def add_inputs(self, *args):
    "Add a sequence of inputs to the function invocation.\n\n    Args:\n      *args: List of inputs to be converted (should be Tf.Tensor).\n    Returns:\n      Wrapped inputs (identity standins that have additional metadata). These\n      are also are also tf.Tensor's.\n    "

    def augmented_identity(arg):
        identity_op = _array_ops.identity(arg)
        identity_op.op._set_attr(OpHint.FUNCTION_NAME_ATTR, _attr_value_pb2.AttrValue(s=self._function_name))
        identity_op.op._set_attr(OpHint.FUNCTION_UUID_ATTR, _attr_value_pb2.AttrValue(s=self._unique_function_id))
        identity_op.op._set_attr(OpHint.FUNCTION_INPUT_INDEX_ATTR, _attr_value_pb2.AttrValue(i=self._curr_input_index))
        self._curr_input_index += 1
        return identity_op
    return [augmented_identity(arg) for arg in args]
Add a sequence of inputs to the function invocation.

Args:
  *args: List of inputs to be converted (should be Tf.Tensor).
Returns:
  Wrapped inputs (identity standins that have additional metadata). These
  are also are also tf.Tensor's.
def add_inputs(self, *args):
    "Add a sequence of inputs to the function invocation.\n\n    Args:\n      *args: List of inputs to be converted (should be Tf.Tensor).\n    Returns:\n      Wrapped inputs (identity standins that have additional metadata). These\n      are also are also tf.Tensor's.\n    "

    def augmented_identity(arg):
        identity_op = _array_ops.identity(arg)
        identity_op.op._set_attr(OpHint.FUNCTION_NAME_ATTR, _attr_value_pb2.AttrValue(s=self._function_name))
        identity_op.op._set_attr(OpHint.FUNCTION_UUID_ATTR, _attr_value_pb2.AttrValue(s=self._unique_function_id))
        identity_op.op._set_attr(OpHint.FUNCTION_INPUT_INDEX_ATTR, _attr_value_pb2.AttrValue(i=self._curr_input_index))
        self._curr_input_index += 1
        return identity_op
    return [augmented_identity(arg) for arg in args]