code: def __init__(self) -> None:
      self.model_config: DLRMModelConfig = load_pickle_config(
          "config.pkl", DLRMModelConfig
      )
  
imports: import logging
  from dataclasses import dataclass
  from typing import Dict, List, Optional
  import torch
  import torchrec.distributed
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel
  from torchrec.distributed.planner import EmbeddingShardingPlanner, ParameterConstraints, Topology
  from torchrec.distributed.quant_embeddingbag import QuantEmbeddingBagCollectionSharder
  from torchrec.distributed.types import ShardingType
  from torchrec.inference.model_packager import load_pickle_config
  from torchrec.inference.modules import PredictFactory, PredictModule, quantize_embeddings
  from torchrec.models.dlrm import DLRM
  from torchrec.modules.embedding_configs import EmbeddingBagConfig
  from torchrec.modules.embedding_modules import EmbeddingBagCollection
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 1 to create a new DLRMPredictFactory object from inherited base classes: PredictFactory with example: obj = DLRMPredictFactory()