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Caffe train_val for learning inception-resnet-v2 - 2ndtry
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| name: "Inception_Resnet2_Imagenet" | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: true | |
| crop_size: 299 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| } | |
| data_param { | |
| source: "/train_imagenet_328_lmdb" | |
| batch_size: 16 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mirror: false | |
| crop_size: 299 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| } | |
| data_param { | |
| source: "/val_imagenet_328_lmdb" | |
| batch_size: 3 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "conv1_3x3_s2" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1_3x3_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_3x3_s2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv1_3x3_s2" | |
| top: "conv1_3x3_s2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "conv1_3x3_s2_scale" | |
| type: "Scale" | |
| bottom: "conv1_3x3_s2" | |
| top: "conv1_3x3_s2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv1_3x3_s2_relu" | |
| type: "ReLU" | |
| bottom: "conv1_3x3_s2" | |
| top: "conv1_3x3_s2" | |
| } | |
| layer { | |
| name: "conv2_3x3_s1" | |
| type: "Convolution" | |
| bottom: "conv1_3x3_s2" | |
| top: "conv2_3x3_s1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3x3_s1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_3x3_s1" | |
| top: "conv2_3x3_s1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "conv2_3x3_s1_scale" | |
| type: "Scale" | |
| bottom: "conv2_3x3_s1" | |
| top: "conv2_3x3_s1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_3x3_s1_relu" | |
| type: "ReLU" | |
| bottom: "conv2_3x3_s1" | |
| top: "conv2_3x3_s1" | |
| } | |
| layer { | |
| name: "conv3_3x3_s1" | |
| type: "Convolution" | |
| bottom: "conv2_3x3_s1" | |
| top: "conv3_3x3_s1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_3x3_s1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_3x3_s1" | |
| top: "conv3_3x3_s1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "conv3_3x3_s1_scale" | |
| type: "Scale" | |
| bottom: "conv3_3x3_s1" | |
| top: "conv3_3x3_s1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_3x3_s1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_3x3_s1" | |
| top: "conv3_3x3_s1" | |
| } | |
| layer { | |
| name: "inception_stem1_3x3_s2" | |
| type: "Convolution" | |
| bottom: "conv3_3x3_s1" | |
| top: "inception_stem1_3x3_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_stem1_3x3_s2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem1_3x3_s2" | |
| top: "inception_stem1_3x3_s2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem1_3x3_s2_scale" | |
| type: "Scale" | |
| bottom: "inception_stem1_3x3_s2" | |
| top: "inception_stem1_3x3_s2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem1_3x3_s2_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem1_3x3_s2" | |
| top: "inception_stem1_3x3_s2" | |
| } | |
| layer { | |
| name: "inception_stem1_pool" | |
| type: "Pooling" | |
| bottom: "conv3_3x3_s1" | |
| top: "inception_stem1_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "inception_stem1" | |
| type: "Concat" | |
| bottom: "inception_stem1_3x3_s2" | |
| bottom: "inception_stem1_pool" | |
| top: "inception_stem1" | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_stem1" | |
| top: "inception_stem2_3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem2_3x3_reduce" | |
| top: "inception_stem2_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_stem2_3x3_reduce" | |
| top: "inception_stem2_3x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem2_3x3_reduce" | |
| top: "inception_stem2_3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_stem2_3x3" | |
| type: "Convolution" | |
| bottom: "inception_stem2_3x3_reduce" | |
| top: "inception_stem2_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem2_3x3" | |
| top: "inception_stem2_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_scale" | |
| type: "Scale" | |
| bottom: "inception_stem2_3x3" | |
| top: "inception_stem2_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem2_3x3" | |
| top: "inception_stem2_3x3" | |
| } | |
| layer { | |
| name: "inception_stem2_7x1_reduce" | |
| type: "Convolution" | |
| bottom: "inception_stem1" | |
| top: "inception_stem2_7x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_7x1_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem2_7x1_reduce" | |
| top: "inception_stem2_7x1_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_7x1_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_stem2_7x1_reduce" | |
| top: "inception_stem2_7x1_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_7x1_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem2_7x1_reduce" | |
| top: "inception_stem2_7x1_reduce" | |
| } | |
| layer { | |
| name: "inception_stem2_7x1" | |
| type: "Convolution" | |
| bottom: "inception_stem2_7x1_reduce" | |
| top: "inception_stem2_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem2_7x1" | |
| top: "inception_stem2_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_stem2_7x1" | |
| top: "inception_stem2_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem2_7x1" | |
| top: "inception_stem2_7x1" | |
| } | |
| layer { | |
| name: "inception_stem2_1x7" | |
| type: "Convolution" | |
| bottom: "inception_stem2_7x1" | |
| top: "inception_stem2_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem2_1x7" | |
| top: "inception_stem2_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_stem2_1x7" | |
| top: "inception_stem2_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem2_1x7" | |
| top: "inception_stem2_1x7" | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_2" | |
| type: "Convolution" | |
| bottom: "inception_stem2_1x7" | |
| top: "inception_stem2_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem2_3x3_2" | |
| top: "inception_stem2_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "inception_stem2_3x3_2" | |
| top: "inception_stem2_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem2_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem2_3x3_2" | |
| top: "inception_stem2_3x3_2" | |
| } | |
| layer { | |
| name: "inception_stem2" | |
| type: "Concat" | |
| bottom: "inception_stem2_3x3" | |
| bottom: "inception_stem2_3x3_2" | |
| top: "inception_stem2" | |
| } | |
| layer { | |
| name: "inception_stem3_3x3_s2" | |
| type: "Convolution" | |
| bottom: "inception_stem2" | |
| top: "inception_stem3_3x3_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_stem3_3x3_s2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_stem3_3x3_s2" | |
| top: "inception_stem3_3x3_s2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_stem3_3x3_s2_scale" | |
| type: "Scale" | |
| bottom: "inception_stem3_3x3_s2" | |
| top: "inception_stem3_3x3_s2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_stem3_3x3_s2_relu" | |
| type: "ReLU" | |
| bottom: "inception_stem3_3x3_s2" | |
| top: "inception_stem3_3x3_s2" | |
| } | |
| layer { | |
| name: "inception_stem3_pool" | |
| type: "Pooling" | |
| bottom: "inception_stem2" | |
| top: "inception_stem3_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "inception_stem3" | |
| type: "Concat" | |
| bottom: "inception_stem3_3x3_s2" | |
| bottom: "inception_stem3_pool" | |
| top: "inception_stem3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_1x1" | |
| type: "Convolution" | |
| bottom: "inception_stem3" | |
| top: "inception_resnet_v2_a1_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a1_1x1" | |
| top: "inception_resnet_v2_a1_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a1_1x1" | |
| top: "inception_resnet_v2_a1_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a1_1x1" | |
| top: "inception_resnet_v2_a1_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_stem3" | |
| top: "inception_resnet_v2_a1_3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a1_3x3_reduce" | |
| top: "inception_resnet_v2_a1_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a1_3x3_reduce" | |
| top: "inception_resnet_v2_a1_3x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a1_3x3_reduce" | |
| top: "inception_resnet_v2_a1_3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a1_3x3_reduce" | |
| top: "inception_resnet_v2_a1_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a1_3x3" | |
| top: "inception_resnet_v2_a1_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a1_3x3" | |
| top: "inception_resnet_v2_a1_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a1_3x3" | |
| top: "inception_resnet_v2_a1_3x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2_reduce" | |
| type: "Convolution" | |
| bottom: "inception_stem3" | |
| top: "inception_resnet_v2_a1_3x3_2_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a1_3x3_2_reduce" | |
| top: "inception_resnet_v2_a1_3x3_2_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a1_3x3_2_reduce" | |
| top: "inception_resnet_v2_a1_3x3_2_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a1_3x3_2_reduce" | |
| top: "inception_resnet_v2_a1_3x3_2_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a1_3x3_2_reduce" | |
| top: "inception_resnet_v2_a1_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a1_3x3_2" | |
| top: "inception_resnet_v2_a1_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a1_3x3_2" | |
| top: "inception_resnet_v2_a1_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a1_3x3_2" | |
| top: "inception_resnet_v2_a1_3x3_2" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a1_3x3_2" | |
| top: "inception_resnet_v2_a1_3x3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a1_3x3_3" | |
| top: "inception_resnet_v2_a1_3x3_3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a1_3x3_3" | |
| top: "inception_resnet_v2_a1_3x3_3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_3x3_3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a1_3x3_3" | |
| top: "inception_resnet_v2_a1_3x3_3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_a1_1x1" | |
| bottom: "inception_resnet_v2_a1_3x3" | |
| bottom: "inception_resnet_v2_a1_3x3_3" | |
| top: "inception_resnet_v2_a1_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a1_concat" | |
| top: "inception_resnet_v2_a1_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a1_1x1_2" | |
| top: "inception_resnet_v2_a1_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a1_1x1_2" | |
| top: "inception_resnet_v2_a1_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a1_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_stem3" | |
| bottom: "inception_resnet_v2_a1_1x1_2" | |
| top: "inception_resnet_v2_a1_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a1_residual_eltwise" | |
| top: "inception_resnet_v2_a2_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a2_1x1" | |
| top: "inception_resnet_v2_a2_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a2_1x1" | |
| top: "inception_resnet_v2_a2_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a2_1x1" | |
| top: "inception_resnet_v2_a2_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a1_residual_eltwise" | |
| top: "inception_resnet_v2_a2_3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a2_3x3_reduce" | |
| top: "inception_resnet_v2_a2_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a2_3x3_reduce" | |
| top: "inception_resnet_v2_a2_3x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a2_3x3_reduce" | |
| top: "inception_resnet_v2_a2_3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a2_3x3_reduce" | |
| top: "inception_resnet_v2_a2_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a2_3x3" | |
| top: "inception_resnet_v2_a2_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a2_3x3" | |
| top: "inception_resnet_v2_a2_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a2_3x3" | |
| top: "inception_resnet_v2_a2_3x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a1_residual_eltwise" | |
| top: "inception_resnet_v2_a2_3x3_2_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a2_3x3_2_reduce" | |
| top: "inception_resnet_v2_a2_3x3_2_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a2_3x3_2_reduce" | |
| top: "inception_resnet_v2_a2_3x3_2_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a2_3x3_2_reduce" | |
| top: "inception_resnet_v2_a2_3x3_2_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a2_3x3_2_reduce" | |
| top: "inception_resnet_v2_a2_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a2_3x3_2" | |
| top: "inception_resnet_v2_a2_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a2_3x3_2" | |
| top: "inception_resnet_v2_a2_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a2_3x3_2" | |
| top: "inception_resnet_v2_a2_3x3_2" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a2_3x3_2" | |
| top: "inception_resnet_v2_a2_3x3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a2_3x3_3" | |
| top: "inception_resnet_v2_a2_3x3_3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a2_3x3_3" | |
| top: "inception_resnet_v2_a2_3x3_3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_3x3_3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a2_3x3_3" | |
| top: "inception_resnet_v2_a2_3x3_3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_a2_1x1" | |
| bottom: "inception_resnet_v2_a2_3x3" | |
| bottom: "inception_resnet_v2_a2_3x3_3" | |
| top: "inception_resnet_v2_a2_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a2_concat" | |
| top: "inception_resnet_v2_a2_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a2_1x1_2" | |
| top: "inception_resnet_v2_a2_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a2_1x1_2" | |
| top: "inception_resnet_v2_a2_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a2_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_a1_residual_eltwise" | |
| bottom: "inception_resnet_v2_a2_1x1_2" | |
| top: "inception_resnet_v2_a2_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a2_residual_eltwise" | |
| top: "inception_resnet_v2_a3_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a3_1x1" | |
| top: "inception_resnet_v2_a3_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a3_1x1" | |
| top: "inception_resnet_v2_a3_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a3_1x1" | |
| top: "inception_resnet_v2_a3_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a2_residual_eltwise" | |
| top: "inception_resnet_v2_a3_3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a3_3x3_reduce" | |
| top: "inception_resnet_v2_a3_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a3_3x3_reduce" | |
| top: "inception_resnet_v2_a3_3x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a3_3x3_reduce" | |
| top: "inception_resnet_v2_a3_3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a3_3x3_reduce" | |
| top: "inception_resnet_v2_a3_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a3_3x3" | |
| top: "inception_resnet_v2_a3_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a3_3x3" | |
| top: "inception_resnet_v2_a3_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a3_3x3" | |
| top: "inception_resnet_v2_a3_3x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a2_residual_eltwise" | |
| top: "inception_resnet_v2_a3_3x3_2_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a3_3x3_2_reduce" | |
| top: "inception_resnet_v2_a3_3x3_2_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a3_3x3_2_reduce" | |
| top: "inception_resnet_v2_a3_3x3_2_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a3_3x3_2_reduce" | |
| top: "inception_resnet_v2_a3_3x3_2_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a3_3x3_2_reduce" | |
| top: "inception_resnet_v2_a3_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a3_3x3_2" | |
| top: "inception_resnet_v2_a3_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a3_3x3_2" | |
| top: "inception_resnet_v2_a3_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a3_3x3_2" | |
| top: "inception_resnet_v2_a3_3x3_2" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a3_3x3_2" | |
| top: "inception_resnet_v2_a3_3x3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a3_3x3_3" | |
| top: "inception_resnet_v2_a3_3x3_3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a3_3x3_3" | |
| top: "inception_resnet_v2_a3_3x3_3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_3x3_3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a3_3x3_3" | |
| top: "inception_resnet_v2_a3_3x3_3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_a3_1x1" | |
| bottom: "inception_resnet_v2_a3_3x3" | |
| bottom: "inception_resnet_v2_a3_3x3_3" | |
| top: "inception_resnet_v2_a3_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a3_concat" | |
| top: "inception_resnet_v2_a3_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a3_1x1_2" | |
| top: "inception_resnet_v2_a3_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a3_1x1_2" | |
| top: "inception_resnet_v2_a3_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a3_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_a2_residual_eltwise" | |
| bottom: "inception_resnet_v2_a3_1x1_2" | |
| top: "inception_resnet_v2_a3_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a3_residual_eltwise" | |
| top: "inception_resnet_v2_a4_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a4_1x1" | |
| top: "inception_resnet_v2_a4_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a4_1x1" | |
| top: "inception_resnet_v2_a4_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a4_1x1" | |
| top: "inception_resnet_v2_a4_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a3_residual_eltwise" | |
| top: "inception_resnet_v2_a4_3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a4_3x3_reduce" | |
| top: "inception_resnet_v2_a4_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a4_3x3_reduce" | |
| top: "inception_resnet_v2_a4_3x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a4_3x3_reduce" | |
| top: "inception_resnet_v2_a4_3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a4_3x3_reduce" | |
| top: "inception_resnet_v2_a4_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a4_3x3" | |
| top: "inception_resnet_v2_a4_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a4_3x3" | |
| top: "inception_resnet_v2_a4_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a4_3x3" | |
| top: "inception_resnet_v2_a4_3x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a3_residual_eltwise" | |
| top: "inception_resnet_v2_a4_3x3_2_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a4_3x3_2_reduce" | |
| top: "inception_resnet_v2_a4_3x3_2_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a4_3x3_2_reduce" | |
| top: "inception_resnet_v2_a4_3x3_2_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a4_3x3_2_reduce" | |
| top: "inception_resnet_v2_a4_3x3_2_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a4_3x3_2_reduce" | |
| top: "inception_resnet_v2_a4_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a4_3x3_2" | |
| top: "inception_resnet_v2_a4_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a4_3x3_2" | |
| top: "inception_resnet_v2_a4_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a4_3x3_2" | |
| top: "inception_resnet_v2_a4_3x3_2" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a4_3x3_2" | |
| top: "inception_resnet_v2_a4_3x3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a4_3x3_3" | |
| top: "inception_resnet_v2_a4_3x3_3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a4_3x3_3" | |
| top: "inception_resnet_v2_a4_3x3_3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_3x3_3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a4_3x3_3" | |
| top: "inception_resnet_v2_a4_3x3_3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_a4_1x1" | |
| bottom: "inception_resnet_v2_a4_3x3" | |
| bottom: "inception_resnet_v2_a4_3x3_3" | |
| top: "inception_resnet_v2_a4_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a4_concat" | |
| top: "inception_resnet_v2_a4_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a4_1x1_2" | |
| top: "inception_resnet_v2_a4_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a4_1x1_2" | |
| top: "inception_resnet_v2_a4_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a4_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_a3_residual_eltwise" | |
| bottom: "inception_resnet_v2_a4_1x1_2" | |
| top: "inception_resnet_v2_a4_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a4_residual_eltwise" | |
| top: "inception_resnet_v2_a5_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a5_1x1" | |
| top: "inception_resnet_v2_a5_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a5_1x1" | |
| top: "inception_resnet_v2_a5_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a5_1x1" | |
| top: "inception_resnet_v2_a5_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a4_residual_eltwise" | |
| top: "inception_resnet_v2_a5_3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a5_3x3_reduce" | |
| top: "inception_resnet_v2_a5_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a5_3x3_reduce" | |
| top: "inception_resnet_v2_a5_3x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a5_3x3_reduce" | |
| top: "inception_resnet_v2_a5_3x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a5_3x3_reduce" | |
| top: "inception_resnet_v2_a5_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a5_3x3" | |
| top: "inception_resnet_v2_a5_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a5_3x3" | |
| top: "inception_resnet_v2_a5_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a5_3x3" | |
| top: "inception_resnet_v2_a5_3x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a4_residual_eltwise" | |
| top: "inception_resnet_v2_a5_3x3_2_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a5_3x3_2_reduce" | |
| top: "inception_resnet_v2_a5_3x3_2_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a5_3x3_2_reduce" | |
| top: "inception_resnet_v2_a5_3x3_2_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a5_3x3_2_reduce" | |
| top: "inception_resnet_v2_a5_3x3_2_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a5_3x3_2_reduce" | |
| top: "inception_resnet_v2_a5_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a5_3x3_2" | |
| top: "inception_resnet_v2_a5_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a5_3x3_2" | |
| top: "inception_resnet_v2_a5_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a5_3x3_2" | |
| top: "inception_resnet_v2_a5_3x3_2" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a5_3x3_2" | |
| top: "inception_resnet_v2_a5_3x3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a5_3x3_3" | |
| top: "inception_resnet_v2_a5_3x3_3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a5_3x3_3" | |
| top: "inception_resnet_v2_a5_3x3_3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_3x3_3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_a5_3x3_3" | |
| top: "inception_resnet_v2_a5_3x3_3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_a5_1x1" | |
| bottom: "inception_resnet_v2_a5_3x3" | |
| bottom: "inception_resnet_v2_a5_3x3_3" | |
| top: "inception_resnet_v2_a5_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a5_concat" | |
| top: "inception_resnet_v2_a5_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_a5_1x1_2" | |
| top: "inception_resnet_v2_a5_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_a5_1x1_2" | |
| top: "inception_resnet_v2_a5_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_a5_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_a4_residual_eltwise" | |
| bottom: "inception_resnet_v2_a5_1x1_2" | |
| top: "inception_resnet_v2_a5_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_pool" | |
| type: "Pooling" | |
| bottom: "inception_resnet_v2_a5_residual_eltwise" | |
| top: "reduction_a_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a5_residual_eltwise" | |
| top: "reduction_a_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_a_3x3" | |
| top: "reduction_a_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_scale" | |
| type: "Scale" | |
| bottom: "reduction_a_3x3" | |
| top: "reduction_a_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_relu" | |
| type: "ReLU" | |
| bottom: "reduction_a_3x3" | |
| top: "reduction_a_3x3" | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_a5_residual_eltwise" | |
| top: "reduction_a_3x3_2_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_a_3x3_2_reduce" | |
| top: "reduction_a_3x3_2_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2_reduce_scale" | |
| type: "Scale" | |
| bottom: "reduction_a_3x3_2_reduce" | |
| top: "reduction_a_3x3_2_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2_reduce_relu" | |
| type: "ReLU" | |
| bottom: "reduction_a_3x3_2_reduce" | |
| top: "reduction_a_3x3_2_reduce" | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2" | |
| type: "Convolution" | |
| bottom: "reduction_a_3x3_2_reduce" | |
| top: "reduction_a_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_a_3x3_2" | |
| top: "reduction_a_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "reduction_a_3x3_2" | |
| top: "reduction_a_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "reduction_a_3x3_2" | |
| top: "reduction_a_3x3_2" | |
| } | |
| layer { | |
| name: "reduction_a_3x3_3" | |
| type: "Convolution" | |
| bottom: "reduction_a_3x3_2" | |
| top: "reduction_a_3x3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_a_3x3_3" | |
| top: "reduction_a_3x3_3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_3_scale" | |
| type: "Scale" | |
| bottom: "reduction_a_3x3_3" | |
| top: "reduction_a_3x3_3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_a_3x3_3_relu" | |
| type: "ReLU" | |
| bottom: "reduction_a_3x3_3" | |
| top: "reduction_a_3x3_3" | |
| } | |
| layer { | |
| name: "reduction_a_concat" | |
| type: "Concat" | |
| bottom: "reduction_a_pool" | |
| bottom: "reduction_a_3x3" | |
| bottom: "reduction_a_3x3_3" | |
| top: "reduction_a_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x1" | |
| type: "Convolution" | |
| bottom: "reduction_a_concat" | |
| top: "inception_resnet_v2_b1_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b1_1x1" | |
| top: "inception_resnet_v2_b1_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b1_1x1" | |
| top: "inception_resnet_v2_b1_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b1_1x1" | |
| top: "inception_resnet_v2_b1_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "reduction_a_concat" | |
| top: "inception_resnet_v2_b1_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b1_1x7_reduce" | |
| top: "inception_resnet_v2_b1_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b1_1x7_reduce" | |
| top: "inception_resnet_v2_b1_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b1_1x7_reduce" | |
| top: "inception_resnet_v2_b1_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b1_1x7_reduce" | |
| top: "inception_resnet_v2_b1_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b1_1x7" | |
| top: "inception_resnet_v2_b1_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b1_1x7" | |
| top: "inception_resnet_v2_b1_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b1_1x7" | |
| top: "inception_resnet_v2_b1_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b1_1x7" | |
| top: "inception_resnet_v2_b1_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b1_7x1" | |
| top: "inception_resnet_v2_b1_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b1_7x1" | |
| top: "inception_resnet_v2_b1_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b1_7x1" | |
| top: "inception_resnet_v2_b1_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b1_1x1" | |
| bottom: "inception_resnet_v2_b1_7x1" | |
| top: "inception_resnet_v2_b1_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b1_concat" | |
| top: "inception_resnet_v2_b1_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b1_1x1_2" | |
| top: "inception_resnet_v2_b1_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b1_1x1_2" | |
| top: "inception_resnet_v2_b1_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b1_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "reduction_a_concat" | |
| bottom: "inception_resnet_v2_b1_1x1_2" | |
| top: "inception_resnet_v2_b1_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b1_residual_eltwise" | |
| top: "inception_resnet_v2_b2_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b2_1x1" | |
| top: "inception_resnet_v2_b2_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b2_1x1" | |
| top: "inception_resnet_v2_b2_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b2_1x1" | |
| top: "inception_resnet_v2_b2_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b1_residual_eltwise" | |
| top: "inception_resnet_v2_b2_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b2_1x7_reduce" | |
| top: "inception_resnet_v2_b2_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b2_1x7_reduce" | |
| top: "inception_resnet_v2_b2_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b2_1x7_reduce" | |
| top: "inception_resnet_v2_b2_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b2_1x7_reduce" | |
| top: "inception_resnet_v2_b2_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b2_1x7" | |
| top: "inception_resnet_v2_b2_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b2_1x7" | |
| top: "inception_resnet_v2_b2_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b2_1x7" | |
| top: "inception_resnet_v2_b2_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b2_1x7" | |
| top: "inception_resnet_v2_b2_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b2_7x1" | |
| top: "inception_resnet_v2_b2_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b2_7x1" | |
| top: "inception_resnet_v2_b2_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b2_7x1" | |
| top: "inception_resnet_v2_b2_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b2_1x1" | |
| bottom: "inception_resnet_v2_b2_7x1" | |
| top: "inception_resnet_v2_b2_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b2_concat" | |
| top: "inception_resnet_v2_b2_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b2_1x1_2" | |
| top: "inception_resnet_v2_b2_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b2_1x1_2" | |
| top: "inception_resnet_v2_b2_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b2_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b1_residual_eltwise" | |
| bottom: "inception_resnet_v2_b2_1x1_2" | |
| top: "inception_resnet_v2_b2_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b2_residual_eltwise" | |
| top: "inception_resnet_v2_b3_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b3_1x1" | |
| top: "inception_resnet_v2_b3_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b3_1x1" | |
| top: "inception_resnet_v2_b3_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b3_1x1" | |
| top: "inception_resnet_v2_b3_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b2_residual_eltwise" | |
| top: "inception_resnet_v2_b3_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b3_1x7_reduce" | |
| top: "inception_resnet_v2_b3_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b3_1x7_reduce" | |
| top: "inception_resnet_v2_b3_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b3_1x7_reduce" | |
| top: "inception_resnet_v2_b3_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b3_1x7_reduce" | |
| top: "inception_resnet_v2_b3_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b3_1x7" | |
| top: "inception_resnet_v2_b3_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b3_1x7" | |
| top: "inception_resnet_v2_b3_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b3_1x7" | |
| top: "inception_resnet_v2_b3_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b3_1x7" | |
| top: "inception_resnet_v2_b3_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b3_7x1" | |
| top: "inception_resnet_v2_b3_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b3_7x1" | |
| top: "inception_resnet_v2_b3_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b3_7x1" | |
| top: "inception_resnet_v2_b3_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b3_1x1" | |
| bottom: "inception_resnet_v2_b3_7x1" | |
| top: "inception_resnet_v2_b3_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b3_concat" | |
| top: "inception_resnet_v2_b3_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b3_1x1_2" | |
| top: "inception_resnet_v2_b3_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b3_1x1_2" | |
| top: "inception_resnet_v2_b3_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b3_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b2_residual_eltwise" | |
| bottom: "inception_resnet_v2_b3_1x1_2" | |
| top: "inception_resnet_v2_b3_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b3_residual_eltwise" | |
| top: "inception_resnet_v2_b4_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b4_1x1" | |
| top: "inception_resnet_v2_b4_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b4_1x1" | |
| top: "inception_resnet_v2_b4_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b4_1x1" | |
| top: "inception_resnet_v2_b4_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b3_residual_eltwise" | |
| top: "inception_resnet_v2_b4_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b4_1x7_reduce" | |
| top: "inception_resnet_v2_b4_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b4_1x7_reduce" | |
| top: "inception_resnet_v2_b4_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b4_1x7_reduce" | |
| top: "inception_resnet_v2_b4_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b4_1x7_reduce" | |
| top: "inception_resnet_v2_b4_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b4_1x7" | |
| top: "inception_resnet_v2_b4_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b4_1x7" | |
| top: "inception_resnet_v2_b4_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b4_1x7" | |
| top: "inception_resnet_v2_b4_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b4_1x7" | |
| top: "inception_resnet_v2_b4_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b4_7x1" | |
| top: "inception_resnet_v2_b4_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b4_7x1" | |
| top: "inception_resnet_v2_b4_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b4_7x1" | |
| top: "inception_resnet_v2_b4_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b4_1x1" | |
| bottom: "inception_resnet_v2_b4_7x1" | |
| top: "inception_resnet_v2_b4_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b4_concat" | |
| top: "inception_resnet_v2_b4_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b4_1x1_2" | |
| top: "inception_resnet_v2_b4_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b4_1x1_2" | |
| top: "inception_resnet_v2_b4_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b4_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b3_residual_eltwise" | |
| bottom: "inception_resnet_v2_b4_1x1_2" | |
| top: "inception_resnet_v2_b4_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b4_residual_eltwise" | |
| top: "inception_resnet_v2_b5_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b5_1x1" | |
| top: "inception_resnet_v2_b5_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b5_1x1" | |
| top: "inception_resnet_v2_b5_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b5_1x1" | |
| top: "inception_resnet_v2_b5_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b4_residual_eltwise" | |
| top: "inception_resnet_v2_b5_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b5_1x7_reduce" | |
| top: "inception_resnet_v2_b5_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b5_1x7_reduce" | |
| top: "inception_resnet_v2_b5_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b5_1x7_reduce" | |
| top: "inception_resnet_v2_b5_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b5_1x7_reduce" | |
| top: "inception_resnet_v2_b5_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b5_1x7" | |
| top: "inception_resnet_v2_b5_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b5_1x7" | |
| top: "inception_resnet_v2_b5_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b5_1x7" | |
| top: "inception_resnet_v2_b5_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b5_1x7" | |
| top: "inception_resnet_v2_b5_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b5_7x1" | |
| top: "inception_resnet_v2_b5_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b5_7x1" | |
| top: "inception_resnet_v2_b5_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b5_7x1" | |
| top: "inception_resnet_v2_b5_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b5_1x1" | |
| bottom: "inception_resnet_v2_b5_7x1" | |
| top: "inception_resnet_v2_b5_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b5_concat" | |
| top: "inception_resnet_v2_b5_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b5_1x1_2" | |
| top: "inception_resnet_v2_b5_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b5_1x1_2" | |
| top: "inception_resnet_v2_b5_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b5_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b4_residual_eltwise" | |
| bottom: "inception_resnet_v2_b5_1x1_2" | |
| top: "inception_resnet_v2_b5_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b5_residual_eltwise" | |
| top: "inception_resnet_v2_b6_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b6_1x1" | |
| top: "inception_resnet_v2_b6_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b6_1x1" | |
| top: "inception_resnet_v2_b6_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b6_1x1" | |
| top: "inception_resnet_v2_b6_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b5_residual_eltwise" | |
| top: "inception_resnet_v2_b6_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b6_1x7_reduce" | |
| top: "inception_resnet_v2_b6_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b6_1x7_reduce" | |
| top: "inception_resnet_v2_b6_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b6_1x7_reduce" | |
| top: "inception_resnet_v2_b6_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b6_1x7_reduce" | |
| top: "inception_resnet_v2_b6_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b6_1x7" | |
| top: "inception_resnet_v2_b6_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b6_1x7" | |
| top: "inception_resnet_v2_b6_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b6_1x7" | |
| top: "inception_resnet_v2_b6_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b6_1x7" | |
| top: "inception_resnet_v2_b6_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b6_7x1" | |
| top: "inception_resnet_v2_b6_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b6_7x1" | |
| top: "inception_resnet_v2_b6_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b6_7x1" | |
| top: "inception_resnet_v2_b6_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b6_1x1" | |
| bottom: "inception_resnet_v2_b6_7x1" | |
| top: "inception_resnet_v2_b6_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b6_concat" | |
| top: "inception_resnet_v2_b6_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b6_1x1_2" | |
| top: "inception_resnet_v2_b6_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b6_1x1_2" | |
| top: "inception_resnet_v2_b6_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b6_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b5_residual_eltwise" | |
| bottom: "inception_resnet_v2_b6_1x1_2" | |
| top: "inception_resnet_v2_b6_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b6_residual_eltwise" | |
| top: "inception_resnet_v2_b7_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b7_1x1" | |
| top: "inception_resnet_v2_b7_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b7_1x1" | |
| top: "inception_resnet_v2_b7_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b7_1x1" | |
| top: "inception_resnet_v2_b7_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b6_residual_eltwise" | |
| top: "inception_resnet_v2_b7_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b7_1x7_reduce" | |
| top: "inception_resnet_v2_b7_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b7_1x7_reduce" | |
| top: "inception_resnet_v2_b7_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b7_1x7_reduce" | |
| top: "inception_resnet_v2_b7_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b7_1x7_reduce" | |
| top: "inception_resnet_v2_b7_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b7_1x7" | |
| top: "inception_resnet_v2_b7_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b7_1x7" | |
| top: "inception_resnet_v2_b7_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b7_1x7" | |
| top: "inception_resnet_v2_b7_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b7_1x7" | |
| top: "inception_resnet_v2_b7_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b7_7x1" | |
| top: "inception_resnet_v2_b7_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b7_7x1" | |
| top: "inception_resnet_v2_b7_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b7_7x1" | |
| top: "inception_resnet_v2_b7_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b7_1x1" | |
| bottom: "inception_resnet_v2_b7_7x1" | |
| top: "inception_resnet_v2_b7_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b7_concat" | |
| top: "inception_resnet_v2_b7_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b7_1x1_2" | |
| top: "inception_resnet_v2_b7_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b7_1x1_2" | |
| top: "inception_resnet_v2_b7_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b7_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b6_residual_eltwise" | |
| bottom: "inception_resnet_v2_b7_1x1_2" | |
| top: "inception_resnet_v2_b7_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b7_residual_eltwise" | |
| top: "inception_resnet_v2_b8_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b8_1x1" | |
| top: "inception_resnet_v2_b8_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b8_1x1" | |
| top: "inception_resnet_v2_b8_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b8_1x1" | |
| top: "inception_resnet_v2_b8_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b7_residual_eltwise" | |
| top: "inception_resnet_v2_b8_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b8_1x7_reduce" | |
| top: "inception_resnet_v2_b8_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b8_1x7_reduce" | |
| top: "inception_resnet_v2_b8_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b8_1x7_reduce" | |
| top: "inception_resnet_v2_b8_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b8_1x7_reduce" | |
| top: "inception_resnet_v2_b8_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b8_1x7" | |
| top: "inception_resnet_v2_b8_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b8_1x7" | |
| top: "inception_resnet_v2_b8_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b8_1x7" | |
| top: "inception_resnet_v2_b8_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b8_1x7" | |
| top: "inception_resnet_v2_b8_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b8_7x1" | |
| top: "inception_resnet_v2_b8_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b8_7x1" | |
| top: "inception_resnet_v2_b8_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b8_7x1" | |
| top: "inception_resnet_v2_b8_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b8_1x1" | |
| bottom: "inception_resnet_v2_b8_7x1" | |
| top: "inception_resnet_v2_b8_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b8_concat" | |
| top: "inception_resnet_v2_b8_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b8_1x1_2" | |
| top: "inception_resnet_v2_b8_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b8_1x1_2" | |
| top: "inception_resnet_v2_b8_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b8_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b7_residual_eltwise" | |
| bottom: "inception_resnet_v2_b8_1x1_2" | |
| top: "inception_resnet_v2_b8_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b8_residual_eltwise" | |
| top: "inception_resnet_v2_b9_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b9_1x1" | |
| top: "inception_resnet_v2_b9_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b9_1x1" | |
| top: "inception_resnet_v2_b9_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b9_1x1" | |
| top: "inception_resnet_v2_b9_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b8_residual_eltwise" | |
| top: "inception_resnet_v2_b9_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b9_1x7_reduce" | |
| top: "inception_resnet_v2_b9_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b9_1x7_reduce" | |
| top: "inception_resnet_v2_b9_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b9_1x7_reduce" | |
| top: "inception_resnet_v2_b9_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b9_1x7_reduce" | |
| top: "inception_resnet_v2_b9_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b9_1x7" | |
| top: "inception_resnet_v2_b9_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b9_1x7" | |
| top: "inception_resnet_v2_b9_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b9_1x7" | |
| top: "inception_resnet_v2_b9_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b9_1x7" | |
| top: "inception_resnet_v2_b9_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b9_7x1" | |
| top: "inception_resnet_v2_b9_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b9_7x1" | |
| top: "inception_resnet_v2_b9_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b9_7x1" | |
| top: "inception_resnet_v2_b9_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b9_1x1" | |
| bottom: "inception_resnet_v2_b9_7x1" | |
| top: "inception_resnet_v2_b9_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b9_concat" | |
| top: "inception_resnet_v2_b9_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b9_1x1_2" | |
| top: "inception_resnet_v2_b9_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b9_1x1_2" | |
| top: "inception_resnet_v2_b9_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b9_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b8_residual_eltwise" | |
| bottom: "inception_resnet_v2_b9_1x1_2" | |
| top: "inception_resnet_v2_b9_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b9_residual_eltwise" | |
| top: "inception_resnet_v2_b10_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b10_1x1" | |
| top: "inception_resnet_v2_b10_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b10_1x1" | |
| top: "inception_resnet_v2_b10_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b10_1x1" | |
| top: "inception_resnet_v2_b10_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b9_residual_eltwise" | |
| top: "inception_resnet_v2_b10_1x7_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b10_1x7_reduce" | |
| top: "inception_resnet_v2_b10_1x7_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b10_1x7_reduce" | |
| top: "inception_resnet_v2_b10_1x7_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b10_1x7_reduce" | |
| top: "inception_resnet_v2_b10_1x7_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b10_1x7_reduce" | |
| top: "inception_resnet_v2_b10_1x7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 3 | |
| kernel_h: 1 | |
| kernel_w: 7 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b10_1x7" | |
| top: "inception_resnet_v2_b10_1x7" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b10_1x7" | |
| top: "inception_resnet_v2_b10_1x7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x7_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b10_1x7" | |
| top: "inception_resnet_v2_b10_1x7" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_7x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b10_1x7" | |
| top: "inception_resnet_v2_b10_7x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 3 | |
| pad_w: 0 | |
| kernel_h: 7 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_7x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b10_7x1" | |
| top: "inception_resnet_v2_b10_7x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_7x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b10_7x1" | |
| top: "inception_resnet_v2_b10_7x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_7x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_b10_7x1" | |
| top: "inception_resnet_v2_b10_7x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_b10_1x1" | |
| bottom: "inception_resnet_v2_b10_7x1" | |
| top: "inception_resnet_v2_b10_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b10_concat" | |
| top: "inception_resnet_v2_b10_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1152 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_b10_1x1_2" | |
| top: "inception_resnet_v2_b10_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_b10_1x1_2" | |
| top: "inception_resnet_v2_b10_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_b10_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_b9_residual_eltwise" | |
| bottom: "inception_resnet_v2_b10_1x1_2" | |
| top: "inception_resnet_v2_b10_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_pool" | |
| type: "Pooling" | |
| bottom: "inception_resnet_v2_b10_residual_eltwise" | |
| top: "reduction_b_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b10_residual_eltwise" | |
| top: "reduction_b_3x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_b_3x3_reduce" | |
| top: "reduction_b_3x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "reduction_b_3x3_reduce" | |
| top: "reduction_b_3x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "reduction_b_3x3_reduce" | |
| top: "reduction_b_3x3_reduce" | |
| } | |
| layer { | |
| name: "reduction_b_3x3" | |
| type: "Convolution" | |
| bottom: "reduction_b_3x3_reduce" | |
| top: "reduction_b_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_b_3x3" | |
| top: "reduction_b_3x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_scale" | |
| type: "Scale" | |
| bottom: "reduction_b_3x3" | |
| top: "reduction_b_3x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_relu" | |
| type: "ReLU" | |
| bottom: "reduction_b_3x3" | |
| top: "reduction_b_3x3" | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b10_residual_eltwise" | |
| top: "reduction_b_3x3_2_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_b_3x3_2_reduce" | |
| top: "reduction_b_3x3_2_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2_reduce_scale" | |
| type: "Scale" | |
| bottom: "reduction_b_3x3_2_reduce" | |
| top: "reduction_b_3x3_2_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2_reduce_relu" | |
| type: "ReLU" | |
| bottom: "reduction_b_3x3_2_reduce" | |
| top: "reduction_b_3x3_2_reduce" | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2" | |
| type: "Convolution" | |
| bottom: "reduction_b_3x3_2_reduce" | |
| top: "reduction_b_3x3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_b_3x3_2" | |
| top: "reduction_b_3x3_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2_scale" | |
| type: "Scale" | |
| bottom: "reduction_b_3x3_2" | |
| top: "reduction_b_3x3_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_2_relu" | |
| type: "ReLU" | |
| bottom: "reduction_b_3x3_2" | |
| top: "reduction_b_3x3_2" | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_b10_residual_eltwise" | |
| top: "reduction_b_3x3_3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_b_3x3_3_reduce" | |
| top: "reduction_b_3x3_3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3_reduce_scale" | |
| type: "Scale" | |
| bottom: "reduction_b_3x3_3_reduce" | |
| top: "reduction_b_3x3_3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "reduction_b_3x3_3_reduce" | |
| top: "reduction_b_3x3_3_reduce" | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3" | |
| type: "Convolution" | |
| bottom: "reduction_b_3x3_3_reduce" | |
| top: "reduction_b_3x3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_b_3x3_3" | |
| top: "reduction_b_3x3_3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3_scale" | |
| type: "Scale" | |
| bottom: "reduction_b_3x3_3" | |
| top: "reduction_b_3x3_3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_3_relu" | |
| type: "ReLU" | |
| bottom: "reduction_b_3x3_3" | |
| top: "reduction_b_3x3_3" | |
| } | |
| layer { | |
| name: "reduction_b_3x3_4" | |
| type: "Convolution" | |
| bottom: "reduction_b_3x3_3" | |
| top: "reduction_b_3x3_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_4_bn" | |
| type: "BatchNorm" | |
| bottom: "reduction_b_3x3_4" | |
| top: "reduction_b_3x3_4" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_4_scale" | |
| type: "Scale" | |
| bottom: "reduction_b_3x3_4" | |
| top: "reduction_b_3x3_4" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "reduction_b_3x3_4_relu" | |
| type: "ReLU" | |
| bottom: "reduction_b_3x3_4" | |
| top: "reduction_b_3x3_4" | |
| } | |
| layer { | |
| name: "reduction_b_concat" | |
| type: "Concat" | |
| bottom: "reduction_b_pool" | |
| bottom: "reduction_b_3x3" | |
| bottom: "reduction_b_3x3_2" | |
| bottom: "reduction_b_3x3_4" | |
| top: "reduction_b_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x1" | |
| type: "Convolution" | |
| bottom: "reduction_b_concat" | |
| top: "inception_resnet_v2_c1_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c1_1x1" | |
| top: "inception_resnet_v2_c1_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c1_1x1" | |
| top: "inception_resnet_v2_c1_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c1_1x1" | |
| top: "inception_resnet_v2_c1_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3_reduce" | |
| type: "Convolution" | |
| bottom: "reduction_b_concat" | |
| top: "inception_resnet_v2_c1_1x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c1_1x3_reduce" | |
| top: "inception_resnet_v2_c1_1x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c1_1x3_reduce" | |
| top: "inception_resnet_v2_c1_1x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c1_1x3_reduce" | |
| top: "inception_resnet_v2_c1_1x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c1_1x3_reduce" | |
| top: "inception_resnet_v2_c1_1x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 224 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 1 | |
| kernel_h: 1 | |
| kernel_w: 3 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c1_1x3" | |
| top: "inception_resnet_v2_c1_1x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c1_1x3" | |
| top: "inception_resnet_v2_c1_1x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c1_1x3" | |
| top: "inception_resnet_v2_c1_1x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_3x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c1_1x3" | |
| top: "inception_resnet_v2_c1_3x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 1 | |
| pad_w: 0 | |
| kernel_h: 3 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_3x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c1_3x1" | |
| top: "inception_resnet_v2_c1_3x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_3x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c1_3x1" | |
| top: "inception_resnet_v2_c1_3x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_3x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c1_3x1" | |
| top: "inception_resnet_v2_c1_3x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_c1_1x1" | |
| bottom: "inception_resnet_v2_c1_3x1" | |
| top: "inception_resnet_v2_c1_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c1_concat" | |
| top: "inception_resnet_v2_c1_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c1_1x1_2" | |
| top: "inception_resnet_v2_c1_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c1_1x1_2" | |
| top: "inception_resnet_v2_c1_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c1_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "reduction_b_concat" | |
| bottom: "inception_resnet_v2_c1_1x1_2" | |
| top: "inception_resnet_v2_c1_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c1_residual_eltwise" | |
| top: "inception_resnet_v2_c2_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c2_1x1" | |
| top: "inception_resnet_v2_c2_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c2_1x1" | |
| top: "inception_resnet_v2_c2_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c2_1x1" | |
| top: "inception_resnet_v2_c2_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c1_residual_eltwise" | |
| top: "inception_resnet_v2_c2_1x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c2_1x3_reduce" | |
| top: "inception_resnet_v2_c2_1x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c2_1x3_reduce" | |
| top: "inception_resnet_v2_c2_1x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c2_1x3_reduce" | |
| top: "inception_resnet_v2_c2_1x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c2_1x3_reduce" | |
| top: "inception_resnet_v2_c2_1x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 224 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 1 | |
| kernel_h: 1 | |
| kernel_w: 3 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c2_1x3" | |
| top: "inception_resnet_v2_c2_1x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c2_1x3" | |
| top: "inception_resnet_v2_c2_1x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c2_1x3" | |
| top: "inception_resnet_v2_c2_1x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_3x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c2_1x3" | |
| top: "inception_resnet_v2_c2_3x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 1 | |
| pad_w: 0 | |
| kernel_h: 3 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_3x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c2_3x1" | |
| top: "inception_resnet_v2_c2_3x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_3x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c2_3x1" | |
| top: "inception_resnet_v2_c2_3x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_3x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c2_3x1" | |
| top: "inception_resnet_v2_c2_3x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_c2_1x1" | |
| bottom: "inception_resnet_v2_c2_3x1" | |
| top: "inception_resnet_v2_c2_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c2_concat" | |
| top: "inception_resnet_v2_c2_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c2_1x1_2" | |
| top: "inception_resnet_v2_c2_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c2_1x1_2" | |
| top: "inception_resnet_v2_c2_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c2_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_c1_residual_eltwise" | |
| bottom: "inception_resnet_v2_c2_1x1_2" | |
| top: "inception_resnet_v2_c2_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c2_residual_eltwise" | |
| top: "inception_resnet_v2_c3_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c3_1x1" | |
| top: "inception_resnet_v2_c3_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c3_1x1" | |
| top: "inception_resnet_v2_c3_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c3_1x1" | |
| top: "inception_resnet_v2_c3_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c2_residual_eltwise" | |
| top: "inception_resnet_v2_c3_1x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c3_1x3_reduce" | |
| top: "inception_resnet_v2_c3_1x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c3_1x3_reduce" | |
| top: "inception_resnet_v2_c3_1x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c3_1x3_reduce" | |
| top: "inception_resnet_v2_c3_1x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c3_1x3_reduce" | |
| top: "inception_resnet_v2_c3_1x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 224 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 1 | |
| kernel_h: 1 | |
| kernel_w: 3 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c3_1x3" | |
| top: "inception_resnet_v2_c3_1x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c3_1x3" | |
| top: "inception_resnet_v2_c3_1x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c3_1x3" | |
| top: "inception_resnet_v2_c3_1x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_3x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c3_1x3" | |
| top: "inception_resnet_v2_c3_3x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 1 | |
| pad_w: 0 | |
| kernel_h: 3 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_3x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c3_3x1" | |
| top: "inception_resnet_v2_c3_3x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_3x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c3_3x1" | |
| top: "inception_resnet_v2_c3_3x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_3x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c3_3x1" | |
| top: "inception_resnet_v2_c3_3x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_c3_1x1" | |
| bottom: "inception_resnet_v2_c3_3x1" | |
| top: "inception_resnet_v2_c3_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c3_concat" | |
| top: "inception_resnet_v2_c3_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c3_1x1_2" | |
| top: "inception_resnet_v2_c3_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c3_1x1_2" | |
| top: "inception_resnet_v2_c3_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c3_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_c2_residual_eltwise" | |
| bottom: "inception_resnet_v2_c3_1x1_2" | |
| top: "inception_resnet_v2_c3_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c3_residual_eltwise" | |
| top: "inception_resnet_v2_c4_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c4_1x1" | |
| top: "inception_resnet_v2_c4_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c4_1x1" | |
| top: "inception_resnet_v2_c4_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c4_1x1" | |
| top: "inception_resnet_v2_c4_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c3_residual_eltwise" | |
| top: "inception_resnet_v2_c4_1x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c4_1x3_reduce" | |
| top: "inception_resnet_v2_c4_1x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c4_1x3_reduce" | |
| top: "inception_resnet_v2_c4_1x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c4_1x3_reduce" | |
| top: "inception_resnet_v2_c4_1x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c4_1x3_reduce" | |
| top: "inception_resnet_v2_c4_1x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 224 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 1 | |
| kernel_h: 1 | |
| kernel_w: 3 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c4_1x3" | |
| top: "inception_resnet_v2_c4_1x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c4_1x3" | |
| top: "inception_resnet_v2_c4_1x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c4_1x3" | |
| top: "inception_resnet_v2_c4_1x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_3x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c4_1x3" | |
| top: "inception_resnet_v2_c4_3x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 1 | |
| pad_w: 0 | |
| kernel_h: 3 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_3x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c4_3x1" | |
| top: "inception_resnet_v2_c4_3x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_3x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c4_3x1" | |
| top: "inception_resnet_v2_c4_3x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_3x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c4_3x1" | |
| top: "inception_resnet_v2_c4_3x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_c4_1x1" | |
| bottom: "inception_resnet_v2_c4_3x1" | |
| top: "inception_resnet_v2_c4_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c4_concat" | |
| top: "inception_resnet_v2_c4_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c4_1x1_2" | |
| top: "inception_resnet_v2_c4_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c4_1x1_2" | |
| top: "inception_resnet_v2_c4_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c4_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_c3_residual_eltwise" | |
| bottom: "inception_resnet_v2_c4_1x1_2" | |
| top: "inception_resnet_v2_c4_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c4_residual_eltwise" | |
| top: "inception_resnet_v2_c5_1x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c5_1x1" | |
| top: "inception_resnet_v2_c5_1x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c5_1x1" | |
| top: "inception_resnet_v2_c5_1x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c5_1x1" | |
| top: "inception_resnet_v2_c5_1x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3_reduce" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c4_residual_eltwise" | |
| top: "inception_resnet_v2_c5_1x3_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3_reduce_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c5_1x3_reduce" | |
| top: "inception_resnet_v2_c5_1x3_reduce" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3_reduce_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c5_1x3_reduce" | |
| top: "inception_resnet_v2_c5_1x3_reduce" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3_reduce_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c5_1x3_reduce" | |
| top: "inception_resnet_v2_c5_1x3_reduce" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c5_1x3_reduce" | |
| top: "inception_resnet_v2_c5_1x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 224 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 0 | |
| pad_w: 1 | |
| kernel_h: 1 | |
| kernel_w: 3 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c5_1x3" | |
| top: "inception_resnet_v2_c5_1x3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c5_1x3" | |
| top: "inception_resnet_v2_c5_1x3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x3_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c5_1x3" | |
| top: "inception_resnet_v2_c5_1x3" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_3x1" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c5_1x3" | |
| top: "inception_resnet_v2_c5_3x1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| pad_h: 1 | |
| pad_w: 0 | |
| kernel_h: 3 | |
| kernel_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_3x1_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c5_3x1" | |
| top: "inception_resnet_v2_c5_3x1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_3x1_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c5_3x1" | |
| top: "inception_resnet_v2_c5_3x1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_3x1_relu" | |
| type: "ReLU" | |
| bottom: "inception_resnet_v2_c5_3x1" | |
| top: "inception_resnet_v2_c5_3x1" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_concat" | |
| type: "Concat" | |
| bottom: "inception_resnet_v2_c5_1x1" | |
| bottom: "inception_resnet_v2_c5_3x1" | |
| top: "inception_resnet_v2_c5_concat" | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x1_2" | |
| type: "Convolution" | |
| bottom: "inception_resnet_v2_c5_concat" | |
| top: "inception_resnet_v2_c5_1x1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "inception_resnet_v2_c5_1x1_2" | |
| top: "inception_resnet_v2_c5_1x1_2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_1x1_2_scale" | |
| type: "Scale" | |
| bottom: "inception_resnet_v2_c5_1x1_2" | |
| top: "inception_resnet_v2_c5_1x1_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "inception_resnet_v2_c5_residual_eltwise" | |
| type: "Eltwise" | |
| bottom: "inception_resnet_v2_c4_residual_eltwise" | |
| bottom: "inception_resnet_v2_c5_1x1_2" | |
| top: "inception_resnet_v2_c5_residual_eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "pool_8x8_s1" | |
| type: "Pooling" | |
| bottom: "inception_resnet_v2_c5_residual_eltwise" | |
| top: "pool_8x8_s1" | |
| pooling_param { | |
| pool: AVE | |
| global_pooling: true | |
| } | |
| } | |
| layer { | |
| name: "pool_8x8_s1_drop" | |
| type: "Dropout" | |
| bottom: "pool_8x8_s1" | |
| top: "pool_8x8_s1_drop" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "classifier" | |
| type: "InnerProduct" | |
| bottom: "pool_8x8_s1_drop" | |
| top: "classifier" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 1000 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "classifier" | |
| bottom: "label" | |
| top: "loss" | |
| } | |
| layer { | |
| name: "accuracy_top1" | |
| type: "Accuracy" | |
| bottom: "classifier" | |
| bottom: "label" | |
| top: "accuracy_top1" | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "accuracy_top5" | |
| type: "Accuracy" | |
| bottom: "classifier" | |
| bottom: "label" | |
| top: "accuracy_top5" | |
| include { | |
| phase: TEST | |
| } | |
| accuracy_param { | |
| top_k: 5 | |
| } | |
| } |
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