| | |
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| | | from funasr.download.file import download_from_url |
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| | | from funasr.auto.auto_model import prepare_data_iterator |
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| | | from funasr.utils.timestamp_tools import timestamp_sentence |
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| | | from funasr.download.download_from_hub import download_model |
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| | | from funasr.download.download_model_from_hub import download_model |
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| | | from funasr.utils.vad_utils import slice_padding_audio_samples |
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| | | from funasr.train_utils.set_all_random_seed import set_all_random_seed |
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| | | from funasr.train_utils.load_pretrained_model import load_pretrained_model |
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| | |
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| | | |
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| | | result_list = [] |
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| | | num_samples = len(data_list) |
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| | | pbar = tqdm(colour="blue", total=num_samples + 1, dynamic_ncols=True) |
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| | | # pbar = tqdm(colour="blue", total=num_samples + 1, dynamic_ncols=True) |
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| | | |
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| | | time0 = time.perf_counter() |
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| | | for beg_idx in range(0, num_samples, batch_size): |
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| | |
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| | | "input": speech, |
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| | | "input_len": speech_lengths, |
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| | | "key": key_batch, |
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| | | data_type: "fbank", |
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| | | "data_type": "fbank", |
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| | | } |
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| | | result_list.append(batch) |
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| | | |
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| | | pbar.update(1) |
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| | | description = f"{meta_data}, " |
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| | | pbar.set_description(description) |
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| | | # pbar.update(1) |
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| | | # description = f"{meta_data}, " |
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| | | # pbar.set_description(description) |
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| | | |
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| | | time_end = time.perf_counter() |
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| | | pbar.set_description(f"time escaped total: {time_end - time0:0.3f}") |
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| | | # pbar.set_description(f"time escaped total: {time_end - time0:0.3f}") |
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| | | |
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| | | return result_list |
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