class_docstr: Base class for TF callables like those created by tf.function.
  
  Note: Callables are conceptually very similar to `tf.Operation`: a
  `tf.Operation` is a kind of callable.
docstr: Executes this callable.
  
  This behaves like a regular op - in eager mode, it immediately starts
  execution, returning results. In graph mode, it creates ops which return
  symbolic TensorFlow values (like `tf.Tensor`, `tf.data.Dataset`,
  etc.). For example, `tf.function` callables typically generate a
  `tf.raw_ops.PartitionedCall` op, but not always - the
  exact operations being generated are an internal implementation detail.
  
  Args:
    *args: positional argument for this call
    **kwargs: keyword arguments for this call
  Returns:
    The execution results.
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code: def __call__(self, *args, **kwargs):
      """Executes this callable.
  
      This behaves like a regular op - in eager mode, it immediately starts
      execution, returning results. In graph mode, it creates ops which return
      symbolic TensorFlow values (like `tf.Tensor`, `tf.data.Dataset`,
      etc.). For example, `tf.function` callables typically generate a
      `tf.raw_ops.PartitionedCall` op, but not always - the
      exact operations being generated are an internal implementation detail.
  
      Args:
        *args: positional argument for this call
        **kwargs: keyword arguments for this call
      Returns:
        The execution results.
      """
  
imports: import abc
  import inspect
  import sys
  import textwrap
  from typing import Union
  import numpy
  from tensorflow.python.types import doc_typealias
  from tensorflow.python import pywrap_tensorflow
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the Callable obj's underlying member method code with example usage: obj.__call__() without return types