code: def create_training_batch(args: argparse.Namespace) -> Batch:
      return next(
          iter(
              DataLoader(
                  RandomRecDataset(
                      keys=DEFAULT_CAT_NAMES,
                      batch_size=args.batch_size,
                      hash_size=args.num_embedding_features,
                      ids_per_feature=1,
                      num_dense=len(DEFAULT_INT_NAMES),
                  ),
                  batch_sampler=None,
                  pin_memory=False,
                  num_workers=0,
              )
          )
      )
  
file_path: torchrec/torchrec/inference/client.py
imports: import argparse
  import logging
  import grpc
  import torch
  from gen.torchrec.inference import predictor_pb2, predictor_pb2_grpc
  from torch.utils.data import DataLoader
  from torchrec.datasets.criteo import DEFAULT_CAT_NAMES, DEFAULT_INT_NAMES
  from torchrec.datasets.random import RandomRecDataset
  from torchrec.datasets.utils import Batch
label_desc: Use image node_id 1 for calling a global function with example usage: create_training_batch(args) and returns: next