code: def setUp(self) -> None:
      num_features = 4
      num_weighted_features = 2
  
      self.tables = [
          EmbeddingBagConfig(
              num_embeddings=(i + 1) * 10000000,
              embedding_dim=(i + 1) * 4,
              name="table_" + str(i),
              feature_names=["feature_" + str(i)],
          )
          for i in range(num_features)
      ]
      self.weighted_tables = [
          EmbeddingBagConfig(
              num_embeddings=(i + 1) * 10,
              embedding_dim=(i + 1) * 4,
              name="weighted_table_" + str(i),
              feature_names=["weighted_feature_" + str(i)],
          )
          for i in range(num_weighted_features)
      ]
  
imports: import unittest
  from typing import Any, cast, Dict, List, Optional, Tuple
  import hypothesis.strategies
  import torch
  from hypothesis import given, settings, Verbosity
  from torch import nn, quantization
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel, ModuleSharder
  from torchrec.distributed.model_parallel import DistributedModelParallel
  from torchrec.distributed.planner import EmbeddingShardingPlanner, Topology
  from torchrec.distributed.planner.enumerators import EmbeddingEnumerator
  from torchrec.distributed.planner.shard_estimators import EmbeddingPerfEstimator, EmbeddingStorageEstimator
  from torchrec.distributed.quant_embeddingbag import QuantEmbeddingBagCollectionSharder
  from torchrec.distributed.shard import _shard_modules
  from torchrec.distributed.test_utils.test_model import _get_default_rtol_and_atol, ModelInput, TestSparseNN
  from torchrec.distributed.types import ShardedModule, ShardingEnv, ShardingType
  from torchrec.distributed.utils import copy_to_device
  from torchrec.modules.embedding_configs import EmbeddingBagConfig, QuantConfig
  from torchrec.modules.embedding_modules import EmbeddingBagCollection
  from torchrec.quant.embedding_modules import EmbeddingBagCollection, quant_prep_enable_quant_state_dict_split_scale_bias_for_types
  from torchrec.types import CopyMixIn
label_desc: Use image node_id 1 for calling the QuantModelParallelModelSharderTest obj's underlying member method code with example usage: obj.setUp() without return types