{"record":{"id":"a02ef6231feba940","repo":"tensorflow/models","slug":"unknown-model-name","errorCode":null,"errorMessage":"Unknown model name {}","messagePattern":"Unknown model name (.+?)","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/legacy/image_classification/efficientnet/efficientnet_model.py","lineNumber":485,"sourceCode":"\n    Args:\n      model_name: the predefined model name\n      model_weights_path: the path to the weights (h5 file or saved model dir)\n      weights_format: the model weights format. One of 'saved_model', 'h5', or\n        'checkpoint'.\n      overrides: (optional) a dict containing keys that can override config\n\n    Returns:\n      A constructed EfficientNet instance.\n    \"\"\"\n    model_configs = dict(MODEL_CONFIGS)\n    overrides = dict(overrides) if overrides else {}\n\n    # One can define their own custom models if necessary\n    model_configs.update(overrides.pop('model_config', {}))\n\n    if model_name not in model_configs:\n      raise ValueError('Unknown model name {}'.format(model_name))\n\n    config = model_configs[model_name]\n\n    model = cls(config=config, overrides=overrides)\n\n    if model_weights_path:\n      common_modules.load_weights(\n          model, model_weights_path, weights_format=weights_format)\n\n    return model\n","sourceCodeStart":467,"sourceCodeEnd":496,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/legacy/image_classification/efficientnet/efficientnet_model.py#L467-L496","documentation":"Error \"Unknown model name {}\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/legacy/image_classification/efficientnet/efficientnet_model.py:485 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"}