class_docstr: Context manager to register PyTree extension.
class_docstr_tok: ["Context","manager","to","register","PyTree","extension","."]
code: def _register_huggingface_model_output_extension(self):
      try:
          from transformers import modeling_outputs  # type: ignore[import]
      except ImportError as e:
          return
  
      @_beartype.beartype
      def model_output_flatten(
          output: modeling_outputs.ModelOutput,
      ) -> Tuple[List[Any], pytree.Context]:
          return list(output.values()), (
              type(output),
              list(output.keys()),
          )
  
      @_beartype.beartype
      def model_output_unflatten(
          values: List[Any], context: pytree.Context
      ) -> modeling_outputs.ModelOutput:
          output_type, keys = context
          return output_type(**dict(zip(keys, values)))
  
      # All 'ModelOutput' subclasses are defined under module 'modeling_outputs'.
      named_model_output_classes = inspect.getmembers(
          modeling_outputs,
          lambda x: (
              inspect.isclass(x)
              and issubclass(x, modeling_outputs.ModelOutput)
              and x is not modeling_outputs.ModelOutput
          ),
      )
  
      for _, class_type in named_model_output_classes:
          self.register_pytree_node(
              class_type, model_output_flatten, model_output_unflatten
          )
  
imports: from __future__ import annotations
  import contextlib
  import functools
  import inspect
  from typing import Any, Callable, Dict, List, Mapping, Optional, Sequence, Tuple, Type, Union
  import torch._dynamo
  import torch.export
  import torch.fx
  import torch.onnx
  from torch.onnx._internal import _beartype, exporter, io_adapter
  from torch.utils import _pytree
label_desc: Use image node_id 5 for calling the _PyTreeExtensionContext obj's underlying member method code with example usage: obj._register_huggingface_model_output_extension() and returns: list,  type,  list, output_type