code: def batching_metadata(self) -> Dict[str, str]:
      return {
          "float_features": "dense",
          "id_list_features": "sparse",
      }
  
file_path: torchrec/examples/inference/dlrm_predict_single_gpu.py
imports: import logging
  from typing import Dict
  import torch
  from dlrm_predict import DLRMModelConfig, DLRMPredictModule
  from torchrec.inference.model_packager import load_pickle_config
  from torchrec.inference.modules import PredictFactory, quantize_embeddings
  from torchrec.modules.embedding_configs import EmbeddingBagConfig
  from torchrec.modules.embedding_modules import EmbeddingBagCollection
label_desc: Use image node_id 3 for calling the DLRMPredictSingleGPUFactory obj's underlying member method code with example usage: obj.batching_metadata() and returns: dict