Merge branch 'RVC-Boss:main' into main

2026-07-06 14:48:46 +08:00 · 2025-07-21 15:19:14 +08:00 · 2025-07-21 15:19:14 +08:00 · 9364ae9842
commit 9364ae9842
parent 52fa9dbf15 0be59c8043
7 changed files with 99 additions and 49 deletions
--- a/GPT_SoVITS/AR/models/t2s_model.py
+++ b/GPT_SoVITS/AR/models/t2s_model.py
@ -356,7 +356,7 @@ class Text2SemanticDecoder(nn.Module):
        x = self.ar_text_embedding(x)
        x = x + self.bert_proj(bert_feature.transpose(1, 2))
        x = self.ar_text_position(x)
-        x_mask = make_pad_mask(x_lens)
+        x_mask = make_pad_mask_left(x_lens)

        y_mask = make_pad_mask(y_lens)
        y_mask_int = y_mask.type(torch.int64)
@ -420,7 +420,7 @@ class Text2SemanticDecoder(nn.Module):
            mask=xy_attn_mask,
        )
        x_len = x_lens.max()
-        logits = self.ar_predict_layer(xy_dec[:, x_len:])
+        logits = self.ar_predict_layer(xy_dec[:, x_len-1:])

        ###### DPO #############
        reject_xy_pos, reject_xy_attn_mask, reject_targets = self.make_input_data(
@ -432,7 +432,7 @@ class Text2SemanticDecoder(nn.Module):
            mask=reject_xy_attn_mask,
        )
        x_len = x_lens.max()
-        reject_logits = self.ar_predict_layer(reject_xy_dec[:, x_len:])
+        reject_logits = self.ar_predict_layer(reject_xy_dec[:, x_len-1:])

        # loss
        # from feiteng: 每次 duration 越多, 梯度更新也应该更多, 所以用 sum
@ -455,7 +455,7 @@ class Text2SemanticDecoder(nn.Module):
        x = self.ar_text_embedding(x)
        x = x + self.bert_proj(bert_feature.transpose(1, 2))
        x = self.ar_text_position(x)
-        x_mask = make_pad_mask(x_lens)
+        x_mask = make_pad_mask_left(x_lens)

        y_mask = make_pad_mask(y_lens)
        y_mask_int = y_mask.type(torch.int64)
@ -502,7 +502,7 @@ class Text2SemanticDecoder(nn.Module):
            (xy_pos, None),
            mask=xy_attn_mask,
        )
-        logits = self.ar_predict_layer(xy_dec[:, x_len:]).permute(0, 2, 1)
+        logits = self.ar_predict_layer(xy_dec[:, x_len-1:]).permute(0, 2, 1)
        # loss
        # from feiteng: 每次 duration 越多, 梯度更新也应该更多, 所以用 sum
        loss = F.cross_entropy(logits, targets, reduction="sum")
@ -578,7 +578,7 @@ class Text2SemanticDecoder(nn.Module):
    def pad_y_eos(self, y, y_mask_int, eos_id):
        targets = F.pad(y, (0, 1), value=0) + eos_id * F.pad(y_mask_int, (0, 1), value=1)
        # 错位
-        return targets[:, :-1], targets[:, 1:]
+        return targets[:, :-1], targets

    def infer_panel_batch_infer(
        self,
--- a/GPT_SoVITS/TTS_infer_pack/TTS.py
+++ b/GPT_SoVITS/TTS_infer_pack/TTS.py
@ -304,10 +304,10 @@ class TTS_Config:
            configs: dict = self._load_configs(self.configs_path)

        assert isinstance(configs, dict)
-        version = configs.get("version", "v2").lower()
-        assert version in ["v1", "v2", "v3", "v4", "v2Pro", "v2ProPlus"]
-        self.default_configs[version] = configs.get(version, self.default_configs[version])
-        self.configs: dict = configs.get("custom", deepcopy(self.default_configs[version]))
+        configs_ = deepcopy(self.default_configs)
+        configs_.update(configs)
+        self.configs: dict = configs_.get("custom", configs_["v2"])
+        self.default_configs = deepcopy(configs_)

        self.device = self.configs.get("device", torch.device("cpu"))
        if "cuda" in str(self.device) and not torch.cuda.is_available():
@ -315,11 +315,13 @@ class TTS_Config:
            self.device = torch.device("cpu")

        self.is_half = self.configs.get("is_half", False)
-        # if str(self.device) == "cpu" and self.is_half:
-        #     print(f"Warning: Half precision is not supported on CPU, set is_half to False.")
-        #     self.is_half = False
+        if str(self.device) == "cpu" and self.is_half:
+            print(f"Warning: Half precision is not supported on CPU, set is_half to False.")
+            self.is_half = False

+        version = self.configs.get("version", None)
        self.version = version
+        assert self.version in ["v1", "v2", "v3", "v4", "v2Pro", "v2ProPlus"], "Invalid version!"
        self.t2s_weights_path = self.configs.get("t2s_weights_path", None)
        self.vits_weights_path = self.configs.get("vits_weights_path", None)
        self.bert_base_path = self.configs.get("bert_base_path", None)
@ -576,6 +578,10 @@ class TTS:
        if self.configs.is_half and str(self.configs.device) != "cpu":
            self.vits_model = self.vits_model.half()

+        self.configs.save_configs()
+
+
+
    def init_t2s_weights(self, weights_path: str):
        print(f"Loading Text2Semantic weights from {weights_path}")
        self.configs.t2s_weights_path = weights_path
--- a/GPT_SoVITS/inference_webui_fast.py
+++ b/GPT_SoVITS/inference_webui_fast.py
@ -133,7 +133,8 @@ is_exist_s2gv4 = os.path.exists(path_sovits_v4)
 tts_config = TTS_Config("GPT_SoVITS/configs/tts_infer.yaml")
 tts_config.device = device
 tts_config.is_half = is_half
-tts_config.version = version
+# tts_config.version = version
+tts_config.update_version(version)
 if gpt_path is not None:
    if "！" in gpt_path or "!" in gpt_path:
        gpt_path = name2gpt_path[gpt_path]
--- a/tools/asr/config.py
+++ b/tools/asr/config.py
@ -6,15 +6,10 @@ def check_fw_local_models():
    启动时检查本地是否有 Faster Whisper 模型.
    """
    model_size_list = [
-        "tiny",
-        "tiny.en",
-        "base",
-        "base.en",
-        "small",
-        "small.en",
        "medium",
        "medium.en",
-        "large",
+        "distil-large-v2",
+        "distil-large-v3",
        "large-v1",
        "large-v2",
        "large-v3",
@ -25,11 +20,24 @@ def check_fw_local_models():
    return model_size_list


+def get_models():
+    model_size_list = [
+        "medium",
+        "medium.en",
+        "distil-large-v2",
+        "distil-large-v3",
+        "large-v1",
+        "large-v2",
+        "large-v3",
+    ]
+    return model_size_list
+
+
 asr_dict = {
    "达摩 ASR (中文)": {"lang": ["zh", "yue"], "size": ["large"], "path": "funasr_asr.py", "precision": ["float32"]},
    "Faster Whisper (多语种)": {
        "lang": ["auto", "zh", "en", "ja", "ko", "yue"],
-        "size": check_fw_local_models(),
+        "size": get_models(),
        "path": "fasterwhisper_asr.py",
        "precision": ["float32", "float16", "int8"],
    },
--- a/tools/asr/fasterwhisper_asr.py
+++ b/tools/asr/fasterwhisper_asr.py
@ -1,15 +1,16 @@
 import argparse
 import os
+import time
 import traceback

-os.environ["HF_ENDPOINT"] = "https://hf-mirror.com"
-os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
-
 import torch
 from faster_whisper import WhisperModel
+from huggingface_hub import snapshot_download
+from huggingface_hub.errors import LocalEntryNotFoundError
 from tqdm import tqdm

-from tools.asr.config import check_fw_local_models
+from tools.asr.config import get_models
+from tools.asr.funasr_asr import only_asr
 from tools.my_utils import load_cudnn

 # fmt: off
@ -38,20 +39,54 @@ language_code_list = [
 # fmt: on


-def execute_asr(input_folder, output_folder, model_size, language, precision):
-    if "-local" in model_size:
-        model_size = model_size[:-6]
-        model_path = f"tools/asr/models/faster-whisper-{model_size}"
+def download_model(model_size: str):
+    if "distil" in model_size:
+        repo_id = "Systran/faster-{}-whisper-{}".format(*model_size.split("-", maxsplit=1))
    else:
-        model_path = model_size
+        repo_id = f"Systran/faster-whisper-{model_size}"
+    model_path = f"tools/asr/models/{repo_id.strip('Systran/')}"
+
+    files: list[str] = [
+        "config.json",
+        "model.bin",
+        "tokenizer.json",
+        "vocabulary.txt",
+    ]
+    if model_size == "large-v3" or "distil" in model_size:
+        files.append("preprocessor_config.json")
+        files.append("vocabulary.json")
+
+        files.remove("vocabulary.txt")
+
+    for attempt in range(2):
+        try:
+            snapshot_download(
+                repo_id=repo_id,
+                allow_patterns=files,
+                local_dir=model_path,
+            )
+            break
+        except LocalEntryNotFoundError:
+            if attempt < 1:
+                time.sleep(2)
+            else:
+                print("[ERROR] LocalEntryNotFoundError and no fallback.")
+                traceback.print_exc()
+                exit(1)
+        except Exception as e:
+            print(f"[ERROR] Unexpected error on attempt {attempt + 1}: {e}")
+            traceback.print_exc()
+            exit(1)
+
+    return model_path
+
+
+def execute_asr(input_folder, output_folder, model_path, language, precision):
    if language == "auto":
        language = None  # 不设置语种由模型自动输出概率最高的语种
-    print("loading faster whisper model:", model_size, model_path)
+    print("loading faster whisper model:", model_path, model_path)
    device = "cuda" if torch.cuda.is_available() else "cpu"
-    try:
-        model = WhisperModel(model_path, device=device, compute_type=precision)
-    except:
-        return print(traceback.format_exc())
+    model = WhisperModel(model_path, device=device, compute_type=precision)

    input_file_names = os.listdir(input_folder)
    input_file_names.sort()
@ -73,16 +108,15 @@ def execute_asr(input_folder, output_folder, model_size, language, precision):

            if info.language == "zh":
                print("检测为中文文本, 转 FunASR 处理")
-                if "only_asr" not in globals():
-                    from tools.asr.funasr_asr import only_asr  # 如果用英文就不需要导入下载模型
                text = only_asr(file_path, language=info.language.lower())

            if text == "":
                for segment in segments:
                    text += segment.text
            output.append(f"{file_path}|{output_file_name}|{info.language.upper()}|{text}")
-        except:
-            print(traceback.format_exc())
+        except Exception as e:
+            print(e)
+            traceback.print_exc()

    output_folder = output_folder or "output/asr_opt"
    os.makedirs(output_folder, exist_ok=True)
@ -107,7 +141,7 @@ if __name__ == "__main__":
        "--model_size",
        type=str,
        default="large-v3",
-        choices=check_fw_local_models(),
+        choices=get_models(),
        help="Model Size of Faster Whisper",
    )
    parser.add_argument(
@ -123,10 +157,14 @@ if __name__ == "__main__":
    )

    cmd = parser.parse_args()
+    model_size = cmd.model_size
+    if model_size == "large":
+        model_size = "large-v3"
+    model_path = download_model(model_size)
    output_file_path = execute_asr(
        input_folder=cmd.input_folder,
        output_folder=cmd.output_folder,
-        model_size=cmd.model_size,
+        model_path=model_path,
        language=cmd.language,
        precision=cmd.precision,
    )
--- a/tools/assets.py
+++ b/tools/assets.py
@ -59,7 +59,7 @@ top_html = """
        <a href="https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e" target="_blank">
            <img src="https://img.shields.io/badge/简体中文-阅读文档-blue?style=for-the-badge&logo=googledocs&logoColor=white" style="width: auto; height: 30px;">
        </a>
-        <a href="https://github.com/RVC-Boss/GPT-SoVITS" target="_blank">
+        <a href="https://lj1995-gpt-sovits-proplus.hf.space/" target="_blank">
            <img src="https://img.shields.io/badge/免费在线体验-free_online_demo-yellow.svg?style=for-the-badge&logo=huggingface" style="width: auto; height: 30px;">
        </a>
        <a href="https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e" target="_blank">
--- a/webui.py
+++ b/webui.py
@ -86,13 +86,10 @@ from config import (
 from tools import my_utils
 from tools.my_utils import check_details, check_for_existance

-# os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 当遇到mps不支持的步骤时使用cpu
-try:
-    import gradio.analytics as analytics
+os.environ["HF_ENDPOINT"] = "https://hf-mirror.com"
+os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"

-    analytics.version_check = lambda: None
-except:
-    ...
+# os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 当遇到mps不支持的步骤时使用cpu
 import gradio as gr

 n_cpu = cpu_count()