ValueError: betas 必须是浮点数或张量,不能同时为两者

Traceback (most recent call last): File "/kaggle/working/GFPGAN/gfpgan/train.py", line 11, in train_pipeline(root_path) File "/usr/local/lib/python3.12/dist-packages/basicsr/train.py", line 124, in train_pipeline model = build_model(opt) File "/usr/local/lib/python3.12/dist-packages/basicsr/models/init.py", line 26, in build_model model = MODEL_REGISTRY.get(opt['model_type'])(opt) File "/kaggle/working/GFPGAN/gfpgan/models/gfpgan_model.py", line 39, in init self.init_training_settings() File "/kaggle/working/GFPGAN/gfpgan/models/gfpgan_model.py", line 147, in init_training_settings self.setup_optimizers() File "/kaggle/working/GFPGAN/gfpgan/models/gfpgan_model.py", line 165, in setup_optimizers self.optimizer_g = self.get_optimizer(optim_type, optim_params_g, lr, betas=betas) File "/usr/local/lib/python3.12/dist-packages/basicsr/models/base_model.py", line 105, in get_optimizer optimizer = torch.optim.Adam(params, lr, **kwargs) File "/usr/local/lib/python3.12/dist-packages/torch/optim/adam.py", line 72, in init raise ValueError("betas must be either both floats or both Tensors") ValueError: betas must be either both floats or both Tensors