9c62f4f3d7c6b98f311ef82863281b088ce4d48a,onnx_tf/handlers/backend/clip.py,Clip,args_check,#Any#Any#,16

Before Change

    x = kwargs["tensor_dict"][node.inputs[0]]
    // uint64 cannot upcast to any tensorflow supported datatype
    // for tf.clip_by_value that didn"t lose precision
    if x.dtype == tf.uint64:
      exception.OP_UNSUPPORTED_EXCEPT(
          "Clip input, min and max in " + str(x.dtype) + " datatype",
          "Tensorflow")

  @classmethod
  def _common(cls, node, **kwargs):
    tensor_dict = kwargs["tensor_dict"]
    x = tensor_dict[node.inputs[0]]

After Change

    // throw an error if the data type is not natively supported by
    // Tensorflow, cannot be safely cast, and auto-cast option is False
    if x.dtype in cls.cast_map and cls.cast_map[x.dtype] is None:
      exception.DTYPE_NOT_CAST_EXCEPT(
          "Clip input " + node.inputs[0] + " with data type "" +
          data_type.tf_to_np_str(x.dtype) + """,
          data_type.tf_to_np_str_list(cls.supported_types))

  @classmethod
  def _common(cls, node, **kwargs):
    tensor_dict = kwargs["tensor_dict"]
    x = tensor_dict[node.inputs[0]]

Instances