{"record":{"id":"8740aa10d0f2e84b","repo":"tensorflow/models","slug":"at-most-one-of-hub-module-url-and-init-checkpoi-8740aa","errorCode":null,"errorMessage":"At most one of `hub_module_url` and `init_checkpoint` can be specified.","messagePattern":"At most one of `hub_module_url` and `init_checkpoint` can be specified\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/nlp/tasks/question_answering.py","lineNumber":104,"sourceCode":"    if params.validation_data.tokenization == 'WordPiece':\n      self.squad_lib = squad_lib_wp\n    elif params.validation_data.tokenization == 'SentencePiece':\n      self.squad_lib = squad_lib_sp\n    else:\n      raise ValueError('Unsupported tokenization method: {}'.format(\n          params.validation_data.tokenization))\n\n    if params.validation_data.input_path:\n      self._tf_record_input_path, self._eval_examples, self._eval_features = (\n          self._preprocess_eval_data(params.validation_data))\n\n  def set_preprocessed_eval_input_path(self, eval_input_path):\n    \"\"\"Sets the path to the preprocessed eval data.\"\"\"\n    self._tf_record_input_path = eval_input_path\n\n  def build_model(self):\n    if self.task_config.hub_module_url and self.task_config.init_checkpoint:\n      raise ValueError('At most one of `hub_module_url` and '\n                       '`init_checkpoint` can be specified.')\n    if self.task_config.hub_module_url:\n      encoder_network = utils.get_encoder_from_hub(\n          self.task_config.hub_module_url)\n    else:\n      encoder_network = encoders.build_encoder(self.task_config.model.encoder)\n    encoder_cfg = self.task_config.model.encoder.get()\n    return models.BertSpanLabeler(\n        network=encoder_network,\n        initializer=tf_keras.initializers.TruncatedNormal(\n            stddev=encoder_cfg.initializer_range))\n\n  def build_losses(self, labels, model_outputs, aux_losses=None) -> tf.Tensor:\n    start_positions = labels['start_positions']\n    end_positions = labels['end_positions']\n    start_logits, end_logits = model_outputs\n\n    start_loss = tf_keras.losses.sparse_categorical_crossentropy(","sourceCodeStart":86,"sourceCodeEnd":122,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/nlp/tasks/question_answering.py#L86-L122","documentation":"Error \"At most one of `hub_module_url` and `init_checkpoint` can be specified.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/nlp/tasks/question_answering.py:104 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"}