code: def begin_capture(self, inputs: List[torch.Tensor], sizes: List[int]):
      counters["compiled_autograd"]["captures"] += 1
      self.fx_tracer.root = torch.nn.Module()
      self.fx_tracer.graph = torch.fx.Graph(tracer_cls=PythonKeyTracer)
      self.fx_tracer.tensor_attrs = {}
      args_proxy = self.fx_tracer.create_proxy(
          "placeholder", "inputs", (), {}
      )
      sizes_proxy = self.fx_tracer.create_proxy(
          "placeholder", "sizes", (), {}
      )
      self.hooks_proxy = self.fx_tracer.create_proxy(
          "placeholder", "hooks", (), {}
      )
  
      # tensor inputs to fake tensors
      inputs = [
          self.wrap_fake(x, self.source("inputs", idx))
          for idx, x in enumerate(inputs)
      ]
      proxies = [args_proxy[i] for i in range(len(inputs))]
      self.bind_tensors_to_proxies(inputs, proxies)
  
      # size inputs to symints
      sizes = [
          self.shape_env.create_unspecified_symint_and_symbol(
              val,
              self.source("sizes", idx),
              DimDynamic.DYNAMIC,
          )
          for idx, val in enumerate(sizes)
      ]
      self.bind_tensors_to_proxies(sizes, sizes_proxy)
  
      # TODO(jansel): are all these modes needed?
      self.stack.enter_context(decompose({}))
      self.stack.enter_context(self.fake_tensor_mode)
      self.stack.enter_context(self.proxy_mode.sym_mode)
      self.stack.enter_context(self.proxy_mode)
      self.stack.enter_context(disable_autocast_cache())
      self.stack.enter_context(
          disable_proxy_modes_tracing(enable_current=True)
      )
      return inputs, sizes
  
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 4 for calling the AutogradCompilerInstance obj's underlying member method code with example usage: obj.begin_capture(inputs, sizes) and returns: inputs,  sizes