code: def __init__(self, compiler_fn) -> None:
      self.compiler_fn = compiler_fn
      self.stack = contextlib.ExitStack()
      self.close = self.stack.close
      self.shape_env = ShapeEnv()
      self.fake_tensor_mode = FakeTensorMode(
          allow_fallback_kernels=True,
          allow_non_fake_inputs=True,
          shape_env=self.shape_env,
      )
      self.fx_tracer = PythonKeyTracer()
      self.proxy_mode = ProxyTorchDispatchMode(
          self.fx_tracer, "symbolic"
      )
      self.hooks_proxy: Optional[Proxy] = None
  
imports: import contextlib
  import functools
  from typing import List, Optional
  import torch
  from torch._dynamo.external_utils import call_backward, call_hook
  from torch._dynamo.source import GetItemSource, LocalSource
  from torch._dynamo.utils import counters, lazy_format_graph_code
  from torch._logging import getArtifactLogger
  from torch._prims_common import clone_preserve_strides
  from torch._subclasses import FakeTensorMode
  from torch.fx import GraphModule
  from torch.fx.experimental.proxy_tensor import decompose, disable_autocast_cache, disable_proxy_modes_tracing, fetch_tensor_proxy, ProxyTorchDispatchMode, PythonKeyTracer, track_tensor_tree
  from torch.fx.experimental.symbolic_shapes import DimDynamic, ShapeEnv
  from torch.fx.proxy import Proxy
label_desc: Use image node_id 1 to create a new AutogradCompilerInstance object  with example: obj = AutogradCompilerInstance(compiler_fn)