def set_weight_decay()

in src/transformers/utils/optimizer.py [0:0]

• 13 lines of code
• 7 McCabe index (conditional complexity)

def set_weight_decay(model, skip_list=(), skip_keywords=()):
    has_decay = []
    no_decay = []

    for name, param in model.named_parameters():
        if not param.requires_grad:
            continue  # frozen weights
        if len(param.shape) == 1 or name.endswith(".bias") or (name in skip_list) or \
                check_keywords_in_name(name, skip_keywords):
            no_decay.append(param)
            # print(f"{name} has no weight decay")
        else:
            has_decay.append(param)
    return [{'params': has_decay},
            {'params': no_decay, 'weight_decay': 0.}]