{"record":{"id":"6369844a2f526fce","repo":"microsoft/qlib","slug":"optimizer-is-not-supported-636984","errorCode":null,"errorMessage":"optimizer {} is not supported!","messagePattern":"optimizer (.+?) is not supported!","errorType":"exception","errorClass":"NotImplementedError","httpStatus":null,"severity":"error","filePath":"qlib/contrib/model/pytorch_hist.py","lineNumber":141,"sourceCode":"        if self.seed is not None:\n            np.random.seed(self.seed)\n            torch.manual_seed(self.seed)\n\n        self.HIST_model = HISTModel(\n            d_feat=self.d_feat,\n            hidden_size=self.hidden_size,\n            num_layers=self.num_layers,\n            dropout=self.dropout,\n            base_model=self.base_model,\n        )\n        self.logger.info(\"model:\\n{:}\".format(self.HIST_model))\n        self.logger.info(\"model size: {:.4f} MB\".format(count_parameters(self.HIST_model)))\n        if optimizer.lower() == \"adam\":\n            self.train_optimizer = optim.Adam(self.HIST_model.parameters(), lr=self.lr)\n        elif optimizer.lower() == \"gd\":\n            self.train_optimizer = optim.SGD(self.HIST_model.parameters(), lr=self.lr)\n        else:\n            raise NotImplementedError(\"optimizer {} is not supported!\".format(optimizer))\n\n        self.fitted = False\n        self.HIST_model.to(self.device)\n\n    @property\n    def use_gpu(self):\n        return self.device != torch.device(\"cpu\")\n\n    def mse(self, pred, label):\n        loss = (pred - label) ** 2\n        return torch.mean(loss)\n\n    def loss_fn(self, pred, label):\n        mask = ~torch.isnan(label)\n\n        if self.loss == \"mse\":\n            return self.mse(pred[mask], label[mask])\n","sourceCodeStart":123,"sourceCodeEnd":159,"githubUrl":"https://github.com/microsoft/qlib/blob/79633dd9506ea689e5400dea0197717b5b3d74b7/qlib/contrib/model/pytorch_hist.py#L123-L159","documentation":"Raised in HIST.__init__ when `optimizer` is not \"adam\" or \"gd\" (case-insensitive). HIST (graph-structured stock prediction) wires up only these two optimizers at construction; anything else raises NotImplementedError immediately.","triggerScenarios":"HIST(optimizer=\"sgd\"/\"adamw\"/..., ...) — \"sgd\" again being the common trap since qlib's alias is \"gd\". Fires during model instantiation in the workflow.","commonSituations":"Copying optimizer names from other models/papers; hyper-parameter sweeps including unsupported values.","solutions":["Use optimizer=\"adam\" or optimizer=\"gd\".","Subclass HIST to install a custom torch optimizer after super().__init__."],"exampleFix":"# before\nHIST(optimizer=\"sgd\", ...)\n\n# after\nHIST(optimizer=\"gd\", ...)","handlingStrategy":"validation","validationCode":"assert params[\"optimizer\"].lower() in {\"adam\", \"gd\"}, \"HIST supports only 'adam' and 'gd'\"","typeGuard":"def is_supported_optimizer(name: str) -> bool:\n    return isinstance(name, str) and name.lower() in {\"adam\", \"gd\"}","tryCatchPattern":"try:\n    model = HIST(**params)\nexcept NotImplementedError as e:\n    if \"optimizer\" in str(e):\n        params[\"optimizer\"] = \"adam\"\n        model = HIST(**params)\n    else:\n        raise","preventionTips":["Use 'gd' for SGD; 'sgd' is not recognized.","Validate optimizer strings against the model whitelist in your config loader."],"tags":["pytorch","qlib","optimizer","configuration"],"backgroundTag":null,"analyzedSha":"79633dd9506ea689e5400dea0197717b5b3d74b7","analyzedAt":"2026-08-15T07:01:27.511Z","schemaVersion":2},"datasetVersion":"2026-08-15T22:17:37.221Z"}