class_docstr: Interpreter-based pass class to help users maintain the IR spec while writing
  transformations.
code: def call(self, graph_module: fx.GraphModule) -> PassResult:
      if not getattr(self, "_initialized", False):
          raise ExportPassBaseError(
              "ExportPass is not initialized with __init__().",
          )
  
      inputs = self.inputs(graph_module)
  
      fake_tensor_mode = None
      for i in inputs:
          if isinstance(i, FakeTensor):
              assert (
                  fake_tensor_mode is None
                  or fake_tensor_mode is i.fake_mode
              ), "Multiple fake tensor mode detected."
              fake_tensor_mode = i.fake_mode
      if fake_tensor_mode is None:
          self.tracer.fake_tensor_mode = FakeTensorMode(
              allow_non_fake_inputs=True
          )
          fake_tensor_mode = nullcontext()  # type: ignore[assignment]
          dispatcher_mode = nullcontext()  # type: ignore[assignment]
      else:
          fake_tensor_mode.allow_non_fake_inputs = True
          self.tracer.fake_tensor_mode = fake_tensor_mode
          dispatcher_mode = enable_python_dispatcher()  # type: ignore[assignment]
      self.fake_tensor_mode = self.tracer.fake_tensor_mode
  
      with fake_tensor_mode, dispatcher_mode:  # type: ignore[assignment, union-attr]
          result = self.call_submodule(graph_module, tuple(inputs))
  
      return result
  
imports: import operator
  import traceback
  import typing
  from contextlib import nullcontext
  from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
  import torch
  from functorch.experimental.control_flow import _unstack_pytree
  from torch import fx
  from torch._dispatch.python import enable_python_dispatcher
  from torch._export.pass_infra.node_metadata import NodeMetadata
  from torch._export.pass_infra.proxy_value import ProxyValue
  from torch._subclasses import FakeTensor, UnsupportedFakeTensorException
  from torch._subclasses.fake_tensor import FakeTensorMode
  from torch.fx import traceback
  from torch.fx.experimental.proxy_tensor import PythonKeyTracer
  from torch.fx.graph import CodeGen
  from torch.fx.passes.infra.pass_base import PassBase, PassResult
  from torch.fx.passes.shape_prop import _extract_tensor_metadata, TensorMetadata
  from torch.utils import _pytree
label_desc: Use image node_id 14 for calling the _ExportPassBaseDeprecatedDoNotUse obj's underlying member method code with example usage: obj.call(graph_module) and returns: result