{"record":{"id":"1684f6777b408c21","repo":"tensorflow/models","slug":"input-shape-input-shape-is-inconsistent-with-num","errorCode":null,"errorMessage":"Input shape {input_shape} is inconsistent with num_experts {self.num_experts}.","messagePattern":"Input shape (.+?) is inconsistent with num_experts (.+?)\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/nlp/modeling/layers/moe.py","lineNumber":459,"sourceCode":"    self.activation = activation\n    self.kernel_initializer = kernel_initializer\n    self.bias_initializer = bias_initializer\n\n    self.intermediate_layer = tf_keras.layers.EinsumDense(\n        \"gech,ehf->gecf\",\n        output_shape=(self.num_experts, None, d_ff),\n        bias_axes=\"ef\",\n        kernel_initializer=tf_utils.clone_initializer(self.kernel_initializer),\n        bias_initializer=tf_utils.clone_initializer(self.bias_initializer),\n        name=\"intermediate\")\n    self.inner_dropout_layer = tf_keras.layers.Dropout(\n        inner_dropout)\n    self.output_dropout_layer = tf_keras.layers.Dropout(output_dropout)\n\n  def build(self, input_shape: Tuple[int, int, int, int]):\n    \"\"\"Creates the input shape dependent output weight variables.\"\"\"\n    if input_shape[1] != self.num_experts:\n      raise ValueError(\n          f\"Input shape {input_shape} is inconsistent with num_experts \"\n          f\"{self.num_experts}.\")\n\n    self.output_layer = tf_keras.layers.EinsumDense(\n        \"gecf,efh->gech\",\n        output_shape=(self.num_experts, None, input_shape[-1]),\n        bias_axes=\"eh\",\n        kernel_initializer=tf_utils.clone_initializer(self.kernel_initializer),\n        bias_initializer=tf_utils.clone_initializer(self.bias_initializer),\n        name=\"output\")\n\n  def call(self,\n           inputs: tf.Tensor,\n           *,\n           training: Optional[bool] = None) -> tf.Tensor:\n    \"\"\"Applies layer to inputs.\n\n    Args:","sourceCodeStart":441,"sourceCodeEnd":477,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/nlp/modeling/layers/moe.py#L441-L477","documentation":"Error \"Input shape {input_shape} is inconsistent with num_experts {self.num_experts}.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/nlp/modeling/layers/moe.py:459 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"}