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| name: "inception_bn" | |
| layer{ | |
| name: 'data' | |
| type: 'Python' | |
| top: 'data' | |
| top: 'label' | |
| python_param { | |
| module: 'data_layer' | |
| layer: 'DataLayer' | |
| } | |
| } | |
| # layer { | |
| # name: "data" | |
| # type: "Data" | |
| # top: "data" | |
| # top: "label" | |
| # include { | |
| # phase: TRAIN | |
| # } | |
| # transform_param { | |
| # mirror: true | |
| # crop_size: 227 | |
| # mean_value: 104 | |
| # mean_value: 117 | |
| # mean_value: 123 | |
| # } | |
| # data_param { | |
| # source: "/home/wenfahu/googlenet_triplet/lfw_lmdb/train_lmdb" | |
| # batch_size: 60 | |
| # backend: LMDB | |
| # } | |
| # } | |
| # layer { | |
| # name: "data" | |
| # type: "Data" | |
| # top: "data" | |
| # top: "label" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # transform_param { | |
| # mirror: false | |
| # crop_size: 227 | |
| # mean_value: 104 | |
| # mean_value: 117 | |
| # mean_value: 123 | |
| # } | |
| # data_param { | |
| # source: "/home/wenfahu/googlenet_triplet/lfw_lmdb/val_lmdb" | |
| # batch_size: 20 | |
| # backend: LMDB | |
| # } | |
| # } | |
| layer { | |
| name: "conv1_7x7_s2" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1_7x7_s2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_7x7_s2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv1_7x7_s2" | |
| top: "conv1_7x7_s2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "conv1_7x7_relu" | |
| 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: "conv2_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "pool1_3x3_s2" | |
| top: "conv2_3x3_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_3x3_reduce" | |
| top: "conv2_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "conv2_3x3_reduce_relu" | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_3x3" | |
| top: "conv2_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "conv2_3x3_relu" | |
| type: "ReLU" | |
| bottom: "conv2_3x3" | |
| top: "conv2_3x3" | |
| } | |
| layer { | |
| name: "pool2_3x3_s2" | |
| type: "Pooling" | |
| bottom: "conv2_3x3" | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3a_1x1" | |
| top: "inception_3a_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3a_3x3_reduce" | |
| top: "inception_3a_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3a_3x3" | |
| top: "inception_3a_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3a_5x5_reduce" | |
| top: "inception_3a_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3a_5x5" | |
| top: "inception_3a_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3a_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3a_pool_proj" | |
| top: "inception_3a_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3b_1x1" | |
| top: "inception_3b_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3b_3x3_reduce" | |
| top: "inception_3b_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3b_3x3" | |
| top: "inception_3b_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3b_5x5_reduce" | |
| top: "inception_3b_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3b_5x5" | |
| top: "inception_3b_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_3b_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_3b_pool_proj" | |
| top: "inception_3b_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4a_1x1" | |
| top: "inception_4a_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4a_3x3_reduce" | |
| top: "inception_4a_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 208 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4a_3x3" | |
| top: "inception_4a_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4a_5x5_reduce" | |
| top: "inception_4a_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4a_5x5" | |
| top: "inception_4a_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4a_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4a_pool_proj" | |
| top: "inception_4a_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| # decay_mult: 0 | |
| # } | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # convolution_param { | |
| # num_output: 128 | |
| # pad: 0 | |
| # kernel_size: 1 | |
| # stride: 1 | |
| # weight_filler { | |
| # type: "xavier" | |
| # std: 1 | |
| # } | |
| # bias_filler { | |
| # type: "constant" | |
| # value: 0.2 | |
| # } | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss1_conv_bn" | |
| # type: "BatchNorm" | |
| # bottom: "loss1_conv" | |
| # top: "loss1_conv" | |
| # batch_norm_param { | |
| # use_global_stats: false | |
| # } | |
| # } | |
| # 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: 0 | |
| # decay_mult: 0 | |
| # } | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # inner_product_param { | |
| # num_output: 1024 | |
| # weight_filler { | |
| # type: "xavier" | |
| # std: 1 | |
| # } | |
| # 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: 0 | |
| # decay_mult: 0 | |
| # } | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # inner_product_param { | |
| # num_output: 1000 | |
| # weight_filler { | |
| # type: "xavier" | |
| # } | |
| # bias_filler { | |
| # type: "constant" | |
| # value: 0 | |
| # } | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss1_loss" | |
| # type: "SoftmaxWithLoss" | |
| # bottom: "loss1_classifier" | |
| # bottom: "label" | |
| # top: "loss1_loss" | |
| # loss_weight: 0.3 | |
| # } | |
| # layer { | |
| # name: "loss1_accuracy_top1" | |
| # type: "Accuracy" | |
| # bottom: "loss1_classifier" | |
| # bottom: "label" | |
| # top: "loss1_accuracy_top1" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss1_accuracy_top5" | |
| # type: "Accuracy" | |
| # bottom: "loss1_classifier" | |
| # bottom: "label" | |
| # top: "loss1_accuracy_top5" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # accuracy_param { | |
| # top_k: 5 | |
| # } | |
| # } | |
| layer { | |
| name: "inception_4b_1x1" | |
| type: "Convolution" | |
| bottom: "inception_4a_output" | |
| top: "inception_4b_1x1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4b_1x1" | |
| top: "inception_4b_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 112 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4b_3x3_reduce" | |
| top: "inception_4b_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 224 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4b_3x3" | |
| top: "inception_4b_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4b_5x5_reduce" | |
| top: "inception_4b_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4b_5x5" | |
| top: "inception_4b_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4b_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4b_pool_proj" | |
| top: "inception_4b_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4c_1x1" | |
| top: "inception_4c_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4c_3x3_reduce" | |
| top: "inception_4c_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4c_3x3" | |
| top: "inception_4c_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4c_5x5_reduce" | |
| top: "inception_4c_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4c_5x5" | |
| top: "inception_4c_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4c_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4c_pool_proj" | |
| top: "inception_4c_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 112 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4d_1x1" | |
| top: "inception_4d_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4d_3x3_reduce" | |
| top: "inception_4d_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 288 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4d_3x3" | |
| top: "inception_4d_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4d_5x5_reduce" | |
| top: "inception_4d_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4d_5x5" | |
| top: "inception_4d_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4d_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4d_pool_proj" | |
| top: "inception_4d_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| # decay_mult: 0 | |
| # } | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # convolution_param { | |
| # num_output: 128 | |
| # pad: 0 | |
| # kernel_size: 1 | |
| # stride: 1 | |
| # weight_filler { | |
| # type: "xavier" | |
| # std: 1 | |
| # } | |
| # bias_filler { | |
| # type: "constant" | |
| # value: 0.2 | |
| # } | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss2_conv_bn" | |
| # type: "BatchNorm" | |
| # bottom: "loss2_conv" | |
| # top: "loss2_conv" | |
| # batch_norm_param { | |
| # use_global_stats: false | |
| # } | |
| # } | |
| # 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: 0 | |
| # decay_mult: 0 | |
| # } | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # inner_product_param { | |
| # num_output: 1024 | |
| # weight_filler { | |
| # type: "xavier" | |
| # std: 1 | |
| # } | |
| # 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: 0 | |
| # decay_mult: 0 | |
| # } | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # inner_product_param { | |
| # num_output: 1000 | |
| # weight_filler { | |
| # type: "xavier" | |
| # } | |
| # bias_filler { | |
| # type: "constant" | |
| # value: 0 | |
| # } | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss2_loss" | |
| # type: "SoftmaxWithLoss" | |
| # bottom: "loss2_classifier" | |
| # bottom: "label" | |
| # top: "loss2_loss" | |
| # loss_weight: 0.3 | |
| # } | |
| # layer { | |
| # name: "loss2_accuracy_top1" | |
| # type: "Accuracy" | |
| # bottom: "loss2_classifier" | |
| # bottom: "label" | |
| # top: "loss2_accuracy_top1" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss2_accuracy_top5" | |
| # type: "Accuracy" | |
| # bottom: "loss2_classifier" | |
| # bottom: "label" | |
| # top: "loss2_accuracy_top5" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # accuracy_param { | |
| # top_k: 5 | |
| # } | |
| # } | |
| layer { | |
| name: "inception_4e_1x1" | |
| type: "Convolution" | |
| bottom: "inception_4d_output" | |
| top: "inception_4e_1x1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4e_1x1" | |
| top: "inception_4e_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4e_3x3_reduce" | |
| top: "inception_4e_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4e_3x3" | |
| top: "inception_4e_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4e_5x5_reduce" | |
| top: "inception_4e_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4e_5x5" | |
| top: "inception_4e_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_4e_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_4e_pool_proj" | |
| top: "inception_4e_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5a_1x1" | |
| top: "inception_5a_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5a_3x3_reduce" | |
| top: "inception_5a_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5a_3x3" | |
| top: "inception_5a_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5a_5x5_reduce" | |
| top: "inception_5a_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5a_5x5" | |
| top: "inception_5a_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5a_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5a_pool_proj" | |
| top: "inception_5a_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5b_1x1" | |
| top: "inception_5b_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5b_3x3_reduce" | |
| top: "inception_5b_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5b_3x3" | |
| top: "inception_5b_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b_5x5_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5b_5x5_reduce" | |
| top: "inception_5b_5x5_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b_5x5_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5b_5x5" | |
| top: "inception_5b_5x5" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_5b_pool_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_5b_pool_proj" | |
| top: "inception_5b_pool_proj" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| 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_tune" | |
| type: "Pooling" | |
| bottom: "inception_5b_output" | |
| top: "pool5_7x7_s1_tune" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 7 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "pool5_drop_7x7_s1" | |
| type: "Dropout" | |
| bottom: "pool5_7x7_s1_tune" | |
| top: "pool5_7x7_s1_tune" | |
| dropout_param { | |
| dropout_ratio: 0.4 | |
| } | |
| } | |
| #### triplet loss ##### | |
| layer{ | |
| name: "embedding" | |
| type: "InnerProduct" | |
| bottom: "pool5_7x7_s1_tune" | |
| top: "embedding" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 128 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler{ | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "norm2" | |
| type: "Python" | |
| bottom: "embedding" | |
| top: "norm2" | |
| python_param { | |
| module: "l2norm_layer" | |
| layer: "L2NormLayer" | |
| } | |
| } | |
| layer { | |
| name: "tripletsample" | |
| type: "Python" | |
| bottom: "norm2" | |
| bottom: "label" | |
| top: "anchor" | |
| top: "positive" | |
| top: "negative" | |
| python_param { | |
| module: "tripletsample_layer" | |
| layer: "TripletSampleLayer" | |
| } | |
| } | |
| layer { | |
| name: "tripletloss" | |
| type: "Python" | |
| bottom: "anchor" | |
| bottom: "positive" | |
| bottom: "negative" | |
| top: "loss" | |
| python_param { | |
| module: "tripletloss_layer" | |
| layer: "TripletLayer" | |
| param_str: "'margin': 0.2" | |
| } | |
| loss_weight: 1 | |
| } | |
| #### softmax loss ##### | |
| # layer { | |
| # name: "loss3_classifier_390" | |
| # type: "InnerProduct" | |
| # bottom: "pool5_7x7_s1" | |
| # top: "loss3_classifier_390" | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # param { | |
| # lr_mult: 0 | |
| # decay_mult: 0 | |
| # } | |
| # inner_product_param { | |
| # num_output: 390 | |
| # weight_filler { | |
| # type: "xavier" | |
| # } | |
| # bias_filler { | |
| # type: "constant" | |
| # value: 0 | |
| # } | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss3_loss" | |
| # type: "SoftmaxWithLoss" | |
| # bottom: "loss3_classifier_390" | |
| # bottom: "label" | |
| # top: "loss3_loss" | |
| # loss_weight: 1 | |
| # } | |
| # layer { | |
| # name: "loss3_accuracy_top1" | |
| # type: "Accuracy" | |
| # bottom: "loss3_classifier_390" | |
| # bottom: "label" | |
| # top: "loss3_accuracy_top1" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # } | |
| # layer { | |
| # name: "loss3_accuracy_top5" | |
| # type: "Accuracy" | |
| # bottom: "loss3_classifier_390" | |
| # bottom: "label" | |
| # top: "loss3_accuracy_top5" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # accuracy_param { | |
| # top_k: 5 | |
| # } | |
| # } |
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