{"id":8130,"date":"2026-05-12T03:25:08","date_gmt":"2026-05-11T19:25:08","guid":{"rendered":"https:\/\/infernews.com\/blog\/?p=8130"},"modified":"2026-05-12T03:25:09","modified_gmt":"2026-05-11T19:25:09","slug":"mv-split","status":"publish","type":"post","link":"https:\/\/infernews.com\/blog\/mv-split\/","title":{"rendered":"mv-split\uff1a\u5343\u5c64\u7d1a\u5716\u50cf\u751f\u6210\u5be6\u9a57\uff0c\u6548\u80fd\u8207\u76f8\u5bb9\u6027\u517c\u9867"},"content":{"rendered":"<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/infernews.com\/blog\/wp-content\/uploads\/2026\/05\/pasted-49f7b49f4bfb.jpg\" alt=\"Repository image for erwold\/mv-split\" \/><\/figure>\n<p>mv-split \u662f\u4e00\u500b\u7528\u4f86\u7522\u751f\u5716\u7247\u7684\u7814\u7a76\u578b\u5c08\u6848\uff0c\u6838\u5fc3\u662f\u540d\u70ba MVSplit-DiT \u7684\u8d85\u6df1\u5c64\u6a21\u578b\uff0c\u6574\u9ad4\u6df1\u5ea6\u9054 1000 \u5c64\u3002\u5b83\u4e0d\u662f\u4e00\u822c\u5373\u88dd\u5373\u7528\u7684\u5716\u7247\u5de5\u5177\uff0c\u800c\u662f\u8f03\u9069\u5408\u60f3\u6e2c\u8a66\u65b0\u4e00\u4ee3\u751f\u6210\u67b6\u69cb\u3001\u6bd4\u8f03\u6548\u80fd\uff0c\u6216\u8005\u91cd\u73fe\u8ad6\u6587\u7d50\u679c\u7684\u4eba\u4f7f\u7528\u3002<\/p>\n<p>\u5be6\u969b\u4f7f\u7528\u4e0a\uff0c\u6d41\u7a0b\u7b97\u6e05\u6670\uff1a\u5148\u6e96\u5099\u6a21\u578b\u6b0a\u91cd\u3001FLUX.2 \u7684\u81ea\u7de8\u78bc\u5668\uff0c\u4ee5\u53ca Qwen3 \u6587\u5b57\u7de8\u78bc\u5668\uff0c\u4e4b\u5f8c\u900f\u904e sample.py \u8f38\u5165\u63d0\u793a\u8a5e\u3001\u6307\u5b9a\u8f38\u51fa\u8cc7\u6599\u593e\uff0c\u5c31\u53ef\u4ee5\u751f\u6210\u5716\u7247\u3002\u5b83\u4ea6\u652f\u63f4\u5f9e\u7bc4\u4f8b\u63d0\u793a\u8a5e\u6e05\u55ae\u9010\u884c\u62bd\u6a23\u3001\u96a8\u6a5f\u62bd\u6a23\uff0c\u751a\u81f3\u4e00\u6b21\u904e\u8dd1\u5b8c\u6574\u6279\u63d0\u793a\uff0c\u65b9\u4fbf\u505a\u6e2c\u8a66\u548c\u6bd4\u8f03\u3002<\/p>\n<p>\u9019\u500b\u5c08\u6848\u6700\u503c\u5f97\u7559\u610f\u7684\u5730\u65b9\uff0c\u662f\u5b83\u540c\u6642\u63d0\u4f9b Triton \u6838\u5fc3\u52a0\u901f\u8207 PyTorch \u5f8c\u5099\u8def\u5f91\u3002\u63db\u53e5\u8a71\u8aaa\uff0c\u5c31\u7b97\u6a5f\u5668\u6c92\u6709 Triton\uff0c\u7406\u8ad6\u4e0a\u4ecd\u53ef\u904b\u884c\uff1b\u53ea\u662f\u5c0d\u65bc 1000 \u5c64\u9019\u7a2e\u6df1\u5ea6\uff0cREADME \u5df2\u660e\u78ba\u63d0\u9192 CPU \u96d6\u53ef\u4f5c\u5f8c\u5099\uff0c\u4f46\u5be6\u969b\u4e0a\u4e26\u4e0d\u5be6\u7528\uff0c\u8f03\u5408\u9069\u7684\u74b0\u5883\u4ecd\u662f PyTorch 2.x \u914d\u5408 CUDA\u3002<\/p>\n<ul>\n<li>\u63a1\u7528\u8d85\u6df1\u5c64 DiT \u67b6\u69cb\uff0c\u5b9a\u4f4d\u504f\u7814\u7a76\u8207\u9ad8\u968e\u5be6\u9a57<\/li>\n<li>\u4ee5 Triton \u6838\u5fc3\u52a0\u901f\u591a\u500b\u95dc\u9375\u904b\u7b97\uff0c\u540c\u6642\u4fdd\u7559 PyTorch \u5f8c\u5099<\/li>\n<li>\u53ef\u76f4\u63a5\u7528\u81ea\u8a02\u63d0\u793a\u8a5e\u3001\u63d0\u793a\u8a5e\u6a94\u6848\u6216\u6279\u6b21\u65b9\u5f0f\u751f\u6210\u5716\u7247<\/li>\n<li>\u6703\u8f38\u51fa PNG \u5716\u7247\u53ca metadata.jsonl\uff0c\u65b9\u4fbf\u8a18\u9304\u5be6\u9a57\u7d50\u679c<\/li>\n<\/ul>\n<p>\u5f9e\u8a2d\u8a08\u4f86\u770b\uff0c\u5b83\u7684\u4e3b\u8981\u5275\u65b0\u4e0d\u53ea\u5728\u300c\u5c64\u6578\u5920\u6df1\u300d\uff0c\u4ea6\u5305\u62ec\u628a\u591a\u500b\u5e95\u5c64\u904b\u7b97\u5143\u4ef6\u62c6\u5f97\u76f8\u7576\u660e\u78ba\uff0c\u4f8b\u5982 RoPE\u3001RMSNorm\u3001QK-Norm \u548c SwiGLU \u90fd\u6709\u7368\u7acb\u5be6\u4f5c\uff0c\u986f\u793a\u4f5c\u8005\u5f88\u91cd\u8996\u63a8\u8ad6\u8def\u5f91\u7684\u6548\u7387\u8207\u53ef\u66ff\u63db\u6027\u3002\u9019\u7a2e\u505a\u6cd5\u5c0d\u4e00\u822c\u7528\u5bb6\u672a\u5fc5\u76f4\u63a5\u6709\u611f\uff0c\u4f46\u5c0d\u958b\u767c\u8005\u6216\u7814\u7a76\u8005\u4f86\u8aaa\uff0c\u4ee3\u8868\u66f4\u5bb9\u6613\u91dd\u5c0d\u6548\u80fd\u74f6\u9838\u505a\u8abf\u6574\u3002<\/p>\n<p>\u6700\u9069\u5408\u7684\u61c9\u7528\u5834\u666f\uff0c\u5305\u62ec\u751f\u6210\u6a21\u578b\u7814\u7a76\u3001\u63a8\u8ad6\u6548\u80fd\u6e2c\u8a66\u3001\u6bd4\u8f03 Triton \u8207 PyTorch \u5f8c\u5099\u8868\u73fe\uff0c\u4ee5\u53ca\u91cd\u73fe\u8ad6\u6587\u65b9\u6cd5\u3002\u82e5\u4f60\u53ea\u662f\u60f3\u7c21\u55ae\u8f38\u5165\u4e00\u53e5\u6587\u5b57\u5c31\u7a69\u5b9a\u51fa\u5716\uff0c\u9019\u500b\u5c08\u6848\u7684\u9580\u6abb\u6703\u504f\u9ad8\uff1b\u4f46\u82e5\u4f60\u9700\u8981\u4e00\u500b\u7d50\u69cb\u6e05\u695a\u3001\u53ef\u89c0\u5bdf\u63a8\u8ad6\u7d30\u7bc0\u7684\u5be6\u9a57\u5e73\u53f0\uff0c\u5b83\u5c31\u76f8\u7576\u6709\u53c3\u8003\u50f9\u503c\u3002\u76f8\u95dc\u6a21\u578b\u65b9\u9762\uff0c\u9700\u914d\u5408 FLUX.2 AutoEncoder \u8207 Qwen\/Qwen3-0.6B \u6587\u5b57\u7de8\u78bc\u5668\u3002<\/p>\n<p><strong>Source:<\/strong> <a href=\"https:\/\/github.com\/erwold\/mv-split\" rel=\"noopener noreferrer\">https:\/\/github.com\/erwold\/mv-split<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u9019\u500b\u5c08\u6848\u628a\u8d85\u6df1\u5c64 DiT 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