25c64fdd9a89337c9eacac730912ba275dbaae8c,torchreid/utils/torchtools.py,,resume_from_checkpoint,#Any#Any#Any#,37

Before Change

def resume_from_checkpoint(ckpt_path, model, optimizer=None):
    print("Loading checkpoint from "{}"".format(ckpt_path))
    ckpt = torch.load(ckpt_path)
    model.load_state_dict(ckpt["state_dict"])
    print("Loaded model weights")
    if optimizer is not None:
        optimizer.load_state_dict(ckpt["optimizer"])

After Change

def resume_from_checkpoint(fpath, model, optimizer=None):
    print("Loading checkpoint from "{}"".format(fpath))
    checkpoint = load_checkpoint(fpath)
    model.load_state_dict(checkpoint["state_dict"])
    print("Loaded model weights")
    if optimizer is not None and "optimizer" in checkpoint.keys():
        optimizer.load_state_dict(checkpoint["optimizer"])

Instances