code: def test_max(self, input_shape, dim, keepdim, backend):
      class TestMax(nn.Module):
          def __init__(self):
              super(TestMax, self).__init__()
  
          def forward(self, x):
              return torch.max(x, dim=dim, keepdim=keepdim)
  
      input_data = torch.rand(input_shape)
      model = TestMax()
      # TODO: Expected results are flipped due to naming issue:
      # rdar://62681982 (Determine the output names of MLModels)
      expected_results = model(input_data)[::-1]
      run_compare_torch(
          input_data,
          model,
          expected_results=expected_results,
          input_as_shape=False,
          backend=backend,
      )
  
imports: import sys
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.testing_reqs import *
  from .testing_utils import *
label_desc: Use image node_id 1 for calling the TestReduction obj's underlying member method code with example usage: obj.test_max(input_shape, dim, keepdim, backend) and returns: torch