tensorflow/models · error · ValueError

`strategy`, `model_fn`, `loss_fn`, `model_dir`, `steps_per_e

Error message

`strategy`, `model_fn`, `loss_fn`, `model_dir`, `steps_per_epoch` and `train_input_fn` are required parameters.

What it means

Error "`strategy`, `model_fn`, `loss_fn`, `model_dir`, `steps_per_epoch` and `train_input_fn` are required parameters." thrown in tensorflow/models.

Source

Thrown at official/legacy/bert/model_training_utils.py:227

  Raises:
      ValueError: (1) When model returned by `model_fn` does not have optimizer
        attribute or when required parameters are set to none. (2) eval args are
        not specified correctly. (3) metric_fn must be a callable if specified.
        (4) sub_model_checkpoint_name is specified, but `sub_model` returned
        by `model_fn` is None.
  """

  if _sentinel is not None:
    raise ValueError('only call `run_customized_training_loop()` '
                     'with named arguments.')

  required_arguments = [
      strategy, model_fn, loss_fn, model_dir, steps_per_epoch, train_input_fn
  ]

  steps_between_evals = int(steps_per_epoch / num_eval_per_epoch)  # pyrefly: ignore[unsupported-operation]
  if [arg for arg in required_arguments if arg is None]:
    raise ValueError('`strategy`, `model_fn`, `loss_fn`, `model_dir`, '
                     '`steps_per_epoch` and `train_input_fn` are required '
                     'parameters.')
  if not steps_per_loop:
    if tf.config.list_logical_devices('TPU'):
      # One can't fully utilize a TPU with steps_per_loop=1, so in this case
      # default users to a more useful value.
      steps_per_loop = min(1000, steps_between_evals)
    else:
      steps_per_loop = 1
    logging.info('steps_per_loop not specified. Using steps_per_loop=%d',
                 steps_per_loop)
  if steps_per_loop > steps_between_evals:
    logging.warning(
        'steps_per_loop: %d is specified to be greater than '
        ' steps_between_evals: %d, we will use steps_between_evals as'
        ' steps_per_loop.', steps_per_loop, steps_between_evals)
    steps_per_loop = steps_between_evals
  assert tf.executing_eagerly()

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/legacy/bert/model_training_utils.py:227 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/55449b2dd063c553. Report an issue: GitHub.