def METHOD_NAME(self) -> None:
    self.assertFalse(parallel_state.model_parallel_is_initialized())
    for tensor_model_parallel_world_size in range(1, self.world_size + 1):
        msg = f"tensor_model_parallel_world_siz: {tensor_model_parallel_world_size}"
        if self.world_size % tensor_model_parallel_world_size:
            continue
        pipeline_model_parallel_world_size = (
            self.world_size // tensor_model_parallel_world_size
        )
        parallel_state.initialize_model_parallel(
            tensor_model_parallel_size_=tensor_model_parallel_world_size,
            pipeline_model_parallel_size_=pipeline_model_parallel_world_size,
        )
        self.assertEqual(
            tensor_model_parallel_world_size,
            parallel_state.get_tensor_model_parallel_world_size(),
            msg=msg,
        )
        expected_tensor_model_parallel_rank = calc_expected_tensor_model_paralell_rank(
            self.rank, tensor_model_parallel_world_size
        )
        self.assertEqual(
            expected_tensor_model_parallel_rank,
            parallel_state.get_tensor_model_parallel_rank(),
            msg=msg,
        )
        expected_tensor_model_parallel_src_rank = (
            self.rank // tensor_model_parallel_world_size
        ) * tensor_model_parallel_world_size
        self.assertEqual(
            expected_tensor_model_parallel_src_rank,
            parallel_state.get_tensor_model_parallel_src_rank(),
            msg=msg,
        )
        parallel_state.destroy_model_parallel()
        self.assertFalse(parallel_state.model_parallel_is_initialized(), msg=msg)