{"record":{"id":"834610f17b8917fb","repo":"tensorflow/models","slug":"when-passing-a-mask-tensor-to-tntransformerexpandc","errorCode":null,"errorMessage":"When passing a mask tensor to TNTransformerExpandCondense, the mask tensor must be of shape [batch, sequence_length, sequence_length] (here %s). Got a mask tensor of shape %s.","messagePattern":"When passing a mask tensor to TNTransformerExpandCondense, the mask tensor must be of shape \\[batch, sequence_length, sequence_length\\] \\(here (.+?)\\)\\. Got a mask tensor of shape (.+?)\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/nlp/modeling/layers/tn_transformer_expand_condense.py","lineNumber":119,"sourceCode":"    else:\n      self._attention_initializer = tf_utils.clone_initializer(\n          self._kernel_initializer)\n\n  def build(self, input_shape):\n    input_tensor = input_shape[0] if len(input_shape) == 2 else input_shape\n    input_tensor_shape = tf.TensorShape(input_tensor)\n    if len(input_tensor_shape.as_list()) != 3:\n      raise ValueError(\n          \"TNTransformerExpandCondense expects a three-dimensional input of \"\n          \"shape [batch, sequence, width].\")\n    batch_size, sequence_length, hidden_size = input_tensor_shape\n\n    if len(input_shape) == 2:\n      mask_tensor_shape = tf.TensorShape(input_shape[1])\n      expected_mask_tensor_shape = tf.TensorShape(\n          [batch_size, sequence_length, sequence_length])\n      if not expected_mask_tensor_shape.is_compatible_with(mask_tensor_shape):\n        raise ValueError(\n            \"When passing a mask tensor to TNTransformerExpandCondense, the \"\n            \"mask tensor must be of shape [batch, \"\n            \"sequence_length, sequence_length] (here %s). Got a \"\n            \"mask tensor of shape %s.\" %\n            (expected_mask_tensor_shape, mask_tensor_shape))\n    if hidden_size % self._num_heads != 0:\n      raise ValueError(\n          \"The input size (%d) is not a multiple of the number of attention \"\n          \"heads (%d)\" % (hidden_size, self._num_heads))\n    self._attention_head_size = int(hidden_size // self._num_heads)\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,\n        bias_constraint=self._bias_constraint)\n    self._attention_layer = tf_keras.layers.MultiHeadAttention(\n        num_heads=self._num_heads,","sourceCodeStart":101,"sourceCodeEnd":137,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/nlp/modeling/layers/tn_transformer_expand_condense.py#L101-L137","documentation":"Error \"When passing a mask tensor to TNTransformerExpandCondense, the mask tensor must be of shape [batch, sequence_length, sequence_length] (here %s). Got a mask tensor of shape %s.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/nlp/modeling/layers/tn_transformer_expand_condense.py:119 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"}