在网络最后加一个训练好的mlp层并将其参数冻结

在网络最后加一个训练好的mlp层并将其参数冻结

for key in model.mlp.state_dict():
    if key in backbone_file:
        model.mlp.state_dict()[key] = backbone_file[key]

for (name, param) in model.mlp.named_parameters():
    if name in backbone_file:
        param.requires_grad = False

optimizer = AdamW(filter(lambda p: p.requires_grad, model.parameters()), lr=args.LR, weight_decay=args.WEIGHT_DECAY)