content: import torch
  import torch.nn as nn
  from parameterized import parameterized
  from torch.testing._internal.common_utils import run_tests
  
  from .harness import DispatchTestCase
  
  
  class TestDropOutConverter(DispatchTestCase):
      @parameterized.expand(
          [
              ((10,), 0, False),
              ((1, 3), 0.3, False),
              ((2, 2, 2), 0.5),
              ((2, 2, 2, 2), 1),
          ]
      )
      def test_native_dropout(self, input_shape, p, train=False):
          class NativeDropout(nn.Module):
              def forward(self, input):
                  return torch.ops.aten.native_dropout.default(input, p, train)
  
          inputs = [torch.randn(input_shape)]
          self.run_test(
              NativeDropout(),
              inputs,
          )
  
      @parameterized.expand(
          [
              (
                  torch.randn(
                      10,
                  ),
                  0,
                  False,
              ),
              (torch.randn(1, 3), 0.3, False),
              (torch.randn(2, 2, 2), 0.5),
              (torch.randn(2, 2, 2, 2), 1),
          ]
      )
      def test_native_dropout_pytorch(self, input, p, train=False):
          class NativeDropout(nn.Module):
              def forward(self):
                  return torch.ops.aten.native_dropout.default(input, p, train)
  
          inputs = []
          self.run_test(
              NativeDropout(),
              inputs,
          )
  
  
  if __name__ == "__main__":
      run_tests()
  