{"record":{"id":"dc88a300e2ecc030","repo":"huggingface/pytorch-image-models","slug":"invalid-beta-parameter-at-index-0-dc88a3","errorCode":null,"errorMessage":"Invalid beta parameter at index 0: {}","messagePattern":"Invalid beta parameter at index 0: (.+?)","errorType":"validation","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"timm/optim/nvnovograd.py","lineNumber":47,"sourceCode":"            (default: False)\n    \"\"\"\n\n    def __init__(\n            self,\n            params,\n            lr=1e-3,\n            betas=(0.95, 0.98),\n            eps=1e-8,\n            weight_decay=0,\n            grad_averaging=False,\n            amsgrad=False,\n    ):\n        if not 0.0 <= lr:\n            raise ValueError(\"Invalid learning rate: {}\".format(lr))\n        if not 0.0 <= eps:\n            raise ValueError(\"Invalid epsilon value: {}\".format(eps))\n        if not 0.0 <= betas[0] < 1.0:\n            raise ValueError(\"Invalid beta parameter at index 0: {}\".format(betas[0]))\n        if not 0.0 <= betas[1] < 1.0:\n            raise ValueError(\"Invalid beta parameter at index 1: {}\".format(betas[1]))\n        defaults = dict(\n            lr=lr,\n            betas=betas,\n            eps=eps,\n            weight_decay=weight_decay,\n            grad_averaging=grad_averaging,\n            amsgrad=amsgrad,\n        )\n\n        super(NvNovoGrad, self).__init__(params, defaults)\n\n    def __setstate__(self, state):\n        super(NvNovoGrad, self).__setstate__(state)\n        for group in self.param_groups:\n            group.setdefault('amsgrad', False)\n","sourceCodeStart":29,"sourceCodeEnd":65,"githubUrl":"https://github.com/huggingface/pytorch-image-models/blob/9a5261e31b3b5128526eb2658333b4c0a54464ae/timm/optim/nvnovograd.py#L29-L65","documentation":"Nvnovograd constructor validation: betas[0] must satisfy 0.0 <= beta1 < 1.0. Out-of-range momentum decay breaks the running gradient-norm average.","triggerScenarios":"Calling timm.optim.Nvnovograd(params, betas=(1.0, 0.999)) or negative beta1.","commonSituations":"Hyperparameter sweeps crossing the boundary, betas copied from incompatible optimizers.","solutions":["Use betas like (0.9, 0.999)","Bound beta1 to [0,1) in sweep configs"],"exampleFix":"# before\nopt = Nvnovograd(model.parameters(), betas=(1.0, 0.999))\n\n# after\nopt = Nvnovograd(model.parameters(), betas=(0.9, 0.999))","handlingStrategy":"validation","validationCode":"assert 0.0 <= betas[0] < 1.0","typeGuard":null,"tryCatchPattern":null,"preventionTips":["Bound beta1 in [0,1)"],"tags":["timm","nvnovograd","betas","valueerror"],"backgroundTag":"invalid-optimizer-hyperparameter","analyzedSha":"9a5261e31b3b5128526eb2658333b4c0a54464ae","analyzedAt":"2026-08-27T02:34:25.417Z","schemaVersion":2},"datasetVersion":"2026-08-27T03:17:27.898Z"}