{"record":{"id":"382ee8163b61bd3e","repo":"keras-team/keras","slug":"unknown-printable-module-name-class-name-p","errorCode":null,"errorMessage":"Unknown {printable_module_name}: '{class_name}'. Please ensure you are using a `keras.utils.custom_object_scope` and that this object is included in the scope. See https://www.tensorflow.org/guide/keras/save_and_serialize#registering_the_custom_object for details.","messagePattern":"Unknown (.+?): '(.+?)'\\. Please ensure you are using a `keras\\.utils\\.custom_object_scope` and that this object is included in the scope\\. See https://www\\.tensorflow\\.org/guide/keras/save_and_serialize#registering_the_custom_object for details\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"keras/src/legacy/saving/serialization.py","lineNumber":353,"sourceCode":"):\n    \"\"\"Returns the class name and config for a serialized keras object.\"\"\"\n\n    if (\n        not isinstance(config, dict)\n        or \"class_name\" not in config\n        or \"config\" not in config\n    ):\n        raise ValueError(\n            f\"Improper config format for {config}. \"\n            \"Expecting python dict contains `class_name` and `config` as keys\"\n        )\n\n    class_name = config[\"class_name\"]\n    cls = object_registration.get_registered_object(\n        class_name, custom_objects, module_objects\n    )\n    if cls is None:\n        raise ValueError(\n            f\"Unknown {printable_module_name}: '{class_name}'. \"\n            \"Please ensure you are using a `keras.utils.custom_object_scope` \"\n            \"and that this object is included in the scope. See \"\n            \"https://www.tensorflow.org/guide/keras/save_and_serialize\"\n            \"#registering_the_custom_object for details.\"\n        )\n\n    cls_config = config[\"config\"]\n    # Check if `cls_config` is a list. If it is a list, return the class and the\n    # associated class configs for recursively deserialization. This case will\n    # happen on the old version of sequential model (e.g. `keras_version` ==\n    # \"2.0.6\"), which is serialized in a different structure, for example\n    # \"{'class_name': 'Sequential',\n    #   'config': [{'class_name': 'Embedding', 'config': ...}, {}, ...]}\".\n    if isinstance(cls_config, list):\n        return (cls, cls_config)\n\n    deserialized_objects = {}","sourceCodeStart":335,"sourceCodeEnd":371,"githubUrl":"https://github.com/keras-team/keras/blob/7a34a03db60bf60042242d6a556fc3be119046a5/keras/src/legacy/saving/serialization.py#L335-L371","documentation":"Error \"Unknown {printable_module_name}: '{class_name}'. Please ensure you are using a `keras.utils.custom_object_scope` and that this object is included in the scope. See https://www.tensorflow.org/guide/keras/save_and_serialize#registering_the_custom_object for details.\" thrown in keras-team/keras.","triggerScenarios":"Thrown at keras/src/legacy/saving/serialization.py:353 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"}