tensorflow/models · error · ValueError

Augmentation policy {} not supported.

Error message

Augmentation policy {} not supported.

What it means

Error "Augmentation policy {} not supported." thrown in tensorflow/models.

Source

Thrown at official/vision/dataloaders/classification_input.py:140

      self._dtype = tf.bfloat16
    else:
      raise ValueError('dtype {!r} is not supported!'.format(dtype))
    if aug_type:
      if aug_type.type == 'autoaug':
        self._augmenter = augment.AutoAugment(
            augmentation_name=aug_type.autoaug.augmentation_name,
            cutout_const=aug_type.autoaug.cutout_const,
            translate_const=aug_type.autoaug.translate_const)
      elif aug_type.type == 'randaug':
        self._augmenter = augment.RandAugment(
            num_layers=aug_type.randaug.num_layers,
            magnitude=aug_type.randaug.magnitude,
            cutout_const=aug_type.randaug.cutout_const,
            translate_const=aug_type.randaug.translate_const,
            prob_to_apply=aug_type.randaug.prob_to_apply,
            exclude_ops=aug_type.randaug.exclude_ops)
      else:
        raise ValueError('Augmentation policy {} not supported.'.format(
            aug_type.type))
    else:
      self._augmenter = None
    self._label_field_key = label_field_key
    self._color_jitter = color_jitter
    if random_erasing:
      self._random_erasing = augment.RandomErasing(
          probability=random_erasing.probability,
          min_area=random_erasing.min_area,
          max_area=random_erasing.max_area,
          min_aspect=random_erasing.min_aspect,
          max_aspect=random_erasing.max_aspect,
          min_count=random_erasing.min_count,
          max_count=random_erasing.max_count,
          trials=random_erasing.trials)
    else:
      self._random_erasing = None
    self._is_multilabel = is_multilabel

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/vision/dataloaders/classification_input.py:140 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/c8bf9824a44c3fc8. Report an issue: GitHub.