import os import json from omegaconf import OmegaConf from funasr_detach.download.name_maps_from_hub import name_maps_ms, name_maps_hf def download_model(**kwargs): model_hub = kwargs.get("model_hub", "ms") if model_hub == "ms": kwargs = download_from_ms(**kwargs) return kwargs def download_from_ms(**kwargs): model_or_path = kwargs.get("model") if model_or_path in name_maps_ms: model_or_path = name_maps_ms[model_or_path] model_revision = kwargs.get("model_revision") if not os.path.exists(model_or_path): model_or_path = get_or_download_model_dir( model_or_path, model_revision, is_training=kwargs.get("is_training"), check_latest=kwargs.get("kwargs", True), ) kwargs["model_path"] = model_or_path if os.path.exists(os.path.join(model_or_path, "configuration.json")): with open( os.path.join(model_or_path, "configuration.json"), "r", encoding="utf-8" ) as f: conf_json = json.load(f) cfg = {} add_file_root_path(model_or_path, conf_json["file_path_metas"], cfg) cfg.update(kwargs) config = OmegaConf.load(cfg["config"]) kwargs = OmegaConf.merge(config, cfg) kwargs["model"] = config["model"] elif os.path.exists(os.path.join(model_or_path, "config.yaml")) and os.path.exists( os.path.join(model_or_path, "model.pt") ): config = OmegaConf.load(os.path.join(model_or_path, "config.yaml")) kwargs = OmegaConf.merge(config, kwargs) init_param = os.path.join(model_or_path, "model.pb") kwargs["init_param"] = init_param if os.path.exists(os.path.join(model_or_path, "tokens.txt")): kwargs["tokenizer_conf"]["token_list"] = os.path.join( model_or_path, "tokens.txt" ) if os.path.exists(os.path.join(model_or_path, "tokens.json")): kwargs["tokenizer_conf"]["token_list"] = os.path.join( model_or_path, "tokens.json" ) if os.path.exists(os.path.join(model_or_path, "seg_dict")): kwargs["tokenizer_conf"]["seg_dict"] = os.path.join( model_or_path, "seg_dict" ) if os.path.exists(os.path.join(model_or_path, "bpe.model")): kwargs["tokenizer_conf"]["bpemodel"] = os.path.join( model_or_path, "bpe.model" ) kwargs["model"] = config["model"] if os.path.exists(os.path.join(model_or_path, "am.mvn")): kwargs["frontend_conf"]["cmvn_file"] = os.path.join(model_or_path, "am.mvn") if os.path.exists(os.path.join(model_or_path, "jieba_usr_dict")): kwargs["jieba_usr_dict"] = os.path.join(model_or_path, "jieba_usr_dict") return OmegaConf.to_container(kwargs, resolve=True) def add_file_root_path(model_or_path: str, file_path_metas: dict, cfg={}): if isinstance(file_path_metas, dict): for k, v in file_path_metas.items(): if isinstance(v, str): p = os.path.join(model_or_path, v) if os.path.exists(p): cfg[k] = p elif isinstance(v, dict): if k not in cfg: cfg[k] = {} add_file_root_path(model_or_path, v, cfg[k]) return cfg def get_or_download_model_dir( model, model_revision=None, is_training=False, check_latest=True, ): """Get local model directory or download model if necessary. Args: model (str): model id or path to local model directory. model_revision (str, optional): model version number. :param is_training: """ from modelscope.hub.check_model import check_local_model_is_latest from modelscope.hub.snapshot_download import snapshot_download from modelscope.utils.constant import Invoke, ThirdParty key = Invoke.LOCAL_TRAINER if is_training else Invoke.PIPELINE if os.path.exists(model) and check_latest: model_cache_dir = model if os.path.isdir(model) else os.path.dirname(model) try: check_local_model_is_latest( model_cache_dir, user_agent={Invoke.KEY: key, ThirdParty.KEY: "funasr"} ) except: print("could not check the latest version") else: model_cache_dir = snapshot_download( model, revision=model_revision, user_agent={Invoke.KEY: key, ThirdParty.KEY: "funasr"}, ) return model_cache_dir