yolo 自带的模型大小减半方法

def strip_optimizer(path, f='weights/best.pt', s=''):  # from yolo_utils.general import *; strip_optimizer()
    # Strip optimizer from 'f' to finalize training, optionally save as 's'
    x = torch.load(f, map_location=torch.device('cpu'))

    for key in 'optimizer', 'training_results', 'wandb_id':
        x[key] = None
    x['epoch'] = -1
    x["model"].half()  # to FP16
    for p in x["model"].parameters():
        p.requires_grad = False
    # torch.save(x, s or f)
    torch.save(x, path)
    # mb = os.path.getsize(s or f) / 1E6  # filesize
    # print('Optimizer stripped from %s,%s %.1fMB' % (f, (' saved as %s,' % s) if s else '', mb))