code: def check_onnx_opsets_operator(
      module,
      x,
      ops,
      opset_versions,
      training=torch.onnx.TrainingMode.EVAL,
      input_names=None,
      dynamic_axes=None,
  ):
      for opset_version in opset_versions:
          f = io.BytesIO()
          torch.onnx.export(
              module,
              x,
              f,
              opset_version=opset_version,
              training=training,
              input_names=input_names,
              dynamic_axes=dynamic_axes,
          )
          model = onnx.load(io.BytesIO(f.getvalue()))
          check_onnx_opset_operator(
              model, ops[opset_version], opset_version
          )
  
imports: import io
  import itertools
  import onnx
  import pytorch_test_common
  import torch
  import torch.onnx
  from torch.nn import Module
  from torch.onnx import producer_name, producer_version
  from torch.onnx._globals import GLOBALS
  from torch.testing._internal import common_utils
label_desc: Use image node_id 2 for calling a global function with example usage: check_onnx_opsets_operator(module, x, ops, opset_versions, training, input_names, dynamic_axes) without return types