Repository: KaimingHe/deep-residual-networks
Branch: master
Commit: a7026cb6d478
Files: 6
Total size: 199.4 KB

Directory structure:
gitextract_rc3c25mq/

├── .gitmodules
├── LICENSE
├── README.md
└── prototxt/
    ├── ResNet-101-deploy.prototxt
    ├── ResNet-152-deploy.prototxt
    └── ResNet-50-deploy.prototxt

================================================
FILE CONTENTS
================================================

================================================
FILE: .gitmodules
================================================
[submodule "caffe"]
	path = caffe
	url = https://github.com/BVLC/caffe.git
	branch = master


================================================
FILE: LICENSE
================================================
The MIT License (MIT)

Copyright (c) 2016 Shaoqing Ren

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


================================================
FILE: README.md
================================================
# Deep Residual Networks

By [Kaiming He](http://kaiminghe.com), [Xiangyu Zhang](https://scholar.google.com/citations?user=yuB-cfoAAAAJ&hl=en), [Shaoqing Ren](http://home.ustc.edu.cn/~sqren/), [Jian Sun](http://research.microsoft.com/en-us/people/jiansun/).

Microsoft Research Asia (MSRA).

### Table of Contents
0. [Introduction](#introduction)
0. [Citation](#citation)
0. [Disclaimer and known issues](#disclaimer-and-known-issues)
0. [Models](#models)
0. [Results](#results)
0. [Third-party re-implementations](#third-party-re-implementations)

### Introduction

This repository contains the original models (ResNet-50, ResNet-101, and ResNet-152) described in the paper "Deep Residual Learning for Image Recognition" (http://arxiv.org/abs/1512.03385). These models are those used in [ILSVRC] (http://image-net.org/challenges/LSVRC/2015/) and [COCO](http://mscoco.org/dataset/#detections-challenge2015) 2015 competitions, which won the 1st places in: ImageNet classification, ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.

**Note**

0. Re-implementations with **training code** and models from Facebook AI Research (FAIR): [blog](http://torch.ch/blog/2016/02/04/resnets.html), [code](https://github.com/facebook/fb.resnet.torch)
0. Code of improved **1K-layer ResNets** with 4.62% test error on CIFAR-10 in our new arXiv paper: https://github.com/KaimingHe/resnet-1k-layers

### Citation

If you use these models in your research, please cite:

	@article{He2015,
		author = {Kaiming He and Xiangyu Zhang and Shaoqing Ren and Jian Sun},
		title = {Deep Residual Learning for Image Recognition},
		journal = {arXiv preprint arXiv:1512.03385},
		year = {2015}
	}

### Disclaimer and known issues

0. These models are converted from our own implementation to a recent version of Caffe (2016/2/3, b590f1d). The numerical results using this code are as in the tables below.
0. These models are for the usage of testing or fine-tuning.
0. These models were **not** trained using this version of Caffe.
0. If you want to train these models using this version of Caffe without modifications, please notice that:
	- GPU memory might be insufficient for extremely deep models.
	- Changes of mini-batch size should impact accuracy (we use a mini-batch of 256 images on 8 GPUs, that is, 32 images per GPU).
	- Implementation of data augmentation might be different (see our paper about the data augmentation we used).
	- We randomly shuffle data at the beginning of every epoch.
	- There might be some other untested issues.
0. In our BN layers, the provided mean and variance are strictly computed using average (**not** moving average) on a sufficiently large training batch after the training procedure. The numerical results are very stable (variation of val error < 0.1%). Using moving average might lead to different results. 
0. In the BN paper, the BN layer learns gamma/beta. To implement BN in this version of Caffe, we use its provided "batch_norm_layer" (which has no gamma/beta learned) followed by "scale_layer" (which learns gamma/beta).
0. We use Caffe's implementation of SGD with momentum: v := momentum\*v + lr\*g. **If you want to port these models to other libraries (e.g., Torch, CNTK), please pay careful attention to the possibly different implementation of SGD with momentum**: v := momentum\*v + (1-momentum)\*lr\*g, which changes the effective learning rates.

	
### Models

0. Visualizations of network structures (tools from [ethereon](http://ethereon.github.io/netscope/quickstart.html)):
	- [ResNet-50] (http://ethereon.github.io/netscope/#/gist/db945b393d40bfa26006)
	- [ResNet-101] (http://ethereon.github.io/netscope/#/gist/b21e2aae116dc1ac7b50)
	- [ResNet-152] (http://ethereon.github.io/netscope/#/gist/d38f3e6091952b45198b)

0. Model files:
	- ~~MSR download: [link] (http://research.microsoft.com/en-us/um/people/kahe/resnet/models.zip)~~
	- OneDrive download: [link](https://onedrive.live.com/?authkey=%21AAFW2-FVoxeVRck&id=4006CBB8476FF777%2117887&cid=4006CBB8476FF777)

### Results
0. Curves on ImageNet (solid lines: 1-crop val error; dashed lines: training error):
	![Training curves](https://cloud.githubusercontent.com/assets/11435359/13046277/e904c04c-d412-11e5-9260-efc5b8301e2f.jpg)

0. 1-crop validation error on ImageNet (center 224x224 crop from resized image with shorter side=256):

	model|top-1|top-5
	:---:|:---:|:---:
	[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%
	ResNet-101|23.6%|7.1%
	ResNet-152|23.0%|6.7%
	
0. 10-crop validation error on ImageNet (averaging softmax scores of 10 224x224 crops from resized image with shorter side=256), the same as those in the paper:

	model|top-1|top-5
	:---:|:---:|:---:
	ResNet-50|22.9%|6.7%
	ResNet-101|21.8%|6.1%
	ResNet-152|21.4%|5.7%
	
### Third-party re-implementations

Deep residual networks are very easy to implement and train. We recommend to see also the following third-party re-implementations and extensions:

0. By Facebook AI Research (FAIR), with **training code in Torch and pre-trained ResNet-18/34/50/101 models for ImageNet**: [blog](http://torch.ch/blog/2016/02/04/resnets.html), [code](https://github.com/facebook/fb.resnet.torch)
0. Torch, CIFAR-10, with ResNet-20 to ResNet-110, training code, and curves: [code](https://github.com/gcr/torch-residual-networks)
0. Lasagne, CIFAR-10, with ResNet-32 and ResNet-56 and training code: [code](https://github.com/Lasagne/Recipes/tree/master/papers/deep_residual_learning)
0. Neon, CIFAR-10, with pre-trained ResNet-32 to ResNet-110 models, training code, and curves: [code](https://github.com/apark263/cfmz)
0. Torch, MNIST, 100 layers: [blog](https://deepmlblog.wordpress.com/2016/01/05/residual-networks-in-torch-mnist/), [code](https://github.com/arunpatala/residual.mnist)
0. A winning entry in Kaggle's right whale recognition challenge: [blog](http://blog.kaggle.com/2016/02/04/noaa-right-whale-recognition-winners-interview-2nd-place-felix-lau/), [code](https://github.com/felixlaumon/kaggle-right-whale)
0. Neon, Place2 (mini), 40 layers: [blog](http://www.nervanasys.com/using-neon-for-scene-recognition-mini-places2/), [code](https://github.com/hunterlang/mpmz/)
0. MatConvNet, CIFAR-10, with ResNet-20 to ResNet-110, training code, and curves: [code](https://github.com/suhangpro/matresnet)
0. TensorFlow, CIFAR-10, with ResNet-32,110,182 training code and curves:
[code](https://github.com/ppwwyyxx/tensorpack/tree/master/examples/ResNet)
0. MatConvNet, reproducing CIFAR-10 and ImageNet experiments (supporting official MatConvNet), training code and curves: [blog](https://zhanghang1989.github.io/ResNet/), [code](https://github.com/zhanghang1989/ResNet-Matconvnet)
0. Keras, ResNet-50: [code](https://github.com/raghakot/keras-resnet)

Converters:

0. MatConvNet: [url](http://www.vlfeat.org/matconvnet/pretrained/#imagenet-ilsvrc-classification)
0. TensorFlow: [url](https://github.com/ry/tensorflow-resnet)


================================================
FILE: prototxt/ResNet-101-deploy.prototxt
================================================
name: "ResNet-101"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224

layer {
	bottom: "data"
	top: "conv1"
	name: "conv1"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 7
		pad: 3
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "bn_conv1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "scale_conv1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "conv1"
	bottom: "conv1"
	name: "conv1_relu"
	type: "ReLU"
}

layer {
	bottom: "conv1"
	top: "pool1"
	name: "pool1"
	type: "Pooling"
	pooling_param {
		kernel_size: 3
		stride: 2
		pool: MAX
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch1"
	name: "res2a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "bn2a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "scale2a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch2a"
	name: "res2a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "bn2a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "scale2a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2a_branch2a"
	bottom: "res2a_branch2a"
	name: "res2a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2b"
	name: "res2a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "bn2a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "scale2a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2a_branch2b"
	bottom: "res2a_branch2b"
	name: "res2a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2c"
	name: "res2a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "bn2a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "scale2a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a_branch1"
	bottom: "res2a_branch2c"
	top: "res2a"
	name: "res2a"
	type: "Eltwise"
}

layer {
	bottom: "res2a"
	top: "res2a"
	name: "res2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a"
	top: "res2b_branch2a"
	name: "res2b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "bn2b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "scale2b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2b_branch2a"
	bottom: "res2b_branch2a"
	name: "res2b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2b"
	name: "res2b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "bn2b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "scale2b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2b_branch2b"
	bottom: "res2b_branch2b"
	name: "res2b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2c"
	name: "res2b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "bn2b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "scale2b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a"
	bottom: "res2b_branch2c"
	top: "res2b"
	name: "res2b"
	type: "Eltwise"
}

layer {
	bottom: "res2b"
	top: "res2b"
	name: "res2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b"
	top: "res2c_branch2a"
	name: "res2c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "bn2c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "scale2c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2c_branch2a"
	bottom: "res2c_branch2a"
	name: "res2c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2b"
	name: "res2c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "bn2c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "scale2c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2c_branch2b"
	bottom: "res2c_branch2b"
	name: "res2c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2c"
	name: "res2c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "bn2c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "scale2c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2b"
	bottom: "res2c_branch2c"
	top: "res2c"
	name: "res2c"
	type: "Eltwise"
}

layer {
	bottom: "res2c"
	top: "res2c"
	name: "res2c_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c"
	top: "res3a_branch1"
	name: "res3a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "bn3a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "scale3a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2c"
	top: "res3a_branch2a"
	name: "res3a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "bn3a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "scale3a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3a_branch2a"
	bottom: "res3a_branch2a"
	name: "res3a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2b"
	name: "res3a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "bn3a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "scale3a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3a_branch2b"
	bottom: "res3a_branch2b"
	name: "res3a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2c"
	name: "res3a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "bn3a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "scale3a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a_branch1"
	bottom: "res3a_branch2c"
	top: "res3a"
	name: "res3a"
	type: "Eltwise"
}

layer {
	bottom: "res3a"
	top: "res3a"
	name: "res3a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a"
	top: "res3b1_branch2a"
	name: "res3b1_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2a"
	name: "bn3b1_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2a"
	name: "scale3b1_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b1_branch2a"
	bottom: "res3b1_branch2a"
	name: "res3b1_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2b"
	name: "res3b1_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2b"
	name: "bn3b1_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2b"
	name: "scale3b1_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b1_branch2b"
	bottom: "res3b1_branch2b"
	name: "res3b1_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2c"
	name: "res3b1_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2c"
	top: "res3b1_branch2c"
	name: "bn3b1_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b1_branch2c"
	top: "res3b1_branch2c"
	name: "scale3b1_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a"
	bottom: "res3b1_branch2c"
	top: "res3b1"
	name: "res3b1"
	type: "Eltwise"
}

layer {
	bottom: "res3b1"
	top: "res3b1"
	name: "res3b1_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1"
	top: "res3b2_branch2a"
	name: "res3b2_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2a"
	name: "bn3b2_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2a"
	name: "scale3b2_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b2_branch2a"
	bottom: "res3b2_branch2a"
	name: "res3b2_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2b"
	name: "res3b2_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2b"
	name: "bn3b2_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2b"
	name: "scale3b2_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b2_branch2b"
	bottom: "res3b2_branch2b"
	name: "res3b2_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2c"
	name: "res3b2_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2c"
	top: "res3b2_branch2c"
	name: "bn3b2_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b2_branch2c"
	top: "res3b2_branch2c"
	name: "scale3b2_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b1"
	bottom: "res3b2_branch2c"
	top: "res3b2"
	name: "res3b2"
	type: "Eltwise"
}

layer {
	bottom: "res3b2"
	top: "res3b2"
	name: "res3b2_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2"
	top: "res3b3_branch2a"
	name: "res3b3_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2a"
	name: "bn3b3_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2a"
	name: "scale3b3_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b3_branch2a"
	bottom: "res3b3_branch2a"
	name: "res3b3_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2b"
	name: "res3b3_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2b"
	name: "bn3b3_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2b"
	name: "scale3b3_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b3_branch2b"
	bottom: "res3b3_branch2b"
	name: "res3b3_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2c"
	name: "res3b3_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2c"
	top: "res3b3_branch2c"
	name: "bn3b3_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b3_branch2c"
	top: "res3b3_branch2c"
	name: "scale3b3_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b2"
	bottom: "res3b3_branch2c"
	top: "res3b3"
	name: "res3b3"
	type: "Eltwise"
}

layer {
	bottom: "res3b3"
	top: "res3b3"
	name: "res3b3_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3"
	top: "res4a_branch1"
	name: "res4a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "bn4a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "scale4a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b3"
	top: "res4a_branch2a"
	name: "res4a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "bn4a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "scale4a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4a_branch2a"
	bottom: "res4a_branch2a"
	name: "res4a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2b"
	name: "res4a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "bn4a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "scale4a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4a_branch2b"
	bottom: "res4a_branch2b"
	name: "res4a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2c"
	name: "res4a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "bn4a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "scale4a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a_branch1"
	bottom: "res4a_branch2c"
	top: "res4a"
	name: "res4a"
	type: "Eltwise"
}

layer {
	bottom: "res4a"
	top: "res4a"
	name: "res4a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a"
	top: "res4b1_branch2a"
	name: "res4b1_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2a"
	name: "bn4b1_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2a"
	name: "scale4b1_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b1_branch2a"
	bottom: "res4b1_branch2a"
	name: "res4b1_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2b"
	name: "res4b1_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2b"
	name: "bn4b1_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2b"
	name: "scale4b1_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b1_branch2b"
	bottom: "res4b1_branch2b"
	name: "res4b1_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2c"
	name: "res4b1_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2c"
	top: "res4b1_branch2c"
	name: "bn4b1_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b1_branch2c"
	top: "res4b1_branch2c"
	name: "scale4b1_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a"
	bottom: "res4b1_branch2c"
	top: "res4b1"
	name: "res4b1"
	type: "Eltwise"
}

layer {
	bottom: "res4b1"
	top: "res4b1"
	name: "res4b1_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1"
	top: "res4b2_branch2a"
	name: "res4b2_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2a"
	name: "bn4b2_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2a"
	name: "scale4b2_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b2_branch2a"
	bottom: "res4b2_branch2a"
	name: "res4b2_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2b"
	name: "res4b2_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2b"
	name: "bn4b2_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2b"
	name: "scale4b2_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b2_branch2b"
	bottom: "res4b2_branch2b"
	name: "res4b2_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2c"
	name: "res4b2_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2c"
	top: "res4b2_branch2c"
	name: "bn4b2_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b2_branch2c"
	top: "res4b2_branch2c"
	name: "scale4b2_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b1"
	bottom: "res4b2_branch2c"
	top: "res4b2"
	name: "res4b2"
	type: "Eltwise"
}

layer {
	bottom: "res4b2"
	top: "res4b2"
	name: "res4b2_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2"
	top: "res4b3_branch2a"
	name: "res4b3_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2a"
	name: "bn4b3_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2a"
	name: "scale4b3_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b3_branch2a"
	bottom: "res4b3_branch2a"
	name: "res4b3_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2b"
	name: "res4b3_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2b"
	name: "bn4b3_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2b"
	name: "scale4b3_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b3_branch2b"
	bottom: "res4b3_branch2b"
	name: "res4b3_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2c"
	name: "res4b3_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2c"
	top: "res4b3_branch2c"
	name: "bn4b3_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b3_branch2c"
	top: "res4b3_branch2c"
	name: "scale4b3_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b2"
	bottom: "res4b3_branch2c"
	top: "res4b3"
	name: "res4b3"
	type: "Eltwise"
}

layer {
	bottom: "res4b3"
	top: "res4b3"
	name: "res4b3_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3"
	top: "res4b4_branch2a"
	name: "res4b4_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2a"
	name: "bn4b4_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2a"
	name: "scale4b4_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b4_branch2a"
	bottom: "res4b4_branch2a"
	name: "res4b4_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2b"
	name: "res4b4_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2b"
	name: "bn4b4_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2b"
	name: "scale4b4_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b4_branch2b"
	bottom: "res4b4_branch2b"
	name: "res4b4_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2c"
	name: "res4b4_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2c"
	top: "res4b4_branch2c"
	name: "bn4b4_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b4_branch2c"
	top: "res4b4_branch2c"
	name: "scale4b4_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b3"
	bottom: "res4b4_branch2c"
	top: "res4b4"
	name: "res4b4"
	type: "Eltwise"
}

layer {
	bottom: "res4b4"
	top: "res4b4"
	name: "res4b4_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4"
	top: "res4b5_branch2a"
	name: "res4b5_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2a"
	name: "bn4b5_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2a"
	name: "scale4b5_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b5_branch2a"
	bottom: "res4b5_branch2a"
	name: "res4b5_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2b"
	name: "res4b5_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2b"
	name: "bn4b5_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2b"
	name: "scale4b5_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b5_branch2b"
	bottom: "res4b5_branch2b"
	name: "res4b5_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2c"
	name: "res4b5_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2c"
	top: "res4b5_branch2c"
	name: "bn4b5_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b5_branch2c"
	top: "res4b5_branch2c"
	name: "scale4b5_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b4"
	bottom: "res4b5_branch2c"
	top: "res4b5"
	name: "res4b5"
	type: "Eltwise"
}

layer {
	bottom: "res4b5"
	top: "res4b5"
	name: "res4b5_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5"
	top: "res4b6_branch2a"
	name: "res4b6_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2a"
	name: "bn4b6_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2a"
	name: "scale4b6_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b6_branch2a"
	bottom: "res4b6_branch2a"
	name: "res4b6_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2b"
	name: "res4b6_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2b"
	name: "bn4b6_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2b"
	name: "scale4b6_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b6_branch2b"
	bottom: "res4b6_branch2b"
	name: "res4b6_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2c"
	name: "res4b6_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2c"
	top: "res4b6_branch2c"
	name: "bn4b6_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b6_branch2c"
	top: "res4b6_branch2c"
	name: "scale4b6_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b5"
	bottom: "res4b6_branch2c"
	top: "res4b6"
	name: "res4b6"
	type: "Eltwise"
}

layer {
	bottom: "res4b6"
	top: "res4b6"
	name: "res4b6_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6"
	top: "res4b7_branch2a"
	name: "res4b7_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2a"
	name: "bn4b7_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2a"
	name: "scale4b7_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b7_branch2a"
	bottom: "res4b7_branch2a"
	name: "res4b7_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2b"
	name: "res4b7_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2b"
	name: "bn4b7_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2b"
	name: "scale4b7_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b7_branch2b"
	bottom: "res4b7_branch2b"
	name: "res4b7_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2c"
	name: "res4b7_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2c"
	top: "res4b7_branch2c"
	name: "bn4b7_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b7_branch2c"
	top: "res4b7_branch2c"
	name: "scale4b7_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b6"
	bottom: "res4b7_branch2c"
	top: "res4b7"
	name: "res4b7"
	type: "Eltwise"
}

layer {
	bottom: "res4b7"
	top: "res4b7"
	name: "res4b7_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7"
	top: "res4b8_branch2a"
	name: "res4b8_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2a"
	name: "bn4b8_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2a"
	name: "scale4b8_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b8_branch2a"
	bottom: "res4b8_branch2a"
	name: "res4b8_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2b"
	name: "res4b8_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2b"
	name: "bn4b8_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2b"
	name: "scale4b8_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b8_branch2b"
	bottom: "res4b8_branch2b"
	name: "res4b8_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2c"
	name: "res4b8_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2c"
	top: "res4b8_branch2c"
	name: "bn4b8_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b8_branch2c"
	top: "res4b8_branch2c"
	name: "scale4b8_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b7"
	bottom: "res4b8_branch2c"
	top: "res4b8"
	name: "res4b8"
	type: "Eltwise"
}

layer {
	bottom: "res4b8"
	top: "res4b8"
	name: "res4b8_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8"
	top: "res4b9_branch2a"
	name: "res4b9_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2a"
	name: "bn4b9_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2a"
	name: "scale4b9_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b9_branch2a"
	bottom: "res4b9_branch2a"
	name: "res4b9_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2b"
	name: "res4b9_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2b"
	name: "bn4b9_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2b"
	name: "scale4b9_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b9_branch2b"
	bottom: "res4b9_branch2b"
	name: "res4b9_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2c"
	name: "res4b9_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2c"
	top: "res4b9_branch2c"
	name: "bn4b9_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b9_branch2c"
	top: "res4b9_branch2c"
	name: "scale4b9_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b8"
	bottom: "res4b9_branch2c"
	top: "res4b9"
	name: "res4b9"
	type: "Eltwise"
}

layer {
	bottom: "res4b9"
	top: "res4b9"
	name: "res4b9_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9"
	top: "res4b10_branch2a"
	name: "res4b10_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2a"
	name: "bn4b10_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2a"
	name: "scale4b10_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b10_branch2a"
	bottom: "res4b10_branch2a"
	name: "res4b10_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2b"
	name: "res4b10_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2b"
	name: "bn4b10_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2b"
	name: "scale4b10_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b10_branch2b"
	bottom: "res4b10_branch2b"
	name: "res4b10_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2c"
	name: "res4b10_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2c"
	top: "res4b10_branch2c"
	name: "bn4b10_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b10_branch2c"
	top: "res4b10_branch2c"
	name: "scale4b10_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b9"
	bottom: "res4b10_branch2c"
	top: "res4b10"
	name: "res4b10"
	type: "Eltwise"
}

layer {
	bottom: "res4b10"
	top: "res4b10"
	name: "res4b10_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10"
	top: "res4b11_branch2a"
	name: "res4b11_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2a"
	name: "bn4b11_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2a"
	name: "scale4b11_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b11_branch2a"
	bottom: "res4b11_branch2a"
	name: "res4b11_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2b"
	name: "res4b11_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2b"
	name: "bn4b11_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2b"
	name: "scale4b11_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b11_branch2b"
	bottom: "res4b11_branch2b"
	name: "res4b11_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2c"
	name: "res4b11_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2c"
	top: "res4b11_branch2c"
	name: "bn4b11_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b11_branch2c"
	top: "res4b11_branch2c"
	name: "scale4b11_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b10"
	bottom: "res4b11_branch2c"
	top: "res4b11"
	name: "res4b11"
	type: "Eltwise"
}

layer {
	bottom: "res4b11"
	top: "res4b11"
	name: "res4b11_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11"
	top: "res4b12_branch2a"
	name: "res4b12_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2a"
	name: "bn4b12_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2a"
	name: "scale4b12_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b12_branch2a"
	bottom: "res4b12_branch2a"
	name: "res4b12_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2b"
	name: "res4b12_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2b"
	name: "bn4b12_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2b"
	name: "scale4b12_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b12_branch2b"
	bottom: "res4b12_branch2b"
	name: "res4b12_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2c"
	name: "res4b12_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2c"
	top: "res4b12_branch2c"
	name: "bn4b12_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b12_branch2c"
	top: "res4b12_branch2c"
	name: "scale4b12_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b11"
	bottom: "res4b12_branch2c"
	top: "res4b12"
	name: "res4b12"
	type: "Eltwise"
}

layer {
	bottom: "res4b12"
	top: "res4b12"
	name: "res4b12_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12"
	top: "res4b13_branch2a"
	name: "res4b13_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2a"
	name: "bn4b13_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2a"
	name: "scale4b13_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b13_branch2a"
	bottom: "res4b13_branch2a"
	name: "res4b13_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2b"
	name: "res4b13_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2b"
	name: "bn4b13_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2b"
	name: "scale4b13_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b13_branch2b"
	bottom: "res4b13_branch2b"
	name: "res4b13_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2c"
	name: "res4b13_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2c"
	top: "res4b13_branch2c"
	name: "bn4b13_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b13_branch2c"
	top: "res4b13_branch2c"
	name: "scale4b13_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b12"
	bottom: "res4b13_branch2c"
	top: "res4b13"
	name: "res4b13"
	type: "Eltwise"
}

layer {
	bottom: "res4b13"
	top: "res4b13"
	name: "res4b13_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13"
	top: "res4b14_branch2a"
	name: "res4b14_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2a"
	name: "bn4b14_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2a"
	name: "scale4b14_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b14_branch2a"
	bottom: "res4b14_branch2a"
	name: "res4b14_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2b"
	name: "res4b14_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2b"
	name: "bn4b14_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2b"
	name: "scale4b14_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b14_branch2b"
	bottom: "res4b14_branch2b"
	name: "res4b14_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2c"
	name: "res4b14_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2c"
	top: "res4b14_branch2c"
	name: "bn4b14_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b14_branch2c"
	top: "res4b14_branch2c"
	name: "scale4b14_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b13"
	bottom: "res4b14_branch2c"
	top: "res4b14"
	name: "res4b14"
	type: "Eltwise"
}

layer {
	bottom: "res4b14"
	top: "res4b14"
	name: "res4b14_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14"
	top: "res4b15_branch2a"
	name: "res4b15_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2a"
	name: "bn4b15_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2a"
	name: "scale4b15_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b15_branch2a"
	bottom: "res4b15_branch2a"
	name: "res4b15_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2b"
	name: "res4b15_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2b"
	name: "bn4b15_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2b"
	name: "scale4b15_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b15_branch2b"
	bottom: "res4b15_branch2b"
	name: "res4b15_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2c"
	name: "res4b15_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2c"
	top: "res4b15_branch2c"
	name: "bn4b15_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b15_branch2c"
	top: "res4b15_branch2c"
	name: "scale4b15_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b14"
	bottom: "res4b15_branch2c"
	top: "res4b15"
	name: "res4b15"
	type: "Eltwise"
}

layer {
	bottom: "res4b15"
	top: "res4b15"
	name: "res4b15_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15"
	top: "res4b16_branch2a"
	name: "res4b16_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2a"
	name: "bn4b16_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2a"
	name: "scale4b16_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b16_branch2a"
	bottom: "res4b16_branch2a"
	name: "res4b16_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2b"
	name: "res4b16_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2b"
	name: "bn4b16_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2b"
	name: "scale4b16_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b16_branch2b"
	bottom: "res4b16_branch2b"
	name: "res4b16_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2c"
	name: "res4b16_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2c"
	top: "res4b16_branch2c"
	name: "bn4b16_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b16_branch2c"
	top: "res4b16_branch2c"
	name: "scale4b16_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b15"
	bottom: "res4b16_branch2c"
	top: "res4b16"
	name: "res4b16"
	type: "Eltwise"
}

layer {
	bottom: "res4b16"
	top: "res4b16"
	name: "res4b16_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16"
	top: "res4b17_branch2a"
	name: "res4b17_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2a"
	name: "bn4b17_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2a"
	name: "scale4b17_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b17_branch2a"
	bottom: "res4b17_branch2a"
	name: "res4b17_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2b"
	name: "res4b17_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2b"
	name: "bn4b17_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2b"
	name: "scale4b17_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b17_branch2b"
	bottom: "res4b17_branch2b"
	name: "res4b17_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2c"
	name: "res4b17_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2c"
	top: "res4b17_branch2c"
	name: "bn4b17_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b17_branch2c"
	top: "res4b17_branch2c"
	name: "scale4b17_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b16"
	bottom: "res4b17_branch2c"
	top: "res4b17"
	name: "res4b17"
	type: "Eltwise"
}

layer {
	bottom: "res4b17"
	top: "res4b17"
	name: "res4b17_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17"
	top: "res4b18_branch2a"
	name: "res4b18_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2a"
	name: "bn4b18_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2a"
	name: "scale4b18_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b18_branch2a"
	bottom: "res4b18_branch2a"
	name: "res4b18_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2b"
	name: "res4b18_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2b"
	name: "bn4b18_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2b"
	name: "scale4b18_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b18_branch2b"
	bottom: "res4b18_branch2b"
	name: "res4b18_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2c"
	name: "res4b18_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2c"
	top: "res4b18_branch2c"
	name: "bn4b18_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b18_branch2c"
	top: "res4b18_branch2c"
	name: "scale4b18_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b17"
	bottom: "res4b18_branch2c"
	top: "res4b18"
	name: "res4b18"
	type: "Eltwise"
}

layer {
	bottom: "res4b18"
	top: "res4b18"
	name: "res4b18_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18"
	top: "res4b19_branch2a"
	name: "res4b19_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2a"
	name: "bn4b19_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2a"
	name: "scale4b19_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b19_branch2a"
	bottom: "res4b19_branch2a"
	name: "res4b19_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2b"
	name: "res4b19_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2b"
	name: "bn4b19_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2b"
	name: "scale4b19_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b19_branch2b"
	bottom: "res4b19_branch2b"
	name: "res4b19_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2c"
	name: "res4b19_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2c"
	top: "res4b19_branch2c"
	name: "bn4b19_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b19_branch2c"
	top: "res4b19_branch2c"
	name: "scale4b19_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b18"
	bottom: "res4b19_branch2c"
	top: "res4b19"
	name: "res4b19"
	type: "Eltwise"
}

layer {
	bottom: "res4b19"
	top: "res4b19"
	name: "res4b19_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19"
	top: "res4b20_branch2a"
	name: "res4b20_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2a"
	name: "bn4b20_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2a"
	name: "scale4b20_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b20_branch2a"
	bottom: "res4b20_branch2a"
	name: "res4b20_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2b"
	name: "res4b20_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2b"
	name: "bn4b20_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2b"
	name: "scale4b20_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b20_branch2b"
	bottom: "res4b20_branch2b"
	name: "res4b20_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2c"
	name: "res4b20_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2c"
	top: "res4b20_branch2c"
	name: "bn4b20_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b20_branch2c"
	top: "res4b20_branch2c"
	name: "scale4b20_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b19"
	bottom: "res4b20_branch2c"
	top: "res4b20"
	name: "res4b20"
	type: "Eltwise"
}

layer {
	bottom: "res4b20"
	top: "res4b20"
	name: "res4b20_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20"
	top: "res4b21_branch2a"
	name: "res4b21_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2a"
	name: "bn4b21_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2a"
	name: "scale4b21_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b21_branch2a"
	bottom: "res4b21_branch2a"
	name: "res4b21_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2b"
	name: "res4b21_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2b"
	name: "bn4b21_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2b"
	name: "scale4b21_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b21_branch2b"
	bottom: "res4b21_branch2b"
	name: "res4b21_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2c"
	name: "res4b21_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2c"
	top: "res4b21_branch2c"
	name: "bn4b21_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b21_branch2c"
	top: "res4b21_branch2c"
	name: "scale4b21_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b20"
	bottom: "res4b21_branch2c"
	top: "res4b21"
	name: "res4b21"
	type: "Eltwise"
}

layer {
	bottom: "res4b21"
	top: "res4b21"
	name: "res4b21_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21"
	top: "res4b22_branch2a"
	name: "res4b22_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2a"
	name: "bn4b22_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2a"
	name: "scale4b22_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b22_branch2a"
	bottom: "res4b22_branch2a"
	name: "res4b22_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2b"
	name: "res4b22_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2b"
	name: "bn4b22_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2b"
	name: "scale4b22_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b22_branch2b"
	bottom: "res4b22_branch2b"
	name: "res4b22_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2c"
	name: "res4b22_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2c"
	top: "res4b22_branch2c"
	name: "bn4b22_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b22_branch2c"
	top: "res4b22_branch2c"
	name: "scale4b22_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b21"
	bottom: "res4b22_branch2c"
	top: "res4b22"
	name: "res4b22"
	type: "Eltwise"
}

layer {
	bottom: "res4b22"
	top: "res4b22"
	name: "res4b22_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22"
	top: "res5a_branch1"
	name: "res5a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "bn5a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "scale5a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b22"
	top: "res5a_branch2a"
	name: "res5a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "bn5a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "scale5a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5a_branch2a"
	bottom: "res5a_branch2a"
	name: "res5a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2b"
	name: "res5a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "bn5a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "scale5a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5a_branch2b"
	bottom: "res5a_branch2b"
	name: "res5a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2c"
	name: "res5a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "bn5a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "scale5a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a_branch1"
	bottom: "res5a_branch2c"
	top: "res5a"
	name: "res5a"
	type: "Eltwise"
}

layer {
	bottom: "res5a"
	top: "res5a"
	name: "res5a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a"
	top: "res5b_branch2a"
	name: "res5b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "bn5b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "scale5b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5b_branch2a"
	bottom: "res5b_branch2a"
	name: "res5b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2b"
	name: "res5b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "bn5b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "scale5b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5b_branch2b"
	bottom: "res5b_branch2b"
	name: "res5b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2c"
	name: "res5b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "bn5b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "scale5b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a"
	bottom: "res5b_branch2c"
	top: "res5b"
	name: "res5b"
	type: "Eltwise"
}

layer {
	bottom: "res5b"
	top: "res5b"
	name: "res5b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b"
	top: "res5c_branch2a"
	name: "res5c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "bn5c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "scale5c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5c_branch2a"
	bottom: "res5c_branch2a"
	name: "res5c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2b"
	name: "res5c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "bn5c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "scale5c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5c_branch2b"
	bottom: "res5c_branch2b"
	name: "res5c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2c"
	name: "res5c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "bn5c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "scale5c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5b"
	bottom: "res5c_branch2c"
	top: "res5c"
	name: "res5c"
	type: "Eltwise"
}

layer {
	bottom: "res5c"
	top: "res5c"
	name: "res5c_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c"
	top: "pool5"
	name: "pool5"
	type: "Pooling"
	pooling_param {
		kernel_size: 7
		stride: 1
		pool: AVE
	}
}

layer {
	bottom: "pool5"
	top: "fc1000"
	name: "fc1000"
	type: "InnerProduct"
	inner_product_param {
		num_output: 1000
	}
}

layer {
	bottom: "fc1000"
	top: "prob"
	name: "prob"
	type: "Softmax"
}



================================================
FILE: prototxt/ResNet-152-deploy.prototxt
================================================
name: "ResNet-152"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224

layer {
	bottom: "data"
	top: "conv1"
	name: "conv1"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 7
		pad: 3
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "bn_conv1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "scale_conv1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "conv1"
	bottom: "conv1"
	name: "conv1_relu"
	type: "ReLU"
}

layer {
	bottom: "conv1"
	top: "pool1"
	name: "pool1"
	type: "Pooling"
	pooling_param {
		kernel_size: 3
		stride: 2
		pool: MAX
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch1"
	name: "res2a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "bn2a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "scale2a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch2a"
	name: "res2a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "bn2a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "scale2a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2a_branch2a"
	bottom: "res2a_branch2a"
	name: "res2a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2b"
	name: "res2a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "bn2a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "scale2a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2a_branch2b"
	bottom: "res2a_branch2b"
	name: "res2a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2c"
	name: "res2a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "bn2a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "scale2a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a_branch1"
	bottom: "res2a_branch2c"
	top: "res2a"
	name: "res2a"
	type: "Eltwise"
}

layer {
	bottom: "res2a"
	top: "res2a"
	name: "res2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a"
	top: "res2b_branch2a"
	name: "res2b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "bn2b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "scale2b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2b_branch2a"
	bottom: "res2b_branch2a"
	name: "res2b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2b"
	name: "res2b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "bn2b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "scale2b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2b_branch2b"
	bottom: "res2b_branch2b"
	name: "res2b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2c"
	name: "res2b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "bn2b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "scale2b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a"
	bottom: "res2b_branch2c"
	top: "res2b"
	name: "res2b"
	type: "Eltwise"
}

layer {
	bottom: "res2b"
	top: "res2b"
	name: "res2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b"
	top: "res2c_branch2a"
	name: "res2c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "bn2c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "scale2c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2c_branch2a"
	bottom: "res2c_branch2a"
	name: "res2c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2b"
	name: "res2c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "bn2c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "scale2c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2c_branch2b"
	bottom: "res2c_branch2b"
	name: "res2c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2c"
	name: "res2c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "bn2c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "scale2c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2b"
	bottom: "res2c_branch2c"
	top: "res2c"
	name: "res2c"
	type: "Eltwise"
}

layer {
	bottom: "res2c"
	top: "res2c"
	name: "res2c_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c"
	top: "res3a_branch1"
	name: "res3a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "bn3a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "scale3a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2c"
	top: "res3a_branch2a"
	name: "res3a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "bn3a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "scale3a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3a_branch2a"
	bottom: "res3a_branch2a"
	name: "res3a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2b"
	name: "res3a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "bn3a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "scale3a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3a_branch2b"
	bottom: "res3a_branch2b"
	name: "res3a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2c"
	name: "res3a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "bn3a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "scale3a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a_branch1"
	bottom: "res3a_branch2c"
	top: "res3a"
	name: "res3a"
	type: "Eltwise"
}

layer {
	bottom: "res3a"
	top: "res3a"
	name: "res3a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a"
	top: "res3b1_branch2a"
	name: "res3b1_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2a"
	name: "bn3b1_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2a"
	name: "scale3b1_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b1_branch2a"
	bottom: "res3b1_branch2a"
	name: "res3b1_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2b"
	name: "res3b1_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2b"
	name: "bn3b1_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2b"
	name: "scale3b1_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b1_branch2b"
	bottom: "res3b1_branch2b"
	name: "res3b1_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2c"
	name: "res3b1_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2c"
	top: "res3b1_branch2c"
	name: "bn3b1_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b1_branch2c"
	top: "res3b1_branch2c"
	name: "scale3b1_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a"
	bottom: "res3b1_branch2c"
	top: "res3b1"
	name: "res3b1"
	type: "Eltwise"
}

layer {
	bottom: "res3b1"
	top: "res3b1"
	name: "res3b1_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1"
	top: "res3b2_branch2a"
	name: "res3b2_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2a"
	name: "bn3b2_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2a"
	name: "scale3b2_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b2_branch2a"
	bottom: "res3b2_branch2a"
	name: "res3b2_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2b"
	name: "res3b2_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2b"
	name: "bn3b2_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2b"
	name: "scale3b2_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b2_branch2b"
	bottom: "res3b2_branch2b"
	name: "res3b2_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2c"
	name: "res3b2_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2c"
	top: "res3b2_branch2c"
	name: "bn3b2_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b2_branch2c"
	top: "res3b2_branch2c"
	name: "scale3b2_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b1"
	bottom: "res3b2_branch2c"
	top: "res3b2"
	name: "res3b2"
	type: "Eltwise"
}

layer {
	bottom: "res3b2"
	top: "res3b2"
	name: "res3b2_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2"
	top: "res3b3_branch2a"
	name: "res3b3_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2a"
	name: "bn3b3_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2a"
	name: "scale3b3_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b3_branch2a"
	bottom: "res3b3_branch2a"
	name: "res3b3_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2b"
	name: "res3b3_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2b"
	name: "bn3b3_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2b"
	name: "scale3b3_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b3_branch2b"
	bottom: "res3b3_branch2b"
	name: "res3b3_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2c"
	name: "res3b3_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2c"
	top: "res3b3_branch2c"
	name: "bn3b3_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b3_branch2c"
	top: "res3b3_branch2c"
	name: "scale3b3_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b2"
	bottom: "res3b3_branch2c"
	top: "res3b3"
	name: "res3b3"
	type: "Eltwise"
}

layer {
	bottom: "res3b3"
	top: "res3b3"
	name: "res3b3_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3"
	top: "res3b4_branch2a"
	name: "res3b4_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b4_branch2a"
	top: "res3b4_branch2a"
	name: "bn3b4_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b4_branch2a"
	top: "res3b4_branch2a"
	name: "scale3b4_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b4_branch2a"
	bottom: "res3b4_branch2a"
	name: "res3b4_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b4_branch2a"
	top: "res3b4_branch2b"
	name: "res3b4_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b4_branch2b"
	top: "res3b4_branch2b"
	name: "bn3b4_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b4_branch2b"
	top: "res3b4_branch2b"
	name: "scale3b4_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b4_branch2b"
	bottom: "res3b4_branch2b"
	name: "res3b4_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b4_branch2b"
	top: "res3b4_branch2c"
	name: "res3b4_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b4_branch2c"
	top: "res3b4_branch2c"
	name: "bn3b4_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b4_branch2c"
	top: "res3b4_branch2c"
	name: "scale3b4_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b3"
	bottom: "res3b4_branch2c"
	top: "res3b4"
	name: "res3b4"
	type: "Eltwise"
}

layer {
	bottom: "res3b4"
	top: "res3b4"
	name: "res3b4_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b4"
	top: "res3b5_branch2a"
	name: "res3b5_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b5_branch2a"
	top: "res3b5_branch2a"
	name: "bn3b5_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b5_branch2a"
	top: "res3b5_branch2a"
	name: "scale3b5_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b5_branch2a"
	bottom: "res3b5_branch2a"
	name: "res3b5_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b5_branch2a"
	top: "res3b5_branch2b"
	name: "res3b5_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b5_branch2b"
	top: "res3b5_branch2b"
	name: "bn3b5_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b5_branch2b"
	top: "res3b5_branch2b"
	name: "scale3b5_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b5_branch2b"
	bottom: "res3b5_branch2b"
	name: "res3b5_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b5_branch2b"
	top: "res3b5_branch2c"
	name: "res3b5_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b5_branch2c"
	top: "res3b5_branch2c"
	name: "bn3b5_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b5_branch2c"
	top: "res3b5_branch2c"
	name: "scale3b5_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b4"
	bottom: "res3b5_branch2c"
	top: "res3b5"
	name: "res3b5"
	type: "Eltwise"
}

layer {
	bottom: "res3b5"
	top: "res3b5"
	name: "res3b5_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b5"
	top: "res3b6_branch2a"
	name: "res3b6_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b6_branch2a"
	top: "res3b6_branch2a"
	name: "bn3b6_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b6_branch2a"
	top: "res3b6_branch2a"
	name: "scale3b6_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b6_branch2a"
	bottom: "res3b6_branch2a"
	name: "res3b6_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b6_branch2a"
	top: "res3b6_branch2b"
	name: "res3b6_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b6_branch2b"
	top: "res3b6_branch2b"
	name: "bn3b6_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b6_branch2b"
	top: "res3b6_branch2b"
	name: "scale3b6_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b6_branch2b"
	bottom: "res3b6_branch2b"
	name: "res3b6_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b6_branch2b"
	top: "res3b6_branch2c"
	name: "res3b6_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b6_branch2c"
	top: "res3b6_branch2c"
	name: "bn3b6_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b6_branch2c"
	top: "res3b6_branch2c"
	name: "scale3b6_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b5"
	bottom: "res3b6_branch2c"
	top: "res3b6"
	name: "res3b6"
	type: "Eltwise"
}

layer {
	bottom: "res3b6"
	top: "res3b6"
	name: "res3b6_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b6"
	top: "res3b7_branch2a"
	name: "res3b7_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b7_branch2a"
	top: "res3b7_branch2a"
	name: "bn3b7_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b7_branch2a"
	top: "res3b7_branch2a"
	name: "scale3b7_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b7_branch2a"
	bottom: "res3b7_branch2a"
	name: "res3b7_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b7_branch2a"
	top: "res3b7_branch2b"
	name: "res3b7_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b7_branch2b"
	top: "res3b7_branch2b"
	name: "bn3b7_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b7_branch2b"
	top: "res3b7_branch2b"
	name: "scale3b7_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b7_branch2b"
	bottom: "res3b7_branch2b"
	name: "res3b7_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b7_branch2b"
	top: "res3b7_branch2c"
	name: "res3b7_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b7_branch2c"
	top: "res3b7_branch2c"
	name: "bn3b7_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b7_branch2c"
	top: "res3b7_branch2c"
	name: "scale3b7_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b6"
	bottom: "res3b7_branch2c"
	top: "res3b7"
	name: "res3b7"
	type: "Eltwise"
}

layer {
	bottom: "res3b7"
	top: "res3b7"
	name: "res3b7_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b7"
	top: "res4a_branch1"
	name: "res4a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "bn4a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "scale4a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b7"
	top: "res4a_branch2a"
	name: "res4a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "bn4a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "scale4a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4a_branch2a"
	bottom: "res4a_branch2a"
	name: "res4a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2b"
	name: "res4a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "bn4a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "scale4a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4a_branch2b"
	bottom: "res4a_branch2b"
	name: "res4a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2c"
	name: "res4a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "bn4a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "scale4a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a_branch1"
	bottom: "res4a_branch2c"
	top: "res4a"
	name: "res4a"
	type: "Eltwise"
}

layer {
	bottom: "res4a"
	top: "res4a"
	name: "res4a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a"
	top: "res4b1_branch2a"
	name: "res4b1_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2a"
	name: "bn4b1_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2a"
	name: "scale4b1_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b1_branch2a"
	bottom: "res4b1_branch2a"
	name: "res4b1_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2b"
	name: "res4b1_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2b"
	name: "bn4b1_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2b"
	name: "scale4b1_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b1_branch2b"
	bottom: "res4b1_branch2b"
	name: "res4b1_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2c"
	name: "res4b1_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2c"
	top: "res4b1_branch2c"
	name: "bn4b1_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b1_branch2c"
	top: "res4b1_branch2c"
	name: "scale4b1_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a"
	bottom: "res4b1_branch2c"
	top: "res4b1"
	name: "res4b1"
	type: "Eltwise"
}

layer {
	bottom: "res4b1"
	top: "res4b1"
	name: "res4b1_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1"
	top: "res4b2_branch2a"
	name: "res4b2_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2a"
	name: "bn4b2_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2a"
	name: "scale4b2_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b2_branch2a"
	bottom: "res4b2_branch2a"
	name: "res4b2_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2b"
	name: "res4b2_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2b"
	name: "bn4b2_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2b"
	name: "scale4b2_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b2_branch2b"
	bottom: "res4b2_branch2b"
	name: "res4b2_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2c"
	name: "res4b2_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2c"
	top: "res4b2_branch2c"
	name: "bn4b2_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b2_branch2c"
	top: "res4b2_branch2c"
	name: "scale4b2_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b1"
	bottom: "res4b2_branch2c"
	top: "res4b2"
	name: "res4b2"
	type: "Eltwise"
}

layer {
	bottom: "res4b2"
	top: "res4b2"
	name: "res4b2_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2"
	top: "res4b3_branch2a"
	name: "res4b3_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2a"
	name: "bn4b3_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2a"
	name: "scale4b3_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b3_branch2a"
	bottom: "res4b3_branch2a"
	name: "res4b3_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2b"
	name: "res4b3_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2b"
	name: "bn4b3_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2b"
	name: "scale4b3_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b3_branch2b"
	bottom: "res4b3_branch2b"
	name: "res4b3_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2c"
	name: "res4b3_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2c"
	top: "res4b3_branch2c"
	name: "bn4b3_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b3_branch2c"
	top: "res4b3_branch2c"
	name: "scale4b3_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b2"
	bottom: "res4b3_branch2c"
	top: "res4b3"
	name: "res4b3"
	type: "Eltwise"
}

layer {
	bottom: "res4b3"
	top: "res4b3"
	name: "res4b3_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3"
	top: "res4b4_branch2a"
	name: "res4b4_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2a"
	name: "bn4b4_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2a"
	name: "scale4b4_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b4_branch2a"
	bottom: "res4b4_branch2a"
	name: "res4b4_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2b"
	name: "res4b4_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2b"
	name: "bn4b4_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2b"
	name: "scale4b4_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b4_branch2b"
	bottom: "res4b4_branch2b"
	name: "res4b4_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2c"
	name: "res4b4_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2c"
	top: "res4b4_branch2c"
	name: "bn4b4_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b4_branch2c"
	top: "res4b4_branch2c"
	name: "scale4b4_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b3"
	bottom: "res4b4_branch2c"
	top: "res4b4"
	name: "res4b4"
	type: "Eltwise"
}

layer {
	bottom: "res4b4"
	top: "res4b4"
	name: "res4b4_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4"
	top: "res4b5_branch2a"
	name: "res4b5_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2a"
	name: "bn4b5_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2a"
	name: "scale4b5_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b5_branch2a"
	bottom: "res4b5_branch2a"
	name: "res4b5_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2b"
	name: "res4b5_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2b"
	name: "bn4b5_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2b"
	name: "scale4b5_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b5_branch2b"
	bottom: "res4b5_branch2b"
	name: "res4b5_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2c"
	name: "res4b5_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2c"
	top: "res4b5_branch2c"
	name: "bn4b5_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b5_branch2c"
	top: "res4b5_branch2c"
	name: "scale4b5_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b4"
	bottom: "res4b5_branch2c"
	top: "res4b5"
	name: "res4b5"
	type: "Eltwise"
}

layer {
	bottom: "res4b5"
	top: "res4b5"
	name: "res4b5_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5"
	top: "res4b6_branch2a"
	name: "res4b6_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2a"
	name: "bn4b6_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2a"
	name: "scale4b6_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b6_branch2a"
	bottom: "res4b6_branch2a"
	name: "res4b6_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2b"
	name: "res4b6_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2b"
	name: "bn4b6_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2b"
	name: "scale4b6_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b6_branch2b"
	bottom: "res4b6_branch2b"
	name: "res4b6_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2c"
	name: "res4b6_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2c"
	top: "res4b6_branch2c"
	name: "bn4b6_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b6_branch2c"
	top: "res4b6_branch2c"
	name: "scale4b6_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b5"
	bottom: "res4b6_branch2c"
	top: "res4b6"
	name: "res4b6"
	type: "Eltwise"
}

layer {
	bottom: "res4b6"
	top: "res4b6"
	name: "res4b6_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6"
	top: "res4b7_branch2a"
	name: "res4b7_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2a"
	name: "bn4b7_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2a"
	name: "scale4b7_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b7_branch2a"
	bottom: "res4b7_branch2a"
	name: "res4b7_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2b"
	name: "res4b7_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2b"
	name: "bn4b7_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2b"
	name: "scale4b7_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b7_branch2b"
	bottom: "res4b7_branch2b"
	name: "res4b7_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2c"
	name: "res4b7_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2c"
	top: "res4b7_branch2c"
	name: "bn4b7_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b7_branch2c"
	top: "res4b7_branch2c"
	name: "scale4b7_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b6"
	bottom: "res4b7_branch2c"
	top: "res4b7"
	name: "res4b7"
	type: "Eltwise"
}

layer {
	bottom: "res4b7"
	top: "res4b7"
	name: "res4b7_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7"
	top: "res4b8_branch2a"
	name: "res4b8_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2a"
	name: "bn4b8_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2a"
	name: "scale4b8_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b8_branch2a"
	bottom: "res4b8_branch2a"
	name: "res4b8_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2b"
	name: "res4b8_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2b"
	name: "bn4b8_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2b"
	name: "scale4b8_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b8_branch2b"
	bottom: "res4b8_branch2b"
	name: "res4b8_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2c"
	name: "res4b8_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2c"
	top: "res4b8_branch2c"
	name: "bn4b8_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b8_branch2c"
	top: "res4b8_branch2c"
	name: "scale4b8_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b7"
	bottom: "res4b8_branch2c"
	top: "res4b8"
	name: "res4b8"
	type: "Eltwise"
}

layer {
	bottom: "res4b8"
	top: "res4b8"
	name: "res4b8_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8"
	top: "res4b9_branch2a"
	name: "res4b9_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2a"
	name: "bn4b9_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2a"
	name: "scale4b9_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b9_branch2a"
	bottom: "res4b9_branch2a"
	name: "res4b9_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2b"
	name: "res4b9_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2b"
	name: "bn4b9_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2b"
	name: "scale4b9_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b9_branch2b"
	bottom: "res4b9_branch2b"
	name: "res4b9_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2c"
	name: "res4b9_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2c"
	top: "res4b9_branch2c"
	name: "bn4b9_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b9_branch2c"
	top: "res4b9_branch2c"
	name: "scale4b9_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b8"
	bottom: "res4b9_branch2c"
	top: "res4b9"
	name: "res4b9"
	type: "Eltwise"
}

layer {
	bottom: "res4b9"
	top: "res4b9"
	name: "res4b9_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9"
	top: "res4b10_branch2a"
	name: "res4b10_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2a"
	name: "bn4b10_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2a"
	name: "scale4b10_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b10_branch2a"
	bottom: "res4b10_branch2a"
	name: "res4b10_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2b"
	name: "res4b10_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2b"
	name: "bn4b10_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2b"
	name: "scale4b10_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b10_branch2b"
	bottom: "res4b10_branch2b"
	name: "res4b10_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2c"
	name: "res4b10_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2c"
	top: "res4b10_branch2c"
	name: "bn4b10_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b10_branch2c"
	top: "res4b10_branch2c"
	name: "scale4b10_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b9"
	bottom: "res4b10_branch2c"
	top: "res4b10"
	name: "res4b10"
	type: "Eltwise"
}

layer {
	bottom: "res4b10"
	top: "res4b10"
	name: "res4b10_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10"
	top: "res4b11_branch2a"
	name: "res4b11_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2a"
	name: "bn4b11_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2a"
	name: "scale4b11_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b11_branch2a"
	bottom: "res4b11_branch2a"
	name: "res4b11_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2b"
	name: "res4b11_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2b"
	name: "bn4b11_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2b"
	name: "scale4b11_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b11_branch2b"
	bottom: "res4b11_branch2b"
	name: "res4b11_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2c"
	name: "res4b11_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2c"
	top: "res4b11_branch2c"
	name: "bn4b11_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b11_branch2c"
	top: "res4b11_branch2c"
	name: "scale4b11_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b10"
	bottom: "res4b11_branch2c"
	top: "res4b11"
	name: "res4b11"
	type: "Eltwise"
}

layer {
	bottom: "res4b11"
	top: "res4b11"
	name: "res4b11_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11"
	top: "res4b12_branch2a"
	name: "res4b12_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2a"
	name: "bn4b12_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2a"
	name: "scale4b12_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b12_branch2a"
	bottom: "res4b12_branch2a"
	name: "res4b12_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2b"
	name: "res4b12_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2b"
	name: "bn4b12_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2b"
	name: "scale4b12_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b12_branch2b"
	bottom: "res4b12_branch2b"
	name: "res4b12_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2c"
	name: "res4b12_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2c"
	top: "res4b12_branch2c"
	name: "bn4b12_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b12_branch2c"
	top: "res4b12_branch2c"
	name: "scale4b12_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b11"
	bottom: "res4b12_branch2c"
	top: "res4b12"
	name: "res4b12"
	type: "Eltwise"
}

layer {
	bottom: "res4b12"
	top: "res4b12"
	name: "res4b12_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12"
	top: "res4b13_branch2a"
	name: "res4b13_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2a"
	name: "bn4b13_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2a"
	name: "scale4b13_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b13_branch2a"
	bottom: "res4b13_branch2a"
	name: "res4b13_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2b"
	name: "res4b13_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2b"
	name: "bn4b13_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2b"
	name: "scale4b13_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b13_branch2b"
	bottom: "res4b13_branch2b"
	name: "res4b13_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2c"
	name: "res4b13_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2c"
	top: "res4b13_branch2c"
	name: "bn4b13_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b13_branch2c"
	top: "res4b13_branch2c"
	name: "scale4b13_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b12"
	bottom: "res4b13_branch2c"
	top: "res4b13"
	name: "res4b13"
	type: "Eltwise"
}

layer {
	bottom: "res4b13"
	top: "res4b13"
	name: "res4b13_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13"
	top: "res4b14_branch2a"
	name: "res4b14_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2a"
	name: "bn4b14_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2a"
	name: "scale4b14_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b14_branch2a"
	bottom: "res4b14_branch2a"
	name: "res4b14_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2b"
	name: "res4b14_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2b"
	name: "bn4b14_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2b"
	name: "scale4b14_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b14_branch2b"
	bottom: "res4b14_branch2b"
	name: "res4b14_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2c"
	name: "res4b14_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2c"
	top: "res4b14_branch2c"
	name: "bn4b14_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b14_branch2c"
	top: "res4b14_branch2c"
	name: "scale4b14_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b13"
	bottom: "res4b14_branch2c"
	top: "res4b14"
	name: "res4b14"
	type: "Eltwise"
}

layer {
	bottom: "res4b14"
	top: "res4b14"
	name: "res4b14_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14"
	top: "res4b15_branch2a"
	name: "res4b15_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2a"
	name: "bn4b15_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2a"
	name: "scale4b15_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b15_branch2a"
	bottom: "res4b15_branch2a"
	name: "res4b15_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2b"
	name: "res4b15_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2b"
	name: "bn4b15_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2b"
	name: "scale4b15_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b15_branch2b"
	bottom: "res4b15_branch2b"
	name: "res4b15_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2c"
	name: "res4b15_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2c"
	top: "res4b15_branch2c"
	name: "bn4b15_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b15_branch2c"
	top: "res4b15_branch2c"
	name: "scale4b15_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b14"
	bottom: "res4b15_branch2c"
	top: "res4b15"
	name: "res4b15"
	type: "Eltwise"
}

layer {
	bottom: "res4b15"
	top: "res4b15"
	name: "res4b15_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15"
	top: "res4b16_branch2a"
	name: "res4b16_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2a"
	name: "bn4b16_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2a"
	name: "scale4b16_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b16_branch2a"
	bottom: "res4b16_branch2a"
	name: "res4b16_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2b"
	name: "res4b16_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2b"
	name: "bn4b16_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2b"
	name: "scale4b16_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b16_branch2b"
	bottom: "res4b16_branch2b"
	name: "res4b16_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2c"
	name: "res4b16_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2c"
	top: "res4b16_branch2c"
	name: "bn4b16_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b16_branch2c"
	top: "res4b16_branch2c"
	name: "scale4b16_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b15"
	bottom: "res4b16_branch2c"
	top: "res4b16"
	name: "res4b16"
	type: "Eltwise"
}

layer {
	bottom: "res4b16"
	top: "res4b16"
	name: "res4b16_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16"
	top: "res4b17_branch2a"
	name: "res4b17_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2a"
	name: "bn4b17_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2a"
	name: "scale4b17_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b17_branch2a"
	bottom: "res4b17_branch2a"
	name: "res4b17_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2b"
	name: "res4b17_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2b"
	name: "bn4b17_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2b"
	name: "scale4b17_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b17_branch2b"
	bottom: "res4b17_branch2b"
	name: "res4b17_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2c"
	name: "res4b17_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2c"
	top: "res4b17_branch2c"
	name: "bn4b17_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b17_branch2c"
	top: "res4b17_branch2c"
	name: "scale4b17_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b16"
	bottom: "res4b17_branch2c"
	top: "res4b17"
	name: "res4b17"
	type: "Eltwise"
}

layer {
	bottom: "res4b17"
	top: "res4b17"
	name: "res4b17_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17"
	top: "res4b18_branch2a"
	name: "res4b18_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2a"
	name: "bn4b18_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2a"
	name: "scale4b18_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b18_branch2a"
	bottom: "res4b18_branch2a"
	name: "res4b18_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2b"
	name: "res4b18_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2b"
	name: "bn4b18_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2b"
	name: "scale4b18_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b18_branch2b"
	bottom: "res4b18_branch2b"
	name: "res4b18_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2c"
	name: "res4b18_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2c"
	top: "res4b18_branch2c"
	name: "bn4b18_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b18_branch2c"
	top: "res4b18_branch2c"
	name: "scale4b18_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b17"
	bottom: "res4b18_branch2c"
	top: "res4b18"
	name: "res4b18"
	type: "Eltwise"
}

layer {
	bottom: "res4b18"
	top: "res4b18"
	name: "res4b18_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18"
	top: "res4b19_branch2a"
	name: "res4b19_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2a"
	name: "bn4b19_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2a"
	name: "scale4b19_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b19_branch2a"
	bottom: "res4b19_branch2a"
	name: "res4b19_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2b"
	name: "res4b19_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2b"
	name: "bn4b19_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2b"
	name: "scale4b19_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b19_branch2b"
	bottom: "res4b19_branch2b"
	name: "res4b19_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2c"
	name: "res4b19_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2c"
	top: "res4b19_branch2c"
	name: "bn4b19_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b19_branch2c"
	top: "res4b19_branch2c"
	name: "scale4b19_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b18"
	bottom: "res4b19_branch2c"
	top: "res4b19"
	name: "res4b19"
	type: "Eltwise"
}

layer {
	bottom: "res4b19"
	top: "res4b19"
	name: "res4b19_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19"
	top: "res4b20_branch2a"
	name: "res4b20_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2a"
	name: "bn4b20_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2a"
	name: "scale4b20_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b20_branch2a"
	bottom: "res4b20_branch2a"
	name: "res4b20_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2b"
	name: "res4b20_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2b"
	name: "bn4b20_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2b"
	name: "scale4b20_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b20_branch2b"
	bottom: "res4b20_branch2b"
	name: "res4b20_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2c"
	name: "res4b20_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2c"
	top: "res4b20_branch2c"
	name: "bn4b20_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b20_branch2c"
	top: "res4b20_branch2c"
	name: "scale4b20_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b19"
	bottom: "res4b20_branch2c"
	top: "res4b20"
	name: "res4b20"
	type: "Eltwise"
}

layer {
	bottom: "res4b20"
	top: "res4b20"
	name: "res4b20_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20"
	top: "res4b21_branch2a"
	name: "res4b21_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2a"
	name: "bn4b21_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2a"
	name: "scale4b21_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b21_branch2a"
	bottom: "res4b21_branch2a"
	name: "res4b21_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2b"
	name: "res4b21_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2b"
	name: "bn4b21_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2b"
	name: "scale4b21_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b21_branch2b"
	bottom: "res4b21_branch2b"
	name: "res4b21_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2c"
	name: "res4b21_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2c"
	top: "res4b21_branch2c"
	name: "bn4b21_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b21_branch2c"
	top: "res4b21_branch2c"
	name: "scale4b21_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b20"
	bottom: "res4b21_branch2c"
	top: "res4b21"
	name: "res4b21"
	type: "Eltwise"
}

layer {
	bottom: "res4b21"
	top: "res4b21"
	name: "res4b21_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21"
	top: "res4b22_branch2a"
	name: "res4b22_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2a"
	name: "bn4b22_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2a"
	name: "scale4b22_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b22_branch2a"
	bottom: "res4b22_branch2a"
	name: "res4b22_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2b"
	name: "res4b22_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2b"
	name: "bn4b22_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2b"
	name: "scale4b22_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b22_branch2b"
	bottom: "res4b22_branch2b"
	name: "res4b22_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2c"
	name: "res4b22_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2c"
	top: "res4b22_branch2c"
	name: "bn4b22_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b22_branch2c"
	top: "res4b22_branch2c"
	name: "scale4b22_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b21"
	bottom: "res4b22_branch2c"
	top: "res4b22"
	name: "res4b22"
	type: "Eltwise"
}

layer {
	bottom: "res4b22"
	top: "res4b22"
	name: "res4b22_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22"
	top: "res4b23_branch2a"
	name: "res4b23_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b23_branch2a"
	top: "res4b23_branch2a"
	name: "bn4b23_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b23_branch2a"
	top: "res4b23_branch2a"
	name: "scale4b23_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b23_branch2a"
	bottom: "res4b23_branch2a"
	name: "res4b23_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b23_branch2a"
	top: "res4b23_branch2b"
	name: "res4b23_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b23_branch2b"
	top: "res4b23_branch2b"
	name: "bn4b23_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b23_branch2b"
	top: "res4b23_branch2b"
	name: "scale4b23_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b23_branch2b"
	bottom: "res4b23_branch2b"
	name: "res4b23_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b23_branch2b"
	top: "res4b23_branch2c"
	name: "res4b23_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b23_branch2c"
	top: "res4b23_branch2c"
	name: "bn4b23_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b23_branch2c"
	top: "res4b23_branch2c"
	name: "scale4b23_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b22"
	bottom: "res4b23_branch2c"
	top: "res4b23"
	name: "res4b23"
	type: "Eltwise"
}

layer {
	bottom: "res4b23"
	top: "res4b23"
	name: "res4b23_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b23"
	top: "res4b24_branch2a"
	name: "res4b24_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b24_branch2a"
	top: "res4b24_branch2a"
	name: "bn4b24_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b24_branch2a"
	top: "res4b24_branch2a"
	name: "scale4b24_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b24_branch2a"
	bottom: "res4b24_branch2a"
	name: "res4b24_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b24_branch2a"
	top: "res4b24_branch2b"
	name: "res4b24_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b24_branch2b"
	top: "res4b24_branch2b"
	name: "bn4b24_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b24_branch2b"
	top: "res4b24_branch2b"
	name: "scale4b24_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b24_branch2b"
	bottom: "res4b24_branch2b"
	name: "res4b24_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b24_branch2b"
	top: "res4b24_branch2c"
	name: "res4b24_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b24_branch2c"
	top: "res4b24_branch2c"
	name: "bn4b24_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b24_branch2c"
	top: "res4b24_branch2c"
	name: "scale4b24_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b23"
	bottom: "res4b24_branch2c"
	top: "res4b24"
	name: "res4b24"
	type: "Eltwise"
}

layer {
	bottom: "res4b24"
	top: "res4b24"
	name: "res4b24_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b24"
	top: "res4b25_branch2a"
	name: "res4b25_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b25_branch2a"
	top: "res4b25_branch2a"
	name: "bn4b25_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b25_branch2a"
	top: "res4b25_branch2a"
	name: "scale4b25_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b25_branch2a"
	bottom: "res4b25_branch2a"
	name: "res4b25_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b25_branch2a"
	top: "res4b25_branch2b"
	name: "res4b25_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b25_branch2b"
	top: "res4b25_branch2b"
	name: "bn4b25_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b25_branch2b"
	top: "res4b25_branch2b"
	name: "scale4b25_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b25_branch2b"
	bottom: "res4b25_branch2b"
	name: "res4b25_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b25_branch2b"
	top: "res4b25_branch2c"
	name: "res4b25_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b25_branch2c"
	top: "res4b25_branch2c"
	name: "bn4b25_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b25_branch2c"
	top: "res4b25_branch2c"
	name: "scale4b25_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b24"
	bottom: "res4b25_branch2c"
	top: "res4b25"
	name: "res4b25"
	type: "Eltwise"
}

layer {
	bottom: "res4b25"
	top: "res4b25"
	name: "res4b25_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b25"
	top: "res4b26_branch2a"
	name: "res4b26_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b26_branch2a"
	top: "res4b26_branch2a"
	name: "bn4b26_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b26_branch2a"
	top: "res4b26_branch2a"
	name: "scale4b26_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b26_branch2a"
	bottom: "res4b26_branch2a"
	name: "res4b26_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b26_branch2a"
	top: "res4b26_branch2b"
	name: "res4b26_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b26_branch2b"
	top: "res4b26_branch2b"
	name: "bn4b26_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b26_branch2b"
	top: "res4b26_branch2b"
	name: "scale4b26_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b26_branch2b"
	bottom: "res4b26_branch2b"
	name: "res4b26_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b26_branch2b"
	top: "res4b26_branch2c"
	name: "res4b26_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b26_branch2c"
	top: "res4b26_branch2c"
	name: "bn4b26_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b26_branch2c"
	top: "res4b26_branch2c"
	name: "scale4b26_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b25"
	bottom: "res4b26_branch2c"
	top: "res4b26"
	name: "res4b26"
	type: "Eltwise"
}

layer {
	bottom: "res4b26"
	top: "res4b26"
	name: "res4b26_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b26"
	top: "res4b27_branch2a"
	name: "res4b27_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b27_branch2a"
	top: "res4b27_branch2a"
	name: "bn4b27_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b27_branch2a"
	top: "res4b27_branch2a"
	name: "scale4b27_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b27_branch2a"
	bottom: "res4b27_branch2a"
	name: "res4b27_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b27_branch2a"
	top: "res4b27_branch2b"
	name: "res4b27_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b27_branch2b"
	top: "res4b27_branch2b"
	name: "bn4b27_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b27_branch2b"
	top: "res4b27_branch2b"
	name: "scale4b27_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b27_branch2b"
	bottom: "res4b27_branch2b"
	name: "res4b27_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b27_branch2b"
	top: "res4b27_branch2c"
	name: "res4b27_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b27_branch2c"
	top: "res4b27_branch2c"
	name: "bn4b27_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b27_branch2c"
	top: "res4b27_branch2c"
	name: "scale4b27_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b26"
	bottom: "res4b27_branch2c"
	top: "res4b27"
	name: "res4b27"
	type: "Eltwise"
}

layer {
	bottom: "res4b27"
	top: "res4b27"
	name: "res4b27_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b27"
	top: "res4b28_branch2a"
	name: "res4b28_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b28_branch2a"
	top: "res4b28_branch2a"
	name: "bn4b28_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b28_branch2a"
	top: "res4b28_branch2a"
	name: "scale4b28_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b28_branch2a"
	bottom: "res4b28_branch2a"
	name: "res4b28_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b28_branch2a"
	top: "res4b28_branch2b"
	name: "res4b28_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b28_branch2b"
	top: "res4b28_branch2b"
	name: "bn4b28_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b28_branch2b"
	top: "res4b28_branch2b"
	name: "scale4b28_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b28_branch2b"
	bottom: "res4b28_branch2b"
	name: "res4b28_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b28_branch2b"
	top: "res4b28_branch2c"
	name: "res4b28_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b28_branch2c"
	top: "res4b28_branch2c"
	name: "bn4b28_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b28_branch2c"
	top: "res4b28_branch2c"
	name: "scale4b28_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b27"
	bottom: "res4b28_branch2c"
	top: "res4b28"
	name: "res4b28"
	type: "Eltwise"
}

layer {
	bottom: "res4b28"
	top: "res4b28"
	name: "res4b28_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b28"
	top: "res4b29_branch2a"
	name: "res4b29_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b29_branch2a"
	top: "res4b29_branch2a"
	name: "bn4b29_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b29_branch2a"
	top: "res4b29_branch2a"
	name: "scale4b29_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b29_branch2a"
	bottom: "res4b29_branch2a"
	name: "res4b29_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b29_branch2a"
	top: "res4b29_branch2b"
	name: "res4b29_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b29_branch2b"
	top: "res4b29_branch2b"
	name: "bn4b29_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b29_branch2b"
	top: "res4b29_branch2b"
	name: "scale4b29_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b29_branch2b"
	bottom: "res4b29_branch2b"
	name: "res4b29_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b29_branch2b"
	top: "res4b29_branch2c"
	name: "res4b29_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b29_branch2c"
	top: "res4b29_branch2c"
	name: "bn4b29_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b29_branch2c"
	top: "res4b29_branch2c"
	name: "scale4b29_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b28"
	bottom: "res4b29_branch2c"
	top: "res4b29"
	name: "res4b29"
	type: "Eltwise"
}

layer {
	bottom: "res4b29"
	top: "res4b29"
	name: "res4b29_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b29"
	top: "res4b30_branch2a"
	name: "res4b30_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b30_branch2a"
	top: "res4b30_branch2a"
	name: "bn4b30_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b30_branch2a"
	top: "res4b30_branch2a"
	name: "scale4b30_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b30_branch2a"
	bottom: "res4b30_branch2a"
	name: "res4b30_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b30_branch2a"
	top: "res4b30_branch2b"
	name: "res4b30_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b30_branch2b"
	top: "res4b30_branch2b"
	name: "bn4b30_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b30_branch2b"
	top: "res4b30_branch2b"
	name: "scale4b30_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b30_branch2b"
	bottom: "res4b30_branch2b"
	name: "res4b30_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b30_branch2b"
	top: "res4b30_branch2c"
	name: "res4b30_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b30_branch2c"
	top: "res4b30_branch2c"
	name: "bn4b30_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b30_branch2c"
	top: "res4b30_branch2c"
	name: "scale4b30_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b29"
	bottom: "res4b30_branch2c"
	top: "res4b30"
	name: "res4b30"
	type: "Eltwise"
}

layer {
	bottom: "res4b30"
	top: "res4b30"
	name: "res4b30_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b30"
	top: "res4b31_branch2a"
	name: "res4b31_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b31_branch2a"
	top: "res4b31_branch2a"
	name: "bn4b31_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b31_branch2a"
	top: "res4b31_branch2a"
	name: "scale4b31_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b31_branch2a"
	bottom: "res4b31_branch2a"
	name: "res4b31_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b31_branch2a"
	top: "res4b31_branch2b"
	name: "res4b31_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b31_branch2b"
	top: "res4b31_branch2b"
	name: "bn4b31_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b31_branch2b"
	top: "res4b31_branch2b"
	name: "scale4b31_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b31_branch2b"
	bottom: "res4b31_branch2b"
	name: "res4b31_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b31_branch2b"
	top: "res4b31_branch2c"
	name: "res4b31_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b31_branch2c"
	top: "res4b31_branch2c"
	name: "bn4b31_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b31_branch2c"
	top: "res4b31_branch2c"
	name: "scale4b31_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b30"
	bottom: "res4b31_branch2c"
	top: "res4b31"
	name: "res4b31"
	type: "Eltwise"
}

layer {
	bottom: "res4b31"
	top: "res4b31"
	name: "res4b31_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b31"
	top: "res4b32_branch2a"
	name: "res4b32_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b32_branch2a"
	top: "res4b32_branch2a"
	name: "bn4b32_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b32_branch2a"
	top: "res4b32_branch2a"
	name: "scale4b32_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b32_branch2a"
	bottom: "res4b32_branch2a"
	name: "res4b32_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b32_branch2a"
	top: "res4b32_branch2b"
	name: "res4b32_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b32_branch2b"
	top: "res4b32_branch2b"
	name: "bn4b32_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b32_branch2b"
	top: "res4b32_branch2b"
	name: "scale4b32_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b32_branch2b"
	bottom: "res4b32_branch2b"
	name: "res4b32_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b32_branch2b"
	top: "res4b32_branch2c"
	name: "res4b32_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b32_branch2c"
	top: "res4b32_branch2c"
	name: "bn4b32_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b32_branch2c"
	top: "res4b32_branch2c"
	name: "scale4b32_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b31"
	bottom: "res4b32_branch2c"
	top: "res4b32"
	name: "res4b32"
	type: "Eltwise"
}

layer {
	bottom: "res4b32"
	top: "res4b32"
	name: "res4b32_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b32"
	top: "res4b33_branch2a"
	name: "res4b33_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b33_branch2a"
	top: "res4b33_branch2a"
	name: "bn4b33_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b33_branch2a"
	top: "res4b33_branch2a"
	name: "scale4b33_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b33_branch2a"
	bottom: "res4b33_branch2a"
	name: "res4b33_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b33_branch2a"
	top: "res4b33_branch2b"
	name: "res4b33_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b33_branch2b"
	top: "res4b33_branch2b"
	name: "bn4b33_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b33_branch2b"
	top: "res4b33_branch2b"
	name: "scale4b33_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b33_branch2b"
	bottom: "res4b33_branch2b"
	name: "res4b33_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b33_branch2b"
	top: "res4b33_branch2c"
	name: "res4b33_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b33_branch2c"
	top: "res4b33_branch2c"
	name: "bn4b33_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b33_branch2c"
	top: "res4b33_branch2c"
	name: "scale4b33_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b32"
	bottom: "res4b33_branch2c"
	top: "res4b33"
	name: "res4b33"
	type: "Eltwise"
}

layer {
	bottom: "res4b33"
	top: "res4b33"
	name: "res4b33_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b33"
	top: "res4b34_branch2a"
	name: "res4b34_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b34_branch2a"
	top: "res4b34_branch2a"
	name: "bn4b34_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b34_branch2a"
	top: "res4b34_branch2a"
	name: "scale4b34_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b34_branch2a"
	bottom: "res4b34_branch2a"
	name: "res4b34_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b34_branch2a"
	top: "res4b34_branch2b"
	name: "res4b34_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b34_branch2b"
	top: "res4b34_branch2b"
	name: "bn4b34_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b34_branch2b"
	top: "res4b34_branch2b"
	name: "scale4b34_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b34_branch2b"
	bottom: "res4b34_branch2b"
	name: "res4b34_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b34_branch2b"
	top: "res4b34_branch2c"
	name: "res4b34_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b34_branch2c"
	top: "res4b34_branch2c"
	name: "bn4b34_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b34_branch2c"
	top: "res4b34_branch2c"
	name: "scale4b34_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b33"
	bottom: "res4b34_branch2c"
	top: "res4b34"
	name: "res4b34"
	type: "Eltwise"
}

layer {
	bottom: "res4b34"
	top: "res4b34"
	name: "res4b34_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b34"
	top: "res4b35_branch2a"
	name: "res4b35_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b35_branch2a"
	top: "res4b35_branch2a"
	name: "bn4b35_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b35_branch2a"
	top: "res4b35_branch2a"
	name: "scale4b35_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b35_branch2a"
	bottom: "res4b35_branch2a"
	name: "res4b35_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b35_branch2a"
	top: "res4b35_branch2b"
	name: "res4b35_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b35_branch2b"
	top: "res4b35_branch2b"
	name: "bn4b35_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b35_branch2b"
	top: "res4b35_branch2b"
	name: "scale4b35_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b35_branch2b"
	bottom: "res4b35_branch2b"
	name: "res4b35_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b35_branch2b"
	top: "res4b35_branch2c"
	name: "res4b35_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b35_branch2c"
	top: "res4b35_branch2c"
	name: "bn4b35_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b35_branch2c"
	top: "res4b35_branch2c"
	name: "scale4b35_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b34"
	bottom: "res4b35_branch2c"
	top: "res4b35"
	name: "res4b35"
	type: "Eltwise"
}

layer {
	bottom: "res4b35"
	top: "res4b35"
	name: "res4b35_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b35"
	top: "res5a_branch1"
	name: "res5a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "bn5a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "scale5a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b35"
	top: "res5a_branch2a"
	name: "res5a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "bn5a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "scale5a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5a_branch2a"
	bottom: "res5a_branch2a"
	name: "res5a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2b"
	name: "res5a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "bn5a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "scale5a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5a_branch2b"
	bottom: "res5a_branch2b"
	name: "res5a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2c"
	name: "res5a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "bn5a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "scale5a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a_branch1"
	bottom: "res5a_branch2c"
	top: "res5a"
	name: "res5a"
	type: "Eltwise"
}

layer {
	bottom: "res5a"
	top: "res5a"
	name: "res5a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a"
	top: "res5b_branch2a"
	name: "res5b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "bn5b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "scale5b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5b_branch2a"
	bottom: "res5b_branch2a"
	name: "res5b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2b"
	name: "res5b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "bn5b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "scale5b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5b_branch2b"
	bottom: "res5b_branch2b"
	name: "res5b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2c"
	name: "res5b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "bn5b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "scale5b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a"
	bottom: "res5b_branch2c"
	top: "res5b"
	name: "res5b"
	type: "Eltwise"
}

layer {
	bottom: "res5b"
	top: "res5b"
	name: "res5b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b"
	top: "res5c_branch2a"
	name: "res5c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "bn5c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "scale5c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5c_branch2a"
	bottom: "res5c_branch2a"
	name: "res5c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2b"
	name: "res5c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "bn5c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "scale5c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5c_branch2b"
	bottom: "res5c_branch2b"
	name: "res5c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2c"
	name: "res5c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "bn5c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "scale5c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5b"
	bottom: "res5c_branch2c"
	top: "res5c"
	name: "res5c"
	type: "Eltwise"
}

layer {
	bottom: "res5c"
	top: "res5c"
	name: "res5c_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c"
	top: "pool5"
	name: "pool5"
	type: "Pooling"
	pooling_param {
		kernel_size: 7
		stride: 1
		pool: AVE
	}
}

layer {
	bottom: "pool5"
	top: "fc1000"
	name: "fc1000"
	type: "InnerProduct"
	inner_product_param {
		num_output: 1000
	}
}

layer {
	bottom: "fc1000"
	top: "prob"
	name: "prob"
	type: "Softmax"
}



================================================
FILE: prototxt/ResNet-50-deploy.prototxt
================================================
name: "ResNet-50"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224

layer {
	bottom: "data"
	top: "conv1"
	name: "conv1"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 7
		pad: 3
		stride: 2
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "bn_conv1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "scale_conv1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "conv1_relu"
	type: "ReLU"
}

layer {
	bottom: "conv1"
	top: "pool1"
	name: "pool1"
	type: "Pooling"
	pooling_param {
		kernel_size: 3
		stride: 2
		pool: MAX
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch1"
	name: "res2a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "bn2a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "scale2a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch2a"
	name: "res2a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "bn2a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "scale2a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "res2a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2b"
	name: "res2a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "bn2a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "scale2a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "res2a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2c"
	name: "res2a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "bn2a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "scale2a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a_branch1"
	bottom: "res2a_branch2c"
	top: "res2a"
	name: "res2a"
	type: "Eltwise"
}

layer {
	bottom: "res2a"
	top: "res2a"
	name: "res2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a"
	top: "res2b_branch2a"
	name: "res2b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "bn2b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "scale2b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "res2b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2b"
	name: "res2b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "bn2b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "scale2b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "res2b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2c"
	name: "res2b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "bn2b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "scale2b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a"
	bottom: "res2b_branch2c"
	top: "res2b"
	name: "res2b"
	type: "Eltwise"
}

layer {
	bottom: "res2b"
	top: "res2b"
	name: "res2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b"
	top: "res2c_branch2a"
	name: "res2c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "bn2c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "scale2c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "res2c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2b"
	name: "res2c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "bn2c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "scale2c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "res2c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2c"
	name: "res2c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "bn2c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "scale2c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2b"
	bottom: "res2c_branch2c"
	top: "res2c"
	name: "res2c"
	type: "Eltwise"
}

layer {
	bottom: "res2c"
	top: "res2c"
	name: "res2c_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c"
	top: "res3a_branch1"
	name: "res3a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "bn3a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "scale3a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2c"
	top: "res3a_branch2a"
	name: "res3a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "bn3a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "scale3a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "res3a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2b"
	name: "res3a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "bn3a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "scale3a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "res3a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2c"
	name: "res3a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "bn3a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "scale3a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a_branch1"
	bottom: "res3a_branch2c"
	top: "res3a"
	name: "res3a"
	type: "Eltwise"
}

layer {
	bottom: "res3a"
	top: "res3a"
	name: "res3a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a"
	top: "res3b_branch2a"
	name: "res3b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b_branch2a"
	top: "res3b_branch2a"
	name: "bn3b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b_branch2a"
	top: "res3b_branch2a"
	name: "scale3b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b_branch2a"
	top: "res3b_branch2a"
	name: "res3b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b_branch2a"
	top: "res3b_branch2b"
	name: "res3b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b_branch2b"
	top: "res3b_branch2b"
	name: "bn3b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b_branch2b"
	top: "res3b_branch2b"
	name: "scale3b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b_branch2b"
	top: "res3b_branch2b"
	name: "res3b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b_branch2b"
	top: "res3b_branch2c"
	name: "res3b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b_branch2c"
	top: "res3b_branch2c"
	name: "bn3b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3b_branch2c"
	top: "res3b_branch2c"
	name: "scale3b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a"
	bottom: "res3b_branch2c"
	top: "res3b"
	name: "res3b"
	type: "Eltwise"
}

layer {
	bottom: "res3b"
	top: "res3b"
	name: "res3b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b"
	top: "res3c_branch2a"
	name: "res3c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3c_branch2a"
	top: "res3c_branch2a"
	name: "bn3c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3c_branch2a"
	top: "res3c_branch2a"
	name: "scale3c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3c_branch2a"
	top: "res3c_branch2a"
	name: "res3c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3c_branch2a"
	top: "res3c_branch2b"
	name: "res3c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3c_branch2b"
	top: "res3c_branch2b"
	name: "bn3c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3c_branch2b"
	top: "res3c_branch2b"
	name: "scale3c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3c_branch2b"
	top: "res3c_branch2b"
	name: "res3c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3c_branch2b"
	top: "res3c_branch2c"
	name: "res3c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3c_branch2c"
	top: "res3c_branch2c"
	name: "bn3c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3c_branch2c"
	top: "res3c_branch2c"
	name: "scale3c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b"
	bottom: "res3c_branch2c"
	top: "res3c"
	name: "res3c"
	type: "Eltwise"
}

layer {
	bottom: "res3c"
	top: "res3c"
	name: "res3c_relu"
	type: "ReLU"
}

layer {
	bottom: "res3c"
	top: "res3d_branch2a"
	name: "res3d_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3d_branch2a"
	top: "res3d_branch2a"
	name: "bn3d_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3d_branch2a"
	top: "res3d_branch2a"
	name: "scale3d_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3d_branch2a"
	top: "res3d_branch2a"
	name: "res3d_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3d_branch2a"
	top: "res3d_branch2b"
	name: "res3d_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3d_branch2b"
	top: "res3d_branch2b"
	name: "bn3d_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3d_branch2b"
	top: "res3d_branch2b"
	name: "scale3d_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3d_branch2b"
	top: "res3d_branch2b"
	name: "res3d_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3d_branch2b"
	top: "res3d_branch2c"
	name: "res3d_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3d_branch2c"
	top: "res3d_branch2c"
	name: "bn3d_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res3d_branch2c"
	top: "res3d_branch2c"
	name: "scale3d_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3c"
	bottom: "res3d_branch2c"
	top: "res3d"
	name: "res3d"
	type: "Eltwise"
}

layer {
	bottom: "res3d"
	top: "res3d"
	name: "res3d_relu"
	type: "ReLU"
}

layer {
	bottom: "res3d"
	top: "res4a_branch1"
	name: "res4a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "bn4a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "scale4a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3d"
	top: "res4a_branch2a"
	name: "res4a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "bn4a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "scale4a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "res4a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2b"
	name: "res4a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "bn4a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "scale4a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "res4a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2c"
	name: "res4a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "bn4a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "scale4a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a_branch1"
	bottom: "res4a_branch2c"
	top: "res4a"
	name: "res4a"
	type: "Eltwise"
}

layer {
	bottom: "res4a"
	top: "res4a"
	name: "res4a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a"
	top: "res4b_branch2a"
	name: "res4b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b_branch2a"
	top: "res4b_branch2a"
	name: "bn4b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b_branch2a"
	top: "res4b_branch2a"
	name: "scale4b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b_branch2a"
	top: "res4b_branch2a"
	name: "res4b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b_branch2a"
	top: "res4b_branch2b"
	name: "res4b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b_branch2b"
	top: "res4b_branch2b"
	name: "bn4b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b_branch2b"
	top: "res4b_branch2b"
	name: "scale4b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b_branch2b"
	top: "res4b_branch2b"
	name: "res4b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b_branch2b"
	top: "res4b_branch2c"
	name: "res4b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b_branch2c"
	top: "res4b_branch2c"
	name: "bn4b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4b_branch2c"
	top: "res4b_branch2c"
	name: "scale4b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a"
	bottom: "res4b_branch2c"
	top: "res4b"
	name: "res4b"
	type: "Eltwise"
}

layer {
	bottom: "res4b"
	top: "res4b"
	name: "res4b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b"
	top: "res4c_branch2a"
	name: "res4c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4c_branch2a"
	top: "res4c_branch2a"
	name: "bn4c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4c_branch2a"
	top: "res4c_branch2a"
	name: "scale4c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4c_branch2a"
	top: "res4c_branch2a"
	name: "res4c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4c_branch2a"
	top: "res4c_branch2b"
	name: "res4c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4c_branch2b"
	top: "res4c_branch2b"
	name: "bn4c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4c_branch2b"
	top: "res4c_branch2b"
	name: "scale4c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4c_branch2b"
	top: "res4c_branch2b"
	name: "res4c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4c_branch2b"
	top: "res4c_branch2c"
	name: "res4c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4c_branch2c"
	top: "res4c_branch2c"
	name: "bn4c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4c_branch2c"
	top: "res4c_branch2c"
	name: "scale4c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b"
	bottom: "res4c_branch2c"
	top: "res4c"
	name: "res4c"
	type: "Eltwise"
}

layer {
	bottom: "res4c"
	top: "res4c"
	name: "res4c_relu"
	type: "ReLU"
}

layer {
	bottom: "res4c"
	top: "res4d_branch2a"
	name: "res4d_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4d_branch2a"
	top: "res4d_branch2a"
	name: "bn4d_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4d_branch2a"
	top: "res4d_branch2a"
	name: "scale4d_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4d_branch2a"
	top: "res4d_branch2a"
	name: "res4d_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4d_branch2a"
	top: "res4d_branch2b"
	name: "res4d_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4d_branch2b"
	top: "res4d_branch2b"
	name: "bn4d_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4d_branch2b"
	top: "res4d_branch2b"
	name: "scale4d_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4d_branch2b"
	top: "res4d_branch2b"
	name: "res4d_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4d_branch2b"
	top: "res4d_branch2c"
	name: "res4d_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4d_branch2c"
	top: "res4d_branch2c"
	name: "bn4d_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4d_branch2c"
	top: "res4d_branch2c"
	name: "scale4d_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4c"
	bottom: "res4d_branch2c"
	top: "res4d"
	name: "res4d"
	type: "Eltwise"
}

layer {
	bottom: "res4d"
	top: "res4d"
	name: "res4d_relu"
	type: "ReLU"
}

layer {
	bottom: "res4d"
	top: "res4e_branch2a"
	name: "res4e_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4e_branch2a"
	top: "res4e_branch2a"
	name: "bn4e_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4e_branch2a"
	top: "res4e_branch2a"
	name: "scale4e_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4e_branch2a"
	top: "res4e_branch2a"
	name: "res4e_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4e_branch2a"
	top: "res4e_branch2b"
	name: "res4e_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4e_branch2b"
	top: "res4e_branch2b"
	name: "bn4e_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4e_branch2b"
	top: "res4e_branch2b"
	name: "scale4e_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4e_branch2b"
	top: "res4e_branch2b"
	name: "res4e_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4e_branch2b"
	top: "res4e_branch2c"
	name: "res4e_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4e_branch2c"
	top: "res4e_branch2c"
	name: "bn4e_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4e_branch2c"
	top: "res4e_branch2c"
	name: "scale4e_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4d"
	bottom: "res4e_branch2c"
	top: "res4e"
	name: "res4e"
	type: "Eltwise"
}

layer {
	bottom: "res4e"
	top: "res4e"
	name: "res4e_relu"
	type: "ReLU"
}

layer {
	bottom: "res4e"
	top: "res4f_branch2a"
	name: "res4f_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4f_branch2a"
	top: "res4f_branch2a"
	name: "bn4f_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4f_branch2a"
	top: "res4f_branch2a"
	name: "scale4f_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4f_branch2a"
	top: "res4f_branch2a"
	name: "res4f_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4f_branch2a"
	top: "res4f_branch2b"
	name: "res4f_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4f_branch2b"
	top: "res4f_branch2b"
	name: "bn4f_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4f_branch2b"
	top: "res4f_branch2b"
	name: "scale4f_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4f_branch2b"
	top: "res4f_branch2b"
	name: "res4f_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4f_branch2b"
	top: "res4f_branch2c"
	name: "res4f_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4f_branch2c"
	top: "res4f_branch2c"
	name: "bn4f_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res4f_branch2c"
	top: "res4f_branch2c"
	name: "scale4f_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4e"
	bottom: "res4f_branch2c"
	top: "res4f"
	name: "res4f"
	type: "Eltwise"
}

layer {
	bottom: "res4f"
	top: "res4f"
	name: "res4f_relu"
	type: "ReLU"
}

layer {
	bottom: "res4f"
	top: "res5a_branch1"
	name: "res5a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "bn5a_branch1"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "scale5a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4f"
	top: "res5a_branch2a"
	name: "res5a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "bn5a_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "scale5a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "res5a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2b"
	name: "res5a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "bn5a_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "scale5a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "res5a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2c"
	name: "res5a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "bn5a_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "scale5a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a_branch1"
	bottom: "res5a_branch2c"
	top: "res5a"
	name: "res5a"
	type: "Eltwise"
}

layer {
	bottom: "res5a"
	top: "res5a"
	name: "res5a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a"
	top: "res5b_branch2a"
	name: "res5b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "bn5b_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "scale5b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "res5b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2b"
	name: "res5b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "bn5b_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "scale5b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "res5b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2c"
	name: "res5b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "bn5b_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "scale5b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a"
	bottom: "res5b_branch2c"
	top: "res5b"
	name: "res5b"
	type: "Eltwise"
}

layer {
	bottom: "res5b"
	top: "res5b"
	name: "res5b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b"
	top: "res5c_branch2a"
	name: "res5c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "bn5c_branch2a"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "scale5c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "res5c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2b"
	name: "res5c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "bn5c_branch2b"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "scale5c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "res5c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2c"
	name: "res5c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "bn5c_branch2c"
	type: "BatchNorm"
	batch_norm_param {
		use_global_stats: true
	}
}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "scale5c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5b"
	bottom: "res5c_branch2c"
	top: "res5c"
	name: "res5c"
	type: "Eltwise"
}

layer {
	bottom: "res5c"
	top: "res5c"
	name: "res5c_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c"
	top: "pool5"
	name: "pool5"
	type: "Pooling"
	pooling_param {
		kernel_size: 7
		stride: 1
		pool: AVE
	}
}

layer {
	bottom: "pool5"
	top: "fc1000"
	name: "fc1000"
	type: "InnerProduct"
	inner_product_param {
		num_output: 1000
	}
}

layer {
	bottom: "fc1000"
	top: "prob"
	name: "prob"
	type: "Softmax"
}