{"record":{"id":"f5d2a265e0661058","repo":"tensorflow/models","slug":"the-inner-dim-of-f-self-class-must-be-an-even","errorCode":null,"errorMessage":"The inner_dim of f{self.__class__} must be an even integer. However, inner_dim is f{inner_dim}","messagePattern":"The inner_dim of f(.+?) must be an even integer\\. However, inner_dim is f(.+?)","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/projects/roformer/roformer_encoder_block.py","lineNumber":88,"sourceCode":"      norm_first: Whether to normalize inputs to attention and intermediate\n        dense layers. If set False, output of attention and intermediate dense\n        layers is normalized.\n      norm_epsilon: Epsilon value to initialize normalization layers.\n      output_dropout: Dropout probability for the post-attention and output\n        dropout.\n      attention_dropout: Dropout probability for within the attention layer.\n      inner_dropout: Dropout probability for the first Dense layer in a\n        two-layer feedforward network.\n      attention_initializer: Initializer for kernels of attention layers. If set\n        `None`, attention layers use kernel_initializer as initializer for\n        kernel.\n      attention_axes: axes over which the attention is applied. `None` means\n        attention over all axes, but batch, heads, and features.\n      **kwargs: keyword arguments.\n    \"\"\"\n    super().__init__(**kwargs)\n    if inner_dim % 2 != 0:\n      raise ValueError(f\"The inner_dim of f{self.__class__} must be an even \"\n                       f\"integer. However, inner_dim is f{inner_dim}\")\n    self._num_heads = num_attention_heads\n    self._inner_dim = inner_dim\n    self._inner_activation = inner_activation\n    self._attention_dropout = attention_dropout\n    self._attention_dropout_rate = attention_dropout\n    self._output_dropout = output_dropout\n    self._output_dropout_rate = output_dropout\n    self._output_range = output_range\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    self._use_bias = use_bias\n    self._norm_first = norm_first","sourceCodeStart":70,"sourceCodeEnd":106,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/projects/roformer/roformer_encoder_block.py#L70-L106","documentation":"Error \"The inner_dim of f{self.__class__} must be an even integer. However, inner_dim is f{inner_dim}\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/projects/roformer/roformer_encoder_block.py:88 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"}