code: def test_split(self):
      for tensor_model_paralell_world_size in range(
          1, self.world_size + 1
      ):
          if self.world_size % tensor_model_paralell_world_size > 0:
              continue
          parallel_state.initialize_model_parallel(
              tensor_model_parallel_size_=tensor_model_paralell_world_size
          )
  
          tensors = [
              torch.randn(10, 1)
              for _ in range(tensor_model_paralell_world_size)
          ]
          x = torch.cat(tensors, 1)
          out = mappings._split_along_last_dim(x)
          self.assertTrue(
              torch.equal(
                  out,
                  tensors[
                      parallel_state.get_tensor_model_parallel_rank()
                  ],
              ),
              msg=f"tensor_model_paralell_world_size: {tensor_model_paralell_world_size}",
          )
          parallel_state.destroy_model_parallel()
  
file_path: apex/tests/L0/run_transformer/test_mapping.py
imports: import logging
  import torch
  from torch.testing._internal import common_utils
  from apex.transformer import parallel_state
  from apex.transformer.tensor_parallel import mappings
  from apex.transformer.testing.distributed_test_base import NcclDistributedTestBase
  from apex.transformer.testing.distributed_test_base import UccDistributedTestBase
label_desc: Use image node_id 2 for calling the MappingTestBase obj's underlying member method code with example usage: obj.test_split() without return types