code: def test_item_id_info(dataset: Dataset, estimator: Estimator):
      predictor = estimator.train(dataset)
      forecasts = predictor.predict(dataset)
      for data_entry, forecast in zip(dataset, forecasts):
          assert ("item_id" not in data_entry) or data_entry[
              "item_id"
          ] == forecast.item_id
          assert ("info" not in data_entry) or data_entry[
              "info"
          ] == forecast.info
  
imports: import numpy
  import pytest
  from gluonts.dataset.common import Dataset, ListDataset
  from gluonts.model.estimator import Estimator
  from gluonts.torch.model.simple_feedforward import SimpleFeedForwardEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_item_id_info(dataset, estimator) without return types