Merge remote-tracking branch 'upstream/main' into Ruff-Format

GPT_SoVITS/TTS_infer_pack/TTS.py

@@ -1,38 +1,40 @@
-from copy import deepcopy
+import gc
 import math
 import os
-import sys
-import gc
 import random
-import traceback
+import sys
 import time
+import traceback
+from copy import deepcopy
+
 import torchaudio
 from tqdm import tqdm
 
 now_dir = os.getcwd()
 sys.path.append(now_dir)
-import ffmpeg
 import os
 from typing import List, Tuple, Union
+
+import ffmpeg
+import librosa
 import numpy as np
 import torch
 import torch.nn.functional as F
 import yaml
-from transformers import AutoModelForMaskedLM, AutoTokenizer
-from tools.audio_sr import AP_BWE
 from AR.models.t2s_lightning_module import Text2SemanticLightningModule
+from BigVGAN.bigvgan import BigVGAN
 from feature_extractor.cnhubert import CNHubert
+from module.mel_processing import mel_spectrogram_torch, spectrogram_torch
 from module.models import SynthesizerTrn, SynthesizerTrnV3
 from peft import LoraConfig, get_peft_model
-import librosa
+from process_ckpt import get_sovits_version_from_path_fast, load_sovits_new
+from transformers import AutoModelForMaskedLM, AutoTokenizer
+
+from tools.audio_sr import AP_BWE
 from tools.i18n.i18n import I18nAuto, scan_language_list
 from tools.my_utils import load_audio
-from module.mel_processing import spectrogram_torch
 from TTS_infer_pack.text_segmentation_method import splits
 from TTS_infer_pack.TextPreprocessor import TextPreprocessor
-from BigVGAN.bigvgan import BigVGAN
-from module.mel_processing import mel_spectrogram_torch
-from process_ckpt import get_sovits_version_from_path_fast, load_sovits_new
 
 language = os.environ.get("language", "Auto")
 language = sys.argv[-1] if sys.argv[-1] in scan_language_list() else language
@@ -461,8 +463,6 @@ class TTS:
                 n_speakers=self.configs.n_speakers,
                 **kwargs,
             )
-            if hasattr(vits_model, "enc_q"):
-                del vits_model.enc_q
             self.configs.is_v3_synthesizer = False
         else:
             vits_model = SynthesizerTrnV3(
@@ -473,6 +473,8 @@ class TTS:
             )
             self.configs.is_v3_synthesizer = True
             self.init_bigvgan()
+            if "pretrained" not in weights_path and hasattr(vits_model, "enc_q"):
+                del vits_model.enc_q
 
         if if_lora_v3 == False:
             print(

GPT_SoVITS/inference_webui.py

@@ -9,9 +9,10 @@
 
 import logging
 import traceback
-import torchaudio
 import warnings
 
+import torchaudio
+
 logging.getLogger("markdown_it").setLevel(logging.ERROR)
 logging.getLogger("urllib3").setLevel(logging.ERROR)
 logging.getLogger("httpcore").setLevel(logging.ERROR)
@@ -22,10 +23,11 @@ logging.getLogger("torchaudio._extension").setLevel(logging.ERROR)
 logging.getLogger("multipart.multipart").setLevel(logging.ERROR)
 warnings.simplefilter(action="ignore", category=FutureWarning)
 
+import json
 import os
 import re
 import sys
-import json
+
 import torch
 from text.LangSegmenter import LangSegmenter
 
@@ -91,16 +93,17 @@ is_half = eval(os.environ.get("is_half", "True")) and torch.cuda.is_available()
 # is_half=False
 punctuation = set(["!", "?", "…", ",", ".", "-", " "])
 import gradio as gr
-from transformers import AutoModelForMaskedLM, AutoTokenizer
-import numpy as np
 import librosa
+import numpy as np
 from feature_extractor import cnhubert
+from transformers import AutoModelForMaskedLM, AutoTokenizer
 
 cnhubert.cnhubert_base_path = cnhubert_base_path
 
-from GPT_SoVITS.module.models import SynthesizerTrn, SynthesizerTrnV3
 import random
 
+from GPT_SoVITS.module.models import SynthesizerTrn, SynthesizerTrnV3
+
 
 def set_seed(seed):
     if seed == -1:
@@ -115,12 +118,14 @@ def set_seed(seed):
 
 # set_seed(42)
 
+from time import time as ttime
+
 from AR.models.t2s_lightning_module import Text2SemanticLightningModule
+from peft import LoraConfig, get_peft_model
 from text import cleaned_text_to_sequence
 from text.cleaner import clean_text
-from time import time as ttime
+
 from tools.i18n.i18n import I18nAuto, scan_language_list
-from peft import LoraConfig, get_peft_model
 
 language = os.environ.get("language", "Auto")
 language = sys.argv[-1] if sys.argv[-1] in scan_language_list() else language
@@ -265,10 +270,11 @@ def change_sovits_weights(sovits_path, prompt_language=None, text_language=None)
             prompt_language_update,
             text_update,
             text_language_update,
-            {"__type__": "update", "visible": visible_sample_steps},
+            {"__type__": "update", "visible": visible_sample_steps, "value": 32},
             {"__type__": "update", "visible": visible_inp_refs},
             {"__type__": "update", "value": False, "interactive": True if model_version != "v3" else False},
             {"__type__": "update", "visible": True if model_version == "v3" else False},
+            {"__type__": "update", "value": i18n("模型加载中，请等待"), "interactive": False},
         )
 
     dict_s2 = load_sovits_new(sovits_path)
@@ -329,6 +335,19 @@ def change_sovits_weights(sovits_path, prompt_language=None, text_language=None)
         # torch.save(vq_model.state_dict(),"merge_win.pth")
         vq_model.eval()
 
+    yield (
+        {"__type__": "update", "choices": list(dict_language.keys())},
+        {"__type__": "update", "choices": list(dict_language.keys())},
+        prompt_text_update,
+        prompt_language_update,
+        text_update,
+        text_language_update,
+        {"__type__": "update", "visible": visible_sample_steps, "value": 32},
+        {"__type__": "update", "visible": visible_inp_refs},
+        {"__type__": "update", "value": False, "interactive": True if model_version != "v3" else False},
+        {"__type__": "update", "visible": True if model_version == "v3" else False},
+        {"__type__": "update", "value": i18n("合成语音"), "interactive": True},
+    )
     with open("./weight.json") as f:
         data = f.read()
         data = json.loads(data)
@@ -530,7 +549,7 @@ def get_phones_and_bert(text, language, version, final=False):
     return phones, bert.to(dtype), norm_text
 
 
-from module.mel_processing import spectrogram_torch, mel_spectrogram_torch
+from module.mel_processing import mel_spectrogram_torch, spectrogram_torch
 
 spec_min = -12
 spec_max = 2
@@ -1020,7 +1039,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
                     label=i18n("开启无参考文本模式。不填参考文本亦相当于开启。")
                     + i18n("v3暂不支持该模式，使用了会报错。"),
                     value=False,
-                    interactive=True,
+                    interactive=True if model_version != "v3" else False,
                     show_label=True,
                     scale=1,
                 )
@@ -1137,7 +1156,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
             #     phoneme=gr.Textbox(label=i18n("音素框"), value="")
             #     get_phoneme_button = gr.Button(i18n("目标文本转音素"), variant="primary")
         with gr.Row():
-            inference_button = gr.Button(i18n("合成语音"), variant="primary", size="lg", scale=25)
+            inference_button = gr.Button(value=i18n("合成语音"), variant="primary", size="lg", scale=25)
             output = gr.Audio(label=i18n("输出的语音"), scale=14)
 
         inference_button.click(
@@ -1176,6 +1195,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
                 inp_refs,
                 ref_text_free,
                 if_sr_Checkbox,
+                inference_button,
             ],
         )
         GPT_dropdown.change(change_gpt_weights, [GPT_dropdown], [])

GPT_SoVITS/inference_webui_fast.py

@@ -7,11 +7,11 @@
 全部按日文识别
 """
 
-import random
-import os
-import re
-import logging
 import json
+import logging
+import os
+import random
+import re
 import sys
 
 now_dir = os.getcwd()
@@ -47,11 +47,13 @@ gpt_path = os.environ.get("gpt_path", None)
 sovits_path = os.environ.get("sovits_path", None)
 cnhubert_base_path = os.environ.get("cnhubert_base_path", None)
 bert_path = os.environ.get("bert_path", None)
-version = os.environ.get("version", "v2")
+version = model_version = os.environ.get("version", "v2")
 
 import gradio as gr
-from TTS_infer_pack.TTS import TTS, TTS_Config, NO_PROMPT_ERROR
+from inference_webui import DictToAttrRecursive
 from TTS_infer_pack.text_segmentation_method import get_method
+from TTS_infer_pack.TTS import NO_PROMPT_ERROR, TTS, TTS_Config
+
 from tools.i18n.i18n import I18nAuto, scan_language_list
 
 language = os.environ.get("language", "Auto")
@@ -254,21 +256,18 @@ def get_weights_names(GPT_weight_root, SoVITS_weight_root):
 SoVITS_names, GPT_names = get_weights_names(GPT_weight_root, SoVITS_weight_root)
 
 
-from process_ckpt import get_sovits_version_from_path_fast
+from process_ckpt import get_sovits_version_from_path_fast, load_sovits_new
 
 
 def change_sovits_weights(sovits_path, prompt_language=None, text_language=None):
-    global version, dict_language
+    global version, model_version, dict_language, if_lora_v3
     version, model_version, if_lora_v3 = get_sovits_version_from_path_fast(sovits_path)
-
+    # print(sovits_path,version, model_version, if_lora_v3)
-    if if_lora_v3 and not os.path.exists(path_sovits_v3):
+    if if_lora_v3 == True and is_exist_s2gv3 == False:  #
-        info = path_sovits_v3 + i18n("SoVITS V3 底模缺失，无法加载相应 LoRA 权重")
+        info = "GPT_SoVITS/pretrained_models/s2Gv3.pth" + i18n("SoVITS V3 底模缺失，无法加载相应 LoRA 权重")
         gr.Warning(info)
         raise FileExistsError(info)
-
+    dict_language = dict_language_v1 if version == "v1" else dict_language_v2
-    tts_pipeline.init_vits_weights(sovits_path)
-
-    dict_language = dict_language_v1 if tts_pipeline.configs.version == "v1" else dict_language_v2
     if prompt_language is not None and text_language is not None:
         if prompt_language in list(dict_language.keys()):
             prompt_text_update, prompt_language_update = (
@@ -289,6 +288,7 @@ def change_sovits_weights(sovits_path, prompt_language=None, text_language=None)
         else:
             visible_sample_steps = False
             visible_inp_refs = True
+        # prompt_language,text_language,prompt_text,prompt_language,text,text_language,inp_refs,ref_text_free,
         yield (
             {"__type__": "update", "choices": list(dict_language.keys())},
             {"__type__": "update", "choices": list(dict_language.keys())},
@@ -296,12 +296,25 @@ def change_sovits_weights(sovits_path, prompt_language=None, text_language=None)
             prompt_language_update,
             text_update,
             text_language_update,
-            {"__type__": "update", "visible": visible_sample_steps},
+            {"__type__": "update", "interactive": visible_sample_steps, "value": 32},
             {"__type__": "update", "visible": visible_inp_refs},
-            {"__type__": "update", "value": False, "interactive": True if model_version != "v3" else False},
+            {"__type__": "update", "interactive": True if model_version != "v3" else False},
-            {"__type__": "update", "visible": True if model_version == "v3" else False},
+            {"__type__": "update", "value": i18n("模型加载中，请等待"), "interactive": False},
         )
 
+    tts_pipeline.init_vits_weights(sovits_path)
+    yield (
+        {"__type__": "update", "choices": list(dict_language.keys())},
+        {"__type__": "update", "choices": list(dict_language.keys())},
+        prompt_text_update,
+        prompt_language_update,
+        text_update,
+        text_language_update,
+        {"__type__": "update", "interactive": visible_sample_steps, "value": 32},
+        {"__type__": "update", "visible": visible_inp_refs},
+        {"__type__": "update", "interactive": True if model_version != "v3" else False},
+        {"__type__": "update", "value": i18n("合成语音"), "interactive": True},
+    )
     with open("./weight.json") as f:
         data = f.read()
         data = json.loads(data)
@@ -341,7 +354,11 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
             gr.Markdown(value=i18n("*请上传并填写参考信息"))
             with gr.Row():
                 inp_ref = gr.Audio(label=i18n("主参考音频(请上传3~10秒内参考音频，超过会报错！)"), type="filepath")
-                inp_refs = gr.File(label=i18n("辅参考音频(可选多个，或不选)"), file_count="multiple")
+                inp_refs = gr.File(
+                    label=i18n("辅参考音频(可选多个，或不选)"),
+                    file_count="multiple",
+                    visible=True if model_version != "v3" else False,
+                )
             prompt_text = gr.Textbox(label=i18n("主参考音频的文本"), value="", lines=2)
             with gr.Row():
                 prompt_language = gr.Dropdown(
@@ -351,7 +368,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
                     ref_text_free = gr.Checkbox(
                         label=i18n("开启无参考文本模式。不填参考文本亦相当于开启。"),
                         value=False,
-                        interactive=True,
+                        interactive=True if model_version != "v3" else False,
                         show_label=True,
                     )
                     gr.Markdown(
@@ -465,8 +482,19 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
         SoVITS_dropdown.change(
             change_sovits_weights,
             [SoVITS_dropdown, prompt_language, text_language],
-            [prompt_language, text_language, prompt_text, prompt_language, text, text_language],
+            [
-        )
+                prompt_language,
+                text_language,
+                prompt_text,
+                prompt_language,
+                text,
+                text_language,
+                sample_steps,
+                inp_refs,
+                ref_text_free,
+                inference_button,
+            ],
+        )  #
         GPT_dropdown.change(tts_pipeline.init_t2s_weights, [GPT_dropdown], [])
 
     with gr.Group():

GPT_SoVITS/text/g2pw/onnx_api.py

@@ -63,7 +63,7 @@ def download_and_decompress(model_dir: str = "G2PWModel/"):
         extract_dir = os.path.join(parent_directory, "G2PWModel_1.1")
         extract_dir_new = os.path.join(parent_directory, "G2PWModel")
         print("Downloading g2pw model...")
-        modelscope_url = "https://paddlespeech.cdn.bcebos.com/Parakeet/released_models/g2p/G2PWModel_1.1.zip"
+        modelscope_url = "https://www.modelscope.cn/models/kamiorinn/g2pw/resolve/master/G2PWModel_1.1.zip"#"https://paddlespeech.cdn.bcebos.com/Parakeet/released_models/g2p/G2PWModel_1.1.zip"
         with requests.get(modelscope_url, stream=True) as r:
             r.raise_for_status()
             with open(zip_dir, "wb") as f:

docs/cn/Changelog_CN.md

@@ -286,3 +286,17 @@ https://github.com/RVC-Boss/GPT-SoVITS/pull/2112 https://github.com/RVC-Boss/GPT
 修复短文本语种选择出错 https://github.com/RVC-Boss/GPT-SoVITS/pull/2122
 
 修复v3sovits未传参以支持调节语速
+
+### 202503
+
+修复一批由依赖的库版本不对导致的问题https://github.com/RVC-Boss/GPT-SoVITS/commit/6c468583c5566e5fbb4fb805e4cc89c403e997b8
+
+修复模型加载异步逻辑https://github.com/RVC-Boss/GPT-SoVITS/commit/03b662a769946b7a6a8569a354860e8eeeb743aa
+
+修复其他若干bug
+
+重点更新：
+
+1-v3支持并行推理 https://github.com/RVC-Boss/GPT-SoVITS/commit/03b662a769946b7a6a8569a354860e8eeeb743aa
+
+2-整合包修复onnxruntime GPU推理的支持，影响：（1）g2pw有个onnx模型原先是CPU推理现在用GPU，显著降低推理的CPU瓶颈 （2）foxjoy去混响模型现在可使用GPU推理

webui.py

@@ -435,9 +435,9 @@ def change_tts_inference(bert_path, cnhubert_base_path, gpu_number, gpt_path, so
         cmd = '"%s" GPT_SoVITS/inference_webui_fast.py "%s"' % (python_exec, language)
     else:
         cmd = '"%s" GPT_SoVITS/inference_webui.py "%s"' % (python_exec, language)
-    #####v3暂不支持加速推理
+    # #####v3暂不支持加速推理
-    if version == "v3":
+    # if version=="v3":
-        cmd = '"%s" GPT_SoVITS/inference_webui.py "%s"' % (python_exec, language)
+    #     cmd = '"%s" GPT_SoVITS/inference_webui.py "%s"'%(python_exec, language)
     if p_tts_inference is None:
         os.environ["gpt_path"] = gpt_path if "/" in gpt_path else "%s/%s" % (GPT_weight_root, gpt_path)
         os.environ["sovits_path"] = sovits_path if "/" in sovits_path else "%s/%s" % (SoVITS_weight_root, sovits_path)
@@ -1312,9 +1312,9 @@ def switch_version(version_):
             "value": False if not if_force_ckpt else True,
             "interactive": True if not if_force_ckpt else False,
         },
-        {"__type__": "update", "interactive": False if version == "v3" else True, "value": False},
+        {"__type__": "update", "interactive": True, "value": False},
         {"__type__": "update", "visible": True if version == "v3" else False},
-    )
+    )  # {'__type__': 'update', "interactive": False if version == "v3" else True, "value": False}, \ ####batch infer
 
 
 if os.path.exists("GPT_SoVITS/text/G2PWModel"):