{"record":{"id":"709495eaeb3c67f1","repo":"tensorflow/models","slug":"the-min-level-must-be-1-but-found","errorCode":null,"errorMessage":"The min_level must be >= 1, but {} found.","messagePattern":"The min_level must be >= 1, but (.+?) found\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/projects/pointpillars/modeling/backbones.py","lineNumber":72,"sourceCode":"        Conv2D. Default to None.\n      **kwargs: Additional keyword arguments to be passed.\n\n    Returns:\n      endpoints: A `dict` of {level: Tensor} pairs for the model output.\n      output_specs: A dict of {level: TensorShape} pairs for the model output.\n    \"\"\"\n    utils.assert_channels_last()\n\n    self._config_dict = {\n        'input_specs': input_specs,\n        'min_level': min_level,\n        'max_level': max_level,\n        'num_convs': num_convs,\n        'kernel_regularizer': kernel_regularizer,\n    }\n    # Onlly allow to output from level 1.\n    if min_level < 1:\n      raise ValueError(\n          'The min_level must be >= 1, but {} found.'.format(min_level))\n\n    input_channels = input_specs[-1]\n    inputs = tf_keras.Input(shape=input_specs[1:])\n\n    # build the net\n    x = inputs\n    net = {}\n    scale = 1\n    for level in range(1, max_level + 1):\n      x = self._block_group(\n          inputs=x,\n          filters=input_channels * scale)\n      scale *= 2\n      net[level] = x\n\n    # build endpoints\n    endpoints = {}","sourceCodeStart":54,"sourceCodeEnd":90,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/projects/pointpillars/modeling/backbones.py#L54-L90","documentation":"Error \"The min_level must be >= 1, but {} found.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/projects/pointpillars/modeling/backbones.py:72 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"}