{"record":{"id":"e40ad77c39742f51","repo":"keras-team/keras","slug":"q-must-be-in-the-interval-0-1","errorCode":null,"errorMessage":"q must be in the interval (0, 1)","messagePattern":"q must be in the interval \\(0, 1\\)","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"keras/src/losses/losses.py","lineNumber":1593,"sourceCode":"    y_pred = np.array([[0.7, 0.3], [0.2, 0.8], [0.6, 0.4], [0.4, 0.6]])\n    keras.losses.CategoricalGeneralizedCrossEntropy()(y_true, y_pred)\n    ```\n\n    References:\n        - [Zhang, Sabuncu, 2018](https://arxiv.org/abs/1805.07836)\n          (\"Generalized Cross Entropy Loss for Training\n            Deep Neural Networks with Noisy Labels\")\n    \"\"\"\n\n    def __init__(\n        self,\n        q=0.5,\n        reduction=\"sum_over_batch_size\",\n        name=\"categorical_generalized_cross_entropy\",\n        dtype=None,\n    ):\n        if not 0 < q < 1:\n            raise ValueError(\"q must be in the interval (0, 1)\")\n        super().__init__(\n            categorical_generalized_cross_entropy,\n            name=name,\n            reduction=reduction,\n            dtype=dtype,\n            q=q,\n        )\n        self.q = q\n\n    def get_config(self):\n        config = Loss.get_config(self)\n        config.update(\n            {\n                \"q\": self.q,\n            }\n        )\n        return config\n","sourceCodeStart":1575,"sourceCodeEnd":1611,"githubUrl":"https://github.com/keras-team/keras/blob/7a34a03db60bf60042242d6a556fc3be119046a5/keras/src/losses/losses.py#L1575-L1611","documentation":"Error \"q must be in the interval (0, 1)\" thrown in keras-team/keras.","triggerScenarios":"Thrown at keras/src/losses/losses.py:1593 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":"7a34a03db60bf60042242d6a556fc3be119046a5","analyzedAt":"2026-08-25T21:25:25.994Z","schemaVersion":2},"datasetVersion":"2026-08-26T02:17:13.382Z"}