tensorflow/models · error · ValueError
Unknown decoder type: {}!
Error message
Unknown decoder type: {}! What it means
Error "Unknown decoder type: {}!" thrown in tensorflow/models.
Source
Thrown at official/projects/panoptic/tasks/panoptic_maskrcnn.py:161
logging.info('Finished loading pretrained checkpoint from %s for %s',
checkpoint_path, init_module)
def build_inputs(
self,
params: exp_cfg.DataConfig,
input_context: Optional[tf.distribute.InputContext] = None
) -> tf.data.Dataset:
"""Builds input dataset."""
decoder_cfg = params.decoder.get()
if params.decoder.type == 'simple_decoder':
decoder = panoptic_maskrcnn_input.TfExampleDecoder(
regenerate_source_id=decoder_cfg.regenerate_source_id,
mask_binarize_threshold=decoder_cfg.mask_binarize_threshold,
include_panoptic_masks=decoder_cfg.include_panoptic_masks,
panoptic_category_mask_key=decoder_cfg.panoptic_category_mask_key,
panoptic_instance_mask_key=decoder_cfg.panoptic_instance_mask_key)
else:
raise ValueError('Unknown decoder type: {}!'.format(params.decoder.type))
parser = panoptic_maskrcnn_input.Parser(
output_size=self.task_config.model.input_size[:2],
min_level=self.task_config.model.min_level,
max_level=self.task_config.model.max_level,
num_scales=self.task_config.model.anchor.num_scales,
aspect_ratios=self.task_config.model.anchor.aspect_ratios,
anchor_size=self.task_config.model.anchor.anchor_size,
rpn_match_threshold=params.parser.rpn_match_threshold,
rpn_unmatched_threshold=params.parser.rpn_unmatched_threshold,
rpn_batch_size_per_im=params.parser.rpn_batch_size_per_im,
rpn_fg_fraction=params.parser.rpn_fg_fraction,
aug_rand_hflip=params.parser.aug_rand_hflip,
aug_rand_vflip=params.parser.aug_rand_vflip,
aug_scale_min=params.parser.aug_scale_min,
aug_scale_max=params.parser.aug_scale_max,
aug_type=params.parser.aug_type,
skip_crowd_during_training=params.parser.skip_crowd_during_training,View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/panoptic/tasks/panoptic_maskrcnn.py:161 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/14c49692e14293eb.
Report an issue: GitHub.