Method create_op

tensorflow/python/framework/ops.py:3308–3361

Creates an `Operation` in this graph. This is a low-level interface for creating an `Operation`. Most programs will not call this method directly, and instead use the Python op constructors, such as `tf.constant()`, which add ops to the default graph. Args: op_type: The `

(
      self,
      op_type,
      inputs,
      dtypes=None,  # pylint: disable=redefined-outer-name
      input_types=None,
      name=None,
      attrs=None,
      op_def=None,
      compute_shapes=True,
      compute_device=True)

                   "Shapes are always computed; don't use the compute_shapes "
                   "as it has no effect.", "compute_shapes")
  def create_op(
      self,
      op_type,
      inputs,
      dtypes=None,  # pylint: disable=redefined-outer-name
      input_types=None,
      name=None,
      attrs=None,
      op_def=None,
      compute_shapes=True,
      compute_device=True):
    """Creates an `Operation` in this graph.

    This is a low-level interface for creating an `Operation`. Most
    programs will not call this method directly, and instead use the
    Python op constructors, such as `tf.constant()`, which add ops to
    the default graph.

    Args:
      op_type: The `Operation` type to create. This corresponds to the
        `OpDef.name` field for the proto that defines the operation.
      inputs: A list of `Tensor` objects that will be inputs to the `Operation`.
      dtypes: (Optional) A list of `DType` objects that will be the types of the
        tensors that the operation produces.
      input_types: (Optional.) A list of `DType`s that will be the types of the
        tensors that the operation consumes. By default, uses the base `DType`
        of each input in `inputs`. Operations that expect reference-typed inputs
        must specify `input_types` explicitly.
      name: (Optional.) A string name for the operation. If not specified, a
        name is generated based on `op_type`.
      attrs: (Optional.) A dictionary where the key is the attribute name (a
        string) and the value is the respective `attr` attribute of the
        `NodeDef` proto that will represent the operation (an `AttrValue`
        proto).
      op_def: (Optional.) The `OpDef` proto that describes the `op_type` that
        the operation will have.
      compute_shapes: (Optional.) Deprecated. Has no effect (shapes are always
        computed).
      compute_device: (Optional.) If True, device functions will be executed to
        compute the device property of the Operation.

    Raises:
      TypeError: if any of the inputs is not a `Tensor`.
      ValueError: if colocation conflicts with existing device assignment.

    Returns:
      An `Operation` object.
    """
    del compute_shapes
    for idx, a in enumerate(inputs):
      if not isinstance(a, Tensor):
        raise TypeError("Input #%d is not a tensor: %s" % (idx, a))
    return self._create_op_internal(op_type, inputs, dtypes, input_types, name,
                                    attrs, op_def, compute_device)

  def _create_op_internal(
      self,