remove unnecessary file

test1.py

@@ -1,37 +0,0 @@
-import sys
-sys.path.append('third_party/Matcha-TTS')
-from cosyvoice.cli.cosyvoice import CosyVoice, CosyVoice2
-from cosyvoice.utils.file_utils import load_wav
-import torchaudio # type: ignore
-
-cosyvoice = CosyVoice2('pretrained_models/CosyVoice2-0.5B', load_jit=False, load_trt=False, fp16=False, use_flow_cache=False)
-
-# NOTE if you want to reproduce the results on https://funaudiollm.github.io/cosyvoice2, please add text_frontend=False during inference
-# zero_shot usage
-prompt_speech_16k = load_wav('./asset/zero_shot_prompt.wav', 16000)
-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)):
-    torchaudio.save('zero_shot_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
-
-# save zero_shot spk for future usage
-assert cosyvoice.add_zero_shot_spk('希望你以后能够做的比我还好呦。', prompt_speech_16k, 'my_zero_shot_spk') is True
-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。', '', '', zero_shot_spk_id='my_zero_shot_spk', stream=False)):
-    torchaudio.save('zero_shot_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
-cosyvoice.save_spkinfo()
-
-# fine grained control, for supported control, check cosyvoice/tokenizer/tokenizer.py#L248
-for i, j in enumerate(cosyvoice.inference_cross_lingual('在他讲述那个荒诞故事的过程中，他突然[laughter]停下来，因为他自己也被逗笑了[laughter]。', prompt_speech_16k, stream=False)):
-    torchaudio.save('fine_grained_control_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
-
-# instruct usage
-for i, j in enumerate(cosyvoice.inference_instruct2('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。', '用四川话说这句话', prompt_speech_16k, stream=False)):
-    torchaudio.save('instruct_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
-
-# bistream usage, you can use generator as input, this is useful when using text llm model as input
-# NOTE you should still have some basic sentence split logic because llm can not handle arbitrary sentence length
-def text_generator():
-    yield '收到好友从远方寄来的生日礼物，'
-    yield '那份意外的惊喜与深深的祝福'
-    yield '让我心中充满了甜蜜的快乐，'
-    yield '笑容如花儿般绽放。'
-for i, j in enumerate(cosyvoice.inference_zero_shot(text_generator(), '希望你以后能够做的比我还好呦。', prompt_speech_16k, stream=False)):
-    torchaudio.save('zero_shot_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)