Cloyir/index-tts2-ForDgxSpark
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Add the calculation time of each module.

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root 2025-04-15 12:48:47 +08:00
parent 6f830327d6
commit b6c11dddb9
1 changed files with 18 additions and 5 deletions
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23
indextts/infer.py
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@ -214,6 +214,9 @@ class IndexTTS:
# lang = "EN"
# lang = "ZH"
wavs = []
gpt_gen_time = 0
gpt_forward_time = 0
bigvgan_time = 0
for sent in sentences:
# sent = " ".join([char for char in sent.upper()]) if lang == "ZH" else sent.upper()
@ -236,6 +239,7 @@ class IndexTTS:
# text_len = torch.IntTensor([text_tokens.size(1)], device=text_tokens.device)
# print(text_len)
m_start_time = time.perf_counter()
with torch.no_grad():
with torch.amp.autocast(self.device, enabled=self.dtype is not None, dtype=self.dtype):
codes = self.gpt.inference_speech(auto_conditioning, text_tokens,
@ -251,6 +255,7 @@ class IndexTTS:
num_beams=num_beams,
repetition_penalty=repetition_penalty,
max_generate_length=max_mel_tokens)
gpt_gen_time += time.perf_counter() - m_start_time
#codes = codes[:, :-2]
code_lens = torch.tensor([codes.shape[-1]], device=codes.device, dtype=codes.dtype)
if verbose:
@ -266,6 +271,7 @@ class IndexTTS:
print(f"fix codes shape: {codes.shape}, codes type: {codes.dtype}")
print(f"code len: {code_lens}")
m_start_time = time.perf_counter()
# latent, text_lens_out, code_lens_out = \
with torch.amp.autocast(self.device, enabled=self.dtype is not None, dtype=self.dtype):
latent = \
@ -274,7 +280,11 @@ class IndexTTS:
code_lens*self.gpt.mel_length_compression,
cond_mel_lengths=torch.tensor([auto_conditioning.shape[-1]], device=text_tokens.device),
return_latent=True, clip_inputs=False)
gpt_forward_time += time.perf_counter() - m_start_time
m_start_time = time.perf_counter()
wav, _ = self.bigvgan(latent, auto_conditioning.transpose(1, 2))
bigvgan_time += time.perf_counter() - m_start_time
wav = wav.squeeze(1)
wav = torch.clamp(32767 * wav, -32767.0, 32767.0)
@ -285,7 +295,10 @@ class IndexTTS:
wav = torch.cat(wavs, dim=1)
wav_length = wav.shape[-1] / sampling_rate
print(f">> Reference audio length: {cond_mel_frame / sampling_rate:.2f} seconds")
print(f">> Reference audio length: {cond_mel_frame*256 / sampling_rate:.2f} seconds")
print(f">> gpt_gen_time: {gpt_gen_time:.2f} seconds")
print(f">> gpt_forward_time: {gpt_forward_time:.2f} seconds")
print(f">> bigvgan_time: {bigvgan_time:.2f} seconds")
print(f">> Total inference time: {end_time - start_time:.2f} seconds")
print(f">> Generated audio length: {wav_length:.2f} seconds")
print(f">> RTF: {(end_time - start_time) / wav_length:.4f}")
@ -295,11 +308,11 @@ class IndexTTS:
if __name__ == "__main__":
prompt_wav = "test_data/input.wav"
prompt_wav = "testwav/input.wav"
prompt_wav = "testwav/spk_1744181067_1.wav"
# text="晕 XUAN4 是 一 种 GAN3 觉"
# text='大家好，我现在正在bilibili 体验 ai 科技，说实话，来之前我绝对想不到！AI技术已经发展到这样匪夷所思的地步了！'
text="晕 XUAN4 是 一 种 GAN3 觉"
text = "There is a vehicle arriving in dock number 7?"
text='大家好，我现在正在bilibili 体验 ai 科技，说实话，来之前我绝对想不到！AI技术已经发展到这样匪夷所思的地步了！'
tts = IndexTTS(cfg_path="checkpoints/config.yaml", model_dir="checkpoints", is_fp16=True)
tts = IndexTTS(cfg_path="checkpoints/config.yaml", model_dir="checkpoints", is_fp16=True, use_cuda_kernel=False)
tts.infer(audio_prompt=prompt_wav, text=text, output_path="gen.wav", verbose=True)