Created
September 6, 2016 08:33
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DMU-Net model
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| input: "data" | |
| input_shape { | |
| dim: 1 | |
| dim: 1 | |
| dim: 224 | |
| dim: 224 | |
| } | |
| layer { | |
| name: "conv1/7x7_s2" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1/7x7_s2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/relu_7x7" | |
| type: "ReLU" | |
| bottom: "conv1/7x7_s2" | |
| top: "conv1/7x7_s2" | |
| } | |
| layer { | |
| name: "pool1/3x3_s2" | |
| type: "Pooling" | |
| bottom: "conv1/7x7_s2" | |
| top: "pool1/3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "pool1/norm1" | |
| type: "LRN" | |
| bottom: "pool1/3x3_s2" | |
| top: "pool1/norm1" | |
| lrn_param { | |
| local_size: 5 | |
| alpha: 0.0001 | |
| beta: 0.75 | |
| } | |
| } | |
| layer { | |
| name: "conv2/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "pool1/norm1" | |
| top: "conv2/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "conv2/3x3_reduce" | |
| top: "conv2/3x3_reduce" | |
| } | |
| layer { | |
| name: "conv2/3x3" | |
| type: "Convolution" | |
| bottom: "conv2/3x3_reduce" | |
| top: "conv2/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/relu_3x3" | |
| type: "ReLU" | |
| bottom: "conv2/3x3" | |
| top: "conv2/3x3" | |
| } | |
| layer { | |
| name: "conv2/norm2" | |
| type: "LRN" | |
| bottom: "conv2/3x3" | |
| top: "conv2/norm2" | |
| lrn_param { | |
| local_size: 5 | |
| alpha: 0.0001 | |
| beta: 0.75 | |
| } | |
| } | |
| layer { | |
| name: "pool2/3x3_s2" | |
| type: "Pooling" | |
| bottom: "conv2/norm2" | |
| top: "pool2/3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/1x1" | |
| type: "Convolution" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_3a/1x1" | |
| top: "inception_3a/1x1" | |
| } | |
| layer { | |
| name: "inception_3a/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_3a/3x3_reduce" | |
| top: "inception_3a/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_3a/3x3" | |
| type: "Convolution" | |
| bottom: "inception_3a/3x3_reduce" | |
| top: "inception_3a/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_3a/3x3" | |
| top: "inception_3a/3x3" | |
| } | |
| layer { | |
| name: "inception_3a/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_3a/5x5_reduce" | |
| top: "inception_3a/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_3a/5x5" | |
| type: "Convolution" | |
| bottom: "inception_3a/5x5_reduce" | |
| top: "inception_3a/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_3a/5x5" | |
| top: "inception_3a/5x5" | |
| } | |
| layer { | |
| name: "inception_3a/pool" | |
| type: "Pooling" | |
| bottom: "pool2/3x3_s2" | |
| top: "inception_3a/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_3a/pool" | |
| top: "inception_3a/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_3a/pool_proj" | |
| top: "inception_3a/pool_proj" | |
| } | |
| layer { | |
| name: "inception_3a/output" | |
| type: "Concat" | |
| bottom: "inception_3a/1x1" | |
| bottom: "inception_3a/3x3" | |
| bottom: "inception_3a/5x5" | |
| bottom: "inception_3a/pool_proj" | |
| top: "inception_3a/output" | |
| } | |
| layer { | |
| name: "inception_3b/1x1" | |
| type: "Convolution" | |
| bottom: "inception_3a/output" | |
| top: "inception_3b/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_3b/1x1" | |
| top: "inception_3b/1x1" | |
| } | |
| layer { | |
| name: "inception_3b/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_3a/output" | |
| top: "inception_3b/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_3b/3x3_reduce" | |
| top: "inception_3b/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_3b/3x3" | |
| type: "Convolution" | |
| bottom: "inception_3b/3x3_reduce" | |
| top: "inception_3b/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_3b/3x3" | |
| top: "inception_3b/3x3" | |
| } | |
| layer { | |
| name: "inception_3b/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "inception_3a/output" | |
| top: "inception_3b/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_3b/5x5_reduce" | |
| top: "inception_3b/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_3b/5x5" | |
| type: "Convolution" | |
| bottom: "inception_3b/5x5_reduce" | |
| top: "inception_3b/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_3b/5x5" | |
| top: "inception_3b/5x5" | |
| } | |
| layer { | |
| name: "inception_3b/pool" | |
| type: "Pooling" | |
| bottom: "inception_3a/output" | |
| top: "inception_3b/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_3b/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_3b/pool" | |
| top: "inception_3b/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_3b/pool_proj" | |
| top: "inception_3b/pool_proj" | |
| } | |
| layer { | |
| name: "inception_3b/output" | |
| type: "Concat" | |
| bottom: "inception_3b/1x1" | |
| bottom: "inception_3b/3x3" | |
| bottom: "inception_3b/5x5" | |
| bottom: "inception_3b/pool_proj" | |
| top: "inception_3b/output" | |
| } | |
| layer { | |
| name: "pool3/3x3_s2" | |
| type: "Pooling" | |
| bottom: "inception_3b/output" | |
| top: "pool3/3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/1x1" | |
| type: "Convolution" | |
| bottom: "pool3/3x3_s2" | |
| top: "inception_4a/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_4a/1x1" | |
| top: "inception_4a/1x1" | |
| } | |
| layer { | |
| name: "inception_4a/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "pool3/3x3_s2" | |
| top: "inception_4a/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4a/3x3_reduce" | |
| top: "inception_4a/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_4a/3x3" | |
| type: "Convolution" | |
| bottom: "inception_4a/3x3_reduce" | |
| top: "inception_4a/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 208 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_4a/3x3" | |
| top: "inception_4a/3x3" | |
| } | |
| layer { | |
| name: "inception_4a/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "pool3/3x3_s2" | |
| top: "inception_4a/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4a/5x5_reduce" | |
| top: "inception_4a/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_4a/5x5" | |
| type: "Convolution" | |
| bottom: "inception_4a/5x5_reduce" | |
| top: "inception_4a/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_4a/5x5" | |
| top: "inception_4a/5x5" | |
| } | |
| layer { | |
| name: "inception_4a/pool" | |
| type: "Pooling" | |
| bottom: "pool3/3x3_s2" | |
| top: "inception_4a/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_4a/pool" | |
| top: "inception_4a/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_4a/pool_proj" | |
| top: "inception_4a/pool_proj" | |
| } | |
| layer { | |
| name: "inception_4a/output" | |
| type: "Concat" | |
| bottom: "inception_4a/1x1" | |
| bottom: "inception_4a/3x3" | |
| bottom: "inception_4a/5x5" | |
| bottom: "inception_4a/pool_proj" | |
| top: "inception_4a/output" | |
| } | |
| layer { | |
| name: "loss1/ave_pool" | |
| type: "Pooling" | |
| bottom: "inception_4a/output" | |
| top: "loss1/ave_pool" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 5 | |
| stride: 3 | |
| } | |
| } | |
| layer { | |
| name: "loss1/conv" | |
| type: "Convolution" | |
| bottom: "loss1/ave_pool" | |
| top: "loss1/conv" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss1/relu_conv" | |
| type: "ReLU" | |
| bottom: "loss1/conv" | |
| top: "loss1/conv" | |
| } | |
| layer { | |
| name: "loss1/fc" | |
| type: "InnerProduct" | |
| bottom: "loss1/conv" | |
| top: "loss1/fc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 1024 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.02 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss1/relu_fc" | |
| type: "ReLU" | |
| bottom: "loss1/fc" | |
| top: "loss1/fc" | |
| } | |
| layer { | |
| name: "loss1/drop_fc" | |
| type: "Dropout" | |
| bottom: "loss1/fc" | |
| top: "loss1/fc" | |
| dropout_param { | |
| dropout_ratio: 0.7 | |
| } | |
| } | |
| layer { | |
| name: "loss1/classifier" | |
| type: "InnerProduct" | |
| bottom: "loss1/fc" | |
| top: "loss1/classifier" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 31 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.0009765625 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/1x1" | |
| type: "Convolution" | |
| bottom: "inception_4a/output" | |
| top: "inception_4b/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_4b/1x1" | |
| top: "inception_4b/1x1" | |
| } | |
| layer { | |
| name: "inception_4b/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4a/output" | |
| top: "inception_4b/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 112 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4b/3x3_reduce" | |
| top: "inception_4b/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_4b/3x3" | |
| type: "Convolution" | |
| bottom: "inception_4b/3x3_reduce" | |
| top: "inception_4b/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 224 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_4b/3x3" | |
| top: "inception_4b/3x3" | |
| } | |
| layer { | |
| name: "inception_4b/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4a/output" | |
| top: "inception_4b/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4b/5x5_reduce" | |
| top: "inception_4b/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_4b/5x5" | |
| type: "Convolution" | |
| bottom: "inception_4b/5x5_reduce" | |
| top: "inception_4b/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_4b/5x5" | |
| top: "inception_4b/5x5" | |
| } | |
| layer { | |
| name: "inception_4b/pool" | |
| type: "Pooling" | |
| bottom: "inception_4a/output" | |
| top: "inception_4b/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_4b/pool" | |
| top: "inception_4b/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_4b/pool_proj" | |
| top: "inception_4b/pool_proj" | |
| } | |
| layer { | |
| name: "inception_4b/output" | |
| type: "Concat" | |
| bottom: "inception_4b/1x1" | |
| bottom: "inception_4b/3x3" | |
| bottom: "inception_4b/5x5" | |
| bottom: "inception_4b/pool_proj" | |
| top: "inception_4b/output" | |
| } | |
| layer { | |
| name: "inception_4c/1x1" | |
| type: "Convolution" | |
| bottom: "inception_4b/output" | |
| top: "inception_4c/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_4c/1x1" | |
| top: "inception_4c/1x1" | |
| } | |
| layer { | |
| name: "inception_4c/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4b/output" | |
| top: "inception_4c/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4c/3x3_reduce" | |
| top: "inception_4c/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_4c/3x3" | |
| type: "Convolution" | |
| bottom: "inception_4c/3x3_reduce" | |
| top: "inception_4c/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_4c/3x3" | |
| top: "inception_4c/3x3" | |
| } | |
| layer { | |
| name: "inception_4c/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4b/output" | |
| top: "inception_4c/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4c/5x5_reduce" | |
| top: "inception_4c/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_4c/5x5" | |
| type: "Convolution" | |
| bottom: "inception_4c/5x5_reduce" | |
| top: "inception_4c/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_4c/5x5" | |
| top: "inception_4c/5x5" | |
| } | |
| layer { | |
| name: "inception_4c/pool" | |
| type: "Pooling" | |
| bottom: "inception_4b/output" | |
| top: "inception_4c/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_4c/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_4c/pool" | |
| top: "inception_4c/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_4c/pool_proj" | |
| top: "inception_4c/pool_proj" | |
| } | |
| layer { | |
| name: "inception_4c/output" | |
| type: "Concat" | |
| bottom: "inception_4c/1x1" | |
| bottom: "inception_4c/3x3" | |
| bottom: "inception_4c/5x5" | |
| bottom: "inception_4c/pool_proj" | |
| top: "inception_4c/output" | |
| } | |
| layer { | |
| name: "inception_4d/1x1" | |
| type: "Convolution" | |
| bottom: "inception_4c/output" | |
| top: "inception_4d/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 112 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_4d/1x1" | |
| top: "inception_4d/1x1" | |
| } | |
| layer { | |
| name: "inception_4d/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4c/output" | |
| top: "inception_4d/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4d/3x3_reduce" | |
| top: "inception_4d/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_4d/3x3" | |
| type: "Convolution" | |
| bottom: "inception_4d/3x3_reduce" | |
| top: "inception_4d/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 288 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_4d/3x3" | |
| top: "inception_4d/3x3" | |
| } | |
| layer { | |
| name: "inception_4d/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4c/output" | |
| top: "inception_4d/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4d/5x5_reduce" | |
| top: "inception_4d/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_4d/5x5" | |
| type: "Convolution" | |
| bottom: "inception_4d/5x5_reduce" | |
| top: "inception_4d/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_4d/5x5" | |
| top: "inception_4d/5x5" | |
| } | |
| layer { | |
| name: "inception_4d/pool" | |
| type: "Pooling" | |
| bottom: "inception_4c/output" | |
| top: "inception_4d/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_4d/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_4d/pool" | |
| top: "inception_4d/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_4d/pool_proj" | |
| top: "inception_4d/pool_proj" | |
| } | |
| layer { | |
| name: "inception_4d/output" | |
| type: "Concat" | |
| bottom: "inception_4d/1x1" | |
| bottom: "inception_4d/3x3" | |
| bottom: "inception_4d/5x5" | |
| bottom: "inception_4d/pool_proj" | |
| top: "inception_4d/output" | |
| } | |
| layer { | |
| name: "loss2/ave_pool" | |
| type: "Pooling" | |
| bottom: "inception_4d/output" | |
| top: "loss2/ave_pool" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 5 | |
| stride: 3 | |
| } | |
| } | |
| layer { | |
| name: "loss2/conv" | |
| type: "Convolution" | |
| bottom: "loss2/ave_pool" | |
| top: "loss2/conv" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss2/relu_conv" | |
| type: "ReLU" | |
| bottom: "loss2/conv" | |
| top: "loss2/conv" | |
| } | |
| layer { | |
| name: "loss2/fc" | |
| type: "InnerProduct" | |
| bottom: "loss2/conv" | |
| top: "loss2/fc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 1024 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.02 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss2/relu_fc" | |
| type: "ReLU" | |
| bottom: "loss2/fc" | |
| top: "loss2/fc" | |
| } | |
| layer { | |
| name: "loss2/drop_fc" | |
| type: "Dropout" | |
| bottom: "loss2/fc" | |
| top: "loss2/fc" | |
| dropout_param { | |
| dropout_ratio: 0.7 | |
| } | |
| } | |
| layer { | |
| name: "loss2/classifier" | |
| type: "InnerProduct" | |
| bottom: "loss2/fc" | |
| top: "loss2/classifier" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 31 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.0009765625 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/1x1" | |
| type: "Convolution" | |
| bottom: "inception_4d/output" | |
| top: "inception_4e/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_4e/1x1" | |
| top: "inception_4e/1x1" | |
| } | |
| layer { | |
| name: "inception_4e/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4d/output" | |
| top: "inception_4e/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4e/3x3_reduce" | |
| top: "inception_4e/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_4e/3x3" | |
| type: "Convolution" | |
| bottom: "inception_4e/3x3_reduce" | |
| top: "inception_4e/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_4e/3x3" | |
| top: "inception_4e/3x3" | |
| } | |
| layer { | |
| name: "inception_4e/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "inception_4d/output" | |
| top: "inception_4e/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_4e/5x5_reduce" | |
| top: "inception_4e/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_4e/5x5" | |
| type: "Convolution" | |
| bottom: "inception_4e/5x5_reduce" | |
| top: "inception_4e/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_4e/5x5" | |
| top: "inception_4e/5x5" | |
| } | |
| layer { | |
| name: "inception_4e/pool" | |
| type: "Pooling" | |
| bottom: "inception_4d/output" | |
| top: "inception_4e/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_4e/pool" | |
| top: "inception_4e/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_4e/pool_proj" | |
| top: "inception_4e/pool_proj" | |
| } | |
| layer { | |
| name: "inception_4e/output" | |
| type: "Concat" | |
| bottom: "inception_4e/1x1" | |
| bottom: "inception_4e/3x3" | |
| bottom: "inception_4e/5x5" | |
| bottom: "inception_4e/pool_proj" | |
| top: "inception_4e/output" | |
| } | |
| layer { | |
| name: "pool4/3x3_s2" | |
| type: "Pooling" | |
| bottom: "inception_4e/output" | |
| top: "pool4/3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/1x1" | |
| type: "Convolution" | |
| bottom: "pool4/3x3_s2" | |
| top: "inception_5a/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_5a/1x1" | |
| top: "inception_5a/1x1" | |
| } | |
| layer { | |
| name: "inception_5a/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "pool4/3x3_s2" | |
| top: "inception_5a/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_5a/3x3_reduce" | |
| top: "inception_5a/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_5a/3x3" | |
| type: "Convolution" | |
| bottom: "inception_5a/3x3_reduce" | |
| top: "inception_5a/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_5a/3x3" | |
| top: "inception_5a/3x3" | |
| } | |
| layer { | |
| name: "inception_5a/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "pool4/3x3_s2" | |
| top: "inception_5a/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_5a/5x5_reduce" | |
| top: "inception_5a/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_5a/5x5" | |
| type: "Convolution" | |
| bottom: "inception_5a/5x5_reduce" | |
| top: "inception_5a/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_5a/5x5" | |
| top: "inception_5a/5x5" | |
| } | |
| layer { | |
| name: "inception_5a/pool" | |
| type: "Pooling" | |
| bottom: "pool4/3x3_s2" | |
| top: "inception_5a/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_5a/pool" | |
| top: "inception_5a/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_5a/pool_proj" | |
| top: "inception_5a/pool_proj" | |
| } | |
| layer { | |
| name: "inception_5a/output" | |
| type: "Concat" | |
| bottom: "inception_5a/1x1" | |
| bottom: "inception_5a/3x3" | |
| bottom: "inception_5a/5x5" | |
| bottom: "inception_5a/pool_proj" | |
| top: "inception_5a/output" | |
| } | |
| layer { | |
| name: "inception_5b/1x1" | |
| type: "Convolution" | |
| bottom: "inception_5a/output" | |
| top: "inception_5b/1x1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b/relu_1x1" | |
| type: "ReLU" | |
| bottom: "inception_5b/1x1" | |
| top: "inception_5b/1x1" | |
| } | |
| layer { | |
| name: "inception_5b/3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_5a/output" | |
| top: "inception_5b/3x3_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.09 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b/relu_3x3_reduce" | |
| type: "ReLU" | |
| bottom: "inception_5b/3x3_reduce" | |
| top: "inception_5b/3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_5b/3x3" | |
| type: "Convolution" | |
| bottom: "inception_5b/3x3_reduce" | |
| top: "inception_5b/3x3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b/relu_3x3" | |
| type: "ReLU" | |
| bottom: "inception_5b/3x3" | |
| top: "inception_5b/3x3" | |
| } | |
| layer { | |
| name: "inception_5b/5x5_reduce" | |
| type: "Convolution" | |
| bottom: "inception_5a/output" | |
| top: "inception_5b/5x5_reduce" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.2 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b/relu_5x5_reduce" | |
| type: "ReLU" | |
| bottom: "inception_5b/5x5_reduce" | |
| top: "inception_5b/5x5_reduce" | |
| } | |
| layer { | |
| name: "inception_5b/5x5" | |
| type: "Convolution" | |
| bottom: "inception_5b/5x5_reduce" | |
| top: "inception_5b/5x5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b/relu_5x5" | |
| type: "ReLU" | |
| bottom: "inception_5b/5x5" | |
| top: "inception_5b/5x5" | |
| } | |
| layer { | |
| name: "inception_5b/pool" | |
| type: "Pooling" | |
| bottom: "inception_5a/output" | |
| top: "inception_5b/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_5b/pool_proj" | |
| type: "Convolution" | |
| bottom: "inception_5b/pool" | |
| top: "inception_5b/pool_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b/relu_pool_proj" | |
| type: "ReLU" | |
| bottom: "inception_5b/pool_proj" | |
| top: "inception_5b/pool_proj" | |
| } | |
| layer { | |
| name: "inception_5b/output" | |
| type: "Concat" | |
| bottom: "inception_5b/1x1" | |
| bottom: "inception_5b/3x3" | |
| bottom: "inception_5b/5x5" | |
| bottom: "inception_5b/pool_proj" | |
| top: "inception_5b/output" | |
| } | |
| layer { | |
| name: "pool5/7x7_s1" | |
| type: "Pooling" | |
| bottom: "inception_5b/output" | |
| top: "pool5/7x7_s1" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 7 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "pool5/drop_7x7_s1" | |
| type: "Dropout" | |
| bottom: "pool5/7x7_s1" | |
| top: "pool5/7x7_s1" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| layer { | |
| name: "loss3/classifier" | |
| type: "InnerProduct" | |
| bottom: "pool5/7x7_s1" | |
| top: "loss3/classifier" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 31 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "prob" | |
| type: "Softmax" | |
| bottom: "loss3/classifier" | |
| top: "prob" | |
| } |
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