" | |
| top: "deconv_encoder6_0_0" | |
| convolution_param { | |
| num_output: 19 | |
| bias_term: true | |
| kernel_size: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "deconv_encoder6_0_0" | |
| bottom: "label" | |
| top: "loss" | |
| loss_param { | |
| ignore_label: 255 | |
| weight_by_label_freqs: false | |
| } | |
| } | |
| layer { | |
| name: "accuracy" | |
| type: "Accuracy" | |
| bottom: "deconv_encoder6_0_0" | |
| bottom: "label" | |
| top: "accuracy" | |
| top: "per_class_accuracy" | |
| } |
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