code: def sharding_types(self, compute_device_type: str) -> List[str]:
      return [
          ShardingType.ROW_WISE.value,
          ShardingType.TABLE_WISE.value,
      ]
  
imports: import unittest
  from typing import cast, List
  import torch
  from torch import nn
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel
  from torchrec.distributed.embeddingbag import EmbeddingBagCollectionSharder
  from torchrec.distributed.planner import ParameterConstraints
  from torchrec.distributed.planner.planners import EmbeddingShardingPlanner
  from torchrec.distributed.planner.types import PlannerError, PlannerErrorType, Topology
  from torchrec.distributed.sharding_plan import get_default_sharders
  from torchrec.distributed.test_utils.test_model import TestSparseNN
  from torchrec.distributed.types import BoundsCheckMode, CacheAlgorithm, CacheParams, DataType, EmbeddingModuleShardingPlan, ModuleSharder, ShardingPlan, ShardingType
  from torchrec.modules.embedding_configs import EmbeddingBagConfig
label_desc: Use image node_id 1 for calling the TWvsRWSharder obj's underlying member method code with example usage: obj.sharding_types(compute_device_type) and returns: list