tensorflow/models · error · ValueError

dtype {!r} is not supported!

Error message

dtype {!r} is not supported!

What it means

Error "dtype {!r} is not supported!" thrown in tensorflow/models.

Source

Thrown at official/vision/dataloaders/classification_input.py:124

        range. The default area range is (0.08, 1.0).
      https://arxiv.org/abs/2204.07118.
      center_crop_fraction: center_crop_fraction.
      tf_resize_method: A `str`, interpolation method for resizing image.
      three_augment: A bool, whether to apply three augmentations.
    """
    self._output_size = output_size
    self._aug_rand_hflip = aug_rand_hflip
    self._aug_crop = aug_crop
    self._num_classes = num_classes
    self._image_field_key = image_field_key
    if dtype == 'float32':
      self._dtype = tf.float32
    elif dtype == 'float16':
      self._dtype = tf.float16
    elif dtype == 'bfloat16':
      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:

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/vision/dataloaders/classification_input.py:124 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/0e4f5ee44b816cf1. Report an issue: GitHub.