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/projects/maskconver/dataloaders/multiscale_maskconver_input.py:176
self._aug_scale_max = aug_scale_max
self._segmentation_ignore_label = segmentation_ignore_label
self._panoptic_ignore_label = panoptic_ignore_label
self.level = level
self._mask_target_level = mask_target_level
self._num_panoptic_categories = num_panoptic_categories
self._num_thing_categories = num_thing_categories
self._gaussian_iou = gaussian_iou
self.fpn_low_range = fpn_low_range
self.fpn_high_range = fpn_high_range
if aug_type and aug_type.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)
else:
raise ValueError('Augmentation policy {} not supported.'.format(
aug_type.type))
else:
self._augmenter = None
def _parse_train_data(self, data):
"""Parses data for training.
Args:
data: the decoded tensor dictionary from TfExampleDecoder.
Returns:
image: image tensor that is preproessed to have normalized value and
dimension [output_size[0], output_size[1], 3]
labels: a dictionary of tensors used for training. The following describes
{key: value} pairs in the dictionary.
"""
# Flips image randomly during training.
if self.aug_rand_hflip:View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/maskconver/dataloaders/multiscale_maskconver_input.py:176 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/9647b06933fb5bbc.
Report an issue: GitHub.