code: def __enter__(self):
      self._previous_log_level = self.logger.level
      # Adjust the logger level based on `options.verbosity_level` and the environment
      # variable `TORCH_LOGS`. See [NOTE: `dynamo_export` diagnostics logging] for details.
      if not is_onnx_diagnostics_log_artifact_enabled():
          return super().__enter__()
      else:
          return self
  
imports: from __future__ import annotations
  import dataclasses
  import functools
  import logging
  from typing import Any, Optional
  import onnxscript
  from onnxscript.function_libs.torch_lib import graph_building
  import torch
  import torch.fx
  from torch.onnx._internal import diagnostics
  from torch.onnx._internal.diagnostics import infra
  from torch.onnx._internal.diagnostics.infra import decorator, formatter
  from torch.onnx._internal.fx import registration, type_utils
label_desc: Use image node_id 1 for calling the DiagnosticContext obj's underlying member method code with example usage: obj.__enter__() and returns: super, self