class_docstr: Wrapper class for a function that has been restored from saved state.
  
  See `def_function.Function`.
class_docstr_tok: ["Wrapper","class","for","a","function","that","has","been","restored","from","saved","state",".","See","`","def_function.Function","`","."]
code: def __init__(
      self, python_function, name, function_spec, concrete_functions
  ):
      # TODO(b/205016819): We may enable autograph once exceptions are supported.
      super(RestoredFunction, self).__init__(
          python_function,
          name,
          autograph=False,
          jit_compile=function_spec.jit_compile,
      )
      self.concrete_functions = concrete_functions
      self._function_type = function_spec.function_type
      self._default_values = function_spec.default_values
  
      # Prevent RestoredFunction from spamming users with frequent tracing
      # warnings.
      self._omit_frequent_tracing_warning = True
  
imports: import collections
  import pprint
  import re
  from absl import logging
  from tensorflow.core.function import trace_type
  from tensorflow.core.function.polymorphism import function_type
  from tensorflow.core.protobuf import saved_object_graph_pb2
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import function
  from tensorflow.python.eager.polymorphic_function import function_type_utils
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import function_def_to_graph
  from tensorflow.python.framework import op_def_registry
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import type_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import default_gradient
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.util import compat
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_decorator
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 1 to create a new RestoredFunction object from inherited base classes: def_function with example: obj = RestoredFunction(python_function, name, function_spec, concrete_functions)