class_docstr: A wrapper for a function owned by an EagerPyFunc.
class_docstr_tok: ["A","wrapper","for","a","function","owned","by","an","EagerPyFunc","."]
docstr: Indicates the object shall support gradient ops.
  
  This function is internally used by _EagerPyFuncGrad to support
  graph mode gradient of EagerFunc via tf.gradient().
code: def set_support_graph_mode_gradient(self):
      """Indicates the object shall support gradient ops.
  
      This function is internally used by _EagerPyFuncGrad to support
      graph mode gradient of EagerFunc via tf.gradient().
      """
      self._support_graph_mode_gradient = True
  
imports: import functools
  import threading
  import traceback
  import weakref
  import numpy
  from tensorflow.python.autograph.impl import api
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import backprop_util
  from tensorflow.python.eager import context
  from tensorflow.python.eager import record
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import function
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import type_spec
  from tensorflow.python.lib.core import _pywrap_py_func
  from tensorflow.python.ops import autograph_ops
  from tensorflow.python.ops import gen_script_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import dispatch
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_inspect
  from tensorflow.python.util import variable_utils
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the EagerFunc obj's underlying member method code with example usage: obj.set_support_graph_mode_gradient() without return types