content: import torch
  import torch_tensorrt.fx.tracer.acc_tracer.acc_ops as acc_ops
  from torch.testing._internal.common_utils import run_tests
  from torch_tensorrt.fx.tools.common_fx2trt import AccTestCase, InputTensorSpec
  
  
  class TestMaximumConverter(AccTestCase):
      def test_maximum(self):
          class Maximum(torch.nn.Module):
              def forward(self, x, y):
                  return torch.maximum(x, y)
  
          inputs = [
              torch.randn(3, 4),
              torch.randn(3, 4),
          ]
          self.run_test(Maximum(), inputs, expected_ops={acc_ops.maximum})
  
  
  class TestMaximumConverterWithDynamicShape(AccTestCase):
      def test_maximum(self):
          class Maximum(torch.nn.Module):
              def forward(self, x, y):
                  return torch.maximum(x, y)
  
          input_specs = [
              InputTensorSpec(
                  shape=(-1, -1, -1, -1),
                  dtype=torch.float32,
                  shape_ranges=[((1, 1, 1, 1), (2, 3, 4, 5), (2, 3, 10, 10))],
              ),
              InputTensorSpec(
                  shape=(-1, -1, -1, -1),
                  dtype=torch.float32,
                  shape_ranges=[((1, 1, 1, 1), (2, 3, 4, 5), (2, 3, 10, 10))],
              ),
          ]
  
          self.run_test_with_dynamic_shape(
              Maximum(), input_specs, expected_ops={acc_ops.maximum}
          )
  
  
  class TestMaximumMethodConverter(AccTestCase):
      def test_maximum(self):
          class Maximum(torch.nn.Module):
              def forward(self, x, y):
                  return x.maximum(y)
  
          inputs = [
              torch.randn(3, 4),
              torch.randn(3, 4),
          ]
          self.run_test(Maximum(), inputs, expected_ops={acc_ops.maximum})
  
  
  class TestMaximumMethodConverterWithDynamicShape(AccTestCase):
      def test_maximum(self):
          class Maximum(torch.nn.Module):
              def forward(self, x, y):
                  return x.maximum(y)
  
          input_specs = [
              InputTensorSpec(
                  shape=(-1, -1, -1, -1),
                  dtype=torch.float32,
                  shape_ranges=[((1, 1, 1, 1), (2, 3, 4, 5), (2, 3, 10, 10))],
              ),
              InputTensorSpec(
                  shape=(-1, -1, -1, -1),
                  dtype=torch.float32,
                  shape_ranges=[((1, 1, 1, 1), (2, 3, 4, 5), (2, 3, 10, 10))],
              ),
          ]
  
          self.run_test_with_dynamic_shape(
              Maximum(), input_specs, expected_ops={acc_ops.maximum}
          )
  
  
  if __name__ == "__main__":
      run_tests()
  