models_64_8_5groups_norelu_deploy.prototxt

name: "models_64_8_5groups_norelu"
input:"data"
input_dim:1
input_dim:3
input_dim:64
input_dim:64

layer {
  bottom: "data"
  top: "conv1"
  name: "conv1"
  type: "Convolution"
  param {
    #lr_mult: 1
    #decay_mult: 1
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 30
    kernel_size: 5
    stride: 1
    pad: 0
	weight_filler {
      type: "fullsrm"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "group1_conv"
  type: "Convolution"
  bottom: "conv1"
  top: "group1_conv"
  param {
    lr_mult: 1
    decay_mult: 0
  } 
  convolution_param {
    num_output: 16
    pad: 2
    kernel_size: 5
    bias_term: false
    weight_filler {
      type: "gaussian"
      std: 0.01
    } 
  } 
  propagate_down: false
}
layer {
  name: "group1_ABS"
  bottom: "group1_conv"
  top: "group1_ABS"
  type: "AbsVal"
}
layer { 
   name: "group1_BN" 
   type: "BatchNorm" 
   bottom: "group1_ABS" 
   top: "group1_ABS" 
   batch_norm_param { 
	use_global_stats: true
   }  
} 
layer {
	bottom: "group1_ABS"
	top: "group1_ABS"
	name: "group1_scale_conv"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "group1_tanH"
  bottom: "group1_ABS"
  top: "group1_tanH"
  type: "TanH"
}
layer {
  name: "group1_pool"
  type: "Pooling"
  bottom: "group1_tanH"
  top: "group1_pool"
  pooling_param {
    pool: AVE
    pad: 1
    kernel_size: 5 # pool over a 5x5 region
    stride: 2      # step two pixels (in the bottom blob) between pooling regions
  }
}
layer {
  name: "group2_conv"
  type: "Convolution"
  bottom: "group1_pool"
  top: "group2_conv"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    bias_term: false
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
   name: "group2_BN"
   type: "BatchNorm"
   bottom: "group2_conv"
   top: "group2_conv"
   batch_norm_param {
        use_global_stats:  true
   }
}
layer {
	bottom: "group2_conv"
	top: "group2_conv"
	name: "group2_scale_conv"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "group2_tanH"
  bottom: "group2_conv"
  top: "group2_tanH"
  type: "TanH"
}
layer {
  name: "group2_pool"
  type: "Pooling"
  bottom: "group2_tanH"
  top: "group2_pool"
  pooling_param {
    pool: AVE
    pad: 1
    kernel_size: 5 # pool over a 5x5 region
    stride: 2      # step two pixels (in the bottom blob) between pooling regions
  }
}
layer {
  name: "group3_conv"
  type: "Convolution"
  bottom: "group2_pool"
  top: "group3_conv"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    bias_term: false
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
   name: "group3_BN"
   type: "BatchNorm"
   bottom: "group3_conv"
   top: "group3_conv"
   batch_norm_param {
        use_global_stats:  true
   }
}
layer {
	bottom: "group3_conv"
	top: "group3_conv"
	name: "group3_scale_conv"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "group3_relu"
  bottom: "group3_conv"
  top: "group3_conv"
  type: "ReLU"
}
layer {
  name: "group3_pool"
  type: "Pooling"
  bottom: "group3_conv"
  top: "group3_pool"
  pooling_param {
    pool: AVE
    pad: 1
    kernel_size: 5 # pool over a 5x5 region
    stride: 2      # step two pixels (in the bottom blob) between pooling regions
  }
}
layer {
  name: "group4_conv"
  type: "Convolution"
  bottom: "group3_pool"
  top: "group4_conv"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    bias_term: false
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
   name: "group4_BN"
   type: "BatchNorm"
   bottom: "group4_conv"
   top: "group4_conv"
   batch_norm_param {
        use_global_stats:  true
   }
}
layer {
	bottom: "group4_conv"
	top: "group4_conv"
	name: "group4_scale_conv"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "group4_relu"
  bottom: "group4_conv"
  top: "group4_conv"
  type: "ReLU"
}
layer {
  name: "group4_pool"
  type: "Pooling"
  bottom: "group4_conv"
  top: "group4_pool"
  pooling_param {
    pool: AVE
    pad: 1
    kernel_size: 5 # pool over a 5x5 region
    stride: 2      # step two pixels (in the bottom blob) between pooling regions
  }
}
layer {
  name: "group5_conv"
  type: "Convolution"
  bottom: "group4_pool"
  top: "group5_conv"
  param {
    lr_mult: 1
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    bias_term: false
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
   name: "group5_BN"
   type: "BatchNorm"
   bottom: "group5_conv"
   top: "group5_conv"
   batch_norm_param {
        use_global_stats:  true
   }
}
layer {
	bottom: "group5_conv"
	top: "group5_conv"
	name: "group5_scale_conv"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "group5_relu"
  bottom: "group5_conv"
  top: "group5_conv"
  type: "ReLU"
}
layer {
  name: "group5_pool"
  type: "Pooling"
  bottom: "group5_conv"
  top: "group5_pool"
  pooling_param {
    pool: AVE
    pad: 0
    kernel_size: 3
    stride: 3      # step two pixels (in the bottom blob) between pooling regions
  }
}
layer {
  name: "fc1"
  type: "InnerProduct"
  # learning rate and decay multipliers for the weights
  param { lr_mult: 1 decay_mult: 1 }
  # learning rate and decay multipliers for the biases
  param { lr_mult: 2 decay_mult: 0 }
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
  bottom: "group5_pool"
  top: "fc1"
}
layer {
  name: "prob"
  type: "Softmax"
  bottom: "fc1"
  top: "prob"
  include { phase: TEST }
}