c3d_ucf101_deploy.prototxt

name: "c3d_ucf101"
input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 16
  dim: 112
  dim: 112
}

# ----- 1st group -----
layer {
  name: "conv1a"
  type: "NdConvolution"
  bottom: "data"
  top: "conv1a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_shape { dim: 3 dim: 3 dim: 3 }
    stride_shape { dim: 1 dim: 1 dim: 1 }
    pad_shape    { dim: 1 dim: 1 dim: 1 }
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1a"
  type: "ReLU"
  bottom: "conv1a"
  top: "conv1a"
}
layer {
  name: "pool1"
  type: "NdPooling"
  bottom: "conv1a"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_shape { dim: 1 dim: 2 dim: 2 }
    stride_shape { dim: 1 dim: 2 dim: 2 }
  }
}

# ----- 2nd group -----
layer {
  name: "conv2a"
  type: "NdConvolution"
  bottom: "pool1"
  top: "conv2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_shape { dim: 3 dim: 3 dim: 3 }
    stride_shape { dim: 1 dim: 1 dim: 1 }
    pad_shape    { dim: 1 dim: 1 dim: 1 }
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu2a"
  type: "ReLU"
  bottom: "conv2a"
  top: "conv2a"
}
layer {
  name: "pool2"
  type: "NdPooling"
  bottom: "conv2a"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_shape { dim: 2 dim: 2 dim: 2 }
    stride_shape { dim: 2 dim: 2 dim: 2 }
  }
}

# ----- 3rd group -----
layer {
  name: "conv3a"
  type: "NdConvolution"
  bottom: "pool2"
  top: "conv3a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_shape { dim: 3 dim: 3 dim: 3 }
    stride_shape { dim: 1 dim: 1 dim: 1 }
    pad_shape    { dim: 1 dim: 1 dim: 1 }
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu3a"
  type: "ReLU"
  bottom: "conv3a"
  top: "conv3a"
}
layer {
  name: "pool3"
  type: "NdPooling"
  bottom: "conv3a"
  top: "pool3"
  pooling_param {
    pool: MAX
    kernel_shape { dim: 2 dim: 2 dim: 2 }
    stride_shape { dim: 2 dim: 2 dim: 2 }
  }
}

# ----- 4th group -----
layer {
  name: "conv4a"
  type: "NdConvolution"
  bottom: "pool3"
  top: "conv4a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_shape { dim: 3 dim: 3 dim: 3 }
    stride_shape { dim: 1 dim: 1 dim: 1 }
    pad_shape    { dim: 1 dim: 1 dim: 1 }
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu4a"
  type: "ReLU"
  bottom: "conv4a"
  top: "conv4a"
}
layer {
  name: "pool4"
  type: "NdPooling"
  bottom: "conv4a"
  top: "pool4"
  pooling_param {
    pool: MAX
    kernel_shape { dim: 2 dim: 2 dim: 2 }
    stride_shape { dim: 2 dim: 2 dim: 2 }
  }
}

# ----- 5th group -----
layer {
  name: "conv5a"
  type: "NdConvolution"
  bottom: "pool4"
  top: "conv5a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_shape { dim: 3 dim: 3 dim: 3 }
    stride_shape { dim: 1 dim: 1 dim: 1 }
    pad_shape    { dim: 1 dim: 1 dim: 1 }
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu5a"
  type: "ReLU"
  bottom: "conv5a"
  top: "conv5a"
}
layer {
  name: "pool5"
  type: "NdPooling"
  bottom: "conv5a"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_shape { dim: 2 dim: 2 dim: 2 }
    stride_shape { dim: 2 dim: 2 dim: 2 }
  }
}

# ----- 1st fc group -----
layer {
  name: "fc6"
  type: "InnerProduct"
  bottom: "pool5"
  top: "fc6"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 2048
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "fc6"
  top: "fc6"
}
layer {
  name: "drop6"
  type: "Dropout"
  bottom: "fc6"
  top: "fc6"
  dropout_param {
    dropout_ratio: 0.5
  }
}

# ----- 2nd fc group -----
layer {
  name: "fc7"
  type: "InnerProduct"
  bottom: "fc6"
  top: "fc7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 2048
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "fc7"
  top: "fc7"
}
layer {
  name: "drop7"
  type: "Dropout"
  bottom: "fc7"
  top: "fc7"
  dropout_param {
    dropout_ratio: 0.5
  }
}

# ----- 3rd fc group -----
layer {
  name: "fc8"
  type: "InnerProduct"
  bottom: "fc7"
  top: "fc8"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 101
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "prob"
  type: "Softmax"
  bottom: "fc8"
  top: "prob"
}