code: def test_dataset(test_data):
      training = TimeSeriesDataSet(
          test_data.copy(),
          time_idx="time_idx",
          target="volume",
          time_varying_known_reals=["price_regular", "time_idx"],
          group_ids=["agency", "sku"],
          static_categoricals=["agency"],
          max_encoder_length=5,
          max_prediction_length=2,
          min_prediction_length=1,
          min_encoder_length=0,
          randomize_length=None,
      )
      return training
  
file_path: pytorch-forecasting/tests/conftest.py
imports: import os
  import sys
  import numpy
  import pytest
  from pytorch_forecasting import TimeSeriesDataSet
  from pytorch_forecasting.data.examples import get_stallion_data
label_desc: Use image node_id 2 for calling a global function with example usage: test_dataset(test_data) and returns: training