code: def make_one_var_tf_dataset_loader(
      hparams: Dict[str, Any], batch_size: int
  ) -> ZipDataset:
      dataset_range = hparams["dataset_range"]
  
      xtrain = tf.data.Dataset.range(dataset_range).batch(batch_size)
      ytrain = tf.data.Dataset.range(dataset_range).batch(batch_size)
  
      train_ds = tf.data.Dataset.zip((xtrain, ytrain))
      return train_ds
  
file_path: determined/harness/tests/experiment/fixtures/ancient_keras_ckpt.py
imports: from typing import Any, Dict, cast
  import tensorflow
  from tensorflow.keras.layers import Dense
  from tensorflow.keras.losses import mean_squared_error
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.optimizers.legacy import SGD
  from tensorflow.raw_ops import ZipDataset
  from determined import keras
label_desc: Use image node_id 1 for calling a global function with example usage: make_one_var_tf_dataset_loader(hparams, batch_size) and returns: train_ds