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https://github.com/modelscope/FunASR
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@ -29,7 +29,6 @@ def gen_jsonl_from_wav_text_list(
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with open(data_file, "r") as f:
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data_file_lists = f.readlines()
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print("")
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lines_for_each_th = (len(data_file_lists) - 1) // cpu_cores + 1
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task_num = cpu_cores if len(data_file_lists) > cpu_cores else 1
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# import pdb;pdb.set_trace()
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@ -7,31 +7,68 @@ from omegaconf import DictConfig, OmegaConf
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import concurrent.futures
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import librosa
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import torch.distributed as dist
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import threading
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from tqdm import tqdm
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from concurrent.futures import ThreadPoolExecutor
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def gen_scp_from_jsonl(jsonl_file, data_type_list, wav_scp_file, text_file):
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wav_f = open(wav_scp_file, "w")
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text_f = open(text_file, "w")
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def gen_scp_from_jsonl(jsonl_file, jsonl_file_out, ncpu):
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jsonl_file_out_f = open(jsonl_file_out, "w")
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with open(jsonl_file, encoding="utf-8") as fin:
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for line in fin:
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data = json.loads(line.strip())
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lines = fin.readlines()
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prompt = data.get("prompt", "<ASR>")
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source = data[data_type_list[0]]
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target = data[data_type_list[1]]
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source_len = data.get("source_len", 1)
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target_len = data.get("target_len", 0)
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if "aishell" in source:
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target = target.replace(" ", "")
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key = data["key"]
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wav_f.write(f"{key}\t{source}\n")
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wav_f.flush()
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text_f.write(f"{key}\t{target}\n")
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text_f.flush()
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num_total = len(lines)
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if ncpu > 1:
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# 使用ThreadPoolExecutor限制并发线程数
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with ThreadPoolExecutor(max_workers=ncpu) as executor:
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# 提交任务到线程池
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futures = {executor.submit(update_data, lines, i) for i in tqdm(range(num_total))}
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wav_f.close()
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text_f.close()
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# 等待所有任务完成,这会阻塞直到所有提交的任务完成
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for future in concurrent.futures.as_completed(futures):
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# 这里可以添加额外的逻辑来处理完成的任务,但在这个例子中我们只是等待
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pass
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else:
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for i in range(num_total):
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update_data(lines, i)
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print("All audio durations have been processed.")
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for line in lines:
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jsonl_file_out_f.write(line)
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jsonl_file_out_f.flush()
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jsonl_file_out_f.close()
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def update_data(lines, i):
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line = lines[i]
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data = json.loads(line.strip())
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wav_path = data["source"].replace("/cpfs01", "/cpfs_speech/data")
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waveform, _ = librosa.load(wav_path, sr=16000)
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sample_num = len(waveform)
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source_len = int(sample_num / 16000 * 1000 / 10)
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source_len_old = data["source_len"]
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if source_len_old != source_len:
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print(f"wav: {wav_path}, old: {source_len_old}, new: {source_len}")
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data["source_len"] = source_len
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jsonl_line = json.dumps(data, ensure_ascii=False)
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lines[i] = jsonl_line
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def update_wav_len(jsonl_file_list_in, jsonl_file_out_dir, ncpu=1):
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os.makedirs(jsonl_file_out_dir, exist_ok=True)
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with open(jsonl_file_list_in, "r") as f:
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data_file_lists = f.readlines()
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for i, jsonl in enumerate(data_file_lists):
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filename_with_extension = os.path.basename(jsonl.strip())
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jsonl_file_out = os.path.join(jsonl_file_out_dir, filename_with_extension)
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print(f"{i}/{len(data_file_lists)}, jsonl: {jsonl}, {jsonl_file_out}")
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gen_scp_from_jsonl(jsonl.strip(), jsonl_file_out, ncpu)
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@hydra.main(config_name=None, version_base=None)
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@ -40,17 +77,13 @@ def main_hydra(cfg: DictConfig):
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kwargs = OmegaConf.to_container(cfg, resolve=True)
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print(kwargs)
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scp_file_list = kwargs.get(
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"scp_file_list",
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("/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"),
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jsonl_file_list_in = kwargs.get(
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"jsonl_file_list_in", "/Users/zhifu/funasr1.0/data/list/data_jsonl.list"
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)
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if isinstance(scp_file_list, str):
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scp_file_list = eval(scp_file_list)
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data_type_list = kwargs.get("data_type_list", ("source", "target"))
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jsonl_file = kwargs.get(
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"jsonl_file_in", "/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl"
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)
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gen_scp_from_jsonl(jsonl_file, data_type_list, *scp_file_list)
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jsonl_file_out_dir = kwargs.get("jsonl_file_out_dir", "/Users/zhifu/funasr1.0/data_tmp")
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ncpu = kwargs.get("ncpu", 1)
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update_wav_len(jsonl_file_list_in, jsonl_file_out_dir, ncpu)
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# gen_scp_from_jsonl(jsonl_file_list_in, jsonl_file_out_dir)
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"""
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