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  name: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/Conv2D"
  op: "Conv2D"
  input: "InceptionResnetV1/Repeat_2/block8_5/Relu"
  input: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/weights"
  attr {
    key: "dilations"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
  attr {
    key: "explicit_paddings"
    value {
      list {
      }
    }
  }
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/BatchNorm/cond/FusedBatchNorm_1"
  op: "BiasAdd"
  input: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/Conv2D"
  input: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/Conv2D_bn_offset"
}
node {
  name: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/Relu"
  op: "Relu"
  input: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/BatchNorm/cond/FusedBatchNorm_1"
}
node {
  name: "InceptionResnetV1/Block8/concat"
  op: "ConcatV2"
  input: "InceptionResnetV1/Block8/Branch_0/Conv2d_1x1/Relu"
  input: "InceptionResnetV1/Block8/Branch_1/Conv2d_0c_3x1/Relu"
  input: "InceptionResnetV1/Block8/concat/axis"
}
node {
  name: "InceptionResnetV1/Block8/Conv2d_1x1/Conv2D"
  op: "Conv2D"
  input: "InceptionResnetV1/Block8/concat"
  input: "InceptionResnetV1/Block8/Conv2d_1x1/weights"
  attr {
    key: "dilations"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
  attr {
    key: "explicit_paddings"
    value {
      list {
      }
    }
  }
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "InceptionResnetV1/Block8/Conv2d_1x1/BiasAdd"
  op: "BiasAdd"
  input: "InceptionResnetV1/Block8/Conv2d_1x1/Conv2D"
  input: "InceptionResnetV1/Block8/Conv2d_1x1/biases"
}
node {
  name: "InceptionResnetV1/Block8/mul"
  op: "Mul"
  input: "InceptionResnetV1/Block8/mul/x"
  input: "InceptionResnetV1/Block8/Conv2d_1x1/BiasAdd"
}
node {
  name: "InceptionResnetV1/Block8/add"
  op: "Add"
  input: "InceptionResnetV1/Repeat_2/block8_5/Relu"
  input: "InceptionResnetV1/Block8/mul"
}
node {
  name: "InceptionResnetV1/Logits/AvgPool_1a_8x8/AvgPool"
  op: "AvgPool"
  input: "InceptionResnetV1/Block8/add"
  attr {
    key: "ksize"
    value {
      list {
        i: 1
        i: 3
        i: 3
        i: 1
      }
    }
  }
  attr {
    key: "padding"
    value {
      s: "VALID"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "InceptionResnetV1/Logits/Flatten/flatten/Reshape"
  op: "Reshape"
  input: "InceptionResnetV1/Logits/AvgPool_1a_8x8/AvgPool"
  input: "InceptionResnetV1/Logits/Flatten/flatten/Reshape/shape/_1__cf__3"
}
node {
  name: "InceptionResnetV1/Bottleneck/MatMul"
  op: "MatMul"
  input: "InceptionResnetV1/Logits/Flatten/flatten/Reshape"
  input: "InceptionResnetV1/Bottleneck/weights"
  attr {
    key: "transpose_a"
    value {
      b: false
    }
  }
  attr {
    key: "transpose_b"
    value {
      b: false
    }
  }
}
node {
  name: "InceptionResnetV1/Bottleneck/BatchNorm/Reshape"
  op: "Reshape"
  input: "InceptionResnetV1/Bottleneck/MatMul"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/Reshape/shape"
}
node {
  name: "InceptionResnetV1/Bottleneck/BatchNorm/cond/FusedBatchNorm_1"
  op: "FusedBatchNorm"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/Reshape"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/Const"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/beta"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/moving_mean"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/moving_variance"
  attr {
    key: "epsilon"
    value {
      f: 0.0010000000474974513
    }
  }
}
node {
  name: "InceptionResnetV1/Bottleneck/BatchNorm/Reshape_1"
  op: "Reshape"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/cond/FusedBatchNorm_1"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/Shape/_0__cf__2"
}
node {
  name: "embeddings/Square"
  op: "Square"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/Reshape_1"
}
node {
  name: "embeddings/Sum"
  op: "Sum"
  input: "embeddings/Square"
  input: "embeddings/Sum/reduction_indices"
  attr {
    key: "keep_dims"
    value {
      b: true
    }
  }
}
node {
  name: "embeddings/Maximum"
  op: "Maximum"
  input: "embeddings/Sum"
  input: "embeddings/Maximum/y"
}
node {
  name: "embeddings/Rsqrt"
  op: "Rsqrt"
  input: "embeddings/Maximum"
}
node {
  name: "embeddings"
  op: "Mul"
  input: "InceptionResnetV1/Bottleneck/BatchNorm/Reshape_1"
  input: "embeddings/Rsqrt"
}
library {
}