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February 12, 2020 19:10
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Eyeriss-VGG-Caffemodel
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| # model + meanfile, https://drive.google.com/drive/folders/1GF_hyCkw46SVxQhP0NSVB4WJraYzlhUp?usp=sharing | |
| # I0208 21:55:14.949070 18811 caffe.cpp:309] Loss: 1.65299 | |
| # I0208 21:55:14.949090 18811 caffe.cpp:321] loss3/loss3 = 1.65299 (* 1 = 1.65299 loss) | |
| # I0208 21:55:14.949101 18811 caffe.cpp:321] loss3/top-1 = 0.607879 | |
| # I0208 21:55:14.949111 18811 caffe.cpp:321] loss3/top-5 = 0.838562 | |
| # | |
| name: "eyeriss" | |
| layer { | |
| name: "data" | |
| type: "ImageData" | |
| top: "data" | |
| top: "label" | |
| transform_param { | |
| mirror: false | |
| mean_file: "data/ilsvrc12/eyeriss.binaryproto" | |
| } | |
| image_data_param { | |
| source: "data/ilsvrc12/eyeriss.txt" | |
| batch_size: 50 | |
| new_height: 224 | |
| new_width: 224 | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| convolution_param { | |
| kernel_h: 7 | |
| kernel_w: 7 | |
| num_output: 64 | |
| stride_h: 2 | |
| stride_w: 2 | |
| pad_h: 3 | |
| pad_w: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1x" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1x" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 2 | |
| stride_w: 2 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "norm1" | |
| type: "LRN" | |
| bottom: "pool1" | |
| top: "norm1" | |
| lrn_param { | |
| local_size: 5 | |
| k: 1.000000 | |
| alpha: 0.000100 | |
| beta: 0.750000 | |
| } | |
| } | |
| layer { | |
| name: "reduction2" | |
| type: "Convolution" | |
| bottom: "norm1" | |
| top: "reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_reduction2" | |
| type: "ReLU" | |
| bottom: "reduction2" | |
| top: "reduction2x" | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "reduction2x" | |
| top: "conv2" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 192 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu2" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2x" | |
| } | |
| layer { | |
| name: "norm2" | |
| type: "LRN" | |
| bottom: "conv2x" | |
| top: "norm2" | |
| lrn_param { | |
| local_size: 5 | |
| k: 1.000000 | |
| alpha: 0.000100 | |
| beta: 0.750000 | |
| } | |
| } | |
| layer { | |
| name: "pool2" | |
| type: "Pooling" | |
| bottom: "norm2" | |
| top: "pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 2 | |
| stride_w: 2 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "icp1_reduction1" | |
| type: "Convolution" | |
| bottom: "pool2" | |
| top: "icp1_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 96 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp1_reduction1" | |
| type: "ReLU" | |
| bottom: "icp1_reduction1" | |
| top: "icp1_reduction1x" | |
| } | |
| layer { | |
| name: "icp1_reduction2" | |
| type: "Convolution" | |
| bottom: "pool2" | |
| top: "icp1_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 16 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp1_reduction2" | |
| type: "ReLU" | |
| bottom: "icp1_reduction2" | |
| top: "icp1_reduction2x" | |
| } | |
| layer { | |
| name: "icp1_pool" | |
| type: "Pooling" | |
| bottom: "pool2" | |
| top: "icp1_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp1_out0" | |
| type: "Convolution" | |
| bottom: "pool2" | |
| top: "icp1_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp1_out0" | |
| type: "ReLU" | |
| bottom: "icp1_out0" | |
| top: "icp1_out0x" | |
| } | |
| layer { | |
| name: "icp1_out1" | |
| type: "Convolution" | |
| bottom: "icp1_reduction1x" | |
| top: "icp1_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp1_out1" | |
| type: "ReLU" | |
| bottom: "icp1_out1" | |
| top: "icp1_out1x" | |
| } | |
| layer { | |
| name: "icp1_out2" | |
| type: "Convolution" | |
| bottom: "icp1_reduction2x" | |
| top: "icp1_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 32 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp1_out2" | |
| type: "ReLU" | |
| bottom: "icp1_out2" | |
| top: "icp1_out2x" | |
| } | |
| layer { | |
| name: "icp1_out3" | |
| type: "Convolution" | |
| bottom: "icp1_pool" | |
| top: "icp1_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 32 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp1_out3" | |
| type: "ReLU" | |
| bottom: "icp1_out3" | |
| top: "icp1_out3x" | |
| } | |
| layer { | |
| name: "icp2_in" | |
| type: "Concat" | |
| bottom: "icp1_out0x" | |
| bottom: "icp1_out1x" | |
| bottom: "icp1_out2x" | |
| bottom: "icp1_out3x" | |
| top: "icp2_in" | |
| } | |
| layer { | |
| name: "icp2_reduction1" | |
| type: "Convolution" | |
| bottom: "icp2_in" | |
| top: "icp2_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp2_reduction1" | |
| type: "ReLU" | |
| bottom: "icp2_reduction1" | |
| top: "icp2_reduction1x" | |
| } | |
| layer { | |
| name: "icp2_reduction2" | |
| type: "Convolution" | |
| bottom: "icp2_in" | |
| top: "icp2_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 32 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp2_reduction2" | |
| type: "ReLU" | |
| bottom: "icp2_reduction2" | |
| top: "icp2_reduction2x" | |
| } | |
| layer { | |
| name: "icp2_pool" | |
| type: "Pooling" | |
| bottom: "icp2_in" | |
| top: "icp2_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp2_out0" | |
| type: "Convolution" | |
| bottom: "icp2_in" | |
| top: "icp2_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp2_out0" | |
| type: "ReLU" | |
| bottom: "icp2_out0" | |
| top: "icp2_out0x" | |
| } | |
| layer { | |
| name: "icp2_out1" | |
| type: "Convolution" | |
| bottom: "icp2_reduction1x" | |
| top: "icp2_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 192 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp2_out1" | |
| type: "ReLU" | |
| bottom: "icp2_out1" | |
| top: "icp2_out1x" | |
| } | |
| layer { | |
| name: "icp2_out2" | |
| type: "Convolution" | |
| bottom: "icp2_reduction2x" | |
| top: "icp2_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 96 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp2_out2" | |
| type: "ReLU" | |
| bottom: "icp2_out2" | |
| top: "icp2_out2x" | |
| } | |
| layer { | |
| name: "icp2_out3" | |
| type: "Convolution" | |
| bottom: "icp2_pool" | |
| top: "icp2_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp2_out3" | |
| type: "ReLU" | |
| bottom: "icp2_out3" | |
| top: "icp2_out3x" | |
| } | |
| layer { | |
| name: "icp2_out" | |
| type: "Concat" | |
| bottom: "icp2_out0x" | |
| bottom: "icp2_out1x" | |
| bottom: "icp2_out2x" | |
| bottom: "icp2_out3x" | |
| top: "icp2_out" | |
| } | |
| layer { | |
| name: "icp3_in" | |
| type: "Pooling" | |
| bottom: "icp2_out" | |
| top: "icp3_in" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 2 | |
| stride_w: 2 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "icp3_reduction1" | |
| type: "Convolution" | |
| bottom: "icp3_in" | |
| top: "icp3_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 96 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp3_reduction1" | |
| type: "ReLU" | |
| bottom: "icp3_reduction1" | |
| top: "icp3_reduction1x" | |
| } | |
| layer { | |
| name: "icp3_reduction2" | |
| type: "Convolution" | |
| bottom: "icp3_in" | |
| top: "icp3_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 16 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp3_reduction2" | |
| type: "ReLU" | |
| bottom: "icp3_reduction2" | |
| top: "icp3_reduction2x" | |
| } | |
| layer { | |
| name: "icp3_pool" | |
| type: "Pooling" | |
| bottom: "icp3_in" | |
| top: "icp3_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp3_out0" | |
| type: "Convolution" | |
| bottom: "icp3_in" | |
| top: "icp3_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 192 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp3_out0" | |
| type: "ReLU" | |
| bottom: "icp3_out0" | |
| top: "icp3_out0x" | |
| } | |
| layer { | |
| name: "icp3_out1" | |
| type: "Convolution" | |
| bottom: "icp3_reduction1x" | |
| top: "icp3_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 208 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp3_out1" | |
| type: "ReLU" | |
| bottom: "icp3_out1" | |
| top: "icp3_out1x" | |
| } | |
| layer { | |
| name: "icp3_out2" | |
| type: "Convolution" | |
| bottom: "icp3_reduction2x" | |
| top: "icp3_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 48 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp3_out2" | |
| type: "ReLU" | |
| bottom: "icp3_out2" | |
| top: "icp3_out2x" | |
| } | |
| layer { | |
| name: "icp3_out3" | |
| type: "Convolution" | |
| bottom: "icp3_pool" | |
| top: "icp3_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp3_out3" | |
| type: "ReLU" | |
| bottom: "icp3_out3" | |
| top: "icp3_out3x" | |
| } | |
| layer { | |
| name: "icp3_out" | |
| type: "Concat" | |
| bottom: "icp3_out0x" | |
| bottom: "icp3_out1x" | |
| bottom: "icp3_out2x" | |
| bottom: "icp3_out3x" | |
| top: "icp3_out" | |
| } | |
| layer { | |
| name: "icp4_reduction1" | |
| type: "Convolution" | |
| bottom: "icp3_out" | |
| top: "icp4_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 112 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp4_reduction1" | |
| type: "ReLU" | |
| bottom: "icp4_reduction1" | |
| top: "icp4_reduction1x" | |
| } | |
| layer { | |
| name: "icp4_reduction2" | |
| type: "Convolution" | |
| bottom: "icp3_out" | |
| top: "icp4_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 24 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp4_reduction2" | |
| type: "ReLU" | |
| bottom: "icp4_reduction2" | |
| top: "icp4_reduction2x" | |
| } | |
| layer { | |
| name: "icp4_pool" | |
| type: "Pooling" | |
| bottom: "icp3_out" | |
| top: "icp4_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp4_out0" | |
| type: "Convolution" | |
| bottom: "icp3_out" | |
| top: "icp4_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 160 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp4_out0" | |
| type: "ReLU" | |
| bottom: "icp4_out0" | |
| top: "icp4_out0x" | |
| } | |
| layer { | |
| name: "icp4_out1" | |
| type: "Convolution" | |
| bottom: "icp4_reduction1x" | |
| top: "icp4_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 224 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp4_out1" | |
| type: "ReLU" | |
| bottom: "icp4_out1" | |
| top: "icp4_out1x" | |
| } | |
| layer { | |
| name: "icp4_out2" | |
| type: "Convolution" | |
| bottom: "icp4_reduction2x" | |
| top: "icp4_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp4_out2" | |
| type: "ReLU" | |
| bottom: "icp4_out2" | |
| top: "icp4_out2x" | |
| } | |
| layer { | |
| name: "icp4_out3" | |
| type: "Convolution" | |
| bottom: "icp4_pool" | |
| top: "icp4_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp4_out3" | |
| type: "ReLU" | |
| bottom: "icp4_out3" | |
| top: "icp4_out3x" | |
| } | |
| layer { | |
| name: "icp4_out" | |
| type: "Concat" | |
| bottom: "icp4_out0x" | |
| bottom: "icp4_out1x" | |
| bottom: "icp4_out2x" | |
| bottom: "icp4_out3x" | |
| top: "icp4_out" | |
| } | |
| layer { | |
| name: "icp5_reduction1" | |
| type: "Convolution" | |
| bottom: "icp4_out" | |
| top: "icp5_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp5_reduction1" | |
| type: "ReLU" | |
| bottom: "icp5_reduction1" | |
| top: "icp5_reduction1x" | |
| } | |
| layer { | |
| name: "icp5_reduction2" | |
| type: "Convolution" | |
| bottom: "icp4_out" | |
| top: "icp5_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 24 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp5_reduction2" | |
| type: "ReLU" | |
| bottom: "icp5_reduction2" | |
| top: "icp5_reduction2x" | |
| } | |
| layer { | |
| name: "icp5_pool" | |
| type: "Pooling" | |
| bottom: "icp4_out" | |
| top: "icp5_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp5_out0" | |
| type: "Convolution" | |
| bottom: "icp4_out" | |
| top: "icp5_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp5_out0" | |
| type: "ReLU" | |
| bottom: "icp5_out0" | |
| top: "icp5_out0x" | |
| } | |
| layer { | |
| name: "icp5_out1" | |
| type: "Convolution" | |
| bottom: "icp5_reduction1x" | |
| top: "icp5_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 256 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp5_out1" | |
| type: "ReLU" | |
| bottom: "icp5_out1" | |
| top: "icp5_out1x" | |
| } | |
| layer { | |
| name: "icp5_out2" | |
| type: "Convolution" | |
| bottom: "icp5_reduction2x" | |
| top: "icp5_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp5_out2" | |
| type: "ReLU" | |
| bottom: "icp5_out2" | |
| top: "icp5_out2x" | |
| } | |
| layer { | |
| name: "icp5_out3" | |
| type: "Convolution" | |
| bottom: "icp5_pool" | |
| top: "icp5_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp5_out3" | |
| type: "ReLU" | |
| bottom: "icp5_out3" | |
| top: "icp5_out3x" | |
| } | |
| layer { | |
| name: "icp5_out" | |
| type: "Concat" | |
| bottom: "icp5_out0x" | |
| bottom: "icp5_out1x" | |
| bottom: "icp5_out2x" | |
| bottom: "icp5_out3x" | |
| top: "icp5_out" | |
| } | |
| layer { | |
| name: "icp6_reduction1" | |
| type: "Convolution" | |
| bottom: "icp5_out" | |
| top: "icp6_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 144 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp6_reduction1" | |
| type: "ReLU" | |
| bottom: "icp6_reduction1" | |
| top: "icp6_reduction1x" | |
| } | |
| layer { | |
| name: "icp6_reduction2" | |
| type: "Convolution" | |
| bottom: "icp5_out" | |
| top: "icp6_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 32 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp6_reduction2" | |
| type: "ReLU" | |
| bottom: "icp6_reduction2" | |
| top: "icp6_reduction2x" | |
| } | |
| layer { | |
| name: "icp6_pool" | |
| type: "Pooling" | |
| bottom: "icp5_out" | |
| top: "icp6_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp6_out0" | |
| type: "Convolution" | |
| bottom: "icp5_out" | |
| top: "icp6_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 112 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp6_out0" | |
| type: "ReLU" | |
| bottom: "icp6_out0" | |
| top: "icp6_out0x" | |
| } | |
| layer { | |
| name: "icp6_out1" | |
| type: "Convolution" | |
| bottom: "icp6_reduction1x" | |
| top: "icp6_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 288 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp6_out1" | |
| type: "ReLU" | |
| bottom: "icp6_out1" | |
| top: "icp6_out1x" | |
| } | |
| layer { | |
| name: "icp6_out2" | |
| type: "Convolution" | |
| bottom: "icp6_reduction2x" | |
| top: "icp6_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp6_out2" | |
| type: "ReLU" | |
| bottom: "icp6_out2" | |
| top: "icp6_out2x" | |
| } | |
| layer { | |
| name: "icp6_out3" | |
| type: "Convolution" | |
| bottom: "icp6_pool" | |
| top: "icp6_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 64 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp6_out3" | |
| type: "ReLU" | |
| bottom: "icp6_out3" | |
| top: "icp6_out3x" | |
| } | |
| layer { | |
| name: "icp6_out" | |
| type: "Concat" | |
| bottom: "icp6_out0x" | |
| bottom: "icp6_out1x" | |
| bottom: "icp6_out2x" | |
| bottom: "icp6_out3x" | |
| top: "icp6_out" | |
| } | |
| layer { | |
| name: "icp7_reduction1" | |
| type: "Convolution" | |
| bottom: "icp6_out" | |
| top: "icp7_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 160 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp7_reduction1" | |
| type: "ReLU" | |
| bottom: "icp7_reduction1" | |
| top: "icp7_reduction1x" | |
| } | |
| layer { | |
| name: "icp7_reduction2" | |
| type: "Convolution" | |
| bottom: "icp6_out" | |
| top: "icp7_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 32 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp7_reduction2" | |
| type: "ReLU" | |
| bottom: "icp7_reduction2" | |
| top: "icp7_reduction2x" | |
| } | |
| layer { | |
| name: "icp7_pool" | |
| type: "Pooling" | |
| bottom: "icp6_out" | |
| top: "icp7_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp7_out0" | |
| type: "Convolution" | |
| bottom: "icp6_out" | |
| top: "icp7_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 256 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp7_out0" | |
| type: "ReLU" | |
| bottom: "icp7_out0" | |
| top: "icp7_out0x" | |
| } | |
| layer { | |
| name: "icp7_out1" | |
| type: "Convolution" | |
| bottom: "icp7_reduction1x" | |
| top: "icp7_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 320 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp7_out1" | |
| type: "ReLU" | |
| bottom: "icp7_out1" | |
| top: "icp7_out1x" | |
| } | |
| layer { | |
| name: "icp7_out2" | |
| type: "Convolution" | |
| bottom: "icp7_reduction2x" | |
| top: "icp7_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp7_out2" | |
| type: "ReLU" | |
| bottom: "icp7_out2" | |
| top: "icp7_out2x" | |
| } | |
| layer { | |
| name: "icp7_out3" | |
| type: "Convolution" | |
| bottom: "icp7_pool" | |
| top: "icp7_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp7_out3" | |
| type: "ReLU" | |
| bottom: "icp7_out3" | |
| top: "icp7_out3x" | |
| } | |
| layer { | |
| name: "icp7_out" | |
| type: "Concat" | |
| bottom: "icp7_out0x" | |
| bottom: "icp7_out1x" | |
| bottom: "icp7_out2x" | |
| bottom: "icp7_out3x" | |
| top: "icp7_out" | |
| } | |
| layer { | |
| name: "icp8_in" | |
| type: "Pooling" | |
| bottom: "icp7_out" | |
| top: "icp8_in" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 2 | |
| stride_w: 2 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "icp8_reduction1" | |
| type: "Convolution" | |
| bottom: "icp8_in" | |
| top: "icp8_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 160 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp8_reduction1" | |
| type: "ReLU" | |
| bottom: "icp8_reduction1" | |
| top: "icp8_reduction1x" | |
| } | |
| layer { | |
| name: "icp8_reduction2" | |
| type: "Convolution" | |
| bottom: "icp8_in" | |
| top: "icp8_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 32 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp8_reduction2" | |
| type: "ReLU" | |
| bottom: "icp8_reduction2" | |
| top: "icp8_reduction2x" | |
| } | |
| layer { | |
| name: "icp8_pool" | |
| type: "Pooling" | |
| bottom: "icp8_in" | |
| top: "icp8_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp8_out0" | |
| type: "Convolution" | |
| bottom: "icp8_in" | |
| top: "icp8_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 256 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp8_out0" | |
| type: "ReLU" | |
| bottom: "icp8_out0" | |
| top: "icp8_out0x" | |
| } | |
| layer { | |
| name: "icp8_out1" | |
| type: "Convolution" | |
| bottom: "icp8_reduction1x" | |
| top: "icp8_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 320 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp8_out1" | |
| type: "ReLU" | |
| bottom: "icp8_out1" | |
| top: "icp8_out1x" | |
| } | |
| layer { | |
| name: "icp8_out2" | |
| type: "Convolution" | |
| bottom: "icp8_reduction2x" | |
| top: "icp8_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp8_out2" | |
| type: "ReLU" | |
| bottom: "icp8_out2" | |
| top: "icp8_out2x" | |
| } | |
| layer { | |
| name: "icp8_out3" | |
| type: "Convolution" | |
| bottom: "icp8_pool" | |
| top: "icp8_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp8_out3" | |
| type: "ReLU" | |
| bottom: "icp8_out3" | |
| top: "icp8_out3x" | |
| } | |
| layer { | |
| name: "icp8_out" | |
| type: "Concat" | |
| bottom: "icp8_out0x" | |
| bottom: "icp8_out1x" | |
| bottom: "icp8_out2x" | |
| bottom: "icp8_out3x" | |
| top: "icp8_out" | |
| } | |
| layer { | |
| name: "icp9_reduction1" | |
| type: "Convolution" | |
| bottom: "icp8_out" | |
| top: "icp9_reduction1" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 192 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp9_reduction1" | |
| type: "ReLU" | |
| bottom: "icp9_reduction1" | |
| top: "icp9_reduction1x" | |
| } | |
| layer { | |
| name: "icp9_reduction2" | |
| type: "Convolution" | |
| bottom: "icp8_out" | |
| top: "icp9_reduction2" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 48 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp9_reduction2" | |
| type: "ReLU" | |
| bottom: "icp9_reduction2" | |
| top: "icp9_reduction2x" | |
| } | |
| layer { | |
| name: "icp9_pool" | |
| type: "Pooling" | |
| bottom: "icp8_out" | |
| top: "icp9_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "icp9_out0" | |
| type: "Convolution" | |
| bottom: "icp8_out" | |
| top: "icp9_out0" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 384 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp9_out0" | |
| type: "ReLU" | |
| bottom: "icp9_out0" | |
| top: "icp9_out0x" | |
| } | |
| layer { | |
| name: "icp9_out1" | |
| type: "Convolution" | |
| bottom: "icp9_reduction1x" | |
| top: "icp9_out1" | |
| convolution_param { | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| num_output: 384 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 1 | |
| pad_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp9_out1" | |
| type: "ReLU" | |
| bottom: "icp9_out1" | |
| top: "icp9_out1x" | |
| } | |
| layer { | |
| name: "icp9_out2" | |
| type: "Convolution" | |
| bottom: "icp9_reduction2x" | |
| top: "icp9_out2" | |
| convolution_param { | |
| kernel_h: 5 | |
| kernel_w: 5 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 2 | |
| pad_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp9_out2" | |
| type: "ReLU" | |
| bottom: "icp9_out2" | |
| top: "icp9_out2x" | |
| } | |
| layer { | |
| name: "icp9_out3" | |
| type: "Convolution" | |
| bottom: "icp9_pool" | |
| top: "icp9_out3" | |
| convolution_param { | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| num_output: 128 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "relu_icp9_out3" | |
| type: "ReLU" | |
| bottom: "icp9_out3" | |
| top: "icp9_out3x" | |
| } | |
| layer { | |
| name: "icp9_out" | |
| type: "Concat" | |
| bottom: "icp9_out0x" | |
| bottom: "icp9_out1x" | |
| bottom: "icp9_out2x" | |
| bottom: "icp9_out3x" | |
| top: "icp9_out" | |
| } | |
| layer { | |
| name: "cls3_pool" | |
| type: "Pooling" | |
| bottom: "icp9_out" | |
| top: "cls3_pool" | |
| pooling_param { | |
| pool: AVE | |
| kernel_h: 7 | |
| kernel_w: 7 | |
| stride_h: 1 | |
| stride_w: 1 | |
| pad_h: 0 | |
| pad_w: 0 | |
| } | |
| } | |
| layer { | |
| name: "cls3_fc" | |
| type: "InnerProduct" | |
| bottom: "cls3_pool" | |
| top: "cls3_fc" | |
| inner_product_param { | |
| num_output: 1000 | |
| } | |
| } | |
| #layer { | |
| # name: "prob" | |
| # type: "Softmax" | |
| # bottom: "cls3_fc" | |
| # top: "prob" | |
| #} | |
| layer { | |
| name: "loss3/loss3" | |
| type: "SoftmaxWithLoss" | |
| bottom: "cls3_fc" | |
| bottom: "label" | |
| top: "loss3/loss3" | |
| loss_weight: 1 | |
| } | |
| layer { | |
| name: "loss3/top-1" | |
| type: "Accuracy" | |
| bottom: "cls3_fc" | |
| bottom: "label" | |
| top: "loss3/top-1" | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "loss3/top-5" | |
| type: "Accuracy" | |
| bottom: "cls3_fc" | |
| bottom: "label" | |
| top: "loss3/top-5" | |
| include { | |
| phase: TEST | |
| } | |
| accuracy_param { | |
| top_k: 5 | |
| } | |
| } |
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