| | |
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| | | from funasr.models.campplus.cluster_backend import ClusterBackend |
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| | | except: |
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| | | print("If you want to use the speaker diarization, please `pip install hdbscan`") |
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| | | import pdb |
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| | | |
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| | | |
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| | | def prepare_data_iterator(data_in, input_len=None, data_type=None, key=None): |
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| | | """ |
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| | |
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| | | chars = string.ascii_letters + string.digits |
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| | | if isinstance(data_in, str) and data_in.startswith('http'): # url |
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| | | data_in = download_from_url(data_in) |
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| | | |
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| | | if isinstance(data_in, str) and os.path.exists(data_in): # wav_path; filelist: wav.scp, file.jsonl;text.txt; |
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| | | _, file_extension = os.path.splitext(data_in) |
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| | | file_extension = file_extension.lower() |
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| | |
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| | | kwargs = download_model(**kwargs) |
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| | | |
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| | | set_all_random_seed(kwargs.get("seed", 0)) |
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| | | |
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| | | |
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| | | device = kwargs.get("device", "cuda") |
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| | | if not torch.cuda.is_available() or kwargs.get("ngpu", 1) == 0: |
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| | | device = "cpu" |
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| | |
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| | | vocab_size = len(kwargs["token_list"]) if kwargs["token_list"] is not None else -1 |
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| | | else: |
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| | | vocab_size = -1 |
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| | | |
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| | | # build frontend |
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| | | frontend = kwargs.get("frontend", None) |
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| | | kwargs["input_size"] = None |
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| | |
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| | | # build model |
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| | | model_class = tables.model_classes.get(kwargs["model"]) |
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| | | model = model_class(**kwargs, **kwargs["model_conf"], vocab_size=vocab_size) |
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| | | |
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| | | model.to(device) |
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| | | |
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| | | # init_param |
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| | |
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| | | batch_size = kwargs.get("batch_size", 1) |
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| | | # if kwargs.get("device", "cpu") == "cpu": |
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| | | # batch_size = 1 |
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| | | |
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| | | |
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| | | key_list, data_list = prepare_data_iterator(input, input_len=input_len, data_type=kwargs.get("data_type", None), key=key) |
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| | | |
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| | | |
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| | | speed_stats = {} |
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| | | asr_result_list = [] |
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| | | num_samples = len(data_list) |
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| | |
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| | | data_batch = data_list[beg_idx:end_idx] |
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| | | key_batch = key_list[beg_idx:end_idx] |
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| | | batch = {"data_in": data_batch, "key": key_batch} |
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| | | |
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| | | if (end_idx - beg_idx) == 1 and kwargs.get("data_type", None) == "fbank": # fbank |
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| | | batch["data_in"] = data_batch[0] |
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| | | batch["data_lengths"] = input_len |
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