content: import unittest
  
  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 TestSymSizeConverter(DispatchTestCase):
      @parameterized.expand(
          [
              ((3, 2, 4),),
          ]
      )
      def test_sym_size_batch(self, input_shape):
          class BatchDim(nn.Module):
              def forward(self, x):
                  return torch.ops.aten.sym_size.int(x, 0)
  
          inputs = [torch.randn(*input_shape)]
          self.run_test(
              BatchDim(),
              inputs,
          )
  
      @parameterized.expand(
          [
              ((3, 2, 4),),
          ]
      )
      def test_sym_size_non_batch(self, input_shape):
          class NonBatchDim(nn.Module):
              def forward(self, x):
                  return torch.ops.aten.sym_size.int(x, 1)
  
          inputs = [torch.randn(*input_shape)]
          self.run_test(
              NonBatchDim(),
              inputs,
          )
  
  
  if __name__ == "__main__":
      run_tests()
  