code: def test_sharding_nccl_cw(
      self,
      sharding_type: str,
      kernel_type: str,
      apply_optimizer_in_backward_config: Optional[
          Dict[str, Tuple[Type[torch.optim.Optimizer], Dict[str, Any]]]
      ],
  ) -> None:
      assume(
          apply_optimizer_in_backward_config is None
          or kernel_type != EmbeddingComputeKernel.DENSE.value
      )
      self._test_sharding(
          sharders=[
              TestEmbeddingCollectionSharder(
                  sharding_type=sharding_type,
                  kernel_type=kernel_type,
              )
          ],
          backend="nccl",
          constraints={
              table.name: ParameterConstraints(min_partition=8)
              for table in self.tables
          },
          apply_optimizer_in_backward_config=apply_optimizer_in_backward_config,
          variable_batch_size=False,
      )
  
imports: import unittest
  from typing import Any, Dict, List, Optional, Tuple, Type
  import hypothesis.strategies
  import torch
  from fbgemm_gpu.split_embedding_configs import EmbOptimType
  from hypothesis import assume, given, settings, Verbosity
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel
  from torchrec.distributed.fbgemm_qcomm_codec import CommType, QCommsConfig
  from torchrec.distributed.planner import ParameterConstraints
  from torchrec.distributed.test_utils.multi_process import MultiProcessTestBase
  from torchrec.distributed.test_utils.test_model import TestSparseNNBase
  from torchrec.distributed.test_utils.test_sharding import sharding_single_rank_test
  from torchrec.distributed.tests.test_sequence_model import TestEmbeddingCollectionSharder, TestSequenceSparseNN
  from torchrec.distributed.types import ShardingType
  from torchrec.modules.embedding_configs import EmbeddingConfig
  from torchrec.test_utils import seed_and_log, skip_if_asan_class
label_desc: Use image node_id 4 for calling the SequenceModelParallelTest obj's underlying member method code with example usage: obj.test_sharding_nccl_cw(sharding_type, kernel_type, apply_optimizer_in_backward_config) without return types