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/vision/tasks/retinanet.py:117

                   params: exp_cfg.DataConfig,
                   input_context: Optional[tf.distribute.InputContext] = None):
    """Build input dataset."""

    if params.tfds_name:
      decoder = tfds_factory.get_detection_decoder(params.tfds_name)
    else:
      decoder_cfg = params.decoder.get()
      if params.decoder.type == 'simple_decoder':
        decoder = tf_example_decoder.TfExampleDecoder(
            regenerate_source_id=decoder_cfg.regenerate_source_id,
            attribute_names=decoder_cfg.attribute_names,
        )
      elif params.decoder.type == 'label_map_decoder':
        decoder = tf_example_label_map_decoder.TfExampleDecoderLabelMap(
            label_map=decoder_cfg.label_map,
            regenerate_source_id=decoder_cfg.regenerate_source_id)
      else:
        raise ValueError('Unknown decoder type: {}!'.format(
            params.decoder.type))

    parser = retinanet_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,
        dtype=params.dtype,
        match_threshold=params.parser.match_threshold,
        unmatched_threshold=params.parser.unmatched_threshold,
        box_coder_weights=(
            self.task_config.model.detection_generator.box_coder_weights
        ),
        aug_type=params.parser.aug_type,
        aug_rand_hflip=params.parser.aug_rand_hflip,
        aug_rand_jpeg=params.parser.aug_rand_jpeg,

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Use a supported decoder type: 'fpn' or 'nasfpn' for RetinaNet.
2. Check the decoder type in the model config for typos.

When it happens

Trigger: Thrown at official/vision/tasks/retinanet.py:117 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/4e790debb8f3e8ef. Report an issue: GitHub.