content: import torch
  import torch.nn as nn
  from parameterized import parameterized
  from torch.testing._internal.common_utils import run_tests
  from torch_tensorrt import Input
  
  from .harness import DispatchTestCase
  
  
  class TestMulConverter(DispatchTestCase):
      @parameterized.expand(
          [
              ("2d", (2, 1)),
              ("3d", (2, 1, 2)),
          ]
      )
      def test_mul_tensor(self, _, shape):
          class mul(nn.Module):
              def forward(self, lhs_val, rhs_val):
                  return torch.ops.aten.mul.Tensor(lhs_val, rhs_val)
  
          inputs = [torch.randn(shape), torch.randn(shape)]
          self.run_test(
              mul(),
              inputs,
          )
  
      @parameterized.expand(
          [
              ("2d_int", (2, 1), 1),
              ("3d_int", (2, 1, 2), 2),
              ("2d_float", (2, 1), 1.0),
              ("3d_float", (2, 1, 2), 2.0),
          ]
      )
      def test_mul_scalar(self, _, shape, scalar):
          class mul(nn.Module):
              def forward(self, lhs_val):
                  return torch.ops.aten.mul.Tensor(lhs_val, scalar)
  
          inputs = [torch.randn(shape)]
          self.run_test(
              mul(),
              inputs,
          )
  
  
  if __name__ == "__main__":
      run_tests()
  