{"record":{"id":"9d353476c084242f","repo":"tensorflow/models","slug":"unimplemented-eval-metrics","errorCode":null,"errorMessage":"Unimplemented eval_metrics","messagePattern":"Unimplemented eval_metrics","errorType":"exception","errorClass":"NotImplementedError","httpStatus":null,"severity":"error","filePath":"official/legacy/detection/modeling/base_model.py","lineNumber":135,"sourceCode":"    ]\n\n    return self._l2_weight_decay * tf.add_n(\n        [tf.nn.l2_loss(v) for v in reg_variables])\n\n  def make_restore_checkpoint_fn(self):\n    \"\"\"Returns scaffold function to restore parameters from v1 checkpoint.\"\"\"\n    if 'skip_checkpoint_variables' in self._checkpoint:\n      skip_regex = self._checkpoint['skip_checkpoint_variables']\n    else:\n      skip_regex = None\n    return checkpoint_utils.make_restore_checkpoint_fn(\n        self._checkpoint['path'],\n        prefix=self._checkpoint['prefix'],\n        skip_regex=skip_regex)\n\n  def eval_metrics(self):\n    \"\"\"Returns tuple of metric function and its inputs for evaluation.\"\"\"\n    raise NotImplementedError('Unimplemented eval_metrics')\n","sourceCodeStart":117,"sourceCodeEnd":136,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/legacy/detection/modeling/base_model.py#L117-L136","documentation":"Error \"Unimplemented eval_metrics\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/legacy/detection/modeling/base_model.py:135 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"}