testdata/dnn/ssd_mobilenet_v1_coco.pbtxt

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  }
}
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"
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    key: "padding"
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  }
  attr {
    key: "strides"
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        i: 2
        i: 2
        i: 1
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    }
  }
}
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"
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  attr {
    key: "strides"
    value {
      list {
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        i: 1
        i: 1
        i: 1
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    }
  }
}
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 {
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        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
  attr { key: "loc_pred_transposed" value { b: true } }
}
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
          }
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        int_val: 0
        int_val: 0
        int_val: 0
        int_val: 1
        int_val: 0
        int_val: 1
        int_val: 0
        int_val: 0
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    }
  }
}
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
      }
    }
  }
  attr { key: "loc_pred_transposed" value { b: true } }
}
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
      }
    }
  }
  attr { key: "loc_pred_transposed" value { b: true } }
}
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
      }
    }
  }
  attr { key: "loc_pred_transposed" value { b: true } }
}
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"
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