这通常涉及使用PyTorch的torch.load函数,并确保正确指定map_location参数以将模型参数映射到CPU。 将模型参数从检查点中读取出来: 加载检查点文件后,我们可以访问其中保存的模型状态字典(state_dict),这个字典包含了模型的所有参数。 将参数转换为CPU上的张量: 使用map_location参数将模型参数映射到CPU上,确保它们不会...
LightningModule): storage = _load_state(cls, checkpoint, strict=strict, **kwargs) restore_location = torch.serialization._get_restore_location(map_location) if isinstance(map_location, dict): return restore_location(storage, map_location.get(str(storage.device))) return restore_location(storage,...
checkpoint = torch.load(config.train.checkpoint.path, map_location='cpu') if 'model_state_dict' in checkpoint: model.load_state_dict(checkpoint['model_state_dict']) elif 'state_dict' in checkpoint: # Checkpoint from other author (from github) checkpoint['state_dict'].pop('decoder.last_con...
DTS_E_INPUTCOLUMNBADMAP DTS_E_INPUTCOLUMNNOTFOUND DTS_E_INPUTCOLUMNUSAGETYPENOTREADONLY DTS_E_INPUTMUSTBESORTED DTS_E_INPUTNOTKNOWN DTS_E_INPUTSNOTREADONLY DTS_E_INPUTWITHOUTPATHS DTS_E_INSERTERCANTREAD DTS_E_INSERTERCOLUMNALREADYREFERENCED DTS_E_INSERTERCOLUMNNOTREFERENCED DTS_E_INSERTERDATACOLU...
(cls, pretrained_model_name_or_path, *model_args, **kwargs) 855 state_dict = torch.load(resolved_archive_file, map_location="cpu") 856 except Exception: --> 857 raise OSError( 858 "Unable to load weights from pytorch checkpoint file. " 859 "If you tried to load a P...
DTS_E_TXCOPYMAP_INCORRECT_OUTPUT_COLUMN_MAPPING 欄位 DTS_E_TXCOPYMAP_MISMATCHED_COLUMN_METADATA 欄位 DTS_E_TXDATACONVERTSTATIC_CANTCONVERTVALUE 欄位 DTS_E_TXDATACONVERTSTATIC_DATAOVERFLOW 欄位 DTS_E_TXDATACONVERTSTATIC_SIGNMISMATCH 欄位 DTS_E_TXDATACONVERTSTATIC_TRUNCATED 欄位 DTS_E_TXDATACONV...
DTS_E_TXCHARMAPLCMAPFAILED Field DTS_E_TXCOPYMAP_INCORRECT_OUTPUT_COLUMN_MAPPING Field DTS_E_TXCOPYMAP_MISMATCHED_COLUMN_METADATA Field DTS_E_TXDATACONVERTSTATIC_CANTCONVERTVALUE Field DTS_E_TXDATACONVERTSTATIC_DATAOVERFLOW Field DTS_E_TXDATACONVERTSTATIC_SIGNMISMATCH Field DTS_E_TXDATACONVERTSTATIC...
checkpoint = torch.load(filepath, map_location='cpu') model = checkpoint['model'] model.classifier = checkpoint['classifier'] model.load_state_dict(checkpoint['state_dict'], strict=False) model.class_to_idx = checkpoint['class_to_idx'] ...
load.LoadMap(map); load.LoadPlayer(player); load.Close();map.NewMap(levels.levels[newMapId]); enemies.PopulateEnemies(&map, &graphics); gameStates.NewState(GSGame); musicHandler.SetNewMusic(&sounds.forest); player.Reset(map.GetSpawnLocation(),false); ...
fit(model, dm) in eval.py model = Model.load_from_checkpoint( checkpoint_path=args.path_to_model, map_location=device ).eval() trainer = pl.Trainer( devices=[1], accelerator=config["accelerator"], ) dm = DataModule(config) dm.setup() trainer.validate(model, datamodule=dm) 👍 2 ...