mirror of
https://github.com/FunAudioLLM/CosyVoice.git
synced 2026-02-05 18:09:24 +08:00
fix lint
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@@ -18,16 +18,15 @@ import argparse
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import logging
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logging.getLogger('matplotlib').setLevel(logging.WARNING)
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import os
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import torch
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from torch.utils.data import DataLoader
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import torchaudio
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from hyperpyyaml import load_hyperpyyaml
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from tqdm import tqdm
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from cosyvoice.cli.model import CosyVoiceModel
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from cosyvoice.dataset.dataset import Dataset
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def get_args():
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parser = argparse.ArgumentParser(description='inference with your model')
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parser.add_argument('--config', required=True, help='config file')
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@@ -66,7 +65,8 @@ def main():
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model = CosyVoiceModel(configs['llm'], configs['flow'], configs['hift'])
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model.load(args.llm_model, args.flow_model, args.hifigan_model)
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test_dataset = Dataset(args.prompt_data, data_pipeline=configs['data_pipeline'], mode='inference', shuffle=False, partition=False, tts_file=args.tts_text, prompt_utt2data=args.prompt_utt2data)
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test_dataset = Dataset(args.prompt_data, data_pipeline=configs['data_pipeline'], mode='inference', shuffle=False, partition=False,
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tts_file=args.tts_text, prompt_utt2data=args.prompt_utt2data)
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test_data_loader = DataLoader(test_dataset, batch_size=None, num_workers=0)
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del configs
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@@ -74,13 +74,11 @@ def main():
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fn = os.path.join(args.result_dir, 'wav.scp')
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f = open(fn, 'w')
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with torch.no_grad():
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for batch_idx, batch in tqdm(enumerate(test_data_loader)):
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for _, batch in tqdm(enumerate(test_data_loader)):
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utts = batch["utts"]
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assert len(utts) == 1, "inference mode only support batchsize 1"
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text = batch["text"]
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text_token = batch["text_token"].to(device)
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text_token_len = batch["text_token_len"].to(device)
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tts_text = batch["tts_text"]
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tts_index = batch["tts_index"]
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tts_text_token = batch["tts_text_token"].to(device)
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tts_text_token_len = batch["tts_text_token_len"].to(device)
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