{"record":{"id":"165b18a9129482aa","repo":"tensorflow/models","slug":"intermediate-size-d-isn-t-a-multiple-of-num-blo","errorCode":null,"errorMessage":"Intermediate_size (%d) isn't a multiple of num_blocks (%d).","messagePattern":"Intermediate_size \\((.+?)\\) isn't a multiple of num_blocks \\((.+?)\\)\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/nlp/modeling/layers/block_diag_feedforward.py","lineNumber":70,"sourceCode":"      num_blocks: int = 1,\n      apply_mixing: bool = True,\n      kernel_initializer: str = \"glorot_uniform\",\n      bias_initializer: str = \"zeros\",\n      kernel_regularizer: Optional[tf_keras.regularizers.Regularizer] = None,\n      bias_regularizer: Optional[tf_keras.regularizers.Regularizer] = None,\n      activity_regularizer: Optional[tf_keras.regularizers.Regularizer] = None,\n      kernel_constraint: Optional[tf_keras.constraints.Constraint] = None,\n      bias_constraint: Optional[tf_keras.constraints.Constraint] = None,\n      **kwargs):  # pylint: disable=g-doc-args\n    super().__init__(**kwargs)\n    self._intermediate_size = intermediate_size\n    self._intermediate_activation = intermediate_activation\n    self._dropout = dropout\n    self._num_blocks = num_blocks\n    self._apply_mixing = apply_mixing\n\n    if intermediate_size % num_blocks != 0:\n      raise ValueError(\"Intermediate_size (%d) isn't a multiple of num_blocks \"\n                       \"(%d).\" % (intermediate_size, num_blocks))\n\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._activity_regularizer = tf_keras.regularizers.get(activity_regularizer)\n    self._kernel_constraint = tf_keras.constraints.get(kernel_constraint)\n    self._bias_constraint = tf_keras.constraints.get(bias_constraint)\n\n  def build(self, input_shape):\n    hidden_size = input_shape.as_list()[-1]\n\n    common_kwargs = dict(\n        kernel_regularizer=self._kernel_regularizer,\n        bias_regularizer=self._bias_regularizer,\n        activity_regularizer=self._activity_regularizer,\n        kernel_constraint=self._kernel_constraint,","sourceCodeStart":52,"sourceCodeEnd":88,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/nlp/modeling/layers/block_diag_feedforward.py#L52-L88","documentation":"Error \"Intermediate_size (%d) isn't a multiple of num_blocks (%d).\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/nlp/modeling/layers/block_diag_feedforward.py:70 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"}