From 110cc3560cac746ca8576b4ed71573c7fec4d5de Mon Sep 17 00:00:00 2001
From: XXXXRT666 <runtongzhong@gmail.com>
Date: Wed, 3 Jul 2024 23:17:09 +0800
Subject: [PATCH] timing

---
 GPT_SoVITS/inference_webui.py | 8 +++++++-
 api.py                        | 6 ------
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/GPT_SoVITS/inference_webui.py b/GPT_SoVITS/inference_webui.py
index 44c6d0eb..a6ff042a 100644
--- a/GPT_SoVITS/inference_webui.py
+++ b/GPT_SoVITS/inference_webui.py
@@ -313,6 +313,7 @@ def merge_short_text_in_array(texts, threshold):
     return result
 
 def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language, how_to_cut=i18n("不切"), top_k=20, top_p=0.6, temperature=0.6, ref_free = False):
+    t=[]
     if prompt_text is None or len(prompt_text) == 0:
         ref_free = True
     t0 = ttime()
@@ -353,6 +354,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
    
         prompt_semantic = codes[0, 0]
     t1 = ttime()
+    t.append(t1-t0)
 
     if (how_to_cut == i18n("凑四句一切")):
         text = cut1(text)
@@ -376,6 +378,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
 
     for text in texts:
         # 解决输入目标文本的空行导致报错的问题
+        t1 = ttime()
         if (len(text.strip()) == 0):
             continue
         if (text[-1] not in splits): text += "。" if text_language != "en" else "."
@@ -430,7 +433,10 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
         audio_opt.append(audio)
         audio_opt.append(zero_wav)
         t4 = ttime()
-    print("%.3f\t%.3f\t%.3f\t%.3f" % (t1 - t0, t2 - t1, t3 - t2, t4 - t3))
+        t.extend([t2 - t1,t3 - t2, t4 - t3])
+    print("%.3f\t%.3f\t%.3f\t%.3f" % 
+          (t[0], sum(t[1::3]), sum(t[2::3]), sum(t[3::3]))
+          )
     yield hps.data.sampling_rate, (np.concatenate(audio_opt, 0) * 32768).astype(
         np.int16
     )
diff --git a/api.py b/api.py
index aa822ca7..d1249ecd 100644
--- a/api.py
+++ b/api.py
@@ -127,7 +127,6 @@ sys.path.append("%s/GPT_SoVITS" % (now_dir))
 
 import signal
 import LangSegment
-from time import time as ttime
 import torch
 import librosa
 import soundfile as sf
@@ -447,7 +446,6 @@ def only_punc(text):
 
 
 def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language):
-    t0 = ttime()
     prompt_text = prompt_text.strip("\n")
     prompt_language, text = prompt_language, text.strip("\n")
     zero_wav = np.zeros(int(hps.data.sampling_rate * 0.3), dtype=np.float16 if is_half == True else np.float32)
@@ -465,7 +463,6 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
         ssl_content = ssl_model.model(wav16k.unsqueeze(0))["last_hidden_state"].transpose(1, 2)  # .float()
         codes = vq_model.extract_latent(ssl_content)
         prompt_semantic = codes[0, 0]
-    t1 = ttime()
     prompt_language = dict_language[prompt_language.lower()]
     text_language = dict_language[text_language.lower()]
     phones1, bert1, norm_text1 = get_phones_and_bert(prompt_text, prompt_language)
@@ -485,7 +482,6 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
         bert = bert.to(device).unsqueeze(0)
         all_phoneme_len = torch.tensor([all_phoneme_ids.shape[-1]]).to(device)
         prompt = prompt_semantic.unsqueeze(0).to(device)
-        t2 = ttime()
         with torch.no_grad():
             # pred_semantic = t2s_model.model.infer(
             pred_semantic, idx = t2s_model.model.infer_panel(
@@ -496,7 +492,6 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
                 # prompt_phone_len=ph_offset,
                 top_k=config['inference']['top_k'],
                 early_stop_num=hz * max_sec)
-        t3 = ttime()
         # print(pred_semantic.shape,idx)
         pred_semantic = pred_semantic[:, -idx:].unsqueeze(0)  # .unsqueeze(0)#mq要多unsqueeze一次
         refer = get_spepc(hps, ref_wav_path)  # .to(device)
@@ -511,7 +506,6 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
                 0, 0]  ###试试重建不带上prompt部分
         audio_opt.append(audio)
         audio_opt.append(zero_wav)
-        t4 = ttime()
         audio_bytes = pack_audio(audio_bytes,(np.concatenate(audio_opt, 0) * 32768).astype(np.int16),hps.data.sampling_rate)
     # logger.info("%.3f\t%.3f\t%.3f\t%.3f" % (t1 - t0, t2 - t1, t3 - t2, t4 - t3))
         if stream_mode == "normal":