{"record":{"id":"339c0f488cc572ba","repo":"tensorflow/models","slug":"if-use-dynamic-slicing-is-true-max-sequence-le","errorCode":null,"errorMessage":"If `use_dynamic_slicing` is True, `max_sequence_length` must be set.","messagePattern":"If `use_dynamic_slicing` is True, `max_sequence_length` must be set\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/nlp/modeling/networks/packed_sequence_embedding.py","lineNumber":226,"sourceCode":"      \"glorot_uniform\".\n    use_dynamic_slicing: Whether to use the dynamic slicing path.\n    max_sequence_length: The maximum size of the dynamic sequence. Only\n      applicable if `use_dynamic_slicing` is True.\n  \"\"\"\n\n  def __init__(self,\n               initializer='glorot_uniform',\n               use_dynamic_slicing=False,\n               max_sequence_length=None,\n               **kwargs):\n    # We need to have a default dtype of float32, since the inputs (which Keras\n    # usually uses to infer the dtype) will always be int32.\n    if 'dtype' not in kwargs:\n      kwargs['dtype'] = 'float32'\n\n    super().__init__(**kwargs)\n    if use_dynamic_slicing and max_sequence_length is None:\n      raise ValueError(\n          'If `use_dynamic_slicing` is True, `max_sequence_length` must be set.'\n      )\n    self._max_sequence_length = max_sequence_length\n    self._initializer = tf_keras.initializers.get(initializer)\n    self._use_dynamic_slicing = use_dynamic_slicing\n\n  def get_config(self):\n    config = {\n        'max_sequence_length': self._max_sequence_length,\n        'initializer': tf_keras.initializers.serialize(self._initializer),\n        'use_dynamic_slicing': self._use_dynamic_slicing,\n    }\n    base_config = super().get_config()\n    return dict(list(base_config.items()) + list(config.items()))\n\n  def build(self, input_shape):\n    \"\"\"Implements build() for the layer.\"\"\"\n    dimension_list = input_shape.as_list()","sourceCodeStart":208,"sourceCodeEnd":244,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/nlp/modeling/networks/packed_sequence_embedding.py#L208-L244","documentation":"Error \"If `use_dynamic_slicing` is True, `max_sequence_length` must be set.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/nlp/modeling/networks/packed_sequence_embedding.py:226 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"}