{"record":{"id":"f71c55d70a2594b6","repo":"tensorflow/models","slug":"only-support-dictionary-decoder-output","errorCode":null,"errorMessage":"Only support dictionary decoder_output.","messagePattern":"Only support dictionary decoder_output\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/projects/maskconver/modeling/layers/maskconver_head.py","lineNumber":259,"sourceCode":"                                               'deeplabv3plus_sum_to_merge'}:\n      # deeplabv3+ feature fusion\n      x = decoder_output[str(self._config_dict['level'])] if isinstance(\n          decoder_output, dict) else decoder_output\n      y = backbone_output[str(self._config_dict['low_level'])] if isinstance(\n          backbone_output, dict) else backbone_output\n      y = self._dlv3p_norm(self._dlv3p_conv(y))\n      y = self._activation(y)\n\n      x = tf.image.resize(\n          x, tf.shape(y)[1:3], method=tf.image.ResizeMethod.BILINEAR)\n      x = tf.cast(x, dtype=y.dtype)\n      if self._config_dict['feature_fusion'] == 'deeplabv3plus':\n        x = tf.concat([x, y], axis=self._bn_axis)\n      else:\n        x = tf_keras.layers.Add()([x, y])\n    elif self._config_dict['feature_fusion'] == 'pyramid_fusion':\n      if not isinstance(decoder_output, dict):\n        raise ValueError('Only support dictionary decoder_output.')\n      x = nn_layers.pyramid_feature_fusion(decoder_output,\n                                           self._config_dict['level'])\n    elif self._config_dict['feature_fusion'] == 'panoptic_fpn_fusion':\n      x = self._panoptic_fpn_fusion(decoder_output)\n    else:\n      x = decoder_output[str(self._config_dict['level'])] if isinstance(\n          decoder_output, dict) else decoder_output\n\n    for conv, norm in zip(self._convs, self._norms):\n      x = conv(x)\n      x = norm(x)\n      x = self._activation(x)\n    if self._config_dict['upsample_factor'] > 1:  # pyrefly: ignore[unsupported-operation]\n      x = spatial_transform_ops.nearest_upsampling(\n          x, scale=self._config_dict['upsample_factor'])\n\n    return self._classifier(x)\n","sourceCodeStart":241,"sourceCodeEnd":277,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/projects/maskconver/modeling/layers/maskconver_head.py#L241-L277","documentation":"Error \"Only support dictionary decoder_output.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/projects/maskconver/modeling/layers/maskconver_head.py:259 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":[],"exampleFix":null,"handlingStrategy":null,"validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"e006f5f0d534913e49c1f1dae87364039fa607e2","analyzedAt":"2026-08-24T14:09:15.576Z","schemaVersion":2},"datasetVersion":"2026-08-24T17:17:21.512Z"}