import os
|
import json
|
import torch
|
import logging
|
import hydra
|
from omegaconf import DictConfig, OmegaConf
|
import concurrent.futures
|
import librosa
|
import torch.distributed as dist
|
|
|
|
def gen_jsonl_from_wav_text_list(path, data_type_list=("source", "target"), jsonl_file_out:str=None, **kwargs):
|
try:
|
rank = dist.get_rank()
|
world_size = dist.get_world_size()
|
except:
|
rank = 0
|
world_size = 1
|
|
cpu_cores = os.cpu_count() or 1
|
|
if rank == 0:
|
json_dict = {}
|
for data_type, data_file in zip(data_type_list, path):
|
json_dict[data_type] = {}
|
with open(data_file, "r") as f:
|
|
data_file_lists = f.readlines()
|
lines_for_each_th = (len(data_file_lists)-1)//cpu_cores + 1
|
task_num = cpu_cores if len(data_file_lists) > cpu_cores else 1
|
with concurrent.futures.ThreadPoolExecutor(max_workers=cpu_cores) as executor:
|
|
futures = [executor.submit(parse_context_length, data_file_lists[i*lines_for_each_th:(i+1)*lines_for_each_th], data_type) for i in range(task_num)]
|
|
for future in concurrent.futures.as_completed(futures):
|
|
json_dict[data_type].update(future.result())
|
# print(json_dict)
|
|
with open(jsonl_file_out, "w") as f:
|
for key in json_dict[data_type_list[0]].keys():
|
jsonl_line = {"key": key}
|
for data_file in data_type_list:
|
jsonl_line.update(json_dict[data_file][key])
|
jsonl_line = json.dumps(jsonl_line, ensure_ascii=False)
|
f.write(jsonl_line+"\n")
|
f.flush()
|
|
else:
|
pass
|
|
if world_size > 1:
|
dist.barrier()
|
|
|
def parse_context_length(data_list: list, data_type: str):
|
|
res = {}
|
for i, line in enumerate(data_list):
|
key, line = line.strip().split(maxsplit=1)
|
line = line.strip()
|
if os.path.exists(line):
|
waveform, _ = librosa.load(line, sr=16000)
|
sample_num = len(waveform)
|
context_len = int(sample_num//16000*1000/10)
|
else:
|
context_len = len(line)
|
res[key] = {data_type: line, f"{data_type}_len": context_len}
|
return res
|
|
|
@hydra.main(config_name=None, version_base=None)
|
def main_hydra(cfg: DictConfig):
|
"""
|
python funasr/datasets/audio_datasets/scp2jsonl.py \
|
++scp_file_list='["/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"]' \
|
++data_type_list='["source", "target"]' \
|
++jsonl_file_out=/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl
|
|
"""
|
|
kwargs = OmegaConf.to_container(cfg, resolve=True)
|
|
scp_file_list = kwargs.get("scp_file_list", ("/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"))
|
data_type_list = kwargs.get("data_type_list", ("source", "target"))
|
jsonl_file_out = kwargs.get("jsonl_file_out", "/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl")
|
gen_jsonl_from_wav_text_list(scp_file_list, data_type_list=data_type_list, jsonl_file_out=jsonl_file_out)
|
|
|
if __name__ == "__main__":
|
main_hydra()
|
|
|
