code: def test_flatten(self):
      class MyModule(Module):
          def forward(self, x):
              return torch.flatten(x)
  
      module = MyModule()
  
      ops_0d = [{"op_name": "Constant"}, {"op_name": "Reshape"}]
      ops_1d = [{"op_name": "Identity"}]
      for shape in ([], [3]):
          x = torch.randn(shape)
          for opset_version in [9, 10]:
              ops = {
                  opset_version: (ops_0d if len(shape) == 0 else ops_1d)
              }
              check_onnx_opsets_operator(
                  module, x, ops, opset_versions=[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 12 for calling the TestONNXOpset obj's underlying member method code with example usage: obj.test_flatten() and returns: torch