class_docstr: Wraps a tf V1 piece of code in a function.
class_docstr_tok: ["Wraps","a","tf","V1","piece","of","code","in","a","function","."]
code: def __init__(
      self, fn_graph, variable_holder, attrs=None, signature=None
  ):
      self._variable_holder = variable_holder
      _lift_unlifted_variables(fn_graph, variable_holder)
      # We call __init__ after lifting variables so that the function's signature
      # properly reflects the new captured inputs.
      for f in fn_graph.as_graph_def(
          use_pybind11_proto=True
      ).library.function:
          context.context().add_function_def(f)
      self._signature = signature
      function_type = function_type_lib.from_structured_signature(
          fn_graph.structured_input_signature,
          fn_graph.structured_outputs,
          fn_graph.function_captures.capture_types,
      )
      atomic_fn = atomic_function.from_func_graph(
          function._inference_name(fn_graph.name),
          fn_graph,
          attrs,
          function_type,
      )
      super().__init__(atomic_fn)
  
imports: import weakref
  from tensorflow.core.function.polymorphism import function_type
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.core.protobuf import struct_pb2
  from tensorflow.python.eager import context
  from tensorflow.python.eager import function
  from tensorflow.python.eager import lift_to_graph
  from tensorflow.python.eager.polymorphic_function import atomic_function
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import importer
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.trackable import data_structures
  from tensorflow.python.util import nest
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 to create a new WrappedFunction object from inherited base classes: function with example: obj = WrappedFunction(fn_graph, variable_holder, attrs, signature)