deploy_resnet101_normpython.prototxt

name: "ResNet-101"
input: "data"
input_shape{
dim: 1
dim: 3
dim: 224
dim: 224
}

input: "rois"
input_shape{
dim: 1
dim: 1
dim: 1
dim: 5
}



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"
}

## Get rmac regions with a RoiPooling layer. If batch size was 1, we end up with N_regions x D x pooled_h x pooled_w 
layer {
   name: "pooled_rois"
   type: "ROIPooling"
   bottom: "res5c"
   bottom: "rois"
   top: "pooled_rois"
   roi_pooling_param {
     pooled_w: 1
     pooled_h: 1
    spatial_scale: 0.03125 # 1/32
   }
 }
layer {
  name: "pooled_rois/normalized"
  type: "Python"
  bottom: "pooled_rois"
  top: "pooled_rois/normalized"
  python_param {
    module: 'custom_layers'
    layer: 'NormalizeLayer'
    param_str: "{}"
  }
}
layer {
	name: "pooled_rois/normalized_flat"
	type: "Reshape"
	reshape_param{
	shape{
		dim: 0
		dim: 2048 # feat x spx (1) x spy (1)
		dim: 1
		dim: 1
		}    
	}
	bottom: "pooled_rois/normalized"
	top: "pooled_rois/normalized_flat"
}
# Mean center done with a scaling (at 1) + shifting. The shifting needs to be copied into the model weights.
layer {
  name: "pooled_rois/centered"
  bottom: "pooled_rois/normalized_flat"
  top: "pooled_rois/centered"
  type: "Scale"
  scale_param {
      bias_term: true
      filler {
        type: "constant"
        value: 1
      }
      bias_filler {
        type: "constant"
		value: 0
      }
  }
}
# And then the PCA, which is another FC layer
layer {
  name: "pooled_rois/pca"
  type: "InnerProduct"
  inner_product_param {
    num_output: 2048 # output PCA dimensionality 
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
  bottom: "pooled_rois/centered"
  top: "pooled_rois/pca"
}
# After the FC layers the size is now n_batches x d. We reshape to n_batches x d x 1 x 1 to L2 normalize again
layer {
	name: "pooled_rois/pca/reshaped"
	type: "Reshape"
	reshape_param{
	shape{
		dim: 0 
		dim: 0
		dim: 1
		dim: 1
		}    
	}
	bottom: "pooled_rois/pca"
	top: "pooled_rois/pca/reshaped"
}
layer {
  name: "pooled_rois/pca/normalized"
  type: "Python"
  bottom: "pooled_rois/pca"
  top: "pooled_rois/pca/normalized"
  python_param {
    module: 'custom_layers'
    layer: 'NormalizeLayer'
    param_str: "{}"
  }
}
layer {
  name: "rmac"
  type: "Python"
  bottom: "pooled_rois/pca/normalized"
  top: "rmac"
  python_param {
    module: 'custom_layers'
    layer: 'AggregateLayer'
    param_str: "{}"
  }
}
## L2, one last time
layer {
  name: "rmac/normalized"
  type: "Python"
  bottom: "rmac"
  top: "rmac/normalized"
  python_param {
    module: 'custom_layers'
    layer: 'NormalizeLayer'
    param_str: "{}"
  }
}