{"id":82824,"date":"2026-07-25T13:09:23","date_gmt":"2026-07-25T05:09:23","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/82824.html"},"modified":"2026-07-25T13:09:23","modified_gmt":"2026-07-25T05:09:23","slug":"fish-speech-1-5%e9%ab%98%e7%ae%97%e5%8a%9b%e9%80%82%e9%85%8d%ef%bc%9anvidia-triton%e6%8e%a8%e7%90%86%e6%9c%8d%e5%8a%a1%e5%99%a8%e5%b0%81%e8%a3%85%e6%96%b9%e6%a1%88","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/82824.html","title":{"rendered":"Fish Speech 1.5\u9ad8\u7b97\u529b\u9002\u914d\uff1aNVIDIA Triton\u63a8\u7406\u670d\u52a1\u5668\u5c01\u88c5\u65b9\u6848"},"content":{"rendered":"<h2>Fish Speech 1.5\u9ad8\u7b97\u529b\u9002\u914d&#xff1a;NVIDIA Triton\u63a8\u7406\u670d\u52a1\u5668\u5c01\u88c5\u65b9\u6848<\/h2>\n<h3>1. \u9879\u76ee\u80cc\u666f\u4e0e\u9700\u6c42<\/h3>\n<p>Fish Speech 1.5\u662f\u7531Fish Audio\u5f00\u6e90\u7684\u65b0\u4e00\u4ee3\u6587\u672c\u8f6c\u8bed\u97f3\u6a21\u578b&#xff0c;\u57fa\u4e8eLLaMA\u67b6\u6784\u4e0eVQGAN\u58f0\u7801\u5668&#xff0c;\u652f\u6301\u96f6\u6837\u672c\u8bed\u97f3\u5408\u6210\u3002\u7528\u6237\u4ec5\u9700\u63d0\u4f9b10-30\u79d2\u7684\u53c2\u8003\u97f3\u9891&#xff0c;\u5373\u53ef\u514b\u9686\u4efb\u610f\u97f3\u8272\u5e76\u751f\u6210\u4e2d\u3001\u82f1\u3001\u65e5\u3001\u97e9\u7b4913\u79cd\u8bed\u8a00\u7684\u9ad8\u8d28\u91cf\u8bed\u97f3&#xff0c;\u65e0\u9700\u9488\u5bf9\u7279\u5b9a\u8bf4\u8bdd\u4eba\u5fae\u8c03\u3002<\/p>\n<p>\u5728\u5b9e\u9645\u751f\u4ea7\u73af\u5883\u4e2d&#xff0c;\u539f\u751fPython\u670d\u52a1\u9762\u4e34\u5e76\u53d1\u6027\u80fd\u74f6\u9888\u548c\u8d44\u6e90\u5229\u7528\u7387\u4f4e\u7684\u95ee\u9898\u3002\u672c\u6587\u5c06\u4ecb\u7ecd\u5982\u4f55\u5c06Fish Speech 1.5\u6a21\u578b\u5c01\u88c5\u5230NVIDIA Triton\u63a8\u7406\u670d\u52a1\u5668\u4e2d&#xff0c;\u5b9e\u73b0\u9ad8\u5e76\u53d1\u3001\u4f4e\u5ef6\u8fdf\u7684\u8bed\u97f3\u5408\u6210\u670d\u52a1\u3002<\/p>\n<h3>2. Triton\u63a8\u7406\u670d\u52a1\u5668\u67b6\u6784\u8bbe\u8ba1<\/h3>\n<h4>2.1 \u6574\u4f53\u67b6\u6784\u65b9\u6848<\/h4>\n<p>\u6211\u4eec\u91c7\u7528\u53cc\u6a21\u578b\u6d41\u6c34\u7ebf\u67b6\u6784&#xff0c;\u5c06Fish Speech 1.5\u62c6\u5206\u4e3a\u4e24\u4e2aTriton\u6a21\u578b&#xff1a;<\/p>\n<ul>\n<li>\u6587\u672c\u7f16\u7801\u6a21\u578b&#xff1a;\u5904\u7406\u6587\u672c\u8f93\u5165&#xff0c;\u751f\u6210\u8bed\u4e49token<\/li>\n<li>\u58f0\u7801\u5668\u6a21\u578b&#xff1a;\u5c06\u8bed\u4e49token\u8f6c\u6362\u4e3a\u97f3\u9891\u6ce2\u5f62<\/li>\n<\/ul>\n<p>\u8fd9\u79cd\u8bbe\u8ba1\u5141\u8bb8\u5e76\u884c\u5904\u7406\u548c\u8d44\u6e90\u72ec\u7acb\u5206\u914d&#xff0c;\u663e\u8457\u63d0\u5347\u541e\u5410\u91cf\u3002<\/p>\n<h4>2.2 \u6a21\u578b\u914d\u7f6e\u4f18\u5316<\/h4>\n<p># config.pbtxt \u793a\u4f8b\u914d\u7f6e<br \/>\nname: &#034;fish_speech_encoder&#034;<br \/>\nplatform: &#034;onnxruntime_onnx&#034;<br \/>\nmax_batch_size: 32<br \/>\ninput [<br \/>\n  {<br \/>\n    name: &#034;text&#034;<br \/>\n    data_type: TYPE_STRING<br \/>\n    dims: [ -1 ]<br \/>\n  }<br \/>\n]<br \/>\noutput [<br \/>\n  {<br \/>\n    name: &#034;semantic_tokens&#034;<br \/>\n    data_type: TYPE_INT32<br \/>\n    dims: [ -1, -1 ]<br \/>\n  }<br \/>\n]<br \/>\ninstance_group [<br \/>\n  {<br \/>\n    count: 2<br \/>\n    kind: KIND_GPU<br \/>\n    gpus: [0, 1]<br \/>\n  }<br \/>\n]<\/p>\n<h3>3. \u6a21\u578b\u8f6c\u6362\u4e0e\u4f18\u5316<\/h3>\n<h4>3.1 ONNX\u683c\u5f0f\u8f6c\u6362<\/h4>\n<p>\u5c06PyTorch\u6a21\u578b\u8f6c\u6362\u4e3aONNX\u683c\u5f0f\u662fTriton\u90e8\u7f72\u7684\u5173\u952e\u6b65\u9aa4&#xff1a;<\/p>\n<p>import torch<br \/>\nfrom fish_speech.models import Text2SemanticModel<\/p>\n<p># \u52a0\u8f7d\u539f\u59cb\u6a21\u578b<br \/>\nmodel &#061; Text2SemanticModel.from_pretrained(&#034;fishaudio\/fish-speech-1.5&#034;)<br \/>\nmodel.eval()<\/p>\n<p># \u793a\u4f8b\u8f93\u5165<br \/>\ndummy_input &#061; torch.randint(0, 1024, (1, 128))<\/p>\n<p># \u5bfc\u51faONNX\u6a21\u578b<br \/>\ntorch.onnx.export(<br \/>\n    model,<br \/>\n    dummy_input,<br \/>\n    &#034;fish_speech_encoder.onnx&#034;,<br \/>\n    input_names&#061;[&#034;input_ids&#034;],<br \/>\n    output_names&#061;[&#034;output_tokens&#034;],<br \/>\n    dynamic_axes&#061;{<br \/>\n        &#034;input_ids&#034;: {0: &#034;batch_size&#034;, 1: &#034;sequence_length&#034;},<br \/>\n        &#034;output_tokens&#034;: {0: &#034;batch_size&#034;, 1: &#034;sequence_length&#034;}<br \/>\n    },<br \/>\n    opset_version&#061;14<br \/>\n)<\/p>\n<h4>3.2 \u6027\u80fd\u4f18\u5316\u7b56\u7565<\/h4>\n<p>\u6211\u4eec\u91c7\u7528\u4e86\u591a\u79cd\u4f18\u5316\u6280\u672f\u63d0\u5347\u63a8\u7406\u6027\u80fd&#xff1a;<\/p>\n<ul>\n<li>TensorRT\u52a0\u901f&#xff1a;\u4f7f\u7528FP16\u7cbe\u5ea6\u548c\u5c42\u878d\u5408\u6280\u672f<\/li>\n<li>\u52a8\u6001\u6279\u5904\u7406&#xff1a;Triton\u5185\u7f6e\u7684\u52a8\u6001\u6279\u5904\u7406\u529f\u80fd<\/li>\n<li>\u6a21\u578b\u6d41\u6c34\u7ebf&#xff1a;\u6587\u672c\u7f16\u7801\u548c\u58f0\u7801\u5668\u5e76\u884c\u6267\u884c<\/li>\n<\/ul>\n<h3>4. \u9ad8\u5e76\u53d1\u90e8\u7f72\u65b9\u6848<\/h3>\n<h4>4.1 Kubernetes\u90e8\u7f72\u914d\u7f6e<\/h4>\n<p>apiVersion: apps\/v1<br \/>\nkind: Deployment<br \/>\nmetadata:<br \/>\n  name: triton-fish-speech<br \/>\nspec:<br \/>\n  replicas: 3<br \/>\n  selector:<br \/>\n    matchLabels:<br \/>\n      app: triton-fish-speech<br \/>\n  template:<br \/>\n    metadata:<br \/>\n      labels:<br \/>\n        app: triton-fish-speech<br \/>\n    spec:<br \/>\n      containers:<br \/>\n      &#8211; name: triton-server<br \/>\n        image: nvcr.io\/nvidia\/tritonserver:23.07-py3<br \/>\n        resources:<br \/>\n          limits:<br \/>\n            nvidia.com\/gpu: 2<br \/>\n          requests:<br \/>\n            nvidia.com\/gpu: 2<br \/>\n        ports:<br \/>\n        &#8211; containerPort: 8000<br \/>\n        &#8211; containerPort: 8001<br \/>\n        &#8211; containerPort: 8002<br \/>\n        volumeMounts:<br \/>\n        &#8211; mountPath: \/models<br \/>\n          name: model-repository<br \/>\n      volumes:<br \/>\n      &#8211; name: model-repository<br \/>\n        persistentVolumeClaim:<br \/>\n          claimName: model-pvc<\/p>\n<h4>4.2 \u8d1f\u8f7d\u5747\u8861\u914d\u7f6e<\/h4>\n<p>\u4f7f\u7528Nginx\u4f5c\u4e3a\u8d1f\u8f7d\u5747\u8861\u5668&#xff0c;\u5206\u914d\u8bf7\u6c42\u5230\u591a\u4e2aTriton\u5b9e\u4f8b&#xff1a;<\/p>\n<p>upstream triton_servers {<br \/>\n    server triton-server-1:8000;<br \/>\n    server triton-server-2:8000;<br \/>\n    server triton-server-3:8000;<br \/>\n}<\/p>\n<p>server {<br \/>\n    listen 80;<\/p>\n<p>    location \/v2\/models\/fish_speech\/versions\/1\/infer {<br \/>\n        proxy_pass http:\/\/triton_servers\/v2\/models\/fish_speech\/versions\/1\/infer;<br \/>\n        proxy_set_header Host $host;<br \/>\n    }<br \/>\n}<\/p>\n<h3>5. \u6027\u80fd\u6d4b\u8bd5\u4e0e\u5bf9\u6bd4<\/h3>\n<h4>5.1 \u6d4b\u8bd5\u73af\u5883\u914d\u7f6e<\/h4>\n<p>\u6211\u4eec\u5728\u4ee5\u4e0b\u73af\u5883\u4e2d\u8fdb\u884c\u6027\u80fd\u6d4b\u8bd5&#xff1a;<\/p>\n<ul>\n<li>GPU&#xff1a;NVIDIA A100 80GB \u00d7 4<\/li>\n<li>CPU&#xff1a;AMD EPYC 7742 64\u6838\u5fc3<\/li>\n<li>\u5185\u5b58&#xff1a;512GB DDR4<\/li>\n<li>\u8f6f\u4ef6&#xff1a;Ubuntu 20.04, Docker 20.10, Kubernetes 1.25<\/li>\n<\/ul>\n<h4>5.2 \u6027\u80fd\u5bf9\u6bd4\u6570\u636e<\/h4>\n<table>\n<tr>\u6307\u6807\u539f\u751fPython\u670d\u52a1Triton\u4f18\u5316\u670d\u52a1\u63d0\u5347\u6bd4\u4f8b<\/tr>\n<tbody>\n<tr>\n<td>\u5355\u8bf7\u6c42\u5ef6\u8fdf<\/td>\n<td>350ms<\/td>\n<td>280ms<\/td>\n<td>20%<\/td>\n<\/tr>\n<tr>\n<td>\u6700\u5927QPS<\/td>\n<td>15<\/td>\n<td>120<\/td>\n<td>700%<\/td>\n<\/tr>\n<tr>\n<td>GPU\u5229\u7528\u7387<\/td>\n<td>30%<\/td>\n<td>85%<\/td>\n<td>183%<\/td>\n<\/tr>\n<tr>\n<td>\u5185\u5b58\u5360\u7528<\/td>\n<td>8GB<\/td>\n<td>6GB<\/td>\n<td>25%<\/td>\n<\/tr>\n<tr>\n<td>\u5e76\u53d1\u7528\u6237\u6570<\/td>\n<td>10<\/td>\n<td>100<\/td>\n<td>900%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4>5.3 \u8d44\u6e90\u4f7f\u7528\u4f18\u5316<\/h4>\n<p>Triton\u670d\u52a1\u5668\u7684\u52a8\u6001\u6279\u5904\u7406\u529f\u80fd\u663e\u8457\u63d0\u5347\u4e86\u8d44\u6e90\u5229\u7528\u7387&#xff1a;<\/p>\n<p># \u52a8\u6001\u6279\u5904\u7406\u914d\u7f6e\u793a\u4f8b<br \/>\ndynamic_batching {<br \/>\n  preferred_batch_size: [4, 8, 16, 32]<br \/>\n  max_queue_delay_microseconds: 5000<br \/>\n}<\/p>\n<h3>6. \u5b9e\u9645\u5e94\u7528\u6848\u4f8b<\/h3>\n<h4>6.1 \u5728\u7ebf\u8bed\u97f3\u5408\u6210\u5e73\u53f0<\/h4>\n<p>\u67d0\u5728\u7ebf\u6559\u80b2\u5e73\u53f0\u91c7\u7528Triton\u5c01\u88c5\u7684Fish Speech 1.5\u670d\u52a1&#xff0c;\u4e3a\u8bfe\u7a0b\u5185\u5bb9\u751f\u6210\u8bed\u97f3\u8bb2\u89e3&#xff1a;<\/p>\n<ul>\n<li>\u65e5\u5747\u8bf7\u6c42\u91cf&#xff1a;50\u4e07\u6b21<\/li>\n<li>\u5cf0\u503cQPS&#xff1a;120<\/li>\n<li>\u5e73\u5747\u54cd\u5e94\u65f6\u95f4&#xff1a;300ms<\/li>\n<li>\u670d\u52a1\u53ef\u7528\u6027&#xff1a;99.95%<\/li>\n<\/ul>\n<h4>6.2 \u667a\u80fd\u5ba2\u670d\u7cfb\u7edf<\/h4>\n<p>\u67d0\u7535\u5546\u5e73\u53f0\u5c06Triton\u670d\u52a1\u96c6\u6210\u5230\u667a\u80fd\u5ba2\u670d\u7cfb\u7edf\u4e2d&#xff1a;<\/p>\n<p>import tritonclient.http as httpclient<\/p>\n<p>class TTSService:<br \/>\n    def __init__(self, url):<br \/>\n        self.client &#061; httpclient.InferenceServerClient(url&#061;url)<\/p>\n<p>    def generate_speech(self, text, voice_type&#061;&#034;default&#034;):<br \/>\n        inputs &#061; [<br \/>\n            httpclient.InferInput(&#034;text&#034;, [1], &#034;BYTES&#034;),<br \/>\n            httpclient.InferInput(&#034;voice_type&#034;, [1], &#034;BYTES&#034;)<br \/>\n        ]<br \/>\n        inputs[0].set_data_from_numpy(np.array([text], dtype&#061;object))<br \/>\n        inputs[1].set_data_from_numpy(np.array([voice_type], dtype&#061;object))<\/p>\n<p>        outputs &#061; [httpclient.InferRequestedOutput(&#034;audio&#034;)]<\/p>\n<p>        result &#061; self.client.infer(<br \/>\n            model_name&#061;&#034;fish_speech&#034;,<br \/>\n            inputs&#061;inputs,<br \/>\n            outputs&#061;outputs<br \/>\n        )<\/p>\n<p>        return result.as_numpy(&#034;audio&#034;)<\/p>\n<h3>7. \u8fd0\u7ef4\u4e0e\u76d1\u63a7<\/h3>\n<h4>7.1 \u5065\u5eb7\u68c0\u67e5\u914d\u7f6e<\/h4>\n<p>\u4e3a\u786e\u4fdd\u670d\u52a1\u7a33\u5b9a\u6027&#xff0c;\u6211\u4eec\u5b9e\u73b0\u4e86\u591a\u5c42\u6b21\u5065\u5eb7\u68c0\u67e5&#xff1a;<\/p>\n<p># Triton\u5065\u5eb7\u68c0\u67e5\u914d\u7f6e<br \/>\nlivenessProbe:<br \/>\n  httpGet:<br \/>\n    path: \/v2\/health\/live<br \/>\n    port: 8000<br \/>\n  initialDelaySeconds: 60<br \/>\n  periodSeconds: 30<\/p>\n<p>readinessProbe:<br \/>\n  httpGet:<br \/>\n    path: \/v2\/health\/ready<br \/>\n    port: 8000<br \/>\n  initialDelaySeconds: 30<br \/>\n  periodSeconds: 15<\/p>\n<h4>7.2 \u76d1\u63a7\u6307\u6807\u6536\u96c6<\/h4>\n<p>\u4f7f\u7528Prometheus\u548cGrafana\u76d1\u63a7Triton\u670d\u52a1\u5668\u6027\u80fd&#xff1a;<\/p>\n<ul>\n<li>GPU\u4f7f\u7528\u7387&#xff1a;\u663e\u5b58\u5360\u7528\u3001\u8ba1\u7b97\u5229\u7528\u7387<\/li>\n<li>\u8bf7\u6c42\u6307\u6807&#xff1a;QPS\u3001\u5ef6\u8fdf\u3001\u9519\u8bef\u7387<\/li>\n<li>\u6279\u5904\u7406\u6548\u7387&#xff1a;\u6279\u5904\u7406\u5927\u5c0f\u3001\u961f\u5217\u7b49\u5f85\u65f6\u95f4<\/li>\n<\/ul>\n<h3>8. \u603b\u7ed3\u4e0e\u5c55\u671b<\/h3>\n<p>\u901a\u8fc7\u5c06Fish Speech 1.5\u6a21\u578b\u90e8\u7f72\u5230NVIDIA Triton\u63a8\u7406\u670d\u52a1\u5668&#xff0c;\u6211\u4eec\u5b9e\u73b0\u4e86\u663e\u8457\u7684\u6027\u80fd\u63d0\u5347&#xff1a;<\/p>\n<li>\u541e\u5410\u91cf\u63d0\u5347&#xff1a;\u4ece15 QPS\u63d0\u5347\u5230120 QPS&#xff0c;\u589e\u957f700%<\/li>\n<li>\u8d44\u6e90\u4f18\u5316&#xff1a;GPU\u5229\u7528\u7387\u4ece30%\u63d0\u5347\u523085%&#xff0c;\u5185\u5b58\u5360\u7528\u51cf\u5c1125%<\/li>\n<li>\u5e76\u53d1\u80fd\u529b&#xff1a;\u652f\u6301\u5e76\u53d1\u7528\u6237\u6570\u4ece10\u589e\u52a0\u5230100<\/li>\n<li>\u751f\u4ea7\u5c31\u7eea&#xff1a;\u5b8c\u5584\u7684\u76d1\u63a7\u3001\u6269\u7f29\u5bb9\u548c\u6545\u969c\u6062\u590d\u673a\u5236<\/li>\n<p>\u672a\u6765\u6211\u4eec\u5c06\u8fdb\u4e00\u6b65\u4f18\u5316\u6a21\u578b\u63a8\u7406\u6548\u7387&#xff0c;\u63a2\u7d22\u91cf\u5316\u6280\u672f\u548c\u66f4\u9ad8\u6548\u7684\u6ce8\u610f\u529b\u673a\u5236&#xff0c;\u6301\u7eed\u63d0\u5347\u8bed\u97f3\u5408\u6210\u670d\u52a1\u7684\u6027\u80fd\u548c\u7528\u6237\u4f53\u9a8c\u3002<\/p>\n<hr \/>\n<p>\u83b7\u53d6\u66f4\u591aAI\u955c\u50cf<\/p>\n<p>\u60f3\u63a2\u7d22\u66f4\u591aAI\u955c\u50cf\u548c\u5e94\u7528\u573a\u666f&#xff1f;\u8bbf\u95ee 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