class_docstr: An old model that should always reload from its equally old checkpoints.
  
  Don't change this model architecture or add any fancy features or the test won't be valid.
class_docstr_tok: ["An","old","model","that","should","always","reload","from","its","equally","old","checkpoints",".","Do","n't","change","this","model","architecture","or","add","any","fancy","features","or","the","test","wo","n't","be","valid","."]
code: def build_training_data_loader(self) -> keras.InputData:
      dataset = make_one_var_tf_dataset_loader(
          self.context.get_hparams(), self.my_batch_size
      )
      dataset = self.context.wrap_dataset(dataset)
      return dataset
  
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 2 for calling the AncientTrial obj's underlying member method code with example usage: obj.build_training_data_loader() and returns: dataset