node {
  name: "image_tensor"
  op: "Placeholder"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/convolution"
  op: "Conv2D"
  input: "image_tensor"
  input: "FeatureExtractor/MobilenetV1/Conv2d_0/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_0/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_0/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_0/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_0/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_1_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_2_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_3_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_4_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_5_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_6_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_7_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_8_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_9_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_10_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_11_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_12_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/depthwise"
  op: "DepthwiseConv2dNative"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_depthwise/depthwise_weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/depthwise"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_depthwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_depthwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_depthwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_depthwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm"
}
node {
  name: "BoxPredictor_1/BoxEncodingPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/Relu6"
  input: "BoxPredictor_1/BoxEncodingPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_1/BoxEncodingPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_1/BoxEncodingPredictor/convolution"
  input: "BoxPredictor_1/BoxEncodingPredictor/biases"
}
node {
  name: "BoxPredictor_1/ClassPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/Relu6"
  input: "BoxPredictor_1/ClassPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_1/ClassPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_1/ClassPredictor/convolution"
  input: "BoxPredictor_1/ClassPredictor/biases"
}
node {
  name: "BoxPredictor_0/BoxEncodingPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/Relu6"
  input: "BoxPredictor_0/BoxEncodingPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_0/BoxEncodingPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_0/BoxEncodingPredictor/convolution"
  input: "BoxPredictor_0/BoxEncodingPredictor/biases"
}
node {
  name: "BoxPredictor_0/ClassPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/Relu6"
  input: "BoxPredictor_0/ClassPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_0/ClassPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_0/ClassPredictor/convolution"
  input: "BoxPredictor_0/ClassPredictor/biases"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm"
}
node {
  name: "BoxPredictor_2/BoxEncodingPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6"
  input: "BoxPredictor_2/BoxEncodingPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_2/BoxEncodingPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_2/BoxEncodingPredictor/convolution"
  input: "BoxPredictor_2/BoxEncodingPredictor/biases"
}
node {
  name: "BoxPredictor_2/ClassPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6"
  input: "BoxPredictor_2/ClassPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_2/ClassPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_2/ClassPredictor/convolution"
  input: "BoxPredictor_2/ClassPredictor/biases"
}
node {
  name: "paddings"
  op: "Const"
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
          dim {
            size: 4
          }
          dim {
            size: 2
          }
        }
        int_val: 0
        int_val: 0
        int_val: 0
        int_val: 1
        int_val: 0
        int_val: 1
        int_val: 0
        int_val: 0
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6/padding"
  op: "Pad"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6"
  input: "paddings"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6/padding"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm"
}
node {
  name: "BoxPredictor_3/BoxEncodingPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
  input: "BoxPredictor_3/BoxEncodingPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_3/BoxEncodingPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_3/BoxEncodingPredictor/convolution"
  input: "BoxPredictor_3/BoxEncodingPredictor/biases"
}
node {
  name: "BoxPredictor_3/ClassPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
  input: "BoxPredictor_3/ClassPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_3/ClassPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_3/ClassPredictor/convolution"
  input: "BoxPredictor_3/ClassPredictor/biases"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6/padding"
  op: "Pad"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6"
  input: "paddings"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6/padding"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm"
}
node {
  name: "BoxPredictor_4/BoxEncodingPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
  input: "BoxPredictor_4/BoxEncodingPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_4/BoxEncodingPredictor/convolution"
  input: "BoxPredictor_4/BoxEncodingPredictor/biases"
}
node {
  name: "BoxPredictor_4/ClassPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
  input: "BoxPredictor_4/ClassPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_4/ClassPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_4/ClassPredictor/convolution"
  input: "BoxPredictor_4/ClassPredictor/biases"
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm"
  op: "FusedBatchNorm"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/convolution"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/gamma"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/beta"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/moving_mean"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/moving_variance"
  attr { key: "epsilon" value { f: 0.001 } }
}
node {
  name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
  op: "Relu6"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm"
}
node {
  name: "BoxPredictor_5/BoxEncodingPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
  input: "BoxPredictor_5/BoxEncodingPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_5/BoxEncodingPredictor/convolution"
  input: "BoxPredictor_5/BoxEncodingPredictor/biases"
}
node {
  name: "BoxPredictor_5/ClassPredictor/convolution"
  op: "Conv2D"
  input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
  input: "BoxPredictor_5/ClassPredictor/weights"
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "BoxPredictor_5/ClassPredictor/BiasAdd"
  op: "BiasAdd"
  input: "BoxPredictor_5/ClassPredictor/convolution"
  input: "BoxPredictor_5/ClassPredictor/biases"
}
### Locations ##################################################################
node {
  name: "BoxPredictor_0/Flatten"
  op: "Flatten"
  input: "BoxPredictor_0/BoxEncodingPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_1/Flatten"
  op: "Flatten"
  input: "BoxPredictor_1/BoxEncodingPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_2/Flatten"
  op: "Flatten"
  input: "BoxPredictor_2/BoxEncodingPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_3/Flatten"
  op: "Flatten"
  input: "BoxPredictor_3/BoxEncodingPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_4/Flatten"
  op: "Flatten"
  input: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_5/Flatten"
  op: "Flatten"
  input: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd"
}
node {
  name: "concat/axis_flatten"
  op: "Const"
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: -1
      }
    }
  }
}
node {
  name: "concat"
  op: "ConcatV2"
  input: "BoxPredictor_0/Flatten"
  input: "BoxPredictor_1/Flatten"
  input: "BoxPredictor_2/Flatten"
  input: "BoxPredictor_3/Flatten"
  input: "BoxPredictor_4/Flatten"
  input: "BoxPredictor_5/Flatten"
  input: "concat/axis_flatten"
}
### Classifications ############################################################
node {
  name: "BoxPredictor_0/Flatten_1"
  op: "Flatten"
  input: "BoxPredictor_0/ClassPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_1/Flatten_1"
  op: "Flatten"
  input: "BoxPredictor_1/ClassPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_2/Flatten_1"
  op: "Flatten"
  input: "BoxPredictor_2/ClassPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_3/Flatten_1"
  op: "Flatten"
  input: "BoxPredictor_3/ClassPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_4/Flatten_1"
  op: "Flatten"
  input: "BoxPredictor_4/ClassPredictor/BiasAdd"
}
node {
  name: "BoxPredictor_5/Flatten_1"
  op: "Flatten"
  input: "BoxPredictor_5/ClassPredictor/BiasAdd"
}
node {
  name: "concat_1"
  op: "ConcatV2"
  input: "BoxPredictor_0/Flatten_1"
  input: "BoxPredictor_1/Flatten_1"
  input: "BoxPredictor_2/Flatten_1"
  input: "BoxPredictor_3/Flatten_1"
  input: "BoxPredictor_4/Flatten_1"
  input: "BoxPredictor_5/Flatten_1"
  input: "concat/axis_flatten"
}
################################################################################
node {
  name: "PriorBox"
  op: "PriorBox"
  input: "BoxPredictor_0/BoxEncodingPredictor/BiasAdd"
  input: "image_tensor"
  attr { key: "min_size" value { i: 60 } }
  attr { key: "flip" value { b: true } }
  attr { key: "clip" value { b: false } }
  attr {
    key: "aspect_ratio"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 1
          }
        }
        float_val: 2.0
      }
    }
  }
  attr {
    key: "scales"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 3
          }
        }
        float_val: 0.5
        float_val: 1.0
        float_val: 1.0
      }
    }
  }
  attr {
    key: "variance"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 4
          }
        }
        float_val: 0.1
        float_val: 0.1
        float_val: 0.2
        float_val: 0.2
      }
    }
  }
}
node {
  name: "PriorBox_1"
  op: "PriorBox"
  input: "BoxPredictor_1/BoxEncodingPredictor/BiasAdd"
  input: "image_tensor"
  attr { key: "min_size" value { i: 105 } }
  attr { key: "max_size" value { i: 150 } }
  attr { key: "flip" value { b: true } }
  attr { key: "clip" value { b: false } }
  attr {
    key: "aspect_ratio"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 2
          }
        }
        float_val: 2.0
        float_val: 3.0
      }
    }
  }
  attr {
    key: "variance"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 4
          }
        }
        float_val: 0.1
        float_val: 0.1
        float_val: 0.2
        float_val: 0.2
      }
    }
  }
}
node {
  name: "PriorBox_2"
  op: "PriorBox"
  input: "BoxPredictor_2/BoxEncodingPredictor/BiasAdd"
  input: "image_tensor"
  attr { key: "min_size" value { i: 150 } }
  attr { key: "max_size" value { i: 195 } }
  attr { key: "flip" value { b: true } }
  attr { key: "clip" value { b: false } }
  attr {
    key: "aspect_ratio"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 2
          }
        }
        float_val: 2.0
        float_val: 3.0
      }
    }
  }
  attr {
    key: "variance"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 4
          }
        }
        float_val: 0.1
        float_val: 0.1
        float_val: 0.2
        float_val: 0.2
      }
    }
  }
}
node {
  name: "PriorBox_3"
  op: "PriorBox"
  input: "BoxPredictor_3/BoxEncodingPredictor/BiasAdd"
  input: "image_tensor"
  attr { key: "min_size" value { i: 195 } }
  attr { key: "max_size" value { i: 240 } }
  attr { key: "flip" value { b: true } }
  attr { key: "clip" value { b: false } }
  attr {
    key: "aspect_ratio"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 2
          }
        }
        float_val: 2.0
        float_val: 3.0
      }
    }
  }
  attr {
    key: "variance"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 4
          }
        }
        float_val: 0.1
        float_val: 0.1
        float_val: 0.2
        float_val: 0.2
      }
    }
  }
}
node {
  name: "PriorBox_4"
  op: "PriorBox"
  input: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd"
  input: "image_tensor"
  attr { key: "min_size" value { i: 240 } }
  attr { key: "max_size" value { i: 285 } }
  attr { key: "flip" value { b: true } }
  attr { key: "clip" value { b: false } }
  attr {
    key: "aspect_ratio"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 2
          }
        }
        float_val: 2.0
        float_val: 3.0
      }
    }
  }
  attr {
    key: "variance"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 4
          }
        }
        float_val: 0.1
        float_val: 0.1
        float_val: 0.2
        float_val: 0.2
      }
    }
  }
}
node {
  name: "PriorBox_5"
  op: "PriorBox"
  input: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd"
  input: "image_tensor"
  attr { key: "min_size" value { i: 285 } }
  attr { key: "max_size" value { i: 300 } }
  attr { key: "flip" value { b: true } }
  attr { key: "clip" value { b: false } }
  attr {
    key: "aspect_ratio"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 2
          }
        }
        float_val: 2.0
        float_val: 3.0
      }
    }
  }
  attr {
    key: "variance"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 4
          }
        }
        float_val: 0.1
        float_val: 0.1
        float_val: 0.2
        float_val: 0.2
      }
    }
  }
}
node {
  name: "concat_2"
  op: "ConcatV2"
  input: "PriorBox"
  input: "PriorBox_1"
  input: "PriorBox_2"
  input: "PriorBox_3"
  input: "PriorBox_4"
  input: "PriorBox_5"
  input: "concat/axis_flatten"
}
################################################################################
node {
  name: "concat_1_sigmoid"
  op: "Sigmoid"
  input: "concat_1"
}
node {
  name: "detection_out"
  op: "DetectionOutput"
  input: "concat"
  input: "concat_1_sigmoid"
  input: "concat_2"
  attr { key: "num_classes" value { i: 1 } }
  attr { key: "share_location" value { b: true } }
  attr { key: "background_label_id" value { i: 0 } }
  attr { key: "nms_threshold" value { f: 0.6 } }
  attr { key: "top_k" value { i: 100 } }
  attr { key: "code_type" value { s: "CENTER_SIZE" } }
  attr { key: "keep_top_k" value { i: 100 } }
  attr { key: "confidence_threshold" value { f: 0.01 } }
  attr { key: "loc_pred_transposed" value { b: true } }
}
