code: def setUp(self) -> None:
      os.environ["RANK"] = "0"
      os.environ["WORLD_SIZE"] = "1"
      os.environ["LOCAL_WORLD_SIZE"] = "1"
      os.environ["MASTER_ADDR"] = str("localhost")
      os.environ["MASTER_PORT"] = str(get_free_port())
      os.environ["NCCL_SOCKET_IFNAME"] = "lo"
      self.device = torch.device("cuda:0")
      backend = "nccl"
      torch.cuda.set_device(self.device)
      dist.init_process_group(backend=backend)
  
imports: import os
  import unittest
  import hypothesis.strategies
  import torch
  import torch.distributed
  import torch.quantization
  from hypothesis import given, settings, Verbosity
  from torchrec.distributed.embedding_lookup import BatchedDenseEmbedding, BatchedDenseEmbeddingBag, BatchedFusedEmbedding, BatchedFusedEmbeddingBag, GroupedEmbeddingsLookup, GroupedPooledEmbeddingsLookup
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel, GroupedEmbeddingConfig, ShardedEmbeddingTable, ShardedTensorMetadata, ShardMetadata
  from torchrec.distributed.quant_embedding_kernel import QuantBatchedEmbedding, QuantBatchedEmbeddingBag
  from torchrec.modules.embedding_configs import DataType, PoolingType
  from torchrec.test_utils import get_free_port
label_desc: Use image node_id 1 for calling the QuantizeKernelTest obj's underlying member method code with example usage: obj.setUp() without return types