code: def train_data_creator(config):
      return DataLoader(
          TensorDataset(
              torch.randn(
                  1000,
                  config.get("past_seq_len", 10),
                  config.get("input_feature_num", 2),
              ),
              torch.randn(
                  1000,
                  config.get("future_seq_len", 2),
                  config.get("output_feature_num", 2),
              ),
          ),
          batch_size=config.get("batch_size", 32),
          shuffle=True,
      )
  
imports: import numpy
  from unittest import TestCase
  import pytest
  from bigdl.chronos.utils import LazyImport
  import os
  import pandas
  import numpy
  from bigdl.chronos.data import TSDataset
  from ..None import op_torch, op_inference
label_desc: Use image node_id 1 for calling a global function with example usage: train_data_creator(config) and returns: DataLoader