From 3047591faddf5b234bde38065848089759f29cba Mon Sep 17 00:00:00 2001 From: "lyuxiang.lx" Date: Mon, 7 Jul 2025 14:49:51 +0800 Subject: [PATCH] fix lint --- cosyvoice/llm/llm.py | 3 ++- examples/libritts/cosyvoice/local/prepare_reject_sample.py | 5 +++-- vllm_example.py | 6 ++++-- 3 files changed, 9 insertions(+), 5 deletions(-) diff --git a/cosyvoice/llm/llm.py b/cosyvoice/llm/llm.py index e4d819d..fc82832 100644 --- a/cosyvoice/llm/llm.py +++ b/cosyvoice/llm/llm.py @@ -401,7 +401,8 @@ class Qwen2LM(TransformerLM): speech_token_combined_emb = self.speech_embedding(speech_token_combined) # 3. prepare llm_input/target - lm_target, lm_input, lm_input_len = self.prepare_lm_input_target(text_token.repeat(2, 1), text_token_emb.repeat(2, 1, 1), text_token_len.repeat(2), speech_token_combined, speech_token_combined_emb, speech_token_combined_len) + lm_target, lm_input, lm_input_len = self.prepare_lm_input_target(text_token.repeat(2, 1), text_token_emb.repeat(2, 1, 1), text_token_len.repeat(2), \ + speech_token_combined, speech_token_combined_emb, speech_token_combined_len) lm_target = lm_target.to(device) # 4. run lm forward diff --git a/examples/libritts/cosyvoice/local/prepare_reject_sample.py b/examples/libritts/cosyvoice/local/prepare_reject_sample.py index 3fe825f..065532c 100644 --- a/examples/libritts/cosyvoice/local/prepare_reject_sample.py +++ b/examples/libritts/cosyvoice/local/prepare_reject_sample.py @@ -2,7 +2,8 @@ import argparse import logging import os from tqdm import tqdm -import torch, torchaudio +import torch +import torchaudio from cosyvoice.cli.cosyvoice import CosyVoice2 from cosyvoice.utils.file_utils import load_wav @@ -30,7 +31,7 @@ def main(): if prompt_speech_16k.shape[1] >= 30 * 16000: continue speech_list = [] - for i, j in enumerate(cosyvoice.inference_zero_shot(utt2text[utt], utt2text[utt], prompt_speech_16k, stream=False, text_frontend=False)): + for _, j in enumerate(cosyvoice.inference_zero_shot(utt2text[utt], utt2text[utt], prompt_speech_16k, stream=False, text_frontend=False)): speech_list.append(j['tts_speech']) negative_wav = os.path.abspath('{}/wav/{}'.format(args.des_dir, os.path.basename(wav))) torchaudio.save(negative_wav, torch.concat(speech_list, dim=1), cosyvoice.sample_rate, backend='soundfile') diff --git a/vllm_example.py b/vllm_example.py index 4fa8d59..e613033 100644 --- a/vllm_example.py +++ b/vllm_example.py @@ -9,13 +9,15 @@ from cosyvoice.utils.file_utils import load_wav from cosyvoice.utils.common import set_all_random_seed from tqdm import tqdm + def main(): cosyvoice = CosyVoice2('pretrained_models/CosyVoice2-0.5B', load_jit=True, load_trt=True, load_vllm=True, fp16=True) prompt_speech_16k = load_wav('./asset/zero_shot_prompt.wav', 16000) for i in tqdm(range(100)): set_all_random_seed(i) - for i, j in enumerate(cosyvoice.inference_zero_shot('收到好友从远方寄来的生日礼物，那份意外的惊喜与深深的祝福让我心中充满了甜蜜的快乐，笑容如花儿般绽放。', '希望你以后能够做的比我还好呦。', prompt_speech_16k, stream=False)): + for _, _ in enumerate(cosyvoice.inference_zero_shot('收到好友从远方寄来的生日礼物，那份意外的惊喜与深深的祝福让我心中充满了甜蜜的快乐，笑容如花儿般绽放。', '希望你以后能够做的比我还好呦。', prompt_speech_16k, stream=False)): continue -if __name__=='__main__': + +if __name__ == '__main__': main()