From 96b85f7fdf205576914806f1369c230d4e8dd087 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sat, 10 Dec 2016 11:24:53 -0800 Subject: [PATCH 01/26] crop 320 --- README.md | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/README.md b/README.md index 4049a8d..5fa63fb 100644 --- a/README.md +++ b/README.md @@ -13,6 +13,15 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) ResNet-101|23.6%|7.1% ResNet-152|23.0%|6.7% **ResNeXt-101**|**22.1**%|**5.8**% + +| Network |crop-size | top-1 | top-5 | +| :------: | :---: | :---: |:---: | +|ResNet-101-v1 | 224x224 |23.6|7.1| +|ResNet-101-v2 | 224x224 |24.6|7.5| +|ResNet-152-v1 | 320x320 |21.3|5.5| +|ResNet-152-v2 | 320x320 |21.1|5.5| +|ResNeXt-101 | 320x320 |20.2|4.9| + 1. Model files: OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495LrjgyQx2cKLOXKEQgN) From be241b915cd1bec8c13d0248898dff120dfecf9c Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sat, 10 Dec 2016 11:29:18 -0800 Subject: [PATCH 02/26] Update README.md --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 5fa63fb..27b4457 100644 --- a/README.md +++ b/README.md @@ -13,6 +13,8 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) ResNet-101|23.6%|7.1% ResNet-152|23.0%|6.7% **ResNeXt-101**|**22.1**%|**5.8**% + +1. 1-crop validation error on ImageNet (center 320x320 crop from resized image with shorter side=320): | Network |crop-size | top-1 | top-5 | | :------: | :---: | :---: |:---: | @@ -20,8 +22,8 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |ResNet-101-v2 | 224x224 |24.6|7.5| |ResNet-152-v1 | 320x320 |21.3|5.5| |ResNet-152-v2 | 320x320 |21.1|5.5| -|ResNeXt-101 | 320x320 |20.2|4.9| +|**ResNeXt-101** | 320x320 |**20.2**|**4.9**| -1. Model files: +2. Model files: OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495LrjgyQx2cKLOXKEQgN) From f95d4f94066d66d9bc81abcf72d5b70799af136e Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sat, 10 Dec 2016 11:36:27 -0800 Subject: [PATCH 03/26] Update README.md --- README.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 27b4457..89a578a 100644 --- a/README.md +++ b/README.md @@ -18,11 +18,13 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) | Network |crop-size | top-1 | top-5 | | :------: | :---: | :---: |:---: | -|ResNet-101-v1 | 224x224 |23.6|7.1| -|ResNet-101-v2 | 224x224 |24.6|7.5| -|ResNet-152-v1 | 320x320 |21.3|5.5| -|ResNet-152-v2 | 320x320 |21.1|5.5| -|**ResNeXt-101** | 320x320 |**20.2**|**4.9**| +|ResNet-101-v1 | 224x224 |23.6%|7.1%| +|ResNet-101-v2 | 224x224 |24.6%|7.5%| +|ResNet-152-v1 | 320x320 |21.3%|5.5%| +|ResNet-152-v2 | 320x320 |21.1%|5.5%| +|ResNet-200-v1 | 320x320 |21.8%|6.0%| +|ResNet-200-v2 | 320x320 |20.7%|5.3%| +|**ResNeXt-101** | 320x320 |**20.2**%|**4.9**%| 2. Model files: From b539a732e834c58c224f805354a636d5351169d7 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sat, 10 Dec 2016 11:41:15 -0800 Subject: [PATCH 04/26] Update README.md --- README.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/README.md b/README.md index 89a578a..37aeee5 100644 --- a/README.md +++ b/README.md @@ -18,8 +18,6 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) | Network |crop-size | top-1 | top-5 | | :------: | :---: | :---: |:---: | -|ResNet-101-v1 | 224x224 |23.6%|7.1%| -|ResNet-101-v2 | 224x224 |24.6%|7.5%| |ResNet-152-v1 | 320x320 |21.3%|5.5%| |ResNet-152-v2 | 320x320 |21.1%|5.5%| |ResNet-200-v1 | 320x320 |21.8%|6.0%| From 996462fa723206de4f986c2d683c715d0c57b32e Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Fri, 16 Dec 2016 17:33:15 -0800 Subject: [PATCH 05/26] update resnext-50 --- ResNeXt-50-deploy.prototxt | 2474 ++++++++++++++++++++++++++++++++++++ 1 file changed, 2474 insertions(+) create mode 100644 ResNeXt-50-deploy.prototxt diff --git a/ResNeXt-50-deploy.prototxt b/ResNeXt-50-deploy.prototxt new file mode 100644 index 0000000..7080487 --- /dev/null +++ b/ResNeXt-50-deploy.prototxt @@ -0,0 +1,2474 @@ +name: "ResNet" +layer { + name: "data" + type: "Input" + top: "data" + input_param { shape: { dim: 1 dim: 3 dim: 224 dim: 224 } } +} + +layer { + name: "bn_data" + type: "BatchNorm" + bottom: "data" + top: "data" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_bn_data" + bottom: "data" + top: "data" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "conv0" + type: "Convolution" + bottom: "data" + top: "conv0" + convolution_param { + num_output: 64 + kernel_size: 7 + stride: 2 + pad: 3 + bias_term: false + } +} + +layer { + name: "bn0" + type: "BatchNorm" + bottom: "conv0" + top: "conv0" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_bn0" + bottom: "conv0" + top: "conv0" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "relu0" + type: "ReLU" + bottom: "conv0" + top: "conv0" +} + +layer { + name: "pooling0" + type: "Pooling" + bottom: "conv0" + top: "pooling0" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} + +layer { + name: "stage1_unit1_conv1" + type: "Convolution" + bottom: "pooling0" + top: "stage1_unit1_conv1" + convolution_param { + num_output: 128 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit1_bn1" + type: "BatchNorm" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_bn1" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_relu1" + type: "ReLU" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv1" +} + +layer { + name: "stage1_unit1_conv2" + type: "Convolution" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv2" + convolution_param { + num_output: 128 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage1_unit1_bn2" + type: "BatchNorm" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_bn2" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_relu2" + type: "ReLU" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv2" +} + +layer { + name: "stage1_unit1_conv3" + type: "Convolution" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv3" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit1_bn3" + type: "BatchNorm" + bottom: "stage1_unit1_conv3" + top: "stage1_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_bn3" + bottom: "stage1_unit1_conv3" + top: "stage1_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_sc" + type: "Convolution" + bottom: "pooling0" + top: "stage1_unit1_sc" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage1_unit1_sc" + top: "stage1_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_sc_bn" + bottom: "stage1_unit1_sc" + top: "stage1_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_plus" + type: "Eltwise" + bottom: "stage1_unit1_sc" + bottom: "stage1_unit1_conv3" + top: "stage1_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage1_unit1_relu" + type: "ReLU" + bottom: "stage1_unit1_plus" + top: "stage1_unit1_plus" +} + +layer { + name: "stage1_unit2_conv1" + type: "Convolution" + bottom: "stage1_unit1_plus" + top: "stage1_unit2_conv1" + convolution_param { + num_output: 128 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit2_bn1" + type: "BatchNorm" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit2_bn1" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit2_relu1" + type: "ReLU" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv1" +} + +layer { + name: "stage1_unit2_conv2" + type: "Convolution" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv2" + convolution_param { + num_output: 128 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage1_unit2_bn2" + type: "BatchNorm" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit2_bn2" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit2_relu2" + type: "ReLU" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv2" +} + +layer { + name: "stage1_unit2_conv3" + type: "Convolution" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv3" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit2_bn3" + type: "BatchNorm" + bottom: "stage1_unit2_conv3" + top: "stage1_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit2_bn3" + bottom: "stage1_unit2_conv3" + top: "stage1_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit2_plus" + type: "Eltwise" + bottom: "stage1_unit1_plus" + bottom: "stage1_unit2_conv3" + top: "stage1_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage1_unit2_relu" + type: "ReLU" + bottom: "stage1_unit2_plus" + top: "stage1_unit2_plus" +} + +layer { + name: "stage1_unit3_conv1" + type: "Convolution" + bottom: "stage1_unit2_plus" + top: "stage1_unit3_conv1" + convolution_param { + num_output: 128 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit3_bn1" + type: "BatchNorm" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit3_bn1" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit3_relu1" + type: "ReLU" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv1" +} + +layer { + name: "stage1_unit3_conv2" + type: "Convolution" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv2" + convolution_param { + num_output: 128 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage1_unit3_bn2" + type: "BatchNorm" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit3_bn2" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit3_relu2" + type: "ReLU" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv2" +} + +layer { + name: "stage1_unit3_conv3" + type: "Convolution" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv3" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit3_bn3" + type: "BatchNorm" + bottom: "stage1_unit3_conv3" + top: "stage1_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit3_bn3" + bottom: "stage1_unit3_conv3" + top: "stage1_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit3_plus" + type: "Eltwise" + bottom: "stage1_unit2_plus" + bottom: "stage1_unit3_conv3" + top: "stage1_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage1_unit3_relu" + type: "ReLU" + bottom: "stage1_unit3_plus" + top: "stage1_unit3_plus" +} + +layer { + name: "stage2_unit1_conv1" + type: "Convolution" + bottom: "stage1_unit3_plus" + top: "stage2_unit1_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit1_bn1" + type: "BatchNorm" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_bn1" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_relu1" + type: "ReLU" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv1" +} + +layer { + name: "stage2_unit1_conv2" + type: "Convolution" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 2 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit1_bn2" + type: "BatchNorm" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_bn2" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_relu2" + type: "ReLU" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv2" +} + +layer { + name: "stage2_unit1_conv3" + type: "Convolution" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit1_bn3" + type: "BatchNorm" + bottom: "stage2_unit1_conv3" + top: "stage2_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_bn3" + bottom: "stage2_unit1_conv3" + top: "stage2_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_sc" + type: "Convolution" + bottom: "stage1_unit3_plus" + top: "stage2_unit1_sc" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 2 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage2_unit1_sc" + top: "stage2_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_sc_bn" + bottom: "stage2_unit1_sc" + top: "stage2_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_plus" + type: "Eltwise" + bottom: "stage2_unit1_sc" + bottom: "stage2_unit1_conv3" + top: "stage2_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit1_relu" + type: "ReLU" + bottom: "stage2_unit1_plus" + top: "stage2_unit1_plus" +} + +layer { + name: "stage2_unit2_conv1" + type: "Convolution" + bottom: "stage2_unit1_plus" + top: "stage2_unit2_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit2_bn1" + type: "BatchNorm" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit2_bn1" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit2_relu1" + type: "ReLU" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv1" +} + +layer { + name: "stage2_unit2_conv2" + type: "Convolution" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit2_bn2" + type: "BatchNorm" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit2_bn2" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit2_relu2" + type: "ReLU" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv2" +} + +layer { + name: "stage2_unit2_conv3" + type: "Convolution" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit2_bn3" + type: "BatchNorm" + bottom: "stage2_unit2_conv3" + top: "stage2_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit2_bn3" + bottom: "stage2_unit2_conv3" + top: "stage2_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit2_plus" + type: "Eltwise" + bottom: "stage2_unit1_plus" + bottom: "stage2_unit2_conv3" + top: "stage2_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit2_relu" + type: "ReLU" + bottom: "stage2_unit2_plus" + top: "stage2_unit2_plus" +} + +layer { + name: "stage2_unit3_conv1" + type: "Convolution" + bottom: "stage2_unit2_plus" + top: "stage2_unit3_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit3_bn1" + type: "BatchNorm" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit3_bn1" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit3_relu1" + type: "ReLU" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv1" +} + +layer { + name: "stage2_unit3_conv2" + type: "Convolution" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit3_bn2" + type: "BatchNorm" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit3_bn2" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit3_relu2" + type: "ReLU" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv2" +} + +layer { + name: "stage2_unit3_conv3" + type: "Convolution" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit3_bn3" + type: "BatchNorm" + bottom: "stage2_unit3_conv3" + top: "stage2_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit3_bn3" + bottom: "stage2_unit3_conv3" + top: "stage2_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit3_plus" + type: "Eltwise" + bottom: "stage2_unit2_plus" + bottom: "stage2_unit3_conv3" + top: "stage2_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit3_relu" + type: "ReLU" + bottom: "stage2_unit3_plus" + top: "stage2_unit3_plus" +} + +layer { + name: "stage2_unit4_conv1" + type: "Convolution" + bottom: "stage2_unit3_plus" + top: "stage2_unit4_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit4_bn1" + type: "BatchNorm" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit4_bn1" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit4_relu1" + type: "ReLU" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv1" +} + +layer { + name: "stage2_unit4_conv2" + type: "Convolution" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit4_bn2" + type: "BatchNorm" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit4_bn2" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit4_relu2" + type: "ReLU" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv2" +} + +layer { + name: "stage2_unit4_conv3" + type: "Convolution" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit4_bn3" + type: "BatchNorm" + bottom: "stage2_unit4_conv3" + top: "stage2_unit4_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit4_bn3" + bottom: "stage2_unit4_conv3" + top: "stage2_unit4_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit4_plus" + type: "Eltwise" + bottom: "stage2_unit3_plus" + bottom: "stage2_unit4_conv3" + top: "stage2_unit4_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit4_relu" + type: "ReLU" + bottom: "stage2_unit4_plus" + top: "stage2_unit4_plus" +} + +layer { + name: "stage3_unit1_conv1" + type: "Convolution" + bottom: "stage2_unit4_plus" + top: "stage3_unit1_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit1_bn1" + type: "BatchNorm" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_bn1" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_relu1" + type: "ReLU" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv1" +} + +layer { + name: "stage3_unit1_conv2" + type: "Convolution" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 2 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit1_bn2" + type: "BatchNorm" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_bn2" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_relu2" + type: "ReLU" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv2" +} + +layer { + name: "stage3_unit1_conv3" + type: "Convolution" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit1_bn3" + type: "BatchNorm" + bottom: "stage3_unit1_conv3" + top: "stage3_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_bn3" + bottom: "stage3_unit1_conv3" + top: "stage3_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_sc" + type: "Convolution" + bottom: "stage2_unit4_plus" + top: "stage3_unit1_sc" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 2 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage3_unit1_sc" + top: "stage3_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_sc_bn" + bottom: "stage3_unit1_sc" + top: "stage3_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_plus" + type: "Eltwise" + bottom: "stage3_unit1_sc" + bottom: "stage3_unit1_conv3" + top: "stage3_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit1_relu" + type: "ReLU" + bottom: "stage3_unit1_plus" + top: "stage3_unit1_plus" +} + +layer { + name: "stage3_unit2_conv1" + type: "Convolution" + bottom: "stage3_unit1_plus" + top: "stage3_unit2_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit2_bn1" + type: "BatchNorm" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit2_bn1" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit2_relu1" + type: "ReLU" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv1" +} + +layer { + name: "stage3_unit2_conv2" + type: "Convolution" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit2_bn2" + type: "BatchNorm" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit2_bn2" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit2_relu2" + type: "ReLU" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv2" +} + +layer { + name: "stage3_unit2_conv3" + type: "Convolution" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit2_bn3" + type: "BatchNorm" + bottom: "stage3_unit2_conv3" + top: "stage3_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit2_bn3" + bottom: "stage3_unit2_conv3" + top: "stage3_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit2_plus" + type: "Eltwise" + bottom: "stage3_unit1_plus" + bottom: "stage3_unit2_conv3" + top: "stage3_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit2_relu" + type: "ReLU" + bottom: "stage3_unit2_plus" + top: "stage3_unit2_plus" +} + +layer { + name: "stage3_unit3_conv1" + type: "Convolution" + bottom: "stage3_unit2_plus" + top: "stage3_unit3_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit3_bn1" + type: "BatchNorm" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit3_bn1" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit3_relu1" + type: "ReLU" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv1" +} + +layer { + name: "stage3_unit3_conv2" + type: "Convolution" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit3_bn2" + type: "BatchNorm" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit3_bn2" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit3_relu2" + type: "ReLU" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv2" +} + +layer { + name: "stage3_unit3_conv3" + type: "Convolution" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit3_bn3" + type: "BatchNorm" + bottom: "stage3_unit3_conv3" + top: "stage3_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit3_bn3" + bottom: "stage3_unit3_conv3" + top: "stage3_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit3_plus" + type: "Eltwise" + bottom: "stage3_unit2_plus" + bottom: "stage3_unit3_conv3" + top: "stage3_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit3_relu" + type: "ReLU" + bottom: "stage3_unit3_plus" + top: "stage3_unit3_plus" +} + +layer { + name: "stage3_unit4_conv1" + type: "Convolution" + bottom: "stage3_unit3_plus" + top: "stage3_unit4_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit4_bn1" + type: "BatchNorm" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit4_bn1" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit4_relu1" + type: "ReLU" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv1" +} + +layer { + name: "stage3_unit4_conv2" + type: "Convolution" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit4_bn2" + type: "BatchNorm" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit4_bn2" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit4_relu2" + type: "ReLU" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv2" +} + +layer { + name: "stage3_unit4_conv3" + type: "Convolution" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit4_bn3" + type: "BatchNorm" + bottom: "stage3_unit4_conv3" + top: "stage3_unit4_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit4_bn3" + bottom: "stage3_unit4_conv3" + top: "stage3_unit4_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit4_plus" + type: "Eltwise" + bottom: "stage3_unit3_plus" + bottom: "stage3_unit4_conv3" + top: "stage3_unit4_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit4_relu" + type: "ReLU" + bottom: "stage3_unit4_plus" + top: "stage3_unit4_plus" +} + +layer { + name: "stage3_unit5_conv1" + type: "Convolution" + bottom: "stage3_unit4_plus" + top: "stage3_unit5_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit5_bn1" + type: "BatchNorm" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit5_bn1" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit5_relu1" + type: "ReLU" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv1" +} + +layer { + name: "stage3_unit5_conv2" + type: "Convolution" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit5_bn2" + type: "BatchNorm" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit5_bn2" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit5_relu2" + type: "ReLU" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv2" +} + +layer { + name: "stage3_unit5_conv3" + type: "Convolution" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit5_bn3" + type: "BatchNorm" + bottom: "stage3_unit5_conv3" + top: "stage3_unit5_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit5_bn3" + bottom: "stage3_unit5_conv3" + top: "stage3_unit5_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit5_plus" + type: "Eltwise" + bottom: "stage3_unit4_plus" + bottom: "stage3_unit5_conv3" + top: "stage3_unit5_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit5_relu" + type: "ReLU" + bottom: "stage3_unit5_plus" + top: "stage3_unit5_plus" +} + +layer { + name: "stage3_unit6_conv1" + type: "Convolution" + bottom: "stage3_unit5_plus" + top: "stage3_unit6_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit6_bn1" + type: "BatchNorm" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit6_bn1" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit6_relu1" + type: "ReLU" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv1" +} + +layer { + name: "stage3_unit6_conv2" + type: "Convolution" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit6_bn2" + type: "BatchNorm" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit6_bn2" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit6_relu2" + type: "ReLU" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv2" +} + +layer { + name: "stage3_unit6_conv3" + type: "Convolution" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit6_bn3" + type: "BatchNorm" + bottom: "stage3_unit6_conv3" + top: "stage3_unit6_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit6_bn3" + bottom: "stage3_unit6_conv3" + top: "stage3_unit6_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit6_plus" + type: "Eltwise" + bottom: "stage3_unit5_plus" + bottom: "stage3_unit6_conv3" + top: "stage3_unit6_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit6_relu" + type: "ReLU" + bottom: "stage3_unit6_plus" + top: "stage3_unit6_plus" +} + +layer { + name: "stage4_unit1_conv1" + type: "Convolution" + bottom: "stage3_unit6_plus" + top: "stage4_unit1_conv1" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit1_bn1" + type: "BatchNorm" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_bn1" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_relu1" + type: "ReLU" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv1" +} + +layer { + name: "stage4_unit1_conv2" + type: "Convolution" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv2" + convolution_param { + num_output: 1024 + kernel_size: 3 + stride: 2 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage4_unit1_bn2" + type: "BatchNorm" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_bn2" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_relu2" + type: "ReLU" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv2" +} + +layer { + name: "stage4_unit1_conv3" + type: "Convolution" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv3" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit1_bn3" + type: "BatchNorm" + bottom: "stage4_unit1_conv3" + top: "stage4_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_bn3" + bottom: "stage4_unit1_conv3" + top: "stage4_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_sc" + type: "Convolution" + bottom: "stage3_unit6_plus" + top: "stage4_unit1_sc" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 2 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage4_unit1_sc" + top: "stage4_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_sc_bn" + bottom: "stage4_unit1_sc" + top: "stage4_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_plus" + type: "Eltwise" + bottom: "stage4_unit1_sc" + bottom: "stage4_unit1_conv3" + top: "stage4_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage4_unit1_relu" + type: "ReLU" + bottom: "stage4_unit1_plus" + top: "stage4_unit1_plus" +} + +layer { + name: "stage4_unit2_conv1" + type: "Convolution" + bottom: "stage4_unit1_plus" + top: "stage4_unit2_conv1" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit2_bn1" + type: "BatchNorm" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit2_bn1" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit2_relu1" + type: "ReLU" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv1" +} + +layer { + name: "stage4_unit2_conv2" + type: "Convolution" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv2" + convolution_param { + num_output: 1024 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage4_unit2_bn2" + type: "BatchNorm" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit2_bn2" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit2_relu2" + type: "ReLU" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv2" +} + +layer { + name: "stage4_unit2_conv3" + type: "Convolution" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv3" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit2_bn3" + type: "BatchNorm" + bottom: "stage4_unit2_conv3" + top: "stage4_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit2_bn3" + bottom: "stage4_unit2_conv3" + top: "stage4_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit2_plus" + type: "Eltwise" + bottom: "stage4_unit1_plus" + bottom: "stage4_unit2_conv3" + top: "stage4_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage4_unit2_relu" + type: "ReLU" + bottom: "stage4_unit2_plus" + top: "stage4_unit2_plus" +} + +layer { + name: "stage4_unit3_conv1" + type: "Convolution" + bottom: "stage4_unit2_plus" + top: "stage4_unit3_conv1" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit3_bn1" + type: "BatchNorm" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit3_bn1" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit3_relu1" + type: "ReLU" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv1" +} + +layer { + name: "stage4_unit3_conv2" + type: "Convolution" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv2" + convolution_param { + num_output: 1024 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage4_unit3_bn2" + type: "BatchNorm" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit3_bn2" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit3_relu2" + type: "ReLU" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv2" +} + +layer { + name: "stage4_unit3_conv3" + type: "Convolution" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv3" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit3_bn3" + type: "BatchNorm" + bottom: "stage4_unit3_conv3" + top: "stage4_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit3_bn3" + bottom: "stage4_unit3_conv3" + top: "stage4_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit3_plus" + type: "Eltwise" + bottom: "stage4_unit2_plus" + bottom: "stage4_unit3_conv3" + top: "stage4_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage4_unit3_relu" + type: "ReLU" + bottom: "stage4_unit3_plus" + top: "stage4_unit3_plus" +} + +layer { + name: "pool1" + type: "Pooling" + bottom: "stage4_unit3_plus" + top: "pool1" + pooling_param { + global_pooling : true + pool: AVE + } +} + +layer { + name: "fc1" + type: "InnerProduct" + bottom: "pool1" + top: "fc1" + 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: "prob" + type: "Softmax" + bottom: "fc1" + top: "prob" +} + From b6f6cb7cc7fadd9eedc5ae7b5485837b3fd0913d Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Fri, 16 Dec 2016 20:32:55 -0800 Subject: [PATCH 06/26] add resnext-50 info and link --- README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 37aeee5..828bb51 100644 --- a/README.md +++ b/README.md @@ -12,6 +12,7 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) ResNet-50|24.7%|7.8% ResNet-101|23.6%|7.1% ResNet-152|23.0%|6.7% + **ResNeXt-50**|**23.1**%|**6.7**% **ResNeXt-101**|**22.1**%|**5.8**% 1. 1-crop validation error on ImageNet (center 320x320 crop from resized image with shorter side=320): @@ -22,8 +23,10 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |ResNet-152-v2 | 320x320 |21.1%|5.5%| |ResNet-200-v1 | 320x320 |21.8%|6.0%| |ResNet-200-v2 | 320x320 |20.7%|5.3%| +|**ResNeXt-50** | 320x320 |**21.9**%|**5.9**%| |**ResNeXt-101** | 320x320 |**20.2**%|**4.9**%| 2. Model files: - OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495LrjgyQx2cKLOXKEQgN) + ResNext-50 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495Lrjg3NE0LxvH-7R81B) + ResNext-101 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495LrjgyQx2cKLOXKEQgN) From c96d2c7e9bbd7ae16648fdfdcb4b56c089650bd6 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Fri, 16 Dec 2016 20:34:37 -0800 Subject: [PATCH 07/26] Update README.md --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 828bb51..4e1e874 100644 --- a/README.md +++ b/README.md @@ -28,5 +28,7 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) 2. Model files: - ResNext-50 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495Lrjg3NE0LxvH-7R81B) - ResNext-101 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495LrjgyQx2cKLOXKEQgN) + + ResNeXt-50 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495Lrjg3NE0LxvH-7R81B) + + ResNeXt-101 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495LrjgyQx2cKLOXKEQgN) From 3c1d0c2f073057d13cb654bfa59d363d5595f3a2 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Fri, 16 Dec 2016 20:43:13 -0800 Subject: [PATCH 08/26] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 4e1e874..3422cd0 100644 --- a/README.md +++ b/README.md @@ -27,7 +27,7 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |**ResNeXt-101** | 320x320 |**20.2**%|**4.9**%| -2. Model files: +### Model files: ResNeXt-50 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495Lrjg3NE0LxvH-7R81B) From def4e0efa34b58f071985332307a3db636501ee8 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sun, 25 Dec 2016 01:05:25 -0800 Subject: [PATCH 09/26] update resnext152 --- README.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 3422cd0..6089046 100644 --- a/README.md +++ b/README.md @@ -10,10 +10,13 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) :---:|:---:|:---: [VGG-16](http://www.vlfeat.org/matconvnet/pretrained/)|[28.5%](http://www.vlfeat.org/matconvnet/pretrained/)|[9.9%](http://www.vlfeat.org/matconvnet/pretrained/) ResNet-50|24.7%|7.8% + **ResNeXt-50**|**23.1**%|**6.7**% ResNet-101|23.6%|7.1% + **ResNeXt-101**|**22.1**%|**5.8**% ResNet-152|23.0%|6.7% - **ResNeXt-50**|**23.1**%|**6.7**% - **ResNeXt-101**|**22.1**%|**5.8**% + **ResNeXt-152**|**21.3**%|**5.6**% + + 1. 1-crop validation error on ImageNet (center 320x320 crop from resized image with shorter side=320): From 7e1e0fc91beb6272cdd4c0d8438e9fb92b750f7f Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sun, 25 Dec 2016 08:48:48 -0800 Subject: [PATCH 10/26] res152 crop320 result --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 6089046..fccd2a3 100644 --- a/README.md +++ b/README.md @@ -28,6 +28,8 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |ResNet-200-v2 | 320x320 |20.7%|5.3%| |**ResNeXt-50** | 320x320 |**21.9**%|**5.9**%| |**ResNeXt-101** | 320x320 |**20.2**%|**4.9**%| +|**ResNeXt-152** | 320x320 |**19.9**%|**4.8**%| + ### Model files: From e935e9e034df0170bc5c8336514ed0f09b955c7c Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sun, 25 Dec 2016 08:58:53 -0800 Subject: [PATCH 11/26] Create ResNeXt-152-deploy.prototxt --- ResNeXt-152-deploy.prototxt | 7166 +++++++++++++++++++++++++++++++++++ 1 file changed, 7166 insertions(+) create mode 100644 ResNeXt-152-deploy.prototxt diff --git a/ResNeXt-152-deploy.prototxt b/ResNeXt-152-deploy.prototxt new file mode 100644 index 0000000..889d16c --- /dev/null +++ b/ResNeXt-152-deploy.prototxt @@ -0,0 +1,7166 @@ +name: "ResNet" +layer { + name: "data" + type: "Input" + top: "data" + input_param { shape: { dim: 1 dim: 3 dim: 224 dim: 224 } } +} + +layer { + name: "bn_data" + type: "BatchNorm" + bottom: "data" + top: "data" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_bn_data" + bottom: "data" + top: "data" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "conv0" + type: "Convolution" + bottom: "data" + top: "conv0" + convolution_param { + num_output: 64 + kernel_size: 7 + stride: 2 + pad: 3 + bias_term: false + } +} + +layer { + name: "bn0" + type: "BatchNorm" + bottom: "conv0" + top: "conv0" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_bn0" + bottom: "conv0" + top: "conv0" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "relu0" + type: "ReLU" + bottom: "conv0" + top: "conv0" +} + +layer { + name: "pooling0" + type: "Pooling" + bottom: "conv0" + top: "pooling0" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} + +layer { + name: "stage1_unit1_conv1" + type: "Convolution" + bottom: "pooling0" + top: "stage1_unit1_conv1" + convolution_param { + num_output: 128 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit1_bn1" + type: "BatchNorm" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_bn1" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_relu1" + type: "ReLU" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv1" +} + +layer { + name: "stage1_unit1_conv2" + type: "Convolution" + bottom: "stage1_unit1_conv1" + top: "stage1_unit1_conv2" + convolution_param { + num_output: 128 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage1_unit1_bn2" + type: "BatchNorm" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_bn2" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_relu2" + type: "ReLU" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv2" +} + +layer { + name: "stage1_unit1_conv3" + type: "Convolution" + bottom: "stage1_unit1_conv2" + top: "stage1_unit1_conv3" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit1_bn3" + type: "BatchNorm" + bottom: "stage1_unit1_conv3" + top: "stage1_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_bn3" + bottom: "stage1_unit1_conv3" + top: "stage1_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_sc" + type: "Convolution" + bottom: "pooling0" + top: "stage1_unit1_sc" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage1_unit1_sc" + top: "stage1_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit1_sc_bn" + bottom: "stage1_unit1_sc" + top: "stage1_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit1_plus" + type: "Eltwise" + bottom: "stage1_unit1_sc" + bottom: "stage1_unit1_conv3" + top: "stage1_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage1_unit1_relu" + type: "ReLU" + bottom: "stage1_unit1_plus" + top: "stage1_unit1_plus" +} + +layer { + name: "stage1_unit2_conv1" + type: "Convolution" + bottom: "stage1_unit1_plus" + top: "stage1_unit2_conv1" + convolution_param { + num_output: 128 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit2_bn1" + type: "BatchNorm" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit2_bn1" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit2_relu1" + type: "ReLU" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv1" +} + +layer { + name: "stage1_unit2_conv2" + type: "Convolution" + bottom: "stage1_unit2_conv1" + top: "stage1_unit2_conv2" + convolution_param { + num_output: 128 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage1_unit2_bn2" + type: "BatchNorm" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit2_bn2" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit2_relu2" + type: "ReLU" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv2" +} + +layer { + name: "stage1_unit2_conv3" + type: "Convolution" + bottom: "stage1_unit2_conv2" + top: "stage1_unit2_conv3" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit2_bn3" + type: "BatchNorm" + bottom: "stage1_unit2_conv3" + top: "stage1_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit2_bn3" + bottom: "stage1_unit2_conv3" + top: "stage1_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit2_plus" + type: "Eltwise" + bottom: "stage1_unit1_plus" + bottom: "stage1_unit2_conv3" + top: "stage1_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage1_unit2_relu" + type: "ReLU" + bottom: "stage1_unit2_plus" + top: "stage1_unit2_plus" +} + +layer { + name: "stage1_unit3_conv1" + type: "Convolution" + bottom: "stage1_unit2_plus" + top: "stage1_unit3_conv1" + convolution_param { + num_output: 128 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit3_bn1" + type: "BatchNorm" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit3_bn1" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit3_relu1" + type: "ReLU" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv1" +} + +layer { + name: "stage1_unit3_conv2" + type: "Convolution" + bottom: "stage1_unit3_conv1" + top: "stage1_unit3_conv2" + convolution_param { + num_output: 128 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage1_unit3_bn2" + type: "BatchNorm" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit3_bn2" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit3_relu2" + type: "ReLU" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv2" +} + +layer { + name: "stage1_unit3_conv3" + type: "Convolution" + bottom: "stage1_unit3_conv2" + top: "stage1_unit3_conv3" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage1_unit3_bn3" + type: "BatchNorm" + bottom: "stage1_unit3_conv3" + top: "stage1_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage1_unit3_bn3" + bottom: "stage1_unit3_conv3" + top: "stage1_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage1_unit3_plus" + type: "Eltwise" + bottom: "stage1_unit2_plus" + bottom: "stage1_unit3_conv3" + top: "stage1_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage1_unit3_relu" + type: "ReLU" + bottom: "stage1_unit3_plus" + top: "stage1_unit3_plus" +} + +layer { + name: "stage2_unit1_conv1" + type: "Convolution" + bottom: "stage1_unit3_plus" + top: "stage2_unit1_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit1_bn1" + type: "BatchNorm" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_bn1" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_relu1" + type: "ReLU" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv1" +} + +layer { + name: "stage2_unit1_conv2" + type: "Convolution" + bottom: "stage2_unit1_conv1" + top: "stage2_unit1_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 2 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit1_bn2" + type: "BatchNorm" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_bn2" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_relu2" + type: "ReLU" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv2" +} + +layer { + name: "stage2_unit1_conv3" + type: "Convolution" + bottom: "stage2_unit1_conv2" + top: "stage2_unit1_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit1_bn3" + type: "BatchNorm" + bottom: "stage2_unit1_conv3" + top: "stage2_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_bn3" + bottom: "stage2_unit1_conv3" + top: "stage2_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_sc" + type: "Convolution" + bottom: "stage1_unit3_plus" + top: "stage2_unit1_sc" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 2 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage2_unit1_sc" + top: "stage2_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit1_sc_bn" + bottom: "stage2_unit1_sc" + top: "stage2_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit1_plus" + type: "Eltwise" + bottom: "stage2_unit1_sc" + bottom: "stage2_unit1_conv3" + top: "stage2_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit1_relu" + type: "ReLU" + bottom: "stage2_unit1_plus" + top: "stage2_unit1_plus" +} + +layer { + name: "stage2_unit2_conv1" + type: "Convolution" + bottom: "stage2_unit1_plus" + top: "stage2_unit2_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit2_bn1" + type: "BatchNorm" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit2_bn1" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit2_relu1" + type: "ReLU" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv1" +} + +layer { + name: "stage2_unit2_conv2" + type: "Convolution" + bottom: "stage2_unit2_conv1" + top: "stage2_unit2_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit2_bn2" + type: "BatchNorm" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit2_bn2" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit2_relu2" + type: "ReLU" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv2" +} + +layer { + name: "stage2_unit2_conv3" + type: "Convolution" + bottom: "stage2_unit2_conv2" + top: "stage2_unit2_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit2_bn3" + type: "BatchNorm" + bottom: "stage2_unit2_conv3" + top: "stage2_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit2_bn3" + bottom: "stage2_unit2_conv3" + top: "stage2_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit2_plus" + type: "Eltwise" + bottom: "stage2_unit1_plus" + bottom: "stage2_unit2_conv3" + top: "stage2_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit2_relu" + type: "ReLU" + bottom: "stage2_unit2_plus" + top: "stage2_unit2_plus" +} + +layer { + name: "stage2_unit3_conv1" + type: "Convolution" + bottom: "stage2_unit2_plus" + top: "stage2_unit3_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit3_bn1" + type: "BatchNorm" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit3_bn1" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit3_relu1" + type: "ReLU" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv1" +} + +layer { + name: "stage2_unit3_conv2" + type: "Convolution" + bottom: "stage2_unit3_conv1" + top: "stage2_unit3_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit3_bn2" + type: "BatchNorm" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit3_bn2" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit3_relu2" + type: "ReLU" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv2" +} + +layer { + name: "stage2_unit3_conv3" + type: "Convolution" + bottom: "stage2_unit3_conv2" + top: "stage2_unit3_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit3_bn3" + type: "BatchNorm" + bottom: "stage2_unit3_conv3" + top: "stage2_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit3_bn3" + bottom: "stage2_unit3_conv3" + top: "stage2_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit3_plus" + type: "Eltwise" + bottom: "stage2_unit2_plus" + bottom: "stage2_unit3_conv3" + top: "stage2_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit3_relu" + type: "ReLU" + bottom: "stage2_unit3_plus" + top: "stage2_unit3_plus" +} + +layer { + name: "stage2_unit4_conv1" + type: "Convolution" + bottom: "stage2_unit3_plus" + top: "stage2_unit4_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit4_bn1" + type: "BatchNorm" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit4_bn1" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit4_relu1" + type: "ReLU" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv1" +} + +layer { + name: "stage2_unit4_conv2" + type: "Convolution" + bottom: "stage2_unit4_conv1" + top: "stage2_unit4_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit4_bn2" + type: "BatchNorm" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit4_bn2" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit4_relu2" + type: "ReLU" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv2" +} + +layer { + name: "stage2_unit4_conv3" + type: "Convolution" + bottom: "stage2_unit4_conv2" + top: "stage2_unit4_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit4_bn3" + type: "BatchNorm" + bottom: "stage2_unit4_conv3" + top: "stage2_unit4_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit4_bn3" + bottom: "stage2_unit4_conv3" + top: "stage2_unit4_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit4_plus" + type: "Eltwise" + bottom: "stage2_unit3_plus" + bottom: "stage2_unit4_conv3" + top: "stage2_unit4_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit4_relu" + type: "ReLU" + bottom: "stage2_unit4_plus" + top: "stage2_unit4_plus" +} + +layer { + name: "stage2_unit5_conv1" + type: "Convolution" + bottom: "stage2_unit4_plus" + top: "stage2_unit5_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit5_bn1" + type: "BatchNorm" + bottom: "stage2_unit5_conv1" + top: "stage2_unit5_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit5_bn1" + bottom: "stage2_unit5_conv1" + top: "stage2_unit5_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit5_relu1" + type: "ReLU" + bottom: "stage2_unit5_conv1" + top: "stage2_unit5_conv1" +} + +layer { + name: "stage2_unit5_conv2" + type: "Convolution" + bottom: "stage2_unit5_conv1" + top: "stage2_unit5_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit5_bn2" + type: "BatchNorm" + bottom: "stage2_unit5_conv2" + top: "stage2_unit5_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit5_bn2" + bottom: "stage2_unit5_conv2" + top: "stage2_unit5_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit5_relu2" + type: "ReLU" + bottom: "stage2_unit5_conv2" + top: "stage2_unit5_conv2" +} + +layer { + name: "stage2_unit5_conv3" + type: "Convolution" + bottom: "stage2_unit5_conv2" + top: "stage2_unit5_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit5_bn3" + type: "BatchNorm" + bottom: "stage2_unit5_conv3" + top: "stage2_unit5_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit5_bn3" + bottom: "stage2_unit5_conv3" + top: "stage2_unit5_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit5_plus" + type: "Eltwise" + bottom: "stage2_unit4_plus" + bottom: "stage2_unit5_conv3" + top: "stage2_unit5_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit5_relu" + type: "ReLU" + bottom: "stage2_unit5_plus" + top: "stage2_unit5_plus" +} + +layer { + name: "stage2_unit6_conv1" + type: "Convolution" + bottom: "stage2_unit5_plus" + top: "stage2_unit6_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit6_bn1" + type: "BatchNorm" + bottom: "stage2_unit6_conv1" + top: "stage2_unit6_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit6_bn1" + bottom: "stage2_unit6_conv1" + top: "stage2_unit6_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit6_relu1" + type: "ReLU" + bottom: "stage2_unit6_conv1" + top: "stage2_unit6_conv1" +} + +layer { + name: "stage2_unit6_conv2" + type: "Convolution" + bottom: "stage2_unit6_conv1" + top: "stage2_unit6_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit6_bn2" + type: "BatchNorm" + bottom: "stage2_unit6_conv2" + top: "stage2_unit6_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit6_bn2" + bottom: "stage2_unit6_conv2" + top: "stage2_unit6_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit6_relu2" + type: "ReLU" + bottom: "stage2_unit6_conv2" + top: "stage2_unit6_conv2" +} + +layer { + name: "stage2_unit6_conv3" + type: "Convolution" + bottom: "stage2_unit6_conv2" + top: "stage2_unit6_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit6_bn3" + type: "BatchNorm" + bottom: "stage2_unit6_conv3" + top: "stage2_unit6_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit6_bn3" + bottom: "stage2_unit6_conv3" + top: "stage2_unit6_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit6_plus" + type: "Eltwise" + bottom: "stage2_unit5_plus" + bottom: "stage2_unit6_conv3" + top: "stage2_unit6_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit6_relu" + type: "ReLU" + bottom: "stage2_unit6_plus" + top: "stage2_unit6_plus" +} + +layer { + name: "stage2_unit7_conv1" + type: "Convolution" + bottom: "stage2_unit6_plus" + top: "stage2_unit7_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit7_bn1" + type: "BatchNorm" + bottom: "stage2_unit7_conv1" + top: "stage2_unit7_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit7_bn1" + bottom: "stage2_unit7_conv1" + top: "stage2_unit7_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit7_relu1" + type: "ReLU" + bottom: "stage2_unit7_conv1" + top: "stage2_unit7_conv1" +} + +layer { + name: "stage2_unit7_conv2" + type: "Convolution" + bottom: "stage2_unit7_conv1" + top: "stage2_unit7_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit7_bn2" + type: "BatchNorm" + bottom: "stage2_unit7_conv2" + top: "stage2_unit7_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit7_bn2" + bottom: "stage2_unit7_conv2" + top: "stage2_unit7_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit7_relu2" + type: "ReLU" + bottom: "stage2_unit7_conv2" + top: "stage2_unit7_conv2" +} + +layer { + name: "stage2_unit7_conv3" + type: "Convolution" + bottom: "stage2_unit7_conv2" + top: "stage2_unit7_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit7_bn3" + type: "BatchNorm" + bottom: "stage2_unit7_conv3" + top: "stage2_unit7_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit7_bn3" + bottom: "stage2_unit7_conv3" + top: "stage2_unit7_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit7_plus" + type: "Eltwise" + bottom: "stage2_unit6_plus" + bottom: "stage2_unit7_conv3" + top: "stage2_unit7_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit7_relu" + type: "ReLU" + bottom: "stage2_unit7_plus" + top: "stage2_unit7_plus" +} + +layer { + name: "stage2_unit8_conv1" + type: "Convolution" + bottom: "stage2_unit7_plus" + top: "stage2_unit8_conv1" + convolution_param { + num_output: 256 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit8_bn1" + type: "BatchNorm" + bottom: "stage2_unit8_conv1" + top: "stage2_unit8_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit8_bn1" + bottom: "stage2_unit8_conv1" + top: "stage2_unit8_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit8_relu1" + type: "ReLU" + bottom: "stage2_unit8_conv1" + top: "stage2_unit8_conv1" +} + +layer { + name: "stage2_unit8_conv2" + type: "Convolution" + bottom: "stage2_unit8_conv1" + top: "stage2_unit8_conv2" + convolution_param { + num_output: 256 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage2_unit8_bn2" + type: "BatchNorm" + bottom: "stage2_unit8_conv2" + top: "stage2_unit8_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit8_bn2" + bottom: "stage2_unit8_conv2" + top: "stage2_unit8_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit8_relu2" + type: "ReLU" + bottom: "stage2_unit8_conv2" + top: "stage2_unit8_conv2" +} + +layer { + name: "stage2_unit8_conv3" + type: "Convolution" + bottom: "stage2_unit8_conv2" + top: "stage2_unit8_conv3" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage2_unit8_bn3" + type: "BatchNorm" + bottom: "stage2_unit8_conv3" + top: "stage2_unit8_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage2_unit8_bn3" + bottom: "stage2_unit8_conv3" + top: "stage2_unit8_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage2_unit8_plus" + type: "Eltwise" + bottom: "stage2_unit7_plus" + bottom: "stage2_unit8_conv3" + top: "stage2_unit8_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage2_unit8_relu" + type: "ReLU" + bottom: "stage2_unit8_plus" + top: "stage2_unit8_plus" +} + +layer { + name: "stage3_unit1_conv1" + type: "Convolution" + bottom: "stage2_unit8_plus" + top: "stage3_unit1_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit1_bn1" + type: "BatchNorm" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_bn1" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_relu1" + type: "ReLU" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv1" +} + +layer { + name: "stage3_unit1_conv2" + type: "Convolution" + bottom: "stage3_unit1_conv1" + top: "stage3_unit1_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 2 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit1_bn2" + type: "BatchNorm" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_bn2" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_relu2" + type: "ReLU" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv2" +} + +layer { + name: "stage3_unit1_conv3" + type: "Convolution" + bottom: "stage3_unit1_conv2" + top: "stage3_unit1_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit1_bn3" + type: "BatchNorm" + bottom: "stage3_unit1_conv3" + top: "stage3_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_bn3" + bottom: "stage3_unit1_conv3" + top: "stage3_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_sc" + type: "Convolution" + bottom: "stage2_unit8_plus" + top: "stage3_unit1_sc" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 2 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage3_unit1_sc" + top: "stage3_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit1_sc_bn" + bottom: "stage3_unit1_sc" + top: "stage3_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit1_plus" + type: "Eltwise" + bottom: "stage3_unit1_sc" + bottom: "stage3_unit1_conv3" + top: "stage3_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit1_relu" + type: "ReLU" + bottom: "stage3_unit1_plus" + top: "stage3_unit1_plus" +} + +layer { + name: "stage3_unit2_conv1" + type: "Convolution" + bottom: "stage3_unit1_plus" + top: "stage3_unit2_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit2_bn1" + type: "BatchNorm" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit2_bn1" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit2_relu1" + type: "ReLU" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv1" +} + +layer { + name: "stage3_unit2_conv2" + type: "Convolution" + bottom: "stage3_unit2_conv1" + top: "stage3_unit2_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit2_bn2" + type: "BatchNorm" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit2_bn2" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit2_relu2" + type: "ReLU" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv2" +} + +layer { + name: "stage3_unit2_conv3" + type: "Convolution" + bottom: "stage3_unit2_conv2" + top: "stage3_unit2_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit2_bn3" + type: "BatchNorm" + bottom: "stage3_unit2_conv3" + top: "stage3_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit2_bn3" + bottom: "stage3_unit2_conv3" + top: "stage3_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit2_plus" + type: "Eltwise" + bottom: "stage3_unit1_plus" + bottom: "stage3_unit2_conv3" + top: "stage3_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit2_relu" + type: "ReLU" + bottom: "stage3_unit2_plus" + top: "stage3_unit2_plus" +} + +layer { + name: "stage3_unit3_conv1" + type: "Convolution" + bottom: "stage3_unit2_plus" + top: "stage3_unit3_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit3_bn1" + type: "BatchNorm" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit3_bn1" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit3_relu1" + type: "ReLU" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv1" +} + +layer { + name: "stage3_unit3_conv2" + type: "Convolution" + bottom: "stage3_unit3_conv1" + top: "stage3_unit3_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit3_bn2" + type: "BatchNorm" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit3_bn2" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit3_relu2" + type: "ReLU" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv2" +} + +layer { + name: "stage3_unit3_conv3" + type: "Convolution" + bottom: "stage3_unit3_conv2" + top: "stage3_unit3_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit3_bn3" + type: "BatchNorm" + bottom: "stage3_unit3_conv3" + top: "stage3_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit3_bn3" + bottom: "stage3_unit3_conv3" + top: "stage3_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit3_plus" + type: "Eltwise" + bottom: "stage3_unit2_plus" + bottom: "stage3_unit3_conv3" + top: "stage3_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit3_relu" + type: "ReLU" + bottom: "stage3_unit3_plus" + top: "stage3_unit3_plus" +} + +layer { + name: "stage3_unit4_conv1" + type: "Convolution" + bottom: "stage3_unit3_plus" + top: "stage3_unit4_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit4_bn1" + type: "BatchNorm" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit4_bn1" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit4_relu1" + type: "ReLU" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv1" +} + +layer { + name: "stage3_unit4_conv2" + type: "Convolution" + bottom: "stage3_unit4_conv1" + top: "stage3_unit4_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit4_bn2" + type: "BatchNorm" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit4_bn2" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit4_relu2" + type: "ReLU" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv2" +} + +layer { + name: "stage3_unit4_conv3" + type: "Convolution" + bottom: "stage3_unit4_conv2" + top: "stage3_unit4_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit4_bn3" + type: "BatchNorm" + bottom: "stage3_unit4_conv3" + top: "stage3_unit4_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit4_bn3" + bottom: "stage3_unit4_conv3" + top: "stage3_unit4_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit4_plus" + type: "Eltwise" + bottom: "stage3_unit3_plus" + bottom: "stage3_unit4_conv3" + top: "stage3_unit4_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit4_relu" + type: "ReLU" + bottom: "stage3_unit4_plus" + top: "stage3_unit4_plus" +} + +layer { + name: "stage3_unit5_conv1" + type: "Convolution" + bottom: "stage3_unit4_plus" + top: "stage3_unit5_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit5_bn1" + type: "BatchNorm" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit5_bn1" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit5_relu1" + type: "ReLU" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv1" +} + +layer { + name: "stage3_unit5_conv2" + type: "Convolution" + bottom: "stage3_unit5_conv1" + top: "stage3_unit5_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit5_bn2" + type: "BatchNorm" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit5_bn2" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit5_relu2" + type: "ReLU" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv2" +} + +layer { + name: "stage3_unit5_conv3" + type: "Convolution" + bottom: "stage3_unit5_conv2" + top: "stage3_unit5_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit5_bn3" + type: "BatchNorm" + bottom: "stage3_unit5_conv3" + top: "stage3_unit5_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit5_bn3" + bottom: "stage3_unit5_conv3" + top: "stage3_unit5_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit5_plus" + type: "Eltwise" + bottom: "stage3_unit4_plus" + bottom: "stage3_unit5_conv3" + top: "stage3_unit5_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit5_relu" + type: "ReLU" + bottom: "stage3_unit5_plus" + top: "stage3_unit5_plus" +} + +layer { + name: "stage3_unit6_conv1" + type: "Convolution" + bottom: "stage3_unit5_plus" + top: "stage3_unit6_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit6_bn1" + type: "BatchNorm" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit6_bn1" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit6_relu1" + type: "ReLU" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv1" +} + +layer { + name: "stage3_unit6_conv2" + type: "Convolution" + bottom: "stage3_unit6_conv1" + top: "stage3_unit6_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit6_bn2" + type: "BatchNorm" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit6_bn2" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit6_relu2" + type: "ReLU" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv2" +} + +layer { + name: "stage3_unit6_conv3" + type: "Convolution" + bottom: "stage3_unit6_conv2" + top: "stage3_unit6_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit6_bn3" + type: "BatchNorm" + bottom: "stage3_unit6_conv3" + top: "stage3_unit6_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit6_bn3" + bottom: "stage3_unit6_conv3" + top: "stage3_unit6_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit6_plus" + type: "Eltwise" + bottom: "stage3_unit5_plus" + bottom: "stage3_unit6_conv3" + top: "stage3_unit6_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit6_relu" + type: "ReLU" + bottom: "stage3_unit6_plus" + top: "stage3_unit6_plus" +} + +layer { + name: "stage3_unit7_conv1" + type: "Convolution" + bottom: "stage3_unit6_plus" + top: "stage3_unit7_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit7_bn1" + type: "BatchNorm" + bottom: "stage3_unit7_conv1" + top: "stage3_unit7_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit7_bn1" + bottom: "stage3_unit7_conv1" + top: "stage3_unit7_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit7_relu1" + type: "ReLU" + bottom: "stage3_unit7_conv1" + top: "stage3_unit7_conv1" +} + +layer { + name: "stage3_unit7_conv2" + type: "Convolution" + bottom: "stage3_unit7_conv1" + top: "stage3_unit7_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit7_bn2" + type: "BatchNorm" + bottom: "stage3_unit7_conv2" + top: "stage3_unit7_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit7_bn2" + bottom: "stage3_unit7_conv2" + top: "stage3_unit7_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit7_relu2" + type: "ReLU" + bottom: "stage3_unit7_conv2" + top: "stage3_unit7_conv2" +} + +layer { + name: "stage3_unit7_conv3" + type: "Convolution" + bottom: "stage3_unit7_conv2" + top: "stage3_unit7_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit7_bn3" + type: "BatchNorm" + bottom: "stage3_unit7_conv3" + top: "stage3_unit7_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit7_bn3" + bottom: "stage3_unit7_conv3" + top: "stage3_unit7_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit7_plus" + type: "Eltwise" + bottom: "stage3_unit6_plus" + bottom: "stage3_unit7_conv3" + top: "stage3_unit7_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit7_relu" + type: "ReLU" + bottom: "stage3_unit7_plus" + top: "stage3_unit7_plus" +} + +layer { + name: "stage3_unit8_conv1" + type: "Convolution" + bottom: "stage3_unit7_plus" + top: "stage3_unit8_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit8_bn1" + type: "BatchNorm" + bottom: "stage3_unit8_conv1" + top: "stage3_unit8_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit8_bn1" + bottom: "stage3_unit8_conv1" + top: "stage3_unit8_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit8_relu1" + type: "ReLU" + bottom: "stage3_unit8_conv1" + top: "stage3_unit8_conv1" +} + +layer { + name: "stage3_unit8_conv2" + type: "Convolution" + bottom: "stage3_unit8_conv1" + top: "stage3_unit8_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit8_bn2" + type: "BatchNorm" + bottom: "stage3_unit8_conv2" + top: "stage3_unit8_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit8_bn2" + bottom: "stage3_unit8_conv2" + top: "stage3_unit8_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit8_relu2" + type: "ReLU" + bottom: "stage3_unit8_conv2" + top: "stage3_unit8_conv2" +} + +layer { + name: "stage3_unit8_conv3" + type: "Convolution" + bottom: "stage3_unit8_conv2" + top: "stage3_unit8_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit8_bn3" + type: "BatchNorm" + bottom: "stage3_unit8_conv3" + top: "stage3_unit8_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit8_bn3" + bottom: "stage3_unit8_conv3" + top: "stage3_unit8_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit8_plus" + type: "Eltwise" + bottom: "stage3_unit7_plus" + bottom: "stage3_unit8_conv3" + top: "stage3_unit8_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit8_relu" + type: "ReLU" + bottom: "stage3_unit8_plus" + top: "stage3_unit8_plus" +} + +layer { + name: "stage3_unit9_conv1" + type: "Convolution" + bottom: "stage3_unit8_plus" + top: "stage3_unit9_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit9_bn1" + type: "BatchNorm" + bottom: "stage3_unit9_conv1" + top: "stage3_unit9_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit9_bn1" + bottom: "stage3_unit9_conv1" + top: "stage3_unit9_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit9_relu1" + type: "ReLU" + bottom: "stage3_unit9_conv1" + top: "stage3_unit9_conv1" +} + +layer { + name: "stage3_unit9_conv2" + type: "Convolution" + bottom: "stage3_unit9_conv1" + top: "stage3_unit9_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit9_bn2" + type: "BatchNorm" + bottom: "stage3_unit9_conv2" + top: "stage3_unit9_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit9_bn2" + bottom: "stage3_unit9_conv2" + top: "stage3_unit9_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit9_relu2" + type: "ReLU" + bottom: "stage3_unit9_conv2" + top: "stage3_unit9_conv2" +} + +layer { + name: "stage3_unit9_conv3" + type: "Convolution" + bottom: "stage3_unit9_conv2" + top: "stage3_unit9_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit9_bn3" + type: "BatchNorm" + bottom: "stage3_unit9_conv3" + top: "stage3_unit9_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit9_bn3" + bottom: "stage3_unit9_conv3" + top: "stage3_unit9_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit9_plus" + type: "Eltwise" + bottom: "stage3_unit8_plus" + bottom: "stage3_unit9_conv3" + top: "stage3_unit9_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit9_relu" + type: "ReLU" + bottom: "stage3_unit9_plus" + top: "stage3_unit9_plus" +} + +layer { + name: "stage3_unit10_conv1" + type: "Convolution" + bottom: "stage3_unit9_plus" + top: "stage3_unit10_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit10_bn1" + type: "BatchNorm" + bottom: "stage3_unit10_conv1" + top: "stage3_unit10_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit10_bn1" + bottom: "stage3_unit10_conv1" + top: "stage3_unit10_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit10_relu1" + type: "ReLU" + bottom: "stage3_unit10_conv1" + top: "stage3_unit10_conv1" +} + +layer { + name: "stage3_unit10_conv2" + type: "Convolution" + bottom: "stage3_unit10_conv1" + top: "stage3_unit10_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit10_bn2" + type: "BatchNorm" + bottom: "stage3_unit10_conv2" + top: "stage3_unit10_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit10_bn2" + bottom: "stage3_unit10_conv2" + top: "stage3_unit10_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit10_relu2" + type: "ReLU" + bottom: "stage3_unit10_conv2" + top: "stage3_unit10_conv2" +} + +layer { + name: "stage3_unit10_conv3" + type: "Convolution" + bottom: "stage3_unit10_conv2" + top: "stage3_unit10_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit10_bn3" + type: "BatchNorm" + bottom: "stage3_unit10_conv3" + top: "stage3_unit10_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit10_bn3" + bottom: "stage3_unit10_conv3" + top: "stage3_unit10_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit10_plus" + type: "Eltwise" + bottom: "stage3_unit9_plus" + bottom: "stage3_unit10_conv3" + top: "stage3_unit10_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit10_relu" + type: "ReLU" + bottom: "stage3_unit10_plus" + top: "stage3_unit10_plus" +} + +layer { + name: "stage3_unit11_conv1" + type: "Convolution" + bottom: "stage3_unit10_plus" + top: "stage3_unit11_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit11_bn1" + type: "BatchNorm" + bottom: "stage3_unit11_conv1" + top: "stage3_unit11_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit11_bn1" + bottom: "stage3_unit11_conv1" + top: "stage3_unit11_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit11_relu1" + type: "ReLU" + bottom: "stage3_unit11_conv1" + top: "stage3_unit11_conv1" +} + +layer { + name: "stage3_unit11_conv2" + type: "Convolution" + bottom: "stage3_unit11_conv1" + top: "stage3_unit11_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit11_bn2" + type: "BatchNorm" + bottom: "stage3_unit11_conv2" + top: "stage3_unit11_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit11_bn2" + bottom: "stage3_unit11_conv2" + top: "stage3_unit11_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit11_relu2" + type: "ReLU" + bottom: "stage3_unit11_conv2" + top: "stage3_unit11_conv2" +} + +layer { + name: "stage3_unit11_conv3" + type: "Convolution" + bottom: "stage3_unit11_conv2" + top: "stage3_unit11_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit11_bn3" + type: "BatchNorm" + bottom: "stage3_unit11_conv3" + top: "stage3_unit11_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit11_bn3" + bottom: "stage3_unit11_conv3" + top: "stage3_unit11_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit11_plus" + type: "Eltwise" + bottom: "stage3_unit10_plus" + bottom: "stage3_unit11_conv3" + top: "stage3_unit11_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit11_relu" + type: "ReLU" + bottom: "stage3_unit11_plus" + top: "stage3_unit11_plus" +} + +layer { + name: "stage3_unit12_conv1" + type: "Convolution" + bottom: "stage3_unit11_plus" + top: "stage3_unit12_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit12_bn1" + type: "BatchNorm" + bottom: "stage3_unit12_conv1" + top: "stage3_unit12_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit12_bn1" + bottom: "stage3_unit12_conv1" + top: "stage3_unit12_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit12_relu1" + type: "ReLU" + bottom: "stage3_unit12_conv1" + top: "stage3_unit12_conv1" +} + +layer { + name: "stage3_unit12_conv2" + type: "Convolution" + bottom: "stage3_unit12_conv1" + top: "stage3_unit12_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit12_bn2" + type: "BatchNorm" + bottom: "stage3_unit12_conv2" + top: "stage3_unit12_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit12_bn2" + bottom: "stage3_unit12_conv2" + top: "stage3_unit12_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit12_relu2" + type: "ReLU" + bottom: "stage3_unit12_conv2" + top: "stage3_unit12_conv2" +} + +layer { + name: "stage3_unit12_conv3" + type: "Convolution" + bottom: "stage3_unit12_conv2" + top: "stage3_unit12_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit12_bn3" + type: "BatchNorm" + bottom: "stage3_unit12_conv3" + top: "stage3_unit12_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit12_bn3" + bottom: "stage3_unit12_conv3" + top: "stage3_unit12_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit12_plus" + type: "Eltwise" + bottom: "stage3_unit11_plus" + bottom: "stage3_unit12_conv3" + top: "stage3_unit12_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit12_relu" + type: "ReLU" + bottom: "stage3_unit12_plus" + top: "stage3_unit12_plus" +} + +layer { + name: "stage3_unit13_conv1" + type: "Convolution" + bottom: "stage3_unit12_plus" + top: "stage3_unit13_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit13_bn1" + type: "BatchNorm" + bottom: "stage3_unit13_conv1" + top: "stage3_unit13_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit13_bn1" + bottom: "stage3_unit13_conv1" + top: "stage3_unit13_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit13_relu1" + type: "ReLU" + bottom: "stage3_unit13_conv1" + top: "stage3_unit13_conv1" +} + +layer { + name: "stage3_unit13_conv2" + type: "Convolution" + bottom: "stage3_unit13_conv1" + top: "stage3_unit13_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit13_bn2" + type: "BatchNorm" + bottom: "stage3_unit13_conv2" + top: "stage3_unit13_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit13_bn2" + bottom: "stage3_unit13_conv2" + top: "stage3_unit13_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit13_relu2" + type: "ReLU" + bottom: "stage3_unit13_conv2" + top: "stage3_unit13_conv2" +} + +layer { + name: "stage3_unit13_conv3" + type: "Convolution" + bottom: "stage3_unit13_conv2" + top: "stage3_unit13_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit13_bn3" + type: "BatchNorm" + bottom: "stage3_unit13_conv3" + top: "stage3_unit13_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit13_bn3" + bottom: "stage3_unit13_conv3" + top: "stage3_unit13_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit13_plus" + type: "Eltwise" + bottom: "stage3_unit12_plus" + bottom: "stage3_unit13_conv3" + top: "stage3_unit13_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit13_relu" + type: "ReLU" + bottom: "stage3_unit13_plus" + top: "stage3_unit13_plus" +} + +layer { + name: "stage3_unit14_conv1" + type: "Convolution" + bottom: "stage3_unit13_plus" + top: "stage3_unit14_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit14_bn1" + type: "BatchNorm" + bottom: "stage3_unit14_conv1" + top: "stage3_unit14_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit14_bn1" + bottom: "stage3_unit14_conv1" + top: "stage3_unit14_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit14_relu1" + type: "ReLU" + bottom: "stage3_unit14_conv1" + top: "stage3_unit14_conv1" +} + +layer { + name: "stage3_unit14_conv2" + type: "Convolution" + bottom: "stage3_unit14_conv1" + top: "stage3_unit14_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit14_bn2" + type: "BatchNorm" + bottom: "stage3_unit14_conv2" + top: "stage3_unit14_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit14_bn2" + bottom: "stage3_unit14_conv2" + top: "stage3_unit14_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit14_relu2" + type: "ReLU" + bottom: "stage3_unit14_conv2" + top: "stage3_unit14_conv2" +} + +layer { + name: "stage3_unit14_conv3" + type: "Convolution" + bottom: "stage3_unit14_conv2" + top: "stage3_unit14_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit14_bn3" + type: "BatchNorm" + bottom: "stage3_unit14_conv3" + top: "stage3_unit14_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit14_bn3" + bottom: "stage3_unit14_conv3" + top: "stage3_unit14_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit14_plus" + type: "Eltwise" + bottom: "stage3_unit13_plus" + bottom: "stage3_unit14_conv3" + top: "stage3_unit14_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit14_relu" + type: "ReLU" + bottom: "stage3_unit14_plus" + top: "stage3_unit14_plus" +} + +layer { + name: "stage3_unit15_conv1" + type: "Convolution" + bottom: "stage3_unit14_plus" + top: "stage3_unit15_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit15_bn1" + type: "BatchNorm" + bottom: "stage3_unit15_conv1" + top: "stage3_unit15_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit15_bn1" + bottom: "stage3_unit15_conv1" + top: "stage3_unit15_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit15_relu1" + type: "ReLU" + bottom: "stage3_unit15_conv1" + top: "stage3_unit15_conv1" +} + +layer { + name: "stage3_unit15_conv2" + type: "Convolution" + bottom: "stage3_unit15_conv1" + top: "stage3_unit15_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit15_bn2" + type: "BatchNorm" + bottom: "stage3_unit15_conv2" + top: "stage3_unit15_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit15_bn2" + bottom: "stage3_unit15_conv2" + top: "stage3_unit15_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit15_relu2" + type: "ReLU" + bottom: "stage3_unit15_conv2" + top: "stage3_unit15_conv2" +} + +layer { + name: "stage3_unit15_conv3" + type: "Convolution" + bottom: "stage3_unit15_conv2" + top: "stage3_unit15_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit15_bn3" + type: "BatchNorm" + bottom: "stage3_unit15_conv3" + top: "stage3_unit15_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit15_bn3" + bottom: "stage3_unit15_conv3" + top: "stage3_unit15_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit15_plus" + type: "Eltwise" + bottom: "stage3_unit14_plus" + bottom: "stage3_unit15_conv3" + top: "stage3_unit15_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit15_relu" + type: "ReLU" + bottom: "stage3_unit15_plus" + top: "stage3_unit15_plus" +} + +layer { + name: "stage3_unit16_conv1" + type: "Convolution" + bottom: "stage3_unit15_plus" + top: "stage3_unit16_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit16_bn1" + type: "BatchNorm" + bottom: "stage3_unit16_conv1" + top: "stage3_unit16_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit16_bn1" + bottom: "stage3_unit16_conv1" + top: "stage3_unit16_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit16_relu1" + type: "ReLU" + bottom: "stage3_unit16_conv1" + top: "stage3_unit16_conv1" +} + +layer { + name: "stage3_unit16_conv2" + type: "Convolution" + bottom: "stage3_unit16_conv1" + top: "stage3_unit16_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit16_bn2" + type: "BatchNorm" + bottom: "stage3_unit16_conv2" + top: "stage3_unit16_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit16_bn2" + bottom: "stage3_unit16_conv2" + top: "stage3_unit16_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit16_relu2" + type: "ReLU" + bottom: "stage3_unit16_conv2" + top: "stage3_unit16_conv2" +} + +layer { + name: "stage3_unit16_conv3" + type: "Convolution" + bottom: "stage3_unit16_conv2" + top: "stage3_unit16_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit16_bn3" + type: "BatchNorm" + bottom: "stage3_unit16_conv3" + top: "stage3_unit16_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit16_bn3" + bottom: "stage3_unit16_conv3" + top: "stage3_unit16_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit16_plus" + type: "Eltwise" + bottom: "stage3_unit15_plus" + bottom: "stage3_unit16_conv3" + top: "stage3_unit16_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit16_relu" + type: "ReLU" + bottom: "stage3_unit16_plus" + top: "stage3_unit16_plus" +} + +layer { + name: "stage3_unit17_conv1" + type: "Convolution" + bottom: "stage3_unit16_plus" + top: "stage3_unit17_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit17_bn1" + type: "BatchNorm" + bottom: "stage3_unit17_conv1" + top: "stage3_unit17_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit17_bn1" + bottom: "stage3_unit17_conv1" + top: "stage3_unit17_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit17_relu1" + type: "ReLU" + bottom: "stage3_unit17_conv1" + top: "stage3_unit17_conv1" +} + +layer { + name: "stage3_unit17_conv2" + type: "Convolution" + bottom: "stage3_unit17_conv1" + top: "stage3_unit17_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit17_bn2" + type: "BatchNorm" + bottom: "stage3_unit17_conv2" + top: "stage3_unit17_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit17_bn2" + bottom: "stage3_unit17_conv2" + top: "stage3_unit17_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit17_relu2" + type: "ReLU" + bottom: "stage3_unit17_conv2" + top: "stage3_unit17_conv2" +} + +layer { + name: "stage3_unit17_conv3" + type: "Convolution" + bottom: "stage3_unit17_conv2" + top: "stage3_unit17_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit17_bn3" + type: "BatchNorm" + bottom: "stage3_unit17_conv3" + top: "stage3_unit17_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit17_bn3" + bottom: "stage3_unit17_conv3" + top: "stage3_unit17_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit17_plus" + type: "Eltwise" + bottom: "stage3_unit16_plus" + bottom: "stage3_unit17_conv3" + top: "stage3_unit17_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit17_relu" + type: "ReLU" + bottom: "stage3_unit17_plus" + top: "stage3_unit17_plus" +} + +layer { + name: "stage3_unit18_conv1" + type: "Convolution" + bottom: "stage3_unit17_plus" + top: "stage3_unit18_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit18_bn1" + type: "BatchNorm" + bottom: "stage3_unit18_conv1" + top: "stage3_unit18_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit18_bn1" + bottom: "stage3_unit18_conv1" + top: "stage3_unit18_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit18_relu1" + type: "ReLU" + bottom: "stage3_unit18_conv1" + top: "stage3_unit18_conv1" +} + +layer { + name: "stage3_unit18_conv2" + type: "Convolution" + bottom: "stage3_unit18_conv1" + top: "stage3_unit18_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit18_bn2" + type: "BatchNorm" + bottom: "stage3_unit18_conv2" + top: "stage3_unit18_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit18_bn2" + bottom: "stage3_unit18_conv2" + top: "stage3_unit18_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit18_relu2" + type: "ReLU" + bottom: "stage3_unit18_conv2" + top: "stage3_unit18_conv2" +} + +layer { + name: "stage3_unit18_conv3" + type: "Convolution" + bottom: "stage3_unit18_conv2" + top: "stage3_unit18_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit18_bn3" + type: "BatchNorm" + bottom: "stage3_unit18_conv3" + top: "stage3_unit18_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit18_bn3" + bottom: "stage3_unit18_conv3" + top: "stage3_unit18_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit18_plus" + type: "Eltwise" + bottom: "stage3_unit17_plus" + bottom: "stage3_unit18_conv3" + top: "stage3_unit18_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit18_relu" + type: "ReLU" + bottom: "stage3_unit18_plus" + top: "stage3_unit18_plus" +} + +layer { + name: "stage3_unit19_conv1" + type: "Convolution" + bottom: "stage3_unit18_plus" + top: "stage3_unit19_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit19_bn1" + type: "BatchNorm" + bottom: "stage3_unit19_conv1" + top: "stage3_unit19_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit19_bn1" + bottom: "stage3_unit19_conv1" + top: "stage3_unit19_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit19_relu1" + type: "ReLU" + bottom: "stage3_unit19_conv1" + top: "stage3_unit19_conv1" +} + +layer { + name: "stage3_unit19_conv2" + type: "Convolution" + bottom: "stage3_unit19_conv1" + top: "stage3_unit19_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit19_bn2" + type: "BatchNorm" + bottom: "stage3_unit19_conv2" + top: "stage3_unit19_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit19_bn2" + bottom: "stage3_unit19_conv2" + top: "stage3_unit19_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit19_relu2" + type: "ReLU" + bottom: "stage3_unit19_conv2" + top: "stage3_unit19_conv2" +} + +layer { + name: "stage3_unit19_conv3" + type: "Convolution" + bottom: "stage3_unit19_conv2" + top: "stage3_unit19_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit19_bn3" + type: "BatchNorm" + bottom: "stage3_unit19_conv3" + top: "stage3_unit19_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit19_bn3" + bottom: "stage3_unit19_conv3" + top: "stage3_unit19_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit19_plus" + type: "Eltwise" + bottom: "stage3_unit18_plus" + bottom: "stage3_unit19_conv3" + top: "stage3_unit19_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit19_relu" + type: "ReLU" + bottom: "stage3_unit19_plus" + top: "stage3_unit19_plus" +} + +layer { + name: "stage3_unit20_conv1" + type: "Convolution" + bottom: "stage3_unit19_plus" + top: "stage3_unit20_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit20_bn1" + type: "BatchNorm" + bottom: "stage3_unit20_conv1" + top: "stage3_unit20_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit20_bn1" + bottom: "stage3_unit20_conv1" + top: "stage3_unit20_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit20_relu1" + type: "ReLU" + bottom: "stage3_unit20_conv1" + top: "stage3_unit20_conv1" +} + +layer { + name: "stage3_unit20_conv2" + type: "Convolution" + bottom: "stage3_unit20_conv1" + top: "stage3_unit20_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit20_bn2" + type: "BatchNorm" + bottom: "stage3_unit20_conv2" + top: "stage3_unit20_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit20_bn2" + bottom: "stage3_unit20_conv2" + top: "stage3_unit20_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit20_relu2" + type: "ReLU" + bottom: "stage3_unit20_conv2" + top: "stage3_unit20_conv2" +} + +layer { + name: "stage3_unit20_conv3" + type: "Convolution" + bottom: "stage3_unit20_conv2" + top: "stage3_unit20_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit20_bn3" + type: "BatchNorm" + bottom: "stage3_unit20_conv3" + top: "stage3_unit20_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit20_bn3" + bottom: "stage3_unit20_conv3" + top: "stage3_unit20_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit20_plus" + type: "Eltwise" + bottom: "stage3_unit19_plus" + bottom: "stage3_unit20_conv3" + top: "stage3_unit20_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit20_relu" + type: "ReLU" + bottom: "stage3_unit20_plus" + top: "stage3_unit20_plus" +} + +layer { + name: "stage3_unit21_conv1" + type: "Convolution" + bottom: "stage3_unit20_plus" + top: "stage3_unit21_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit21_bn1" + type: "BatchNorm" + bottom: "stage3_unit21_conv1" + top: "stage3_unit21_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit21_bn1" + bottom: "stage3_unit21_conv1" + top: "stage3_unit21_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit21_relu1" + type: "ReLU" + bottom: "stage3_unit21_conv1" + top: "stage3_unit21_conv1" +} + +layer { + name: "stage3_unit21_conv2" + type: "Convolution" + bottom: "stage3_unit21_conv1" + top: "stage3_unit21_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit21_bn2" + type: "BatchNorm" + bottom: "stage3_unit21_conv2" + top: "stage3_unit21_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit21_bn2" + bottom: "stage3_unit21_conv2" + top: "stage3_unit21_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit21_relu2" + type: "ReLU" + bottom: "stage3_unit21_conv2" + top: "stage3_unit21_conv2" +} + +layer { + name: "stage3_unit21_conv3" + type: "Convolution" + bottom: "stage3_unit21_conv2" + top: "stage3_unit21_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit21_bn3" + type: "BatchNorm" + bottom: "stage3_unit21_conv3" + top: "stage3_unit21_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit21_bn3" + bottom: "stage3_unit21_conv3" + top: "stage3_unit21_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit21_plus" + type: "Eltwise" + bottom: "stage3_unit20_plus" + bottom: "stage3_unit21_conv3" + top: "stage3_unit21_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit21_relu" + type: "ReLU" + bottom: "stage3_unit21_plus" + top: "stage3_unit21_plus" +} + +layer { + name: "stage3_unit22_conv1" + type: "Convolution" + bottom: "stage3_unit21_plus" + top: "stage3_unit22_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit22_bn1" + type: "BatchNorm" + bottom: "stage3_unit22_conv1" + top: "stage3_unit22_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit22_bn1" + bottom: "stage3_unit22_conv1" + top: "stage3_unit22_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit22_relu1" + type: "ReLU" + bottom: "stage3_unit22_conv1" + top: "stage3_unit22_conv1" +} + +layer { + name: "stage3_unit22_conv2" + type: "Convolution" + bottom: "stage3_unit22_conv1" + top: "stage3_unit22_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit22_bn2" + type: "BatchNorm" + bottom: "stage3_unit22_conv2" + top: "stage3_unit22_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit22_bn2" + bottom: "stage3_unit22_conv2" + top: "stage3_unit22_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit22_relu2" + type: "ReLU" + bottom: "stage3_unit22_conv2" + top: "stage3_unit22_conv2" +} + +layer { + name: "stage3_unit22_conv3" + type: "Convolution" + bottom: "stage3_unit22_conv2" + top: "stage3_unit22_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit22_bn3" + type: "BatchNorm" + bottom: "stage3_unit22_conv3" + top: "stage3_unit22_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit22_bn3" + bottom: "stage3_unit22_conv3" + top: "stage3_unit22_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit22_plus" + type: "Eltwise" + bottom: "stage3_unit21_plus" + bottom: "stage3_unit22_conv3" + top: "stage3_unit22_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit22_relu" + type: "ReLU" + bottom: "stage3_unit22_plus" + top: "stage3_unit22_plus" +} + +layer { + name: "stage3_unit23_conv1" + type: "Convolution" + bottom: "stage3_unit22_plus" + top: "stage3_unit23_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit23_bn1" + type: "BatchNorm" + bottom: "stage3_unit23_conv1" + top: "stage3_unit23_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit23_bn1" + bottom: "stage3_unit23_conv1" + top: "stage3_unit23_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit23_relu1" + type: "ReLU" + bottom: "stage3_unit23_conv1" + top: "stage3_unit23_conv1" +} + +layer { + name: "stage3_unit23_conv2" + type: "Convolution" + bottom: "stage3_unit23_conv1" + top: "stage3_unit23_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit23_bn2" + type: "BatchNorm" + bottom: "stage3_unit23_conv2" + top: "stage3_unit23_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit23_bn2" + bottom: "stage3_unit23_conv2" + top: "stage3_unit23_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit23_relu2" + type: "ReLU" + bottom: "stage3_unit23_conv2" + top: "stage3_unit23_conv2" +} + +layer { + name: "stage3_unit23_conv3" + type: "Convolution" + bottom: "stage3_unit23_conv2" + top: "stage3_unit23_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit23_bn3" + type: "BatchNorm" + bottom: "stage3_unit23_conv3" + top: "stage3_unit23_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit23_bn3" + bottom: "stage3_unit23_conv3" + top: "stage3_unit23_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit23_plus" + type: "Eltwise" + bottom: "stage3_unit22_plus" + bottom: "stage3_unit23_conv3" + top: "stage3_unit23_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit23_relu" + type: "ReLU" + bottom: "stage3_unit23_plus" + top: "stage3_unit23_plus" +} + +layer { + name: "stage3_unit24_conv1" + type: "Convolution" + bottom: "stage3_unit23_plus" + top: "stage3_unit24_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit24_bn1" + type: "BatchNorm" + bottom: "stage3_unit24_conv1" + top: "stage3_unit24_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit24_bn1" + bottom: "stage3_unit24_conv1" + top: "stage3_unit24_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit24_relu1" + type: "ReLU" + bottom: "stage3_unit24_conv1" + top: "stage3_unit24_conv1" +} + +layer { + name: "stage3_unit24_conv2" + type: "Convolution" + bottom: "stage3_unit24_conv1" + top: "stage3_unit24_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit24_bn2" + type: "BatchNorm" + bottom: "stage3_unit24_conv2" + top: "stage3_unit24_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit24_bn2" + bottom: "stage3_unit24_conv2" + top: "stage3_unit24_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit24_relu2" + type: "ReLU" + bottom: "stage3_unit24_conv2" + top: "stage3_unit24_conv2" +} + +layer { + name: "stage3_unit24_conv3" + type: "Convolution" + bottom: "stage3_unit24_conv2" + top: "stage3_unit24_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit24_bn3" + type: "BatchNorm" + bottom: "stage3_unit24_conv3" + top: "stage3_unit24_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit24_bn3" + bottom: "stage3_unit24_conv3" + top: "stage3_unit24_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit24_plus" + type: "Eltwise" + bottom: "stage3_unit23_plus" + bottom: "stage3_unit24_conv3" + top: "stage3_unit24_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit24_relu" + type: "ReLU" + bottom: "stage3_unit24_plus" + top: "stage3_unit24_plus" +} + +layer { + name: "stage3_unit25_conv1" + type: "Convolution" + bottom: "stage3_unit24_plus" + top: "stage3_unit25_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit25_bn1" + type: "BatchNorm" + bottom: "stage3_unit25_conv1" + top: "stage3_unit25_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit25_bn1" + bottom: "stage3_unit25_conv1" + top: "stage3_unit25_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit25_relu1" + type: "ReLU" + bottom: "stage3_unit25_conv1" + top: "stage3_unit25_conv1" +} + +layer { + name: "stage3_unit25_conv2" + type: "Convolution" + bottom: "stage3_unit25_conv1" + top: "stage3_unit25_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit25_bn2" + type: "BatchNorm" + bottom: "stage3_unit25_conv2" + top: "stage3_unit25_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit25_bn2" + bottom: "stage3_unit25_conv2" + top: "stage3_unit25_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit25_relu2" + type: "ReLU" + bottom: "stage3_unit25_conv2" + top: "stage3_unit25_conv2" +} + +layer { + name: "stage3_unit25_conv3" + type: "Convolution" + bottom: "stage3_unit25_conv2" + top: "stage3_unit25_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit25_bn3" + type: "BatchNorm" + bottom: "stage3_unit25_conv3" + top: "stage3_unit25_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit25_bn3" + bottom: "stage3_unit25_conv3" + top: "stage3_unit25_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit25_plus" + type: "Eltwise" + bottom: "stage3_unit24_plus" + bottom: "stage3_unit25_conv3" + top: "stage3_unit25_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit25_relu" + type: "ReLU" + bottom: "stage3_unit25_plus" + top: "stage3_unit25_plus" +} + +layer { + name: "stage3_unit26_conv1" + type: "Convolution" + bottom: "stage3_unit25_plus" + top: "stage3_unit26_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit26_bn1" + type: "BatchNorm" + bottom: "stage3_unit26_conv1" + top: "stage3_unit26_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit26_bn1" + bottom: "stage3_unit26_conv1" + top: "stage3_unit26_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit26_relu1" + type: "ReLU" + bottom: "stage3_unit26_conv1" + top: "stage3_unit26_conv1" +} + +layer { + name: "stage3_unit26_conv2" + type: "Convolution" + bottom: "stage3_unit26_conv1" + top: "stage3_unit26_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit26_bn2" + type: "BatchNorm" + bottom: "stage3_unit26_conv2" + top: "stage3_unit26_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit26_bn2" + bottom: "stage3_unit26_conv2" + top: "stage3_unit26_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit26_relu2" + type: "ReLU" + bottom: "stage3_unit26_conv2" + top: "stage3_unit26_conv2" +} + +layer { + name: "stage3_unit26_conv3" + type: "Convolution" + bottom: "stage3_unit26_conv2" + top: "stage3_unit26_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit26_bn3" + type: "BatchNorm" + bottom: "stage3_unit26_conv3" + top: "stage3_unit26_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit26_bn3" + bottom: "stage3_unit26_conv3" + top: "stage3_unit26_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit26_plus" + type: "Eltwise" + bottom: "stage3_unit25_plus" + bottom: "stage3_unit26_conv3" + top: "stage3_unit26_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit26_relu" + type: "ReLU" + bottom: "stage3_unit26_plus" + top: "stage3_unit26_plus" +} + +layer { + name: "stage3_unit27_conv1" + type: "Convolution" + bottom: "stage3_unit26_plus" + top: "stage3_unit27_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit27_bn1" + type: "BatchNorm" + bottom: "stage3_unit27_conv1" + top: "stage3_unit27_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit27_bn1" + bottom: "stage3_unit27_conv1" + top: "stage3_unit27_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit27_relu1" + type: "ReLU" + bottom: "stage3_unit27_conv1" + top: "stage3_unit27_conv1" +} + +layer { + name: "stage3_unit27_conv2" + type: "Convolution" + bottom: "stage3_unit27_conv1" + top: "stage3_unit27_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit27_bn2" + type: "BatchNorm" + bottom: "stage3_unit27_conv2" + top: "stage3_unit27_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit27_bn2" + bottom: "stage3_unit27_conv2" + top: "stage3_unit27_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit27_relu2" + type: "ReLU" + bottom: "stage3_unit27_conv2" + top: "stage3_unit27_conv2" +} + +layer { + name: "stage3_unit27_conv3" + type: "Convolution" + bottom: "stage3_unit27_conv2" + top: "stage3_unit27_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit27_bn3" + type: "BatchNorm" + bottom: "stage3_unit27_conv3" + top: "stage3_unit27_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit27_bn3" + bottom: "stage3_unit27_conv3" + top: "stage3_unit27_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit27_plus" + type: "Eltwise" + bottom: "stage3_unit26_plus" + bottom: "stage3_unit27_conv3" + top: "stage3_unit27_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit27_relu" + type: "ReLU" + bottom: "stage3_unit27_plus" + top: "stage3_unit27_plus" +} + +layer { + name: "stage3_unit28_conv1" + type: "Convolution" + bottom: "stage3_unit27_plus" + top: "stage3_unit28_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit28_bn1" + type: "BatchNorm" + bottom: "stage3_unit28_conv1" + top: "stage3_unit28_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit28_bn1" + bottom: "stage3_unit28_conv1" + top: "stage3_unit28_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit28_relu1" + type: "ReLU" + bottom: "stage3_unit28_conv1" + top: "stage3_unit28_conv1" +} + +layer { + name: "stage3_unit28_conv2" + type: "Convolution" + bottom: "stage3_unit28_conv1" + top: "stage3_unit28_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit28_bn2" + type: "BatchNorm" + bottom: "stage3_unit28_conv2" + top: "stage3_unit28_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit28_bn2" + bottom: "stage3_unit28_conv2" + top: "stage3_unit28_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit28_relu2" + type: "ReLU" + bottom: "stage3_unit28_conv2" + top: "stage3_unit28_conv2" +} + +layer { + name: "stage3_unit28_conv3" + type: "Convolution" + bottom: "stage3_unit28_conv2" + top: "stage3_unit28_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit28_bn3" + type: "BatchNorm" + bottom: "stage3_unit28_conv3" + top: "stage3_unit28_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit28_bn3" + bottom: "stage3_unit28_conv3" + top: "stage3_unit28_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit28_plus" + type: "Eltwise" + bottom: "stage3_unit27_plus" + bottom: "stage3_unit28_conv3" + top: "stage3_unit28_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit28_relu" + type: "ReLU" + bottom: "stage3_unit28_plus" + top: "stage3_unit28_plus" +} + +layer { + name: "stage3_unit29_conv1" + type: "Convolution" + bottom: "stage3_unit28_plus" + top: "stage3_unit29_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit29_bn1" + type: "BatchNorm" + bottom: "stage3_unit29_conv1" + top: "stage3_unit29_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit29_bn1" + bottom: "stage3_unit29_conv1" + top: "stage3_unit29_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit29_relu1" + type: "ReLU" + bottom: "stage3_unit29_conv1" + top: "stage3_unit29_conv1" +} + +layer { + name: "stage3_unit29_conv2" + type: "Convolution" + bottom: "stage3_unit29_conv1" + top: "stage3_unit29_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit29_bn2" + type: "BatchNorm" + bottom: "stage3_unit29_conv2" + top: "stage3_unit29_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit29_bn2" + bottom: "stage3_unit29_conv2" + top: "stage3_unit29_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit29_relu2" + type: "ReLU" + bottom: "stage3_unit29_conv2" + top: "stage3_unit29_conv2" +} + +layer { + name: "stage3_unit29_conv3" + type: "Convolution" + bottom: "stage3_unit29_conv2" + top: "stage3_unit29_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit29_bn3" + type: "BatchNorm" + bottom: "stage3_unit29_conv3" + top: "stage3_unit29_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit29_bn3" + bottom: "stage3_unit29_conv3" + top: "stage3_unit29_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit29_plus" + type: "Eltwise" + bottom: "stage3_unit28_plus" + bottom: "stage3_unit29_conv3" + top: "stage3_unit29_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit29_relu" + type: "ReLU" + bottom: "stage3_unit29_plus" + top: "stage3_unit29_plus" +} + +layer { + name: "stage3_unit30_conv1" + type: "Convolution" + bottom: "stage3_unit29_plus" + top: "stage3_unit30_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit30_bn1" + type: "BatchNorm" + bottom: "stage3_unit30_conv1" + top: "stage3_unit30_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit30_bn1" + bottom: "stage3_unit30_conv1" + top: "stage3_unit30_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit30_relu1" + type: "ReLU" + bottom: "stage3_unit30_conv1" + top: "stage3_unit30_conv1" +} + +layer { + name: "stage3_unit30_conv2" + type: "Convolution" + bottom: "stage3_unit30_conv1" + top: "stage3_unit30_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit30_bn2" + type: "BatchNorm" + bottom: "stage3_unit30_conv2" + top: "stage3_unit30_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit30_bn2" + bottom: "stage3_unit30_conv2" + top: "stage3_unit30_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit30_relu2" + type: "ReLU" + bottom: "stage3_unit30_conv2" + top: "stage3_unit30_conv2" +} + +layer { + name: "stage3_unit30_conv3" + type: "Convolution" + bottom: "stage3_unit30_conv2" + top: "stage3_unit30_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit30_bn3" + type: "BatchNorm" + bottom: "stage3_unit30_conv3" + top: "stage3_unit30_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit30_bn3" + bottom: "stage3_unit30_conv3" + top: "stage3_unit30_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit30_plus" + type: "Eltwise" + bottom: "stage3_unit29_plus" + bottom: "stage3_unit30_conv3" + top: "stage3_unit30_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit30_relu" + type: "ReLU" + bottom: "stage3_unit30_plus" + top: "stage3_unit30_plus" +} + +layer { + name: "stage3_unit31_conv1" + type: "Convolution" + bottom: "stage3_unit30_plus" + top: "stage3_unit31_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit31_bn1" + type: "BatchNorm" + bottom: "stage3_unit31_conv1" + top: "stage3_unit31_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit31_bn1" + bottom: "stage3_unit31_conv1" + top: "stage3_unit31_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit31_relu1" + type: "ReLU" + bottom: "stage3_unit31_conv1" + top: "stage3_unit31_conv1" +} + +layer { + name: "stage3_unit31_conv2" + type: "Convolution" + bottom: "stage3_unit31_conv1" + top: "stage3_unit31_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit31_bn2" + type: "BatchNorm" + bottom: "stage3_unit31_conv2" + top: "stage3_unit31_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit31_bn2" + bottom: "stage3_unit31_conv2" + top: "stage3_unit31_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit31_relu2" + type: "ReLU" + bottom: "stage3_unit31_conv2" + top: "stage3_unit31_conv2" +} + +layer { + name: "stage3_unit31_conv3" + type: "Convolution" + bottom: "stage3_unit31_conv2" + top: "stage3_unit31_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit31_bn3" + type: "BatchNorm" + bottom: "stage3_unit31_conv3" + top: "stage3_unit31_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit31_bn3" + bottom: "stage3_unit31_conv3" + top: "stage3_unit31_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit31_plus" + type: "Eltwise" + bottom: "stage3_unit30_plus" + bottom: "stage3_unit31_conv3" + top: "stage3_unit31_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit31_relu" + type: "ReLU" + bottom: "stage3_unit31_plus" + top: "stage3_unit31_plus" +} + +layer { + name: "stage3_unit32_conv1" + type: "Convolution" + bottom: "stage3_unit31_plus" + top: "stage3_unit32_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit32_bn1" + type: "BatchNorm" + bottom: "stage3_unit32_conv1" + top: "stage3_unit32_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit32_bn1" + bottom: "stage3_unit32_conv1" + top: "stage3_unit32_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit32_relu1" + type: "ReLU" + bottom: "stage3_unit32_conv1" + top: "stage3_unit32_conv1" +} + +layer { + name: "stage3_unit32_conv2" + type: "Convolution" + bottom: "stage3_unit32_conv1" + top: "stage3_unit32_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit32_bn2" + type: "BatchNorm" + bottom: "stage3_unit32_conv2" + top: "stage3_unit32_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit32_bn2" + bottom: "stage3_unit32_conv2" + top: "stage3_unit32_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit32_relu2" + type: "ReLU" + bottom: "stage3_unit32_conv2" + top: "stage3_unit32_conv2" +} + +layer { + name: "stage3_unit32_conv3" + type: "Convolution" + bottom: "stage3_unit32_conv2" + top: "stage3_unit32_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit32_bn3" + type: "BatchNorm" + bottom: "stage3_unit32_conv3" + top: "stage3_unit32_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit32_bn3" + bottom: "stage3_unit32_conv3" + top: "stage3_unit32_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit32_plus" + type: "Eltwise" + bottom: "stage3_unit31_plus" + bottom: "stage3_unit32_conv3" + top: "stage3_unit32_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit32_relu" + type: "ReLU" + bottom: "stage3_unit32_plus" + top: "stage3_unit32_plus" +} + +layer { + name: "stage3_unit33_conv1" + type: "Convolution" + bottom: "stage3_unit32_plus" + top: "stage3_unit33_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit33_bn1" + type: "BatchNorm" + bottom: "stage3_unit33_conv1" + top: "stage3_unit33_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit33_bn1" + bottom: "stage3_unit33_conv1" + top: "stage3_unit33_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit33_relu1" + type: "ReLU" + bottom: "stage3_unit33_conv1" + top: "stage3_unit33_conv1" +} + +layer { + name: "stage3_unit33_conv2" + type: "Convolution" + bottom: "stage3_unit33_conv1" + top: "stage3_unit33_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit33_bn2" + type: "BatchNorm" + bottom: "stage3_unit33_conv2" + top: "stage3_unit33_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit33_bn2" + bottom: "stage3_unit33_conv2" + top: "stage3_unit33_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit33_relu2" + type: "ReLU" + bottom: "stage3_unit33_conv2" + top: "stage3_unit33_conv2" +} + +layer { + name: "stage3_unit33_conv3" + type: "Convolution" + bottom: "stage3_unit33_conv2" + top: "stage3_unit33_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit33_bn3" + type: "BatchNorm" + bottom: "stage3_unit33_conv3" + top: "stage3_unit33_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit33_bn3" + bottom: "stage3_unit33_conv3" + top: "stage3_unit33_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit33_plus" + type: "Eltwise" + bottom: "stage3_unit32_plus" + bottom: "stage3_unit33_conv3" + top: "stage3_unit33_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit33_relu" + type: "ReLU" + bottom: "stage3_unit33_plus" + top: "stage3_unit33_plus" +} + +layer { + name: "stage3_unit34_conv1" + type: "Convolution" + bottom: "stage3_unit33_plus" + top: "stage3_unit34_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit34_bn1" + type: "BatchNorm" + bottom: "stage3_unit34_conv1" + top: "stage3_unit34_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit34_bn1" + bottom: "stage3_unit34_conv1" + top: "stage3_unit34_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit34_relu1" + type: "ReLU" + bottom: "stage3_unit34_conv1" + top: "stage3_unit34_conv1" +} + +layer { + name: "stage3_unit34_conv2" + type: "Convolution" + bottom: "stage3_unit34_conv1" + top: "stage3_unit34_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit34_bn2" + type: "BatchNorm" + bottom: "stage3_unit34_conv2" + top: "stage3_unit34_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit34_bn2" + bottom: "stage3_unit34_conv2" + top: "stage3_unit34_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit34_relu2" + type: "ReLU" + bottom: "stage3_unit34_conv2" + top: "stage3_unit34_conv2" +} + +layer { + name: "stage3_unit34_conv3" + type: "Convolution" + bottom: "stage3_unit34_conv2" + top: "stage3_unit34_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit34_bn3" + type: "BatchNorm" + bottom: "stage3_unit34_conv3" + top: "stage3_unit34_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit34_bn3" + bottom: "stage3_unit34_conv3" + top: "stage3_unit34_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit34_plus" + type: "Eltwise" + bottom: "stage3_unit33_plus" + bottom: "stage3_unit34_conv3" + top: "stage3_unit34_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit34_relu" + type: "ReLU" + bottom: "stage3_unit34_plus" + top: "stage3_unit34_plus" +} + +layer { + name: "stage3_unit35_conv1" + type: "Convolution" + bottom: "stage3_unit34_plus" + top: "stage3_unit35_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit35_bn1" + type: "BatchNorm" + bottom: "stage3_unit35_conv1" + top: "stage3_unit35_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit35_bn1" + bottom: "stage3_unit35_conv1" + top: "stage3_unit35_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit35_relu1" + type: "ReLU" + bottom: "stage3_unit35_conv1" + top: "stage3_unit35_conv1" +} + +layer { + name: "stage3_unit35_conv2" + type: "Convolution" + bottom: "stage3_unit35_conv1" + top: "stage3_unit35_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit35_bn2" + type: "BatchNorm" + bottom: "stage3_unit35_conv2" + top: "stage3_unit35_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit35_bn2" + bottom: "stage3_unit35_conv2" + top: "stage3_unit35_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit35_relu2" + type: "ReLU" + bottom: "stage3_unit35_conv2" + top: "stage3_unit35_conv2" +} + +layer { + name: "stage3_unit35_conv3" + type: "Convolution" + bottom: "stage3_unit35_conv2" + top: "stage3_unit35_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit35_bn3" + type: "BatchNorm" + bottom: "stage3_unit35_conv3" + top: "stage3_unit35_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit35_bn3" + bottom: "stage3_unit35_conv3" + top: "stage3_unit35_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit35_plus" + type: "Eltwise" + bottom: "stage3_unit34_plus" + bottom: "stage3_unit35_conv3" + top: "stage3_unit35_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit35_relu" + type: "ReLU" + bottom: "stage3_unit35_plus" + top: "stage3_unit35_plus" +} + +layer { + name: "stage3_unit36_conv1" + type: "Convolution" + bottom: "stage3_unit35_plus" + top: "stage3_unit36_conv1" + convolution_param { + num_output: 512 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit36_bn1" + type: "BatchNorm" + bottom: "stage3_unit36_conv1" + top: "stage3_unit36_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit36_bn1" + bottom: "stage3_unit36_conv1" + top: "stage3_unit36_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit36_relu1" + type: "ReLU" + bottom: "stage3_unit36_conv1" + top: "stage3_unit36_conv1" +} + +layer { + name: "stage3_unit36_conv2" + type: "Convolution" + bottom: "stage3_unit36_conv1" + top: "stage3_unit36_conv2" + convolution_param { + num_output: 512 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage3_unit36_bn2" + type: "BatchNorm" + bottom: "stage3_unit36_conv2" + top: "stage3_unit36_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit36_bn2" + bottom: "stage3_unit36_conv2" + top: "stage3_unit36_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit36_relu2" + type: "ReLU" + bottom: "stage3_unit36_conv2" + top: "stage3_unit36_conv2" +} + +layer { + name: "stage3_unit36_conv3" + type: "Convolution" + bottom: "stage3_unit36_conv2" + top: "stage3_unit36_conv3" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage3_unit36_bn3" + type: "BatchNorm" + bottom: "stage3_unit36_conv3" + top: "stage3_unit36_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage3_unit36_bn3" + bottom: "stage3_unit36_conv3" + top: "stage3_unit36_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage3_unit36_plus" + type: "Eltwise" + bottom: "stage3_unit35_plus" + bottom: "stage3_unit36_conv3" + top: "stage3_unit36_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage3_unit36_relu" + type: "ReLU" + bottom: "stage3_unit36_plus" + top: "stage3_unit36_plus" +} + +layer { + name: "stage4_unit1_conv1" + type: "Convolution" + bottom: "stage3_unit36_plus" + top: "stage4_unit1_conv1" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit1_bn1" + type: "BatchNorm" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_bn1" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_relu1" + type: "ReLU" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv1" +} + +layer { + name: "stage4_unit1_conv2" + type: "Convolution" + bottom: "stage4_unit1_conv1" + top: "stage4_unit1_conv2" + convolution_param { + num_output: 1024 + kernel_size: 3 + stride: 2 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage4_unit1_bn2" + type: "BatchNorm" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_bn2" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_relu2" + type: "ReLU" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv2" +} + +layer { + name: "stage4_unit1_conv3" + type: "Convolution" + bottom: "stage4_unit1_conv2" + top: "stage4_unit1_conv3" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit1_bn3" + type: "BatchNorm" + bottom: "stage4_unit1_conv3" + top: "stage4_unit1_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_bn3" + bottom: "stage4_unit1_conv3" + top: "stage4_unit1_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_sc" + type: "Convolution" + bottom: "stage3_unit36_plus" + top: "stage4_unit1_sc" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 2 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit1_sc_bn" + type: "BatchNorm" + bottom: "stage4_unit1_sc" + top: "stage4_unit1_sc" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit1_sc_bn" + bottom: "stage4_unit1_sc" + top: "stage4_unit1_sc" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit1_plus" + type: "Eltwise" + bottom: "stage4_unit1_sc" + bottom: "stage4_unit1_conv3" + top: "stage4_unit1_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage4_unit1_relu" + type: "ReLU" + bottom: "stage4_unit1_plus" + top: "stage4_unit1_plus" +} + +layer { + name: "stage4_unit2_conv1" + type: "Convolution" + bottom: "stage4_unit1_plus" + top: "stage4_unit2_conv1" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit2_bn1" + type: "BatchNorm" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit2_bn1" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit2_relu1" + type: "ReLU" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv1" +} + +layer { + name: "stage4_unit2_conv2" + type: "Convolution" + bottom: "stage4_unit2_conv1" + top: "stage4_unit2_conv2" + convolution_param { + num_output: 1024 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage4_unit2_bn2" + type: "BatchNorm" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit2_bn2" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit2_relu2" + type: "ReLU" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv2" +} + +layer { + name: "stage4_unit2_conv3" + type: "Convolution" + bottom: "stage4_unit2_conv2" + top: "stage4_unit2_conv3" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit2_bn3" + type: "BatchNorm" + bottom: "stage4_unit2_conv3" + top: "stage4_unit2_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit2_bn3" + bottom: "stage4_unit2_conv3" + top: "stage4_unit2_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit2_plus" + type: "Eltwise" + bottom: "stage4_unit1_plus" + bottom: "stage4_unit2_conv3" + top: "stage4_unit2_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage4_unit2_relu" + type: "ReLU" + bottom: "stage4_unit2_plus" + top: "stage4_unit2_plus" +} + +layer { + name: "stage4_unit3_conv1" + type: "Convolution" + bottom: "stage4_unit2_plus" + top: "stage4_unit3_conv1" + convolution_param { + num_output: 1024 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit3_bn1" + type: "BatchNorm" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv1" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit3_bn1" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv1" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit3_relu1" + type: "ReLU" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv1" +} + +layer { + name: "stage4_unit3_conv2" + type: "Convolution" + bottom: "stage4_unit3_conv1" + top: "stage4_unit3_conv2" + convolution_param { + num_output: 1024 + kernel_size: 3 + stride: 1 + group: 32 + pad: 1 + bias_term: false + } +} + +layer { + name: "stage4_unit3_bn2" + type: "BatchNorm" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv2" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit3_bn2" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv2" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit3_relu2" + type: "ReLU" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv2" +} + +layer { + name: "stage4_unit3_conv3" + type: "Convolution" + bottom: "stage4_unit3_conv2" + top: "stage4_unit3_conv3" + convolution_param { + num_output: 2048 + kernel_size: 1 + stride: 1 + pad: 0 + bias_term: false + } +} + +layer { + name: "stage4_unit3_bn3" + type: "BatchNorm" + bottom: "stage4_unit3_conv3" + top: "stage4_unit3_conv3" + batch_norm_param { + use_global_stats: true + eps: 2e-5 + } +} + +layer { + name: "scale_stage4_unit3_bn3" + bottom: "stage4_unit3_conv3" + top: "stage4_unit3_conv3" + type: "Scale" + scale_param { + bias_term: true + } +} + +layer { + name: "stage4_unit3_plus" + type: "Eltwise" + bottom: "stage4_unit2_plus" + bottom: "stage4_unit3_conv3" + top: "stage4_unit3_plus" + eltwise_param { + operation: SUM + } +} + +layer { + name: "stage4_unit3_relu" + type: "ReLU" + bottom: "stage4_unit3_plus" + top: "stage4_unit3_plus" +} + +layer { + name: "pool1" + type: "Pooling" + bottom: "stage4_unit3_plus" + top: "pool1" + pooling_param { + global_pooling : true + pool: AVE + } +} + +layer { + name: "fc1" + type: "InnerProduct" + bottom: "pool1" + top: "fc1" + 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: "prob" + type: "Softmax" + bottom: "fc1" + top: "prob" +} + From 92065d498013ebf7e68c8bb2574b6020c1791dd7 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Sun, 25 Dec 2016 09:03:35 -0800 Subject: [PATCH 12/26] res152 onedrive link --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index fccd2a3..b6862ef 100644 --- a/README.md +++ b/README.md @@ -37,3 +37,5 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) ResNeXt-50 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495Lrjg3NE0LxvH-7R81B) ResNeXt-101 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495LrjgyQx2cKLOXKEQgN) + + ResNeXt-152 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495Lrjk2kN1ebw77WkyZN) From 8d5bddc7de1ad6964f6678f45ca93c06667e3058 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Tue, 27 Dec 2016 20:36:12 -0800 Subject: [PATCH 13/26] Add files via upload --- 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zc1hON)rosA<+JOSqNqXXIb*=wTy)fvuSX=4L*Ax7Eb}8@9G3^jR`}VUxch@mo!Rhnd6>J8)?_AcASXO8VMLE$!(yhM-Fx9{I;z**vu z2hhksI5QVsYHxqPz88p&2Jj5jY)e)7PTKI3E(1@IFRah066LfYD0Yn42cl~&i5qm~ z@mYRg;^5>Y!;YepP8_3%T~bsO6Q)TKOz20Lz%(N`FYw=vfj)-kKkfiLs)x(PAZzHMi~GXO9O*|!QU!{gJ&Sq`%2v5<8v>~Bl*HMj?8>YM=HM5E+D}aQ`H)(t5eEG7HUPvk7myN0nglAuapnqM^&PHa`IiO$ zG2?iZ#y7$=>!P|D4b2)a`E#c=emu>U8l sH~jb4{ILZ8|C@;szzF}3qp`wjAepzm^8OAg@dH5F8%Sp0MS^?=>Px# literal 0 HcmV?d00001 From 51652797657a7b112788332af6803b207eddf14f Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Tue, 27 Dec 2016 20:37:23 -0800 Subject: [PATCH 14/26] add training curve --- README.md | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index b6862ef..6bfd51c 100644 --- a/README.md +++ b/README.md @@ -31,7 +31,14 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |**ResNeXt-152** | 320x320 |**19.9**%|**4.8**%| - +### Training Curve: + +
+ +
+ + + ### Model files: ResNeXt-50 OneDrive download: [link](https://1drv.ms/u/s!Aqd-q_R495Lrjg3NE0LxvH-7R81B) From aa3a82a1376cf0bbb94e0f4de37289783cae71f6 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Tue, 27 Dec 2016 20:38:25 -0800 Subject: [PATCH 15/26] Add files via upload --- training-curve.png | Bin 131739 -> 132306 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/training-curve.png b/training-curve.png index c3b52cf8647e4fa2c5ac74f7ef50a408069513f2..6f37be76e9820d8fa508df06695d83d93ded8c11 100644 GIT binary patch literal 132306 zcmeFZcUaE-|2Li$B3&p^Dl2KDrAHd3Q94m2_UZy#S=SlXBLM*dl3V)%`kv}FrkYnC<1sUMBBxbBo!v-Y zQCd@$YWd9Iuvh?pTiI*ggyg+xr)n?U{q`6k`xHm$@_&DM>11`+ zhF@RbS?fX0{rlV0mw0X0{QCOUov`99zrVeKno{fcmq%Xx-%De8{NDi~Bl|yhg?P#c zIW45G%p|$QT>s!PIX9Y*1fRrK7&X}LI(Mes!(n-Gc(bN_d6?(F)=aCjI^pqNlCTj*^JRJm{kS|vRw|l z$LKhIYM`k)Tr$JB`MA|sM|*RdZ$yZwL+qJ{I|2mEIx@63{TiN2=c~KiBb{|$9Z<4 zjlXZ8?kirzA{X-9%gd`ZJ1Hs2!a=LzC6Ak>Afc?T?blV45LQBtgNhtc-8Q23_>SLtAYf>AJYrO 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zc1hON)rosA<+JOSqNqXXIb*=wTy)fvuSX=4L*Ax7Eb}8@9G3^jR`}VUxch@mo!Rhnd6>J8)?_AcASXO8VMLE$!(yhM-Fx9{I;z**vu z2hhksI5QVsYHxqPz88p&2Jj5jY)e)7PTKI3E(1@IFRah066LfYD0Yn42cl~&i5qm~ z@mYRg;^5>Y!;YepP8_3%T~bsO6Q)TKOz20Lz%(N`FYw=vfj)-kKkfiLs)x(PAZzHMi~GXO9O*|!QU!{gJ&Sq`%2v5<8v>~Bl*HMj?8>YM=HM5E+D}aQ`H)(t5eEG7HUPvk7myN0nglAuapnqM^&PHa`IiO$ zG2?iZ#y7$=>!P|D4b2)a`E#c=emu>U8l sH~jb4{ILZ8|C@;szzF}3qp`wjAepzm^8OAg@dH5F8%Sp0MS^?=>Px# From 027507bf3a95c74186f9e8f45b3bb1ca858bc19b Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Tue, 27 Dec 2016 20:39:07 -0800 Subject: [PATCH 16/26] Update README.md --- README.md | 3 --- 1 file changed, 3 deletions(-) diff --git a/README.md b/README.md index 6bfd51c..fefdedc 100644 --- a/README.md +++ b/README.md @@ -33,9 +33,6 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) ### Training Curve: -
- -
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zl^56U(X%OEHp+#%Q&jZJPCSE$a%;r->BAC`wHHZHB$^gLy0zFRW(mx9&1WWDdfKWq zL|84S-K%*{LVy5F9AceUP*JUTDIs=Re%Hsp>c88afvYopBB}`nf{aSq3slXRM54|b{eiOnfPZ3`6we}mD z)X>Z@@4b?1Vcgl->FeY36d~~|ds@5Yqs#GE;?a&Qm6nMN(T53%8p2j0pE?ZN{s@6$Cu*7r zfTxy6pJs#t6+oGhx4Z?$iu!1a#)y)!(7&&<66!zmKL*fbMe6NL11qa zu2T;1sXpv3BgSRIg2cejf$@S$sZLB$X5&}Q%uMW`B~Bh$`*@b+2E6Hh4g24iaq}up zR)3%_CA+?!ko{YXh9kej<9FR7UZI=B&lkJf&+V$9Ysw>5H6ITC-&*+J)%Q=KBL1Qy rLhlcsLtK%?`ac){TGc6Rxkro3Oy~89t0c}zizS`8_SgRcarZ)> literal 0 HcmV?d00001 From 5d65204f24ba0e98ba1a0281d296b400d985c793 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Tue, 27 Dec 2016 20:42:18 -0800 Subject: [PATCH 21/26] Update README.md --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index fefdedc..16b1287 100644 --- a/README.md +++ b/README.md @@ -33,7 +33,9 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) ### Training Curve: - +
+ +
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zl^56U(X%OEHp+#%Q&jZJPCSE$a%;r->BAC`wHHZHB$^gLy0zFRW(mx9&1WWDdfKWq zL|84S-K%*{LVy5F9AceUP*JUTDIs=Re%Hsp>c88afvYopBB}`nf{aSq3slXRM54|b{eiOnfPZ3`6we}mD z)X>Z@@4b?1Vcgl->FeY36d~~|ds@5Yqs#GE;?a&Qm6nMN(T53%8p2j0pE?ZN{s@6$Cu*7r zfTxy6pJs#t6+oGhx4Z?$iu!1a#)y)!(7&&<66!zmKL*fbMe6NL11qa zu2T;1sXpv3BgSRIg2cejf$@S$sZLB$X5&}Q%uMW`B~Bh$`*@b+2E6Hh4g24iaq}up zR)3%_CA+?!ko{YXh9kej<9FR7UZI=B&lkJf&+V$9Ysw>5H6ITC-&*+J)%Q=KBL1Qy rLhlcsLtK%?`ac){TGc6Rxkro3Oy~89t0c}zizS`8_SgRcarZ)> From 439acfaea24e0c9d7e13e875005b9e446fb16560 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Mon, 16 Jan 2017 10:22:05 -0800 Subject: [PATCH 23/26] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 16b1287..f8a965d 100644 --- a/README.md +++ b/README.md @@ -12,9 +12,10 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) ResNet-50|24.7%|7.8% **ResNeXt-50**|**23.1**%|**6.7**% ResNet-101|23.6%|7.1% - **ResNeXt-101**|**22.1**%|**5.8**% + **ResNeXt-101(32x4d)**|**22.1**%|**5.8**% ResNet-152|23.0%|6.7% **ResNeXt-152**|**21.3**%|**5.6**% + **ResNeXt-101(64x4d)**|**20.8**%|**5.5**% From 4c4094410b8102115ae3afe1a4c4aa2563998e0a Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Mon, 16 Jan 2017 10:23:25 -0800 Subject: [PATCH 24/26] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index f8a965d..0d94d98 100644 --- a/README.md +++ b/README.md @@ -28,8 +28,9 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |ResNet-200-v1 | 320x320 |21.8%|6.0%| |ResNet-200-v2 | 320x320 |20.7%|5.3%| |**ResNeXt-50** | 320x320 |**21.9**%|**5.9**%| -|**ResNeXt-101** | 320x320 |**20.2**%|**4.9**%| +|**ResNeXt-101(32x4d)** | 320x320 |**20.2**%|**4.9**%| |**ResNeXt-152** | 320x320 |**19.9**%|**4.8**%| +|**ResNeXt-101(64x4d)** | 320x320 |**19.8**%|**4.8**%| ### Training Curve: From 9c43edbc4be15d444c06de90712e1810cdf6f734 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Mon, 16 Jan 2017 11:33:52 -0800 Subject: [PATCH 25/26] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 0d94d98..3b6d423 100644 --- a/README.md +++ b/README.md @@ -30,7 +30,7 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |**ResNeXt-50** | 320x320 |**21.9**%|**5.9**%| |**ResNeXt-101(32x4d)** | 320x320 |**20.2**%|**4.9**%| |**ResNeXt-152** | 320x320 |**19.9**%|**4.8**%| -|**ResNeXt-101(64x4d)** | 320x320 |**19.8**%|**4.8**%| +|**ResNeXt-101(64x4d)** | 320x320 |**19.7**%|**4.8**%| ### Training Curve: From b8b50b34f416a3b1f42f03cbb5c4bb00ef414d59 Mon Sep 17 00:00:00 2001 From: Terry Chen Date: Mon, 16 Jan 2017 19:52:44 -0800 Subject: [PATCH 26/26] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3b6d423..e1f454f 100644 --- a/README.md +++ b/README.md @@ -30,7 +30,7 @@ Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) |**ResNeXt-50** | 320x320 |**21.9**%|**5.9**%| |**ResNeXt-101(32x4d)** | 320x320 |**20.2**%|**4.9**%| |**ResNeXt-152** | 320x320 |**19.9**%|**4.8**%| -|**ResNeXt-101(64x4d)** | 320x320 |**19.7**%|**4.8**%| +|**ResNeXt-101(64x4d)** | 320x320 |**19.5**%|**4.8**%| ### Training Curve: