{"record":{"id":"0a35319c1f125e69","repo":"tensorflow/models","slug":"reuse-attention-should-be-between-1-and-d-in-cal","errorCode":null,"errorMessage":"reuse_attention should be between -1 and %d in call to %s.","messagePattern":"reuse_attention should be between -1 and (.+?) in call to (.+?)\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/nlp/modeling/layers/reuse_attention.py","lineNumber":232,"sourceCode":"               pe_max_seq_length=512,\n               use_bias=True,\n               output_shape=None,\n               attention_axes=None,\n               kernel_initializer=\"glorot_uniform\",\n               bias_initializer=\"zeros\",\n               kernel_regularizer=None,\n               bias_regularizer=None,\n               activity_regularizer=None,\n               kernel_constraint=None,\n               bias_constraint=None,\n               **kwargs):\n    super().__init__(**kwargs)\n    self._num_heads = num_heads\n    self._key_dim = key_dim\n    self._value_dim = value_dim if value_dim else key_dim\n    self._dropout = dropout\n    if reuse_attention > self._num_heads or reuse_attention < -1:\n      raise ValueError(\"reuse_attention should be between -1 \"\n                       \"and %d in call to %s.\" % (self.__class__,\n                                                  self._num_heads))\n    if reuse_attention == -1:\n      reuse_attention = self._num_heads\n    self._reuse_heads = reuse_attention\n    self._use_relative_pe = use_relative_pe\n    self._pe_max_seq_length = pe_max_seq_length\n    self._use_bias = use_bias\n    self._output_shape = output_shape\n    self._kernel_initializer = tf_keras.initializers.get(kernel_initializer)\n    self._bias_initializer = tf_keras.initializers.get(bias_initializer)\n    self._kernel_regularizer = tf_keras.regularizers.get(kernel_regularizer)\n    self._bias_regularizer = tf_keras.regularizers.get(bias_regularizer)\n    self._kernel_constraint = tf_keras.constraints.get(kernel_constraint)\n    self._bias_constraint = tf_keras.constraints.get(bias_constraint)\n    if attention_axes is not None and not isinstance(attention_axes,\n                                                     collections.abc.Sized):\n      self._attention_axes = (attention_axes,)","sourceCodeStart":214,"sourceCodeEnd":250,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/nlp/modeling/layers/reuse_attention.py#L214-L250","documentation":"Error \"reuse_attention should be between -1 and %d in call to %s.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/nlp/modeling/layers/reuse_attention.py:232 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"}