我在训练yolov7时，之前显示错误 subprocess.CalledProcessError: Command 'git tag' returned non-zero exit status 1.，但是我下载预训练权重并执行了pip install wandb之后，显示为：
YOLOR 2022-10-6 torch 1.8.0+cpu CPU
Traceback (most recent call last):
File "D:/graduation thesis/yolov7-main/train.py", line 616, in
train(hyp, opt, device, tb_writer)
File "D:/graduation thesis/yolov7-main/train.py", line 72, in train
wandb_logger = WandbLogger(opt, Path(opt.save_dir).stem, run_id, data_dict)
File "D:\graduation thesis\yolov7-main\utils\wandb_logging\wandb_utils.py", line 95, in init
self.wandb_run = wandb.init(config=opt,
File "C:\ProgramData\Anaconda3\lib\site-packages\wandb\sdk\wandb_init.py", line 1075, in init
wi.setup(kwargs)
File "C:\ProgramData\Anaconda3\lib\site-packages\wandb\sdk\wandb_init.py", line 274, in setup
wandb_login._login(
File "C:\ProgramData\Anaconda3\lib\site-packages\wandb\sdk\wandb_login.py", line 298, in _login
wlogin.prompt_api_key()
File "C:\ProgramData\Anaconda3\lib\site-packages\wandb\sdk\wandb_login.py", line 228, in prompt_api_key
raise UsageError("api_key not configured (no-tty). call " + directive)
wandb.errors.UsageError: api_key not configured (no-tty). call wandb.login(key=[your_api_key])
parser = argparse.ArgumentParser()
parser.add_argument('--weights', type=str, default='yolov7_training.pt', help='initial weights path')
parser.add_argument('--cfg', type=str, default='training/yolov7.yaml', help='model.yaml path')
parser.add_argument('--data', type=str, default='data/coco.yaml', help='data.yaml path')
parser.add_argument('--hyp', type=str, default='data/hyp.scratch.p5.yaml', help='hyperparameters path')
parser.add_argument('--epochs', type=int, default=300)
parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs')
parser.add_argument('--img-size', nargs='+', type=int, default=[640, 640], help='[train, test] image sizes')
parser.add_argument('--rect', action='store_true', help='rectangular training')
parser.add_argument('--resume', nargs='?', const=True, default=False, help='resume most recent training')
parser.add_argument('--nosave', action='store_true', help='only save final checkpoint')
parser.add_argument('--notest', action='store_true', help='only test final epoch')
parser.add_argument('--noautoanchor', action='store_true', help='disable autoanchor check')
parser.add_argument('--evolve', action='store_true', help='evolve hyperparameters')
parser.add_argument('--bucket', type=str, default='', help='gsutil bucket')
parser.add_argument('--cache-images', action='store_true', help='cache images for faster training')
parser.add_argument('--image-weights', action='store_true', help='use weighted image selection for training')
parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
parser.add_argument('--multi-scale', action='store_true', help='vary img-size +/- 50%%')
parser.add_argument('--single-cls', action='store_true', help='train multi-class data as single-class')
parser.add_argument('--adam', action='store_true', help='use torch.optim.Adam() optimizer')
parser.add_argument('--sync-bn', action='store_true', help='use SyncBatchNorm, only available in DDP mode')
parser.add_argument('--local_rank', type=int, default=-1, help='DDP parameter, do not modify')
parser.add_argument('--workers', type=int, default=8, help='maximum number of dataloader workers')
parser.add_argument('--project', default='runs/train', help='save to project/name')
parser.add_argument('--entity', default=None, help='W&B entity')
parser.add_argument('--name', default='exp', help='save to project/name')
parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')
parser.add_argument('--quad', action='store_true', help='quad dataloader')
parser.add_argument('--linear-lr', action='store_true', help='linear LR')
parser.add_argument('--label-smoothing', type=float, default=0.0, help='Label smoothing epsilon')
parser.add_argument('--upload_dataset', action='store_true', help='Upload dataset as W&B artifact table')
parser.add_argument('--bbox_interval', type=int, default=-1, help='Set bounding-box image logging interval for W&B')
parser.add_argument('--save_period', type=int, default=-1, help='Log model after every "save_period" epoch')
parser.add_argument('--artifact_alias', type=str, default="latest", help='version of dataset artifact to be used')
parser.add_argument('--freeze', nargs='+', type=int, default=[0], help='Freeze layers: backbone of yolov7=50, first3=0 1 2')
parser.add_argument('--v5-metric', action='store_true', help='assume maximum recall as 1.0 in AP calculation')
opt = parser.parse_args()
