增加cuda graph支持，普通推理模式推理速度原地翻倍，效果不变。1

增加cuda graph支持，普通推理模式推理速度原地翻倍，效果不变。1

GPT_SoVITS/inference_webui.py

@@ -137,6 +137,38 @@ if torch.cuda.is_available():
 else:
     device = "cpu"
 
+
+def check_cuda_graph_support():
+    if device != "cuda":
+        return False
+    try:
+        major, _ = torch.cuda.get_device_capability()
+        if major < 7:
+            print("CUDA Graph: GPU compute capability < 7.0, disabled")
+            return False
+        a = torch.randn(2, 2, device="cuda")
+        g = torch.cuda.CUDAGraph()
+        s = torch.cuda.Stream()
+        s.wait_stream(torch.cuda.current_stream())
+        with torch.cuda.stream(s):
+            b = a * 2
+        torch.cuda.current_stream().wait_stream(s)
+        out = torch.empty_like(b)
+        with torch.cuda.graph(g):
+            out.copy_(a * 2)
+        g.replay()
+        torch.cuda.synchronize()
+        del a, b, out, g, s
+        torch.cuda.empty_cache()
+        print("CUDA Graph: support check passed, auto-enabled")
+        return True
+    except Exception as e:
+        print(f"CUDA Graph: support check failed ({e}), disabled")
+        return False
+
+
+cuda_graph_supported = check_cuda_graph_support()
+
 dict_language_v1 = {
     i18n("中文"): "all_zh",  # 全部按中文识别
     i18n("英文"): "en",  # 全部按英文识别#######不变
@@ -229,7 +261,8 @@ v3v4set = {"v3", "v4"}
 def change_sovits_weights(sovits_path, prompt_language=None, text_language=None):
     if "！" in sovits_path or "!" in sovits_path:
         sovits_path = name2sovits_path[sovits_path]
-    global vq_model, hps, version, model_version, dict_language, if_lora_v3
+    global vq_model, hps, version, model_version, dict_language, if_lora_v3, t2s_model_cudagraph
+    t2s_model_cudagraph = None
     version, model_version, if_lora_v3 = get_sovits_version_from_path_fast(sovits_path)
     print(sovits_path, version, model_version, if_lora_v3)
     is_exist = is_exist_s2gv3 if model_version == "v3" else is_exist_s2gv4
@@ -373,10 +406,16 @@ except:
     pass
 
 
+t2s_model_cudagraph = None
+gpt_path_global = None
+
+
 def change_gpt_weights(gpt_path):
     if "！" in gpt_path or "!" in gpt_path:
         gpt_path = name2gpt_path[gpt_path]
-    global hz, max_sec, t2s_model, config
+    global hz, max_sec, t2s_model, config, t2s_model_cudagraph, gpt_path_global
+    t2s_model_cudagraph = None
+    gpt_path_global = gpt_path
     hz = 50
     dict_s1 = torch.load(gpt_path, map_location="cpu", weights_only=False)
     config = dict_s1["config"]
@@ -765,6 +804,7 @@ def get_tts_wav(
     sample_steps=8,
     if_sr=False,
     pause_second=0.3,
+    use_cuda_graph=False,
 ):
     global cache
     if ref_wav_path:
@@ -873,6 +913,37 @@ def get_tts_wav(
         # print(cache.keys(),if_freeze)
         if i_text in cache and if_freeze == True:
             pred_semantic = cache[i_text]
+        else:
+            if use_cuda_graph and device == "cuda":
+                global t2s_model_cudagraph
+                if t2s_model_cudagraph is None:
+                    from AR.models.t2s_model_cudagraph import CUDAGraphRunner
+                    t2s_model_cudagraph = CUDAGraphRunner(
+                        CUDAGraphRunner.load_decoder(gpt_path_global),
+                        torch.device(device),
+                        torch.float16 if is_half else torch.float32,
+                    )
+                from AR.models.structs_cudagraph import T2SRequest
+                with torch.no_grad():
+                    t2s_request = T2SRequest(
+                        [all_phoneme_ids.squeeze(0)],
+                        all_phoneme_len,
+                        all_phoneme_ids.new_zeros((1, 0)) if ref_free else prompt,
+                        [bert.squeeze(0)],
+                        valid_length=1,
+                        top_k=top_k,
+                        top_p=top_p,
+                        temperature=temperature,
+                        early_stop_num=hz * max_sec,
+                        use_cuda_graph=True,
+                    )
+                    t2s_result = t2s_model_cudagraph.generate(t2s_request)
+                    if t2s_result.exception is not None:
+                        print(t2s_result.exception)
+                        print(t2s_result.traceback)
+                        raise RuntimeError("CUDA Graph T2S inference failed")
+                    pred_semantic = t2s_result.result[0].unsqueeze(0).unsqueeze(0)
+                    cache[i_text] = pred_semantic
             else:
                 with torch.no_grad():
                     pred_semantic, idx = t2s_model.model.infer_panel(
@@ -1284,6 +1355,14 @@ with gr.Blocks(title="GPT-SoVITS WebUI", analytics_enabled=False, js=js, css=css
             #     get_phoneme_button = gr.Button(i18n("目标文本转音素"), variant="primary")
         with gr.Row():
             inference_button = gr.Button(value=i18n("合成语音"), variant="primary", size="lg", scale=25)
+            use_cuda_graph_checkbox = gr.Checkbox(
+                label="CUDA Graph " + i18n("加速"),
+                value=cuda_graph_supported,
+                interactive=True if torch.cuda.is_available() else False,
+                show_label=True,
+                scale=5,
+                visible=False,
+            )
             output = gr.Audio(label=i18n("输出的语音"), scale=14)
 
         inference_button.click(
@@ -1305,6 +1384,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI", analytics_enabled=False, js=js, css=css
                 sample_steps,
                 if_sr_Checkbox,
                 pause_second_slider,
+                use_cuda_graph_checkbox,
             ],
             [output],
         )