{"record":{"id":"27549a60d62d5430","repo":"tensorflow/models","slug":"input-should-have-rank-got","errorCode":null,"errorMessage":"Input should have rank {}, got {}","messagePattern":"Input should have rank (.+?), got (.+?)","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/vision/modeling/layers/nn_layers.py","lineNumber":819,"sourceCode":"  def get_config(self):\n    \"\"\"Returns a dictionary containing the config used for initialization.\"\"\"\n    config = {\n        'keepdims': self._keepdims,\n    }\n    base_config = super(SpatialAveragePool3D, self).get_config()\n    return dict(list(base_config.items()) + list(config.items()))\n\n  def build(self, input_shape):\n    \"\"\"Builds the layer with the given input shape.\"\"\"\n    if tf_keras.backend.image_data_format() == 'channels_first':\n      raise ValueError('\"channels_first\" mode is unsupported.')\n\n    super(SpatialAveragePool3D, self).build(input_shape)\n\n  def call(self, inputs, states=None, output_states: bool = False):\n    \"\"\"Calls the layer with the given inputs.\"\"\"\n    if inputs.shape.rank != 5:\n      raise ValueError(\n          'Input should have rank {}, got {}'.format(5, inputs.shape.rank))\n\n    output = tf.reduce_mean(inputs, axis=(2, 3), keepdims=self._keepdims)\n    return (output, states) if output_states else output\n\n\nclass CausalConvMixin:\n  \"\"\"Mixin class to implement CausalConv for `tf_keras.layers.Conv` layers.\"\"\"\n\n  @property\n  def use_buffered_input(self) -> bool:\n    return self._use_buffered_input\n\n  @use_buffered_input.setter\n  def use_buffered_input(self, variable: bool):\n    self._use_buffered_input = variable\n\n  def _compute_buffered_causal_padding(self,","sourceCodeStart":801,"sourceCodeEnd":837,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/vision/modeling/layers/nn_layers.py#L801-L837","documentation":"Error \"Input should have rank {}, got {}\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/vision/modeling/layers/nn_layers.py:819 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":["Pass an input tensor whose rank equals the expected rank shown in the error.","Add or remove dimensions (e.g. with tf.expand_dims or tf.squeeze) to match the expected rank."],"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"}