Function load_head_from_pretrained_model

code/ASR/Adapter/utils.py:10–20

(model, model_path)

def load_head_from_pretrained_model(model, model_path):
    model_dict = torch.load(model_path, map_location=lambda storage, loc: storage)
    if "model" in model_dict.keys():
        model_dict = model_dict["model"]
    src_dict = {k: v for k, v in model_dict.items() if "decoder.embed." in k or "ctc." in k or "decoder.output_layer." in k}
    dst_state = model.state_dict()
    dst_state.update(src_dict)
    for key in dst_state.keys():
        if key in src_dict.keys():
            logging.info("loading " + key)
    model.load_state_dict(dst_state)

def load_adapter_from_pretrained_model(model, model_path, src_adapter, tgt_adapter):
    '''