{"id":1305,"date":"2023-04-18T16:14:54","date_gmt":"2023-04-18T07:14:54","guid":{"rendered":"http:\/\/edu.ujhb.org\/?p=1305"},"modified":"2023-04-18T16:14:54","modified_gmt":"2023-04-18T07:14:54","slug":"mlflow%e5%85%a5%e9%97%a8%ef%bc%88%e4%b8%ad%e6%96%87%e7%89%88%ef%bc%89","status":"publish","type":"post","link":"https:\/\/edu.ujhb.org\/?p=1305","title":{"rendered":"MLFlow\u5165\u95e8\uff08\u4e2d\u6587\u7248\uff09"},"content":{"rendered":"\n<p>\u6211\u662f\u8981\u505aIT\u6559\u7a0b\u7684\u89c6\u9891\uff0c\u4f60\u80fd\u5426\u6839\u636e\u7f51\u7ad9\u7684\u5185\u5bb9\uff0c\u4e3a\u6211\u5b89\u6392\u89c6\u9891\u6559\u7a0b\u7684\u6587\u5b57\u5185\u5bb9\u3002\u6211\u4eec\u5148\u4ecemlflow\u6559\u7a0b\u5f00\u59cb\uff0c\u4f60\u5148\u4e3a\u6211\u5217\u51fa\u8981\u8bb2\u89e3\u7684\u5185\u5bb9\u4e00\u89c8\u3002<\/p>\n\n\n\n<p>\u5f53\u7136\u53ef\u4ee5\uff01\u4ee5\u4e0b\u662f\u4e00\u4e2a\u57fa\u4e8e MLflow \u7684\u6559\u7a0b\u5927\u7eb2\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u8bfe\u7a0b\u4ecb\u7ecd\u4e0e\u76ee\u6807\n<ul class=\"wp-block-list\">\n<li>\u672c\u8bfe\u7a0b\u7684\u76ee\u7684\u4e0e\u76ee\u6807<\/li>\n\n\n\n<li>\u4e3a\u4ec0\u4e48\u9009\u62e9 MLflow<\/li>\n\n\n\n<li>MLflow \u7684\u4f18\u52bf\u548c\u7279\u70b9<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>MLflow \u6982\u8ff0\n<ul class=\"wp-block-list\">\n<li>MLflow \u7ec4\u4ef6\u4e0e\u67b6\u6784<\/li>\n\n\n\n<li>MLflow \u8ddf\u8e2a\u3001\u9879\u76ee\u3001\u6a21\u578b\u3001\u6ce8\u518c\u8868\u7684\u6982\u5ff5\u4ecb\u7ecd<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>\u5b89\u88c5\u4e0e\u914d\u7f6e\n<ul class=\"wp-block-list\">\n<li>\u5982\u4f55\u5b89\u88c5 MLflow<\/li>\n\n\n\n<li>\u914d\u7f6e MLflow \u7684\u73af\u5883\u4e0e\u540e\u7aef\u5b58\u50a8<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>MLflow Tracking\n<ul class=\"wp-block-list\">\n<li>\u4f7f\u7528 MLflow Tracking \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e<\/li>\n\n\n\n<li>\u901a\u8fc7 MLflow UI \u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c<\/li>\n\n\n\n<li>\u67e5\u8be2\u4e0e\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c<\/li>\n\n\n\n<li>\u8bb0\u5f55\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>MLflow Projects\n<ul class=\"wp-block-list\">\n<li>\u521b\u5efa\u4e00\u4e2a MLflow \u9879\u76ee<\/li>\n\n\n\n<li>\u5b9a\u4e49 MLproject \u6587\u4ef6<\/li>\n\n\n\n<li>\u9879\u76ee\u4f9d\u8d56\u7ba1\u7406<\/li>\n\n\n\n<li>\u4f7f\u7528 MLflow \u8fd0\u884c\u9879\u76ee<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>MLflow Models\n<ul class=\"wp-block-list\">\n<li>\u521b\u5efa MLflow Model<\/li>\n\n\n\n<li>\u4f7f\u7528\u4e0d\u540c\u7684\u6a21\u578b\u683c\u5f0f\u4fdd\u5b58\u6a21\u578b<\/li>\n\n\n\n<li>\u90e8\u7f72 MLflow Model<\/li>\n\n\n\n<li>\u4f7f\u7528 MLflow Model Registry \u7ba1\u7406\u6a21\u578b<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>MLflow Model Registry\n<ul class=\"wp-block-list\">\n<li>\u4ecb\u7ecd MLflow Model Registry<\/li>\n\n\n\n<li>\u6ce8\u518c\u6a21\u578b\u4e0e\u7248\u672c\u7ba1\u7406<\/li>\n\n\n\n<li>\u6a21\u578b\u751f\u547d\u5468\u671f\u7ba1\u7406\u4e0e\u534f\u4f5c<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>\u96c6\u6210 MLflow \u4e0e\u5176\u4ed6\u5de5\u5177\n<ul class=\"wp-block-list\">\n<li>\u96c6\u6210 MLflow \u4e0e TensorFlow, PyTorch \u7b49\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6<\/li>\n\n\n\n<li>\u4f7f\u7528 MLflow \u4e0e Jupyter Notebook<\/li>\n\n\n\n<li>\u4e0e\u4e91\u670d\u52a1\u5546\u96c6\u6210\uff0c\u5982 AWS SageMaker, Azure ML \u7b49<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>\u751f\u4ea7\u73af\u5883\u90e8\u7f72\u4e0e\u6700\u4f73\u5b9e\u8df5\n<ul class=\"wp-block-list\">\n<li>\u5982\u4f55\u5c06 MLflow Model \u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883<\/li>\n\n\n\n<li>MLflow \u5728\u751f\u4ea7\u73af\u5883\u4e2d\u7684\u6700\u4f73\u5b9e\u8df5<\/li>\n\n\n\n<li>\u5b89\u5168\u4e0e\u6027\u80fd\u4f18\u5316<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>\u8bfe\u7a0b\u603b\u7ed3\u4e0e\u5c55\u671b<\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u672c\u8bfe\u7a0b\u7684\u56de\u987e\u4e0e\u603b\u7ed3<\/li>\n\n\n\n<li>MLflow \u793e\u533a\u4e0e\u8d44\u6e90<\/li>\n\n\n\n<li>MLflow \u7684\u672a\u6765\u53d1\u5c55<\/li>\n<\/ul>\n\n\n\n<p>\u6839\u636e\u8fd9\u4e2a\u5927\u7eb2\uff0c\u60a8\u53ef\u4ee5\u5206\u522b\u5236\u4f5c\u4e00\u7cfb\u5217\u7684\u89c6\u9891\u6559\u7a0b\uff0c\u9010\u6b65\u6df1\u5165\u8bb2\u89e3 MLflow \u7684\u5404\u4e2a\u65b9\u9762\u3002\u5e0c\u671b\u8fd9\u5bf9\u60a8\u6709\u6240\u5e2e\u52a9\uff01<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u672c\u8bfe\u7a0b\u7684\u76ee\u7684\u4e0e\u76ee\u6807<\/p>\n\n\n\n<p>\u672c\u8bfe\u7a0b\u7684\u76ee\u7684\u4e0e\u76ee\u6807\u5982\u4e0b\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u7406\u89e3 MLflow \u7684\u57fa\u672c\u6982\u5ff5\u548c\u7ec4\u4ef6\uff1a\u901a\u8fc7\u672c\u8bfe\u7a0b\uff0c\u5b66\u5458\u5c06\u4e86\u89e3 MLflow \u7684\u57fa\u672c\u67b6\u6784\u548c\u7ec4\u4ef6\uff0c\u5305\u62ec\u8ddf\u8e2a\u3001\u9879\u76ee\u3001\u6a21\u578b\u548c\u6ce8\u518c\u8868\u3002\u8fd9\u6709\u52a9\u4e8e\u5b66\u5458\u638c\u63e1 MLflow \u7684\u6838\u5fc3\u529f\u80fd\u548c\u4f7f\u7528\u573a\u666f\u3002<\/li>\n\n\n\n<li>\u638c\u63e1 MLflow \u7684\u5b9e\u9645\u5e94\u7528\uff1a\u672c\u8bfe\u7a0b\u5c06\u5e2e\u52a9\u5b66\u5458\u5b66\u4f1a\u4f7f\u7528 MLflow \u8ddf\u8e2a\u5b9e\u9a8c\u6570\u636e\u3001\u7ec4\u7ec7\u673a\u5668\u5b66\u4e60\u9879\u76ee\u3001\u4fdd\u5b58\u548c\u90e8\u7f72\u6a21\u578b\u4ee5\u53ca\u7ba1\u7406\u6a21\u578b\u751f\u547d\u5468\u671f\u3002\u5b66\u5458\u5c06\u80fd\u591f\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\u7075\u6d3b\u8fd0\u7528 MLflow\uff0c\u63d0\u9ad8\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u7a0b\u7684\u6548\u7387\u3002<\/li>\n\n\n\n<li>\u63d0\u9ad8\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u53ef\u91cd\u73b0\u6027\u548c\u534f\u4f5c\u6548\u7387\uff1a\u901a\u8fc7\u4f7f\u7528 MLflow\uff0c\u5b66\u5458\u53ef\u4ee5\u66f4\u597d\u5730\u8bb0\u5f55\u5b9e\u9a8c\u8fc7\u7a0b\u3001\u53c2\u6570\u548c\u7ed3\u679c\uff0c\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u91cd\u73b0\u6027\u3002\u540c\u65f6\uff0c\u901a\u8fc7\u6a21\u578b\u6ce8\u518c\u8868\uff0c\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u66f4\u5bb9\u6613\u5730\u5171\u4eab\u548c\u534f\u4f5c\u6a21\u578b\uff0c\u63d0\u9ad8\u6574\u4f53\u5de5\u4f5c\u6548\u7387\u3002<\/li>\n\n\n\n<li>\u5b66\u4f1a\u4e0e\u5176\u4ed6\u5de5\u5177\u548c\u4e91\u670d\u52a1\u96c6\u6210\uff1a\u672c\u8bfe\u7a0b\u5c06\u6559\u6388\u5b66\u5458\u5982\u4f55\u5c06 MLflow \u4e0e\u5176\u4ed6\u6d41\u884c\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff08\u5982 TensorFlow \u548c PyTorch\uff09\u96c6\u6210\uff0c\u4ee5\u53ca\u5982\u4f55\u4e0e Jupyter Notebook \u548c\u4e91\u670d\u52a1\uff08\u5982 AWS SageMaker \u548c Azure ML\uff09\u96c6\u6210\uff0c\u4ee5\u4fbf\u5728\u5404\u79cd\u73af\u5883\u4e2d\u7075\u6d3b\u4f7f\u7528 MLflow\u3002<\/li>\n\n\n\n<li>\u638c\u63e1 MLflow \u7684\u751f\u4ea7\u73af\u5883\u90e8\u7f72\u4e0e\u6700\u4f73\u5b9e\u8df5\uff1a\u672c\u8bfe\u7a0b\u5c06\u6307\u5bfc\u5b66\u5458\u5982\u4f55\u5c06 MLflow Model \u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883\uff0c\u5e76\u4ecb\u7ecd\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528 MLflow \u7684\u6700\u4f73\u5b9e\u8df5\u3001\u5b89\u5168\u6027\u548c\u6027\u80fd\u4f18\u5316\u65b9\u6cd5\uff0c\u5e2e\u52a9\u5b66\u5458\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\u66f4\u597d\u5730\u5e94\u7528 MLflow\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u7684\u6765\u8bf4\uff0c\u672c\u8bfe\u7a0b\u65e8\u5728\u5e2e\u52a9\u5b66\u5458\u5168\u9762\u638c\u63e1 MLflow \u7684\u529f\u80fd\u548c\u5e94\u7528\uff0c\u63d0\u9ad8\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u5f00\u53d1\u6548\u7387\u548c\u8d28\u91cf\uff0c\u4fc3\u8fdb\u56e2\u961f\u534f\u4f5c\u548c\u9879\u76ee\u53ef\u7ef4\u62a4\u6027\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u4e3a\u4ec0\u4e48\u9009\u62e9 MLflow<\/p>\n\n\n\n<p>\u9009\u62e9 MLflow \u7684\u539f\u56e0\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u70b9\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u5f00\u6e90\u4e14\u6613\u4e8e\u4f7f\u7528\uff1aMLflow \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u673a\u5668\u5b66\u4e60\u5e73\u53f0\uff0c\u62e5\u6709\u6d3b\u8dc3\u7684\u793e\u533a\u548c\u4e30\u5bcc\u7684\u8d44\u6e90\u3002\u5b83\u7684\u8bbe\u8ba1\u521d\u8877\u5c31\u662f\u8ba9\u673a\u5668\u5b66\u4e60\u5de5\u7a0b\u5e08\u548c\u6570\u636e\u79d1\u5b66\u5bb6\u80fd\u591f\u66f4\u8f7b\u677e\u5730\u7ba1\u7406\u590d\u6742\u7684\u673a\u5668\u5b66\u4e60\u9879\u76ee\u3002MLflow \u7684 API \u8bbe\u8ba1\u7b80\u5355\u76f4\u89c2\uff0c\u6613\u4e8e\u4e0a\u624b\u3002<\/li>\n\n\n\n<li>\u7ec4\u4ef6\u5316\u4e0e\u6a21\u5757\u5316\uff1aMLflow \u7531 Tracking\u3001Projects\u3001Models \u548c Model Registry \u56db\u4e2a\u7ec4\u4ef6\u7ec4\u6210\uff0c\u8fd9\u4e9b\u7ec4\u4ef6\u53ef\u4ee5\u72ec\u7acb\u4f7f\u7528\uff0c\u4e5f\u53ef\u4ee5\u7ec4\u5408\u4f7f\u7528\uff0c\u6ee1\u8db3\u4e0d\u540c\u7684\u9700\u6c42\u3002\u8fd9\u79cd\u6a21\u5757\u5316\u8bbe\u8ba1\u4f7f\u5f97 MLflow \u975e\u5e38\u7075\u6d3b\uff0c\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u573a\u666f\u8fdb\u884c\u5b9a\u5236\u3002<\/li>\n\n\n\n<li>\u9002\u5e94\u591a\u79cd\u673a\u5668\u5b66\u4e60\u6846\u67b6\uff1aMLflow \u652f\u6301\u591a\u79cd\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60\u6846\u67b6\uff0c\u5982 TensorFlow\u3001PyTorch\u3001Scikit-learn \u7b49\u3002\u8fd9\u610f\u5473\u7740\uff0c\u65e0\u8bba\u60a8\u5728\u9879\u76ee\u4e2d\u4f7f\u7528\u54ea\u79cd\u6846\u67b6\uff0c\u90fd\u53ef\u4ee5\u501f\u52a9 MLflow \u8fdb\u884c\u7ba1\u7406\u548c\u8ddf\u8e2a\u3002<\/li>\n\n\n\n<li>\u4fc3\u8fdb\u56e2\u961f\u534f\u4f5c\u4e0e\u9879\u76ee\u53ef\u7ef4\u62a4\u6027\uff1a\u901a\u8fc7 MLflow \u7684\u6a21\u578b\u6ce8\u518c\u8868\uff0c\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u66f4\u65b9\u4fbf\u5730\u5171\u4eab\u548c\u534f\u4f5c\u6a21\u578b\u3002\u6b64\u5916\uff0cMLflow \u53ef\u4ee5\u8bb0\u5f55\u5b9e\u9a8c\u7684\u8be6\u7ec6\u4fe1\u606f\uff08\u5982\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\uff09\uff0c\u6709\u52a9\u4e8e\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u91cd\u73b0\u6027\u548c\u53ef\u7ef4\u62a4\u6027\u3002<\/li>\n\n\n\n<li>\u6613\u4e8e\u90e8\u7f72\u548c\u6269\u5c55\uff1aMLflow Model \u53ef\u4ee5\u4ee5\u591a\u79cd\u683c\u5f0f\u8fdb\u884c\u4fdd\u5b58\uff0c\u5e76\u652f\u6301\u5c06\u6a21\u578b\u90e8\u7f72\u5230\u4e0d\u540c\u7684\u73af\u5883\uff08\u5982\u672c\u5730\u670d\u52a1\u5668\u3001\u4e91\u670d\u52a1\u548c\u5bb9\u5668\u5e73\u53f0\u7b49\uff09\u3002\u6b64\u5916\uff0cMLflow \u652f\u6301\u4e0e\u5404\u79cd\u4e91\u670d\u52a1\uff08\u5982 AWS SageMaker\u3001Azure ML \u7b49\uff09\u96c6\u6210\uff0c\u65b9\u4fbf\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u8fdb\u884c\u6269\u5c55\u3002<\/li>\n\n\n\n<li>\u6d3b\u8dc3\u7684\u793e\u533a\u548c\u4e0d\u65ad\u66f4\u65b0\u7684\u529f\u80fd\uff1aMLflow \u62e5\u6709\u6d3b\u8dc3\u7684\u5f00\u53d1\u8005\u793e\u533a\uff0c\u5b9a\u671f\u53d1\u5e03\u65b0\u529f\u80fd\u548c\u4f18\u5316\u3002\u8fd9\u610f\u5473\u7740 MLflow \u5c06\u4e0d\u65ad\u9002\u5e94\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u6700\u65b0\u6280\u672f\u548c\u9700\u6c42\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0cMLflow \u4ee5\u5176\u6613\u7528\u6027\u3001\u7075\u6d3b\u6027\u3001\u517c\u5bb9\u6027\u3001\u534f\u4f5c\u6027\u548c\u53ef\u6269\u5c55\u6027\u7b49\u7279\u70b9\uff0c\u6210\u4e3a\u4e86\u7ba1\u7406\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u4f18\u79c0\u5de5\u5177\u3002\u4f7f\u7528 MLflow \u53ef\u4ee5\u5e2e\u52a9\u60a8\u63d0\u9ad8\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u5f00\u53d1\u6548\u7387\u3001\u8d28\u91cf\u548c\u53ef\u7ef4\u62a4\u6027\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91caMLflow \u7684\u4f18\u52bf\u548c\u7279\u70b9<\/p>\n\n\n\n<p>\u4ee5\u4e0b\u662f MLflow \u7684\u4f18\u52bf\u548c\u7279\u70b9\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u6613\u4e8e\u4f7f\u7528\uff1aMLflow \u7684 API \u8bbe\u8ba1\u7b80\u5355\u76f4\u89c2\uff0c\u65e0\u8bba\u662f Python\u3001R \u8fd8\u662f Java\uff0c\u90fd\u53ef\u4ee5\u8f7b\u677e\u5730\u4e0e MLflow \u8fdb\u884c\u96c6\u6210\u3002\u540c\u65f6\uff0cMLflow \u63d0\u4f9b\u4e86\u53cb\u597d\u7684\u7528\u6237\u754c\u9762\uff0c\u53ef\u4ee5\u76f4\u89c2\u5730\u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c\u548c\u6a21\u578b\u4fe1\u606f\u3002<\/li>\n\n\n\n<li>\u6a21\u5757\u5316\u8bbe\u8ba1\uff1aMLflow \u7531\u56db\u4e2a\u4e3b\u8981\u7ec4\u4ef6\u7ec4\u6210\uff0c\u5206\u522b\u662f Tracking\u3001Projects\u3001Models \u548c Model Registry\u3002\u8fd9\u4e9b\u7ec4\u4ef6\u53ef\u4ee5\u72ec\u7acb\u4f7f\u7528\uff0c\u4e5f\u53ef\u4ee5\u7ec4\u5408\u4f7f\u7528\uff0c\u6839\u636e\u5b9e\u9645\u9700\u6c42\u8fdb\u884c\u7075\u6d3b\u914d\u7f6e\u3002<\/li>\n\n\n\n<li>\u591a\u6846\u67b6\u652f\u6301\uff1aMLflow \u652f\u6301\u591a\u79cd\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60\u6846\u67b6\uff0c\u5982 TensorFlow\u3001PyTorch\u3001Scikit-learn \u7b49\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u7ba1\u7406\u548c\u8ddf\u8e2a\u4e0d\u540c\u6846\u67b6\u4e0b\u7684\u6a21\u578b\u3002<\/li>\n\n\n\n<li>\u7edf\u4e00\u7684\u6a21\u578b\u683c\u5f0f\uff1aMLflow \u63d0\u4f9b\u4e86\u7edf\u4e00\u7684\u6a21\u578b\u683c\u5f0f\uff0c\u53ef\u4ee5\u5c06\u4e0d\u540c\u6846\u67b6\u4e0b\u7684\u6a21\u578b\u4fdd\u5b58\u4e3a\u6807\u51c6\u5316\u7684\u683c\u5f0f\uff0c\u65b9\u4fbf\u5728\u4e0d\u540c\u73af\u5883\u4e0b\u90e8\u7f72\u548c\u4f7f\u7528\u3002<\/li>\n\n\n\n<li>\u6a21\u578b\u7248\u672c\u63a7\u5236\u4e0e\u534f\u4f5c\uff1a\u901a\u8fc7 MLflow Model Registry\uff0c\u53ef\u4ee5\u5b9e\u73b0\u6a21\u578b\u7684\u7248\u672c\u63a7\u5236\uff0c\u65b9\u4fbf\u56e2\u961f\u6210\u5458\u4e4b\u95f4\u7684\u534f\u4f5c\u3002\u540c\u65f6\uff0c\u53ef\u4ee5\u66f4\u597d\u5730\u7ba1\u7406\u6a21\u578b\u7684\u751f\u547d\u5468\u671f\uff0c\u5982\u5ba1\u6279\u3001\u4e0a\u7ebf\u3001\u4e0b\u7ebf\u7b49\u3002<\/li>\n\n\n\n<li>\u6613\u4e8e\u90e8\u7f72\uff1aMLflow \u652f\u6301\u5c06\u6a21\u578b\u90e8\u7f72\u5230\u591a\u79cd\u73af\u5883\uff0c\u5982\u672c\u5730\u670d\u52a1\u5668\u3001\u4e91\u670d\u52a1\u3001\u5bb9\u5668\u5e73\u53f0\u7b49\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u5c06\u6a21\u578b\u5e94\u7528\u5230\u751f\u4ea7\u73af\u5883\u4e2d\u3002<\/li>\n\n\n\n<li>\u53ef\u6269\u5c55\u6027\uff1aMLflow \u53ef\u4ee5\u4e0e\u5404\u79cd\u4e91\u670d\u52a1\uff08\u5982 AWS SageMaker\u3001Azure ML \u7b49\uff09\u96c6\u6210\uff0c\u65b9\u4fbf\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u8fdb\u884c\u6269\u5c55\u3002\u540c\u65f6\uff0cMLflow \u7684\u8bbe\u8ba1\u4e5f\u5141\u8bb8\u7528\u6237\u81ea\u5b9a\u4e49\u63d2\u4ef6\uff0c\u4ee5\u6ee1\u8db3\u7279\u5b9a\u9700\u6c42\u3002<\/li>\n\n\n\n<li>\u5f00\u6e90\u4e14\u6d3b\u8dc3\u7684\u793e\u533a\uff1aMLflow \u662f\u4e00\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u6709\u7740\u6d3b\u8dc3\u7684\u5f00\u53d1\u8005\u793e\u533a\u3002\u8fd9\u610f\u5473\u7740 MLflow \u4e0d\u65ad\u5730\u5728\u66f4\u65b0\u548c\u5b8c\u5584\uff0c\u80fd\u591f\u9002\u5e94\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u6700\u65b0\u6280\u672f\u548c\u9700\u6c42\u3002<\/li>\n\n\n\n<li>\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u91cd\u73b0\u6027\uff1aMLflow \u53ef\u4ee5\u8bb0\u5f55\u5b9e\u9a8c\u7684\u8be6\u7ec6\u4fe1\u606f\uff08\u5982\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\uff09\uff0c\u6709\u52a9\u4e8e\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u91cd\u73b0\u6027\u548c\u53ef\u7ef4\u62a4\u6027\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0cMLflow \u7684\u4f18\u52bf\u548c\u7279\u70b9\u4e3b\u8981\u4f53\u73b0\u5728\u6613\u7528\u6027\u3001\u7075\u6d3b\u6027\u3001\u517c\u5bb9\u6027\u3001\u534f\u4f5c\u6027\u3001\u90e8\u7f72\u4fbf\u6377\u6027\u3001\u53ef\u6269\u5c55\u6027\u548c\u53ef\u91cd\u73b0\u6027\u7b49\u65b9\u9762\uff0c\u4f7f\u5176\u6210\u4e3a\u7ba1\u7406\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u7406\u60f3\u5de5\u5177\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91caMLflow \u7ec4\u4ef6\u4e0e\u67b6\u6784<\/p>\n\n\n\n<p>MLflow \u662f\u4e00\u4e2a\u6a21\u5757\u5316\u7684\u673a\u5668\u5b66\u4e60\u751f\u547d\u5468\u671f\u7ba1\u7406\u5e73\u53f0\uff0c\u4e3b\u8981\u5305\u62ec\u56db\u4e2a\u7ec4\u4ef6\uff1aTracking\u3001Projects\u3001Models \u548c Model Registry\u3002\u4e0b\u9762\u662f\u8fd9\u56db\u4e2a\u7ec4\u4ef6\u7684\u8be6\u7ec6\u4ecb\u7ecd\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>MLflow Tracking\uff1a<\/li>\n<\/ol>\n\n\n\n<p>MLflow Tracking \u662f\u4e00\u4e2a\u7528\u4e8e\u8bb0\u5f55\u548c\u67e5\u8be2\u5b9e\u9a8c\u7684 API \u548c UI\u3002\u5b83\u5141\u8bb8\u60a8\u8bb0\u5f55\u5b9e\u9a8c\u7684\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\uff08\u5982\u6a21\u578b\u6587\u4ef6\u3001\u6570\u636e\u96c6\u7b49\uff09\uff0c\u4ee5\u4fbf\u5728\u540e\u7eed\u9636\u6bb5\u8fdb\u884c\u5206\u6790\u548c\u6bd4\u8f83\u3002MLflow Tracking \u652f\u6301\u672c\u5730\u6587\u4ef6\u7cfb\u7edf\u3001\u6570\u636e\u5e93\u548c\u8fdc\u7a0b\u670d\u52a1\u5668\u7b49\u591a\u79cd\u5b58\u50a8\u65b9\u5f0f\uff0c\u4fbf\u4e8e\u5b9e\u73b0\u8de8\u56e2\u961f\u548c\u8de8\u5e73\u53f0\u7684\u5b9e\u9a8c\u6570\u636e\u5171\u4eab\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"2\">\n<li>MLflow Projects\uff1a<\/li>\n<\/ol>\n\n\n\n<p>MLflow Projects \u662f\u4e00\u4e2a\u7528\u4e8e\u7ec4\u7ec7\u548c\u8fd0\u884c\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u6807\u51c6\u683c\u5f0f\u3002\u901a\u8fc7\u5b9a\u4e49\u4e00\u4e2a\u540d\u4e3a MLproject \u7684 YAML \u6587\u4ef6\uff0c\u60a8\u53ef\u4ee5\u6307\u5b9a\u9879\u76ee\u7684\u73af\u5883\u3001\u4f9d\u8d56\u548c\u5165\u53e3\u70b9\u3002\u8fd9\u79cd\u6807\u51c6\u5316\u7684\u683c\u5f0f\u6709\u52a9\u4e8e\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u91cd\u590d\u6027\u548c\u53ef\u79fb\u690d\u6027\u3002\u5176\u4ed6\u5f00\u53d1\u8005\u53ef\u4ee5\u901a\u8fc7 MLflow \u547d\u4ee4\u884c\u5de5\u5177\u6216 API \u8f7b\u677e\u8fd0\u884c\u60a8\u7684\u9879\u76ee\uff0c\u800c\u65e0\u9700\u5173\u5fc3\u5e95\u5c42\u5b9e\u73b0\u7ec6\u8282\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"3\">\n<li>MLflow Models\uff1a<\/li>\n<\/ol>\n\n\n\n<p>MLflow Models \u662f\u4e00\u4e2a\u7528\u4e8e\u4fdd\u5b58\u3001\u90e8\u7f72\u548c\u5171\u4eab\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u6807\u51c6\u683c\u5f0f\u3002MLflow Models \u652f\u6301\u591a\u79cd\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60\u6846\u67b6\uff0c\u5982 TensorFlow\u3001PyTorch\u3001Scikit-learn \u7b49\u3002\u901a\u8fc7\u5c06\u6a21\u578b\u4fdd\u5b58\u4e3a MLflow Model \u683c\u5f0f\uff0c\u60a8\u53ef\u4ee5\u5c06\u6a21\u578b\u90e8\u7f72\u5230\u4e0d\u540c\u7684\u73af\u5883\uff08\u5982\u672c\u5730\u670d\u52a1\u5668\u3001\u4e91\u670d\u52a1\u548c\u5bb9\u5668\u5e73\u53f0\u7b49\uff09\uff0c\u5b9e\u73b0\u8de8\u5e73\u53f0\u7684\u6a21\u578b\u5171\u4eab\u548c\u90e8\u7f72\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"4\">\n<li>MLflow Model Registry\uff1a<\/li>\n<\/ol>\n\n\n\n<p>MLflow Model Registry \u662f\u4e00\u4e2a\u7528\u4e8e\u7ba1\u7406\u6a21\u578b\u751f\u547d\u5468\u671f\u7684\u96c6\u4e2d\u5f0f\u5b58\u50a8\u5e93\u3002\u901a\u8fc7 MLflow Model Registry\uff0c\u60a8\u53ef\u4ee5\u8bb0\u5f55\u6a21\u578b\u7684\u7248\u672c\u3001\u72b6\u6001\u548c\u6ce8\u91ca\u7b49\u5143\u6570\u636e\u3002\u6b64\u5916\uff0cMLflow Model Registry \u652f\u6301\u6a21\u578b\u7684\u5ba1\u6279\u3001\u4e0a\u7ebf\u3001\u4e0b\u7ebf\u7b49\u751f\u547d\u5468\u671f\u7ba1\u7406\u64cd\u4f5c\uff0c\u4fbf\u4e8e\u56e2\u961f\u6210\u5458\u4e4b\u95f4\u7684\u534f\u4f5c\u548c\u6a21\u578b\u7684\u5171\u4eab\u3002<\/p>\n\n\n\n<p>\u603b\u7684\u6765\u8bf4\uff0cMLflow \u7684\u67b6\u6784\u4e3b\u8981\u7531\u4e0a\u8ff0\u56db\u4e2a\u7ec4\u4ef6\u6784\u6210\uff0c\u5b83\u4eec\u53ef\u4ee5\u72ec\u7acb\u4f7f\u7528\uff0c\u4e5f\u53ef\u4ee5\u7ec4\u5408\u4f7f\u7528\uff0c\u4ee5\u6ee1\u8db3\u5404\u79cd\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u9700\u6c42\u3002\u901a\u8fc7 MLflow\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u7ba1\u7406\u5b9e\u9a8c\u6570\u636e\u3001\u7ec4\u7ec7\u9879\u76ee\u3001\u4fdd\u5b58\u548c\u90e8\u7f72\u6a21\u578b\uff0c\u4ee5\u53ca\u534f\u540c\u5de5\u4f5c\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91caMLflow Tracking<\/p>\n\n\n\n<p>MLflow Tracking \u662f MLflow \u7684\u4e00\u4e2a\u7ec4\u4ef6\uff0c\u7528\u4e8e\u8bb0\u5f55\u3001\u67e5\u8be2\u548c\u53ef\u89c6\u5316\u673a\u5668\u5b66\u4e60\u5b9e\u9a8c\u8fc7\u7a0b\u4e2d\u4ea7\u751f\u7684\u6570\u636e\u3002\u5b83\u4e3b\u8981\u5305\u62ec\u4e00\u4e2a API \u548c\u4e00\u4e2a\u53ef\u89c6\u5316\u754c\u9762\uff0c\u53ef\u4ee5\u5e2e\u52a9\u60a8\u8ddf\u8e2a\u5b9e\u9a8c\u7684\u53c2\u6570\u3001\u6307\u6807\u3001\u6807\u7b7e\u548c\u5de5\u4ef6\uff08\u5982\u6a21\u578b\u6587\u4ef6\u3001\u6570\u636e\u96c6\u7b49\uff09\u3002<\/p>\n\n\n\n<p>\u4ee5\u4e0b\u662f MLflow Tracking \u7684\u4e00\u4e9b\u5173\u952e\u7279\u6027\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u8ddf\u8e2a\u5b9e\u9a8c\u53c2\u6570\u548c\u6307\u6807\uff1a\u5728\u5b9e\u9a8c\u8fc7\u7a0b\u4e2d\uff0c\u60a8\u53ef\u80fd\u9700\u8981\u5c1d\u8bd5\u4e0d\u540c\u7684\u8d85\u53c2\u6570\u3001\u6570\u636e\u9884\u5904\u7406\u65b9\u6cd5\u548c\u6a21\u578b\u7ed3\u6784\u3002\u901a\u8fc7 MLflow Tracking API\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u8bb0\u5f55\u8fd9\u4e9b\u53c2\u6570\u548c\u5b9e\u9a8c\u7ed3\u679c\uff08\u5982\u51c6\u786e\u7387\u3001\u635f\u5931\u503c\u7b49\u6307\u6807\uff09\uff0c\u4ee5\u4fbf\u5728\u540e\u7eed\u9636\u6bb5\u8fdb\u884c\u6bd4\u8f83\u548c\u5206\u6790\u3002<\/li>\n\n\n\n<li>\u8bb0\u5f55\u5de5\u4ef6\uff1a\u9664\u4e86\u53c2\u6570\u548c\u6307\u6807\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528 MLflow Tracking API \u4fdd\u5b58\u5b9e\u9a8c\u8fc7\u7a0b\u4e2d\u4ea7\u751f\u7684\u5de5\u4ef6\uff0c\u5982\u6a21\u578b\u6587\u4ef6\u3001\u9884\u5904\u7406\u811a\u672c\u548c\u6570\u636e\u96c6\u7b49\u3002\u8fd9\u6709\u52a9\u4e8e\u63d0\u9ad8\u5b9e\u9a8c\u7684\u53ef\u91cd\u590d\u6027\uff0c\u540c\u65f6\u65b9\u4fbf\u60a8\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u91cd\u7528\u8fd9\u4e9b\u8d44\u6e90\u3002<\/li>\n\n\n\n<li>\u53ef\u89c6\u5316\u5b9e\u9a8c\u7ed3\u679c\uff1aMLflow Tracking \u63d0\u4f9b\u4e86\u4e00\u4e2a\u53cb\u597d\u7684\u7528\u6237\u754c\u9762\uff0c\u53ef\u4ee5\u76f4\u89c2\u5730\u67e5\u770b\u5b9e\u9a8c\u7684\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528\u8be5\u754c\u9762\u5bf9\u5b9e\u9a8c\u7ed3\u679c\u8fdb\u884c\u6392\u5e8f\u3001\u7b5b\u9009\u548c\u6bd4\u8f83\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u5206\u6790\u5b9e\u9a8c\u6548\u679c\u3002<\/li>\n\n\n\n<li>\u652f\u6301\u591a\u79cd\u5b58\u50a8\u540e\u7aef\uff1aMLflow Tracking \u652f\u6301\u672c\u5730\u6587\u4ef6\u7cfb\u7edf\u3001\u6570\u636e\u5e93\u548c\u8fdc\u7a0b\u670d\u52a1\u5668\u7b49\u591a\u79cd\u5b58\u50a8\u540e\u7aef\u3002\u8fd9\u610f\u5473\u7740\u60a8\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5b58\u50a8\u65b9\u5f0f\uff0c\u5b9e\u73b0\u8de8\u56e2\u961f\u548c\u8de8\u5e73\u53f0\u7684\u5b9e\u9a8c\u6570\u636e\u5171\u4eab\u3002<\/li>\n\n\n\n<li>\u96c6\u6210\u5176\u4ed6 MLflow \u7ec4\u4ef6\uff1aMLflow Tracking \u53ef\u4ee5\u4e0e MLflow Projects \u548c MLflow Models \u7ec4\u4ef6\u65e0\u7f1d\u96c6\u6210\uff0c\u5b9e\u73b0\u7aef\u5230\u7aef\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u5728 MLflow Project \u4e2d\u81ea\u52a8\u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\uff0c\u7136\u540e\u5c06\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u4fdd\u5b58\u4e3a MLflow Model \u683c\u5f0f\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow Tracking \u662f\u4e00\u4e2a\u5f3a\u5927\u4e14\u7075\u6d3b\u7684\u5b9e\u9a8c\u7ba1\u7406\u5de5\u5177\uff0c\u53ef\u4ee5\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u8bb0\u5f55\u548c\u5206\u6790\u673a\u5668\u5b66\u4e60\u5b9e\u9a8c\u8fc7\u7a0b\uff0c\u63d0\u9ad8\u5b9e\u9a8c\u7684\u53ef\u91cd\u590d\u6027\u548c\u6548\u7387\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91caMLflow Projects<\/p>\n\n\n\n<p>MLflow Projects \u662f MLflow \u7684\u4e00\u4e2a\u7ec4\u4ef6\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e00\u79cd\u6807\u51c6\u5316\u7684\u65b9\u5f0f\u6765\u7ec4\u7ec7\u548c\u63cf\u8ff0\u673a\u5668\u5b66\u4e60\u9879\u76ee\u3002\u901a\u8fc7\u4f7f\u7528 MLflow Projects\uff0c\u60a8\u53ef\u4ee5\u66f4\u5bb9\u6613\u5730\u5206\u4eab\u3001\u91cd\u7528\u548c\u590d\u73b0\u673a\u5668\u5b66\u4e60\u4ee3\u7801\uff0c\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u79fb\u690d\u6027\u548c\u53ef\u7ef4\u62a4\u6027\u3002<\/p>\n\n\n\n<p>\u4ee5\u4e0b\u662f MLflow Projects \u7684\u4e3b\u8981\u7279\u6027\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u9879\u76ee\u63cf\u8ff0\u6587\u4ef6\uff1aMLflow Projects \u4f7f\u7528\u540d\u4e3a MLproject \u7684 YAML \u6587\u4ef6\u6765\u63cf\u8ff0\u9879\u76ee\u7684\u5143\u6570\u636e\uff0c\u5982\u9879\u76ee\u540d\u79f0\u3001\u7248\u672c\u3001\u63cf\u8ff0\u7b49\u3002\u6b64\u5916\uff0cMLproject \u6587\u4ef6\u8fd8\u53ef\u4ee5\u6307\u5b9a\u9879\u76ee\u7684\u4f9d\u8d56\u9879\uff08\u5982 Python \u5e93\u3001\u7cfb\u7edf\u5e93\u7b49\uff09\u548c\u5165\u53e3\u70b9\uff08\u5373\u53ef\u6267\u884c\u7684\u811a\u672c\u6216\u547d\u4ee4\uff09\u3002<\/li>\n\n\n\n<li>\u73af\u5883\u914d\u7f6e\uff1a\u4e3a\u4e86\u786e\u4fdd\u9879\u76ee\u53ef\u4ee5\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u6b63\u786e\u8fd0\u884c\uff0cMLflow Projects \u652f\u6301\u591a\u79cd\u73af\u5883\u914d\u7f6e\u65b9\u5f0f\uff0c\u5982 Conda\u3001Docker \u548c\u865a\u62df\u73af\u5883\u7b49\u3002\u60a8\u53ef\u4ee5\u5728 MLproject \u6587\u4ef6\u4e2d\u6307\u5b9a\u6240\u9700\u7684\u73af\u5883\u914d\u7f6e\uff0cMLflow \u4f1a\u81ea\u52a8\u5904\u7406\u76f8\u5173\u7684\u4f9d\u8d56\u548c\u8bbe\u7f6e\u3002<\/li>\n\n\n\n<li>\u5165\u53e3\u70b9\u53c2\u6570\u5316\uff1aMLflow Projects \u5141\u8bb8\u60a8\u4e3a\u9879\u76ee\u5165\u53e3\u70b9\u5b9a\u4e49\u53c2\u6570\uff0c\u8fd9\u6837\u5176\u4ed6\u7528\u6237\u53ef\u4ee5\u5728\u8fd0\u884c\u9879\u76ee\u65f6\u6839\u636e\u9700\u8981\u4f20\u5165\u4e0d\u540c\u7684\u53c2\u6570\u503c\u3002\u8fd9\u79cd\u53c2\u6570\u5316\u8bbe\u8ba1\u4f7f\u5f97\u9879\u76ee\u66f4\u52a0\u7075\u6d3b\uff0c\u53ef\u4ee5\u9002\u5e94\u4e0d\u540c\u7684\u5b9e\u9a8c\u573a\u666f\u3002<\/li>\n\n\n\n<li>\u7b80\u5316\u7684\u547d\u4ee4\u884c\u5de5\u5177\uff1a\u901a\u8fc7 MLflow \u547d\u4ee4\u884c\u5de5\u5177\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u8fd0\u884c MLflow Project\uff0c\u800c\u65e0\u9700\u5173\u5fc3\u5e95\u5c42\u7684\u5b9e\u73b0\u7ec6\u8282\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fd0\u884c\u4e00\u4e2a MLflow Project\uff1a<code>mlflow run &lt;project_uri&gt; -P &lt;parameter_name&gt;=&lt;parameter_value&gt;<\/code>\u3002\u6b64\u5916\uff0cMLflow \u547d\u4ee4\u884c\u5de5\u5177\u8fd8\u652f\u6301\u5176\u4ed6\u5b9e\u7528\u529f\u80fd\uff0c\u5982\u67e5\u770b\u9879\u76ee\u4fe1\u606f\u3001\u5217\u51fa\u9879\u76ee\u5165\u53e3\u70b9\u7b49\u3002<\/li>\n\n\n\n<li>\u96c6\u6210\u5176\u4ed6 MLflow \u7ec4\u4ef6\uff1aMLflow Projects \u53ef\u4ee5\u4e0e\u5176\u4ed6 MLflow \u7ec4\u4ef6\uff08\u5982 Tracking \u548c Models\uff09\u65e0\u7f1d\u96c6\u6210\uff0c\u5b9e\u73b0\u7aef\u5230\u7aef\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u3002\u4f8b\u5982\uff0c\u5728 MLflow Project \u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow Tracking API \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\uff0c\u7136\u540e\u5c06\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u4fdd\u5b58\u4e3a MLflow Model \u683c\u5f0f\u3002<\/li>\n\n\n\n<li>Git \u96c6\u6210\uff1aMLflow Projects \u652f\u6301\u76f4\u63a5\u4ece Git \u4ed3\u5e93\uff08\u5982 GitHub\u3001GitLab \u7b49\uff09\u8fd0\u884c\u9879\u76ee\u3002\u8fd9\u610f\u5473\u7740\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u4e0e\u56e2\u961f\u6210\u5458\u5171\u4eab\u9879\u76ee\uff0c\u5e76\u4fdd\u6301\u9879\u76ee\u7684\u7248\u672c\u63a7\u5236\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow Projects \u63d0\u4f9b\u4e86\u4e00\u79cd\u6807\u51c6\u5316\u3001\u53ef\u79fb\u690d\u548c\u6613\u4e8e\u5171\u4eab\u7684\u673a\u5668\u5b66\u4e60\u9879\u76ee\u683c\u5f0f\u3002\u901a\u8fc7\u4f7f\u7528 MLflow Projects\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u9879\u76ee\uff0c\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u91cd\u590d\u6027\u548c\u53ef\u7ef4\u62a4\u6027\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91caMLflow Models<\/p>\n\n\n\n<p>MLflow Models \u662f MLflow \u7684\u4e00\u4e2a\u7ec4\u4ef6\uff0c\u7528\u4e8e\u7ba1\u7406\u3001\u4fdd\u5b58\u548c\u90e8\u7f72\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u79cd\u7edf\u4e00\u7684\u6a21\u578b\u683c\u5f0f\uff0c\u53ef\u4ee5\u5c06\u4e0d\u540c\u6846\u67b6\uff08\u5982 TensorFlow\u3001PyTorch\u3001Scikit-learn \u7b49\uff09\u4e0b\u7684\u6a21\u578b\u4fdd\u5b58\u4e3a\u6807\u51c6\u5316\u7684\u683c\u5f0f\uff0c\u4ee5\u4fbf\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u90e8\u7f72\u548c\u4f7f\u7528\u3002<\/p>\n\n\n\n<p>\u4ee5\u4e0b\u662f MLflow Models \u7684\u4e3b\u8981\u7279\u6027\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u7edf\u4e00\u7684\u6a21\u578b\u683c\u5f0f\uff1aMLflow Models \u4f7f\u7528\u540d\u4e3a MLmodel \u7684 YAML \u6587\u4ef6\u6765\u63cf\u8ff0\u6a21\u578b\u7684\u5143\u6570\u636e\uff0c\u5982\u6a21\u578b\u540d\u79f0\u3001\u7248\u672c\u3001\u6846\u67b6\u7b49\u3002\u6b64\u5916\uff0cMLmodel \u6587\u4ef6\u8fd8\u5305\u542b\u4e86\u6a21\u578b\u6587\u4ef6\u3001\u9884\u5904\u7406\u811a\u672c\u548c\u4f9d\u8d56\u9879\u7b49\u4fe1\u606f\u3002\u901a\u8fc7\u8fd9\u79cd\u7edf\u4e00\u7684\u683c\u5f0f\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u5728\u4e0d\u540c\u6846\u67b6\u548c\u73af\u5883\u4e2d\u5171\u4eab\u548c\u90e8\u7f72\u6a21\u578b\u3002<\/li>\n\n\n\n<li>\u591a\u6846\u67b6\u652f\u6301\uff1aMLflow Models \u652f\u6301\u591a\u79cd\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60\u6846\u67b6\uff0c\u5982 TensorFlow\u3001PyTorch\u3001Scikit-learn \u7b49\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow \u63d0\u4f9b\u7684 Python API \u6216\u547d\u4ee4\u884c\u5de5\u5177\u5c06\u4e0d\u540c\u6846\u67b6\u4e0b\u7684\u6a21\u578b\u4fdd\u5b58\u4e3a MLflow Model \u683c\u5f0f\u3002<\/li>\n\n\n\n<li>\u7075\u6d3b\u7684\u90e8\u7f72\u9009\u9879\uff1aMLflow Models \u652f\u6301\u5c06\u6a21\u578b\u90e8\u7f72\u5230\u591a\u79cd\u73af\u5883\uff0c\u5982\u672c\u5730\u670d\u52a1\u5668\u3001\u4e91\u670d\u52a1\uff08\u5982 AWS SageMaker\u3001Azure ML \u7b49\uff09\u3001\u5bb9\u5668\u5e73\u53f0\uff08\u5982 Docker\u3001Kubernetes \u7b49\uff09\u7b49\u3002\u8fd9\u610f\u5473\u7740\u60a8\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u90e8\u7f72\u65b9\u5f0f\uff0c\u5c06\u6a21\u578b\u5e94\u7528\u5230\u751f\u4ea7\u73af\u5883\u4e2d\u3002<\/li>\n\n\n\n<li>\u4e0e\u5176\u4ed6 MLflow \u7ec4\u4ef6\u96c6\u6210\uff1aMLflow Models \u53ef\u4ee5\u4e0e\u5176\u4ed6 MLflow \u7ec4\u4ef6\uff08\u5982 Tracking \u548c Projects\uff09\u65e0\u7f1d\u96c6\u6210\uff0c\u5b9e\u73b0\u7aef\u5230\u7aef\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u3002\u4f8b\u5982\uff0c\u5728 MLflow Project \u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow Tracking API \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\uff0c\u7136\u540e\u5c06\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u4fdd\u5b58\u4e3a MLflow Model \u683c\u5f0f\u3002<\/li>\n\n\n\n<li>\u6a21\u578b\u9884\u6d4b\u63a5\u53e3\uff1aMLflow Models \u63d0\u4f9b\u4e86\u4e00\u79cd\u6807\u51c6\u5316\u7684\u6a21\u578b\u9884\u6d4b\u63a5\u53e3\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u52a0\u8f7d\u548c\u4f7f\u7528\u5df2\u4fdd\u5b58\u7684\u6a21\u578b\u3002\u901a\u8fc7\u8fd9\u79cd\u63a5\u53e3\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06\u6a21\u578b\u5e94\u7528\u5230\u4e0d\u540c\u7684\u5e94\u7528\u573a\u666f\uff0c\u5982\u5728\u7ebf\u63a8\u7406\u3001\u6279\u91cf\u5904\u7406\u7b49\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow Models \u63d0\u4f9b\u4e86\u4e00\u79cd\u7edf\u4e00\u3001\u53ef\u79fb\u690d\u548c\u6613\u4e8e\u90e8\u7f72\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u683c\u5f0f\u3002\u901a\u8fc7\u4f7f\u7528 MLflow Models\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u7ba1\u7406\u548c\u5171\u4eab\u6a21\u578b\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u53ef\u7ef4\u62a4\u6027\u548c\u751f\u4ea7\u6548\u7387\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91caMLflow Model Registry<\/p>\n\n\n\n<p>MLflow Model Registry \u662f MLflow \u7684\u4e00\u4e2a\u7ec4\u4ef6\uff0c\u5b83\u662f\u4e00\u4e2a\u96c6\u4e2d\u5f0f\u7684\u6a21\u578b\u5b58\u50a8\u5e93\uff0c\u7528\u4e8e\u7ba1\u7406\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u6574\u4e2a\u751f\u547d\u5468\u671f\u3002\u901a\u8fc7\u4f7f\u7528 MLflow Model Registry\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u8ddf\u8e2a\u6a21\u578b\u7684\u7248\u672c\u3001\u72b6\u6001\u548c\u6ce8\u91ca\u7b49\u5143\u6570\u636e\uff0c\u5b9e\u73b0\u56e2\u961f\u95f4\u7684\u534f\u4f5c\u548c\u6a21\u578b\u7684\u5171\u4eab\u3002<\/p>\n\n\n\n<p>\u4ee5\u4e0b\u662f MLflow Model Registry \u7684\u4e3b\u8981\u7279\u6027\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u6a21\u578b\u7248\u672c\u7ba1\u7406\uff1aMLflow Model Registry \u652f\u6301\u6a21\u578b\u7684\u7248\u672c\u63a7\u5236\u3002\u6bcf\u5f53\u60a8\u5411\u6a21\u578b\u5e93\u4e2d\u6dfb\u52a0\u4e00\u4e2a\u65b0\u7684\u6a21\u578b\u6216\u66f4\u65b0\u73b0\u6709\u6a21\u578b\u65f6\uff0c\u90fd\u4f1a\u81ea\u52a8\u751f\u6210\u4e00\u4e2a\u65b0\u7684\u7248\u672c\u3002\u8fd9\u6837\uff0c\u60a8\u53ef\u4ee5\u65b9\u4fbf\u5730\u56de\u6eaf\u548c\u6bd4\u8f83\u6a21\u578b\u7684\u5386\u53f2\u7248\u672c\uff0c\u4ee5\u4fbf\u627e\u5230\u6700\u4f73\u7684\u6a21\u578b\u914d\u7f6e\u3002<\/li>\n\n\n\n<li>\u6a21\u578b\u72b6\u6001\u8ddf\u8e2a\uff1aMLflow Model Registry \u5141\u8bb8\u60a8\u4e3a\u6a21\u578b\u5b9a\u4e49\u4e0d\u540c\u7684\u72b6\u6001\uff0c\u5982 &#8220;Staging&#8221;\uff08\u6d4b\u8bd5\u4e2d\uff09\u3001&#8221;Production&#8221;\uff08\u751f\u4ea7\u4e2d\uff09\u548c &#8220;Archived&#8221;\uff08\u5df2\u5f52\u6863\uff09\u7b49\u3002\u901a\u8fc7\u8fd9\u79cd\u72b6\u6001\u8ddf\u8e2a\u673a\u5236\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u7ba1\u7406\u6a21\u578b\u7684\u751f\u547d\u5468\u671f\uff0c\u5e76\u786e\u4fdd\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528\u7684\u6a21\u578b\u59cb\u7ec8\u662f\u6700\u65b0\u548c\u6700\u6709\u6548\u7684\u7248\u672c\u3002<\/li>\n\n\n\n<li>\u6ce8\u91ca\u548c\u6807\u7b7e\uff1aMLflow Model Registry \u652f\u6301\u4e3a\u6a21\u578b\u6dfb\u52a0\u6ce8\u91ca\u548c\u6807\u7b7e\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u63cf\u8ff0\u6a21\u578b\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u4e3a\u6a21\u578b\u6dfb\u52a0\u63cf\u8ff0\u6027\u7684\u6807\u7b7e\uff08\u5982 &#8220;\u63a8\u8350\u7cfb\u7edf&#8221;\u3001&#8221;\u56fe\u50cf\u5206\u7c7b&#8221; \u7b49\uff09\uff0c\u5e76\u8bb0\u5f55\u6a21\u578b\u7684\u521b\u5efa\u8005\u3001\u521b\u5efa\u65e5\u671f\u7b49\u4fe1\u606f\u3002<\/li>\n\n\n\n<li>\u6a21\u578b\u5ba1\u6279\u6d41\u7a0b\uff1aMLflow Model Registry \u652f\u6301\u6a21\u578b\u7684\u5ba1\u6279\u6d41\u7a0b\u3002\u60a8\u53ef\u4ee5\u4e3a\u6a21\u578b\u5b9a\u4e49\u4e0d\u540c\u7684\u5ba1\u6279\u9636\u6bb5\uff08\u5982 &#8220;Pending&#8221;\u3001&#8221;Approved&#8221; \u7b49\uff09\uff0c\u5e76\u5728\u6a21\u578b\u901a\u8fc7\u5ba1\u6279\u540e\u5c06\u5176\u72b6\u6001\u66f4\u6539\u4e3a &#8220;Production&#8221;\u3002\u8fd9\u6709\u52a9\u4e8e\u786e\u4fdd\u56e2\u961f\u95f4\u7684\u534f\u4f5c\u548c\u6a21\u578b\u8d28\u91cf\u3002<\/li>\n\n\n\n<li>\u96c6\u6210\u5176\u4ed6 MLflow \u7ec4\u4ef6\uff1aMLflow Model Registry \u53ef\u4ee5\u4e0e\u5176\u4ed6 MLflow \u7ec4\u4ef6\uff08\u5982 Tracking \u548c Models\uff09\u65e0\u7f1d\u96c6\u6210\uff0c\u5b9e\u73b0\u7aef\u5230\u7aef\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u3002\u4f8b\u5982\uff0c\u5728 MLflow Project \u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow Tracking API \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\uff0c\u7136\u540e\u5c06\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u4fdd\u5b58\u4e3a MLflow Model \u683c\u5f0f\uff0c\u5e76\u5c06\u5176\u6ce8\u518c\u5230 MLflow Model Registry \u4e2d\u3002<\/li>\n\n\n\n<li>\u53ef\u89c6\u5316\u754c\u9762\uff1aMLflow Model Registry \u63d0\u4f9b\u4e86\u4e00\u4e2a\u53cb\u597d\u7684\u7528\u6237\u754c\u9762\uff0c\u53ef\u4ee5\u76f4\u89c2\u5730\u67e5\u770b\u548c\u7ba1\u7406\u6a21\u578b\u5e93\u4e2d\u7684\u6a21\u578b\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528\u8be5\u754c\u9762\u5bf9\u6a21\u578b\u8fdb\u884c\u641c\u7d22\u3001\u7b5b\u9009\u548c\u6bd4\u8f83\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u4e86\u89e3\u6a21\u578b\u7684\u6027\u80fd\u548c\u72b6\u6001\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow Model Registry \u662f\u4e00\u4e2a\u5f3a\u5927\u4e14\u7075\u6d3b\u7684\u6a21\u578b\u7ba1\u7406\u5de5\u5177\uff0c\u53ef\u4ee5\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u8ddf\u8e2a\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u6574\u4e2a\u751f\u547d\u5468\u671f\u3002\u901a\u8fc7\u4f7f\u7528 MLflow Model Registry\uff0c\u60a8\u53ef\u4ee5\u5b9e\u73b0\u56e2\u961f\u95f4\u7684\u534f\u4f5c\u548c\u6a21\u578b\u7684\u5171\u4eab\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u53ef\u7ef4\u62a4\u6027\u548c\u751f\u4ea7\u6548\u7387\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u5b89\u88c5 MLflow<\/p>\n\n\n\n<p>\u5b89\u88c5 MLflow \u76f8\u5bf9\u7b80\u5355\uff0c\u53ef\u4ee5\u901a\u8fc7 Python \u7684\u5305\u7ba1\u7406\u5de5\u5177\uff08\u5982 pip\uff09\u6765\u5b89\u88c5\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u7684\u5b89\u88c5\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u9996\u5148\uff0c\u786e\u4fdd\u60a8\u7684\u8ba1\u7b97\u673a\u4e0a\u5df2\u5b89\u88c5\u4e86 Python\uff08\u5efa\u8bae\u4f7f\u7528 Python 3.6 \u53ca\u4ee5\u4e0a\u7248\u672c\uff09\u3002\u60a8\u53ef\u4ee5\u901a\u8fc7\u5728\u547d\u4ee4\u884c\u4e2d\u8f93\u5165 <code>python --version<\/code> \u6216 <code>python3 --version<\/code> \u6765\u68c0\u67e5 Python \u7684\u7248\u672c\u3002<\/li>\n\n\n\n<li>\uff08\u53ef\u9009\uff09\u5efa\u8bae\u5728\u865a\u62df\u73af\u5883\u4e2d\u5b89\u88c5 MLflow\uff0c\u4ee5\u907f\u514d\u4e0e\u5176\u4ed6 Python \u5e93\u4ea7\u751f\u51b2\u7a81\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528 <code>virtualenv<\/code> \u6216 <code>conda<\/code> \u7b49\u5de5\u5177\u521b\u5efa\u865a\u62df\u73af\u5883\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 <code>virtualenv<\/code> \u521b\u5efa\u865a\u62df\u73af\u5883\u7684\u793a\u4f8b\uff1aCopy code<code>pip install virtualenv virtualenv mlflow_env <\/code>\u5bf9\u4e8e Windows \u7528\u6237\uff1aCopy code<code>mlflow_env\\Scripts\\activate <\/code>\u5bf9\u4e8e macOS \u548c Linux \u7528\u6237\uff1abashCopy code<code>source mlflow_env\/bin\/activate <\/code>\u5982\u679c\u60a8\u9009\u62e9\u4f7f\u7528 <code>conda<\/code> \u521b\u5efa\u865a\u62df\u73af\u5883\uff0c\u53ef\u4ee5\u53c2\u8003\u4ee5\u4e0b\u547d\u4ee4\uff1aluaCopy code<code>conda create -n mlflow_env python=3.8 conda activate mlflow_env<\/code><\/li>\n\n\n\n<li>\u4f7f\u7528 <code>pip<\/code> \u5b89\u88c5 MLflow\u3002\u5728\u547d\u4ee4\u884c\u4e2d\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\uff1aCopy code<code>pip install mlflow <\/code>\u8fd9\u5c06\u4f1a\u81ea\u52a8\u5b89\u88c5 MLflow \u53ca\u5176\u4f9d\u8d56\u5e93\u3002<\/li>\n\n\n\n<li>\u68c0\u67e5 MLflow \u662f\u5426\u5b89\u88c5\u6210\u529f\u3002\u5728\u547d\u4ee4\u884c\u4e2d\u8f93\u5165 <code>mlflow --version<\/code>\u3002\u5982\u679c\u663e\u793a\u51fa MLflow \u7684\u7248\u672c\u53f7\uff0c\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u60a8\u5c31\u53ef\u4ee5\u5f00\u59cb\u4f7f\u7528 MLflow \u7684\u5404\u79cd\u529f\u80fd\uff0c\u5982 Tracking\u3001Projects\u3001Models \u548c Model Registry \u7b49\u3002\u5177\u4f53\u7684\u4f7f\u7528\u65b9\u6cd5\u53ef\u4ee5\u53c2\u8003 MLflow \u7684\u5b98\u65b9\u6587\u6863\uff08<a href=\"https:\/\/mlflow.org\/docs\/latest\/index.html%EF%BC%89%E3%80%82\">https:\/\/mlflow.org\/docs\/latest\/index.html\uff09\u3002<\/a><\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u914d\u7f6e MLflow \u7684\u73af\u5883\u4e0e\u540e\u7aef\u5b58\u50a8<\/p>\n\n\n\n<p>MLflow \u652f\u6301\u591a\u79cd\u73af\u5883\u548c\u540e\u7aef\u5b58\u50a8\u914d\u7f6e\uff0c\u4ee5\u6ee1\u8db3\u4e0d\u540c\u573a\u666f\u7684\u9700\u6c42\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u7684\u914d\u7f6e\u65b9\u6cd5\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u914d\u7f6e\u73af\u5883MLflow \u53ef\u4ee5\u5728\u672c\u5730\u6216\u8fdc\u7a0b\u670d\u52a1\u5668\u4e0a\u8fd0\u884c\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0cMLflow \u4f1a\u5728\u672c\u5730\u542f\u52a8\u4e00\u4e2a Web \u670d\u52a1\u5668\u3002\u8981\u542f\u52a8 MLflow \u670d\u52a1\u5668\uff0c\u8bf7\u5728\u547d\u4ee4\u884c\u4e2d\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\uff1aCopy code<code>mlflow server <\/code>\u8fd9\u5c06\u5728\u672c\u5730\u7684\u9ed8\u8ba4\u7aef\u53e3\uff085000\uff09\u4e0a\u542f\u52a8 MLflow \u670d\u52a1\u5668\u3002\u60a8\u53ef\u4ee5\u901a\u8fc7\u6d4f\u89c8\u5668\u8bbf\u95ee <code>http:\/\/localhost:5000<\/code> \u6765\u67e5\u770b MLflow \u7684\u7528\u6237\u754c\u9762\u3002\u5982\u679c\u60a8\u60f3\u5728\u7279\u5b9a\u7684\u7aef\u53e3\u6216 IP \u5730\u5740\u4e0a\u8fd0\u884c MLflow \u670d\u52a1\u5668\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>--host<\/code> \u548c <code>--port<\/code> \u53c2\u6570\u3002\u4f8b\u5982\uff1acssCopy code<code>mlflow server --host 0.0.0.0 --port 6000 <\/code>\u8fd9\u5c06\u5728 IP \u5730\u5740 <code>0.0.0.0<\/code> \u548c\u7aef\u53e3 <code>6000<\/code> \u4e0a\u542f\u52a8 MLflow \u670d\u52a1\u5668\u3002<\/li>\n\n\n\n<li>\u914d\u7f6e\u540e\u7aef\u5b58\u50a8MLflow \u652f\u6301\u591a\u79cd\u540e\u7aef\u5b58\u50a8\u9009\u9879\uff0c\u5982\u672c\u5730\u6587\u4ef6\u7cfb\u7edf\u3001\u8fdc\u7a0b\u670d\u52a1\u5668\uff08\u5982 Amazon S3\u3001Azure Blob Storage \u7b49\uff09\u548c\u6570\u636e\u5e93\uff08\u5982 MySQL\u3001PostgreSQL \u7b49\uff09\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0cMLflow \u4f1a\u5c06\u6570\u636e\u5b58\u50a8\u5728\u672c\u5730\u7684 <code>.\/mlruns<\/code> \u76ee\u5f55\u4e2d\u3002\u8981\u914d\u7f6e MLflow \u7684\u540e\u7aef\u5b58\u50a8\uff0c\u8bf7\u4f7f\u7528 <code>--backend-store-uri<\/code> \u53c2\u6570\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u793a\u4f8b\uff1a<ul><li>\u4f7f\u7528\u672c\u5730\u6587\u4ef6\u7cfb\u7edf\uff1ajavascriptCopy code<code>mlflow server --backend-store-uri file:\/path\/to\/local\/directory<\/code><\/li><li>\u4f7f\u7528 Amazon S3\uff1arubyCopy code<code>mlflow server --backend-store-uri s3:\/\/your-bucket-name\/path\/to\/mlruns <\/code>\u8bf7\u786e\u4fdd\u5df2\u5b89\u88c5 <code>boto3<\/code> \u5e93\uff08<code>pip install boto3<\/code>\uff09\uff0c\u5e76\u6b63\u786e\u914d\u7f6e\u4e86 AWS \u51ed\u636e\uff08\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u73af\u5883\u53d8\u91cf <code>AWS_ACCESS_KEY_ID<\/code> \u548c <code>AWS_SECRET_ACCESS_KEY<\/code>\uff0c\u6216\u4f7f\u7528 AWS CLI \u8fdb\u884c\u914d\u7f6e\uff09\u3002<\/li><li>\u4f7f\u7528 Azure Blob Storage\uff1arubyCopy code<code>mlflow server --backend-store-uri azure:\/\/your-container-name\/path\/to\/mlruns <\/code>\u8bf7\u786e\u4fdd\u5df2\u5b89\u88c5 <code>azure-storage-blob<\/code> \u5e93\uff08<code>pip install azure-storage-blob<\/code>\uff09\uff0c\u5e76\u6b63\u786e\u914d\u7f6e\u4e86 Azure Storage \u51ed\u636e\uff08\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u73af\u5883\u53d8\u91cf <code>AZURE_STORAGE_CONNECTION_STRING<\/code>\uff0c\u6216\u5728 <code>mlflow server<\/code> \u547d\u4ee4\u4e2d\u6dfb\u52a0 <code>--azure-storage-connection-string<\/code> \u53c2\u6570\uff09\u3002<\/li><li>\u4f7f\u7528 MySQL\uff1abashCopy code<code>mlflow server --backend-store-uri mysql:\/\/username:password@host:port\/database <\/code>\u8bf7\u786e\u4fdd\u5df2\u5b89\u88c5 <code>mysql-connector-python<\/code> \u5e93\uff08<code>pip install mysql-connector-python<\/code>\uff09\u3002<\/li><li>\u4f7f\u7528 PostgreSQL\uff1abashCopy code<code>mlflow server --backend-store-uri postgresql:\/\/username:password@host:port\/database <\/code>\u8bf7\u786e\u4fdd\u5df2\u5b89\u88c5 <code>psycopg2<\/code> \u5e93\uff08<code>pip install psycopg2<\/code>\uff09\u3002<\/li><\/ul>\u4e0a\u8ff0\u914d\u7f6e\u53ea\u9700\u5728\u542f\u52a8 MLflow \u670d\u52a1\u5668\u65f6\u8fdb\u884c\u5373\u53ef\u3002\u5728\u5b9e\u9645\u4f7f\u7528\u4e2d\uff0c\u60a8\u8fd8\u53ef\u4ee5\u5c06\u8fd9\u4e9b\u914d\u7f6e\u4e0e\u5176\u4ed6\u53c2\u6570\uff08\u5982<\/li>\n<\/ol>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u5982 <code>--default-artifact-root<\/code> \u548c <code>--host<\/code> \u7b49\uff09\u7ed3\u5408\u4f7f\u7528\uff0c\u4ee5\u4fbf\u6839\u636e\u5b9e\u9645\u9700\u6c42\u5b9a\u5236 MLflow \u7684\u8fd0\u884c\u73af\u5883\u3002<\/p>\n\n\n\n<p>\u4ee5\u4e0b\u662f\u4e00\u4e2a\u5b8c\u6574\u7684\u793a\u4f8b\uff0c\u6f14\u793a\u5982\u4f55\u5728\u6307\u5b9a\u7684 IP \u5730\u5740\u548c\u7aef\u53e3\u4e0a\u8fd0\u884c MLflow \u670d\u52a1\u5668\uff0c\u5e76\u4f7f\u7528 Amazon S3 \u4f5c\u4e3a\u540e\u7aef\u5b58\u50a8\u548c\u9ed8\u8ba4\u7684\u5de5\u4ef6\u5b58\u50a8\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">arduinoCopy code<code>mlflow server \\\n  --backend-store-uri s3:\/\/your-bucket-name\/path\/to\/mlruns \\\n  --default-artifact-root s3:\/\/your-bucket-name\/path\/to\/artifacts \\\n  --host 0.0.0.0 \\\n  --port 6000\n<\/code><\/pre>\n\n\n\n<p>\u5728\u914d\u7f6e\u597d MLflow \u7684\u73af\u5883\u548c\u540e\u7aef\u5b58\u50a8\u540e\uff0c\u60a8\u53ef\u4ee5\u5f00\u59cb\u4f7f\u7528 MLflow \u7684\u5404\u79cd\u529f\u80fd\uff0c\u5982 Tracking\u3001Projects\u3001Models \u548c Model Registry \u7b49\u3002\u5728\u4f7f\u7528 MLflow API \u65f6\uff0c\u60a8\u9700\u8981\u6307\u5b9a MLflow \u670d\u52a1\u5668\u7684 URI\u3002\u4f8b\u5982\uff0c\u5728 Python \u811a\u672c\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow\n\nmlflow.set_tracking_uri(\"http:\/\/your-mlflow-server-ip:your-mlflow-server-port\")\n<\/code><\/pre>\n\n\n\n<p>\u8bf7\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u66ff\u6362 <code>your-mlflow-server-ip<\/code> \u548c <code>your-mlflow-server-port<\/code>\u3002\u914d\u7f6e\u597d Tracking URI \u540e\uff0c\u60a8\u5c31\u53ef\u4ee5\u4f7f\u7528 MLflow API \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\u3001\u4fdd\u5b58\u6a21\u578b\u7b49\u3002<\/p>\n\n\n\n<p>\u603b\u4e4b\uff0c\u914d\u7f6e MLflow \u7684\u73af\u5883\u548c\u540e\u7aef\u5b58\u50a8\u76f8\u5bf9\u7b80\u5355\uff0c\u53ea\u9700\u51e0\u4e2a\u547d\u4ee4\u884c\u53c2\u6570\u5373\u53ef\u5b8c\u6210\u3002\u901a\u8fc7\u6b63\u786e\u5730\u914d\u7f6e MLflow\uff0c\u60a8\u53ef\u4ee5\u5b9e\u73b0\u66f4\u9ad8\u6548\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\uff0c\u5e76\u66f4\u597d\u5730\u6ee1\u8db3\u56e2\u961f\u534f\u4f5c\u548c\u6570\u636e\u5171\u4eab\u7684\u9700\u6c42\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u4f7f\u7528 MLflow Tracking \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e<\/p>\n\n\n\n<p>MLflow Tracking \u662f MLflow \u7684\u4e00\u4e2a\u7ec4\u4ef6\uff0c\u7528\u4e8e\u8bb0\u5f55\u548c\u67e5\u770b\u673a\u5668\u5b66\u4e60\u5b9e\u9a8c\u7684\u6570\u636e\uff0c\u5982\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u7b49\u3002\u8981\u4f7f\u7528 MLflow Tracking \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\uff0c\u60a8\u9700\u8981\u9075\u5faa\u4ee5\u4e0b\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u9996\u5148\uff0c\u5bfc\u5165 <code>mlflow<\/code> \u5e93\uff0c\u5e76\u8bbe\u7f6e MLflow \u670d\u52a1\u5668\u7684 URI\u3002\u5728 Python \u811a\u672c\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1apythonCopy code<code>import mlflow mlflow.set_tracking_uri(\"http:\/\/your-mlflow-server-ip:your-mlflow-server-port\") <\/code>\u8bf7\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u66ff\u6362 <code>your-mlflow-server-ip<\/code> \u548c <code>your-mlflow-server-port<\/code>\u3002<\/li>\n\n\n\n<li>\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u5b9e\u9a8c\uff08\u5982\u679c\u5c1a\u672a\u521b\u5efa\uff09\u3002\u4f7f\u7528 <code>mlflow.create_experiment<\/code> \u51fd\u6570\u521b\u5efa\u4e00\u4e2a\u5b9e\u9a8c\uff0c\u5e76\u4e3a\u5176\u6307\u5b9a\u4e00\u4e2a\u540d\u79f0\uff1apythonCopy code<code>experiment_id = mlflow.create_experiment(\"your_experiment_name\") <\/code>\u5982\u679c\u5b9e\u9a8c\u5df2\u5b58\u5728\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 <code>mlflow.get_experiment_by_name<\/code> \u51fd\u6570\u83b7\u53d6\u5176 ID\uff1apythonCopy code<code>experiment = mlflow.get_experiment_by_name(\"your_experiment_name\") experiment_id = experiment.experiment_id<\/code><\/li>\n\n\n\n<li>\u4f7f\u7528 <code>mlflow.start_run<\/code> \u4e0a\u4e0b\u6587\u7ba1\u7406\u5668\u5f00\u59cb\u4e00\u4e2a\u65b0\u7684\u8fd0\u884c\u3002\u5728 <code>with<\/code> \u8bed\u53e5\u5757\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow API \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\uff0c\u5982\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u7b49\uff1apythonCopy code<code>with mlflow.start_run(experiment_id=experiment_id): # \u8bb0\u5f55\u53c2\u6570 mlflow.log_param(\"param_name\", param_value) # \u8bb0\u5f55\u6307\u6807 mlflow.log_metric(\"metric_name\", metric_value) # \u8bb0\u5f55\u5de5\u4ef6\uff08\u5982\u6a21\u578b\u6587\u4ef6\u3001\u56fe\u7247\u7b49\uff09 mlflow.log_artifact(\"path\/to\/local\/file\", \"artifact_subfolder\") # ... <\/code>\u8bf7\u6ce8\u610f\uff0c\u5728 <code>with<\/code> \u8bed\u53e5\u5757\u4e2d\uff0c\u60a8\u53ef\u4ee5\u591a\u6b21\u8c03\u7528 <code>mlflow.log_metric<\/code> \u51fd\u6570\u6765\u8bb0\u5f55\u6307\u6807\u7684\u4e0d\u540c\u503c\uff08\u4f8b\u5982\uff0c\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u7684\u6bcf\u4e2a\u6b65\u9aa4\uff09\u3002MLflow \u4f1a\u81ea\u52a8\u8bb0\u5f55\u6307\u6807\u7684\u5386\u53f2\u6570\u636e\uff0c\u4ee5\u4fbf\u60a8\u53ef\u4ee5\u5728\u7528\u6237\u754c\u9762\u4e2d\u67e5\u770b\u548c\u6bd4\u8f83\u6307\u6807\u7684\u53d8\u5316\u8d8b\u52bf\u3002<\/li>\n\n\n\n<li>\u5728 MLflow \u7528\u6237\u754c\u9762\u4e2d\u67e5\u770b\u5b9e\u9a8c\u6570\u636e\u3002\u8bbf\u95ee <code>http:\/\/your-mlflow-server-ip:your-mlflow-server-port<\/code>\uff0c\u5e76\u9009\u62e9\u60a8\u521b\u5efa\u7684\u5b9e\u9a8c\u3002\u60a8\u53ef\u4ee5\u770b\u5230\u5df2\u8bb0\u5f55\u7684\u8fd0\u884c\u5217\u8868\uff0c\u4ee5\u53ca\u76f8\u5173\u7684\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u7b49\u6570\u636e\u3002\u70b9\u51fb\u8fd0\u884c\u7684 ID \u53ef\u4ee5\u67e5\u770b\u66f4\u8be6\u7ec6\u7684\u4fe1\u606f\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow Tracking \u8bb0\u5f55\u548c\u67e5\u770b\u5b9e\u9a8c\u6570\u636e\uff0c\u4ece\u800c\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u673a\u5668\u5b66\u4e60\u5b9e\u9a8c\u3002MLflow \u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684 API \u548c\u53ef\u89c6\u5316\u754c\u9762\uff0c\u5e2e\u52a9\u60a8\u5feb\u901f\u627e\u5230\u6700\u4f73\u7684\u6a21\u578b\u914d\u7f6e\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u53ef\u7ef4\u62a4\u6027\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u901a\u8fc7 MLflow UI \u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c<\/p>\n\n\n\n<p>MLflow \u63d0\u4f9b\u4e86\u4e00\u4e2a\u7528\u6237\u53cb\u597d\u7684 Web \u7528\u6237\u754c\u9762\uff08UI\uff09\uff0c\u4f7f\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u67e5\u770b\u548c\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u901a\u8fc7 MLflow UI \u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c\u7684\u8be6\u7ec6\u8bf4\u660e\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u9996\u5148\uff0c\u786e\u4fdd MLflow \u670d\u52a1\u5668\u6b63\u5728\u8fd0\u884c\u3002\u5728\u547d\u4ee4\u884c\u4e2d\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\u542f\u52a8 MLflow \u670d\u52a1\u5668\uff08\u5982\u6709\u9700\u8981\uff0c\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u66f4\u6539\u540e\u7aef\u5b58\u50a8\u548c\u7aef\u53e3\u53f7\uff09\uff1ajavascriptCopy code<code>mlflow server --backend-store-uri file:\/path\/to\/local\/directory --host 0.0.0.0 --port 5000<\/code><\/li>\n\n\n\n<li>\u4f7f\u7528\u6d4f\u89c8\u5668\u8bbf\u95ee MLflow UI\u3002\u8f93\u5165 MLflow \u670d\u52a1\u5668\u7684\u5730\u5740\uff0c\u683c\u5f0f\u4e3a\uff1a<code>http:\/\/your-mlflow-server-ip:your-mlflow-server-port<\/code>\u3002\u4f8b\u5982\uff0c\u5982\u679c MLflow \u670d\u52a1\u5668\u8fd0\u884c\u5728\u672c\u5730\uff0c\u9ed8\u8ba4\u5730\u5740\u4e3a\uff1a<code>http:\/\/localhost:5000<\/code>\u3002<\/li>\n\n\n\n<li>\u5728 MLflow UI \u4e2d\uff0c\u60a8\u53ef\u4ee5\u770b\u5230\u4e00\u4e2a\u5b9e\u9a8c\u5217\u8868\u3002\u70b9\u51fb\u5b9e\u9a8c\u540d\u79f0\uff0c\u8fdb\u5165\u8be5\u5b9e\u9a8c\u7684\u8be6\u7ec6\u9875\u9762\u3002\u5728\u8fd9\u4e2a\u9875\u9762\u4e0a\uff0c\u60a8\u53ef\u4ee5\u770b\u5230\u4e00\u4e2a\u8868\u683c\uff0c\u663e\u793a\u4e86\u5b9e\u9a8c\u4e2d\u7684\u6240\u6709\u8fd0\u884c\uff0c\u4ee5\u53ca\u6bcf\u4e2a\u8fd0\u884c\u7684\u53c2\u6570\u3001\u6307\u6807\u3001\u7528\u6237\u3001\u8fd0\u884c\u65f6\u95f4\u7b49\u4fe1\u606f\u3002<\/li>\n\n\n\n<li>\u901a\u8fc7\u5355\u51fb\u8868\u5934\u4e0a\u7684\u5217\u540d\uff0c\u60a8\u53ef\u4ee5\u5bf9\u8fd0\u884c\u8fdb\u884c\u6392\u5e8f\uff0c\u5feb\u901f\u627e\u5230\u5177\u6709\u6700\u4f73\u6307\u6807\u503c\u7684\u8fd0\u884c\u3002\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528\u8868\u683c\u53f3\u4e0a\u89d2\u7684\u641c\u7d22\u6846\u5bf9\u8fd0\u884c\u8fdb\u884c\u7b5b\u9009\uff0c\u6839\u636e\u53c2\u6570\u3001\u6307\u6807\u3001\u6807\u7b7e\u7b49\u6761\u4ef6\u67e5\u627e\u7279\u5b9a\u7684\u8fd0\u884c\u3002<\/li>\n\n\n\n<li>\u9009\u62e9\u4e00\u4e2a\u8fd0\u884c\uff0c\u70b9\u51fb\u5176 ID\uff0c\u60a8\u5c06\u8fdb\u5165\u8be5\u8fd0\u884c\u7684\u8be6\u7ec6\u9875\u9762\u3002\u5728\u8fd9\u4e2a\u9875\u9762\u4e0a\uff0c\u60a8\u53ef\u4ee5\u67e5\u770b\u8fd0\u884c\u7684\u6240\u6709\u53c2\u6570\u3001\u6307\u6807\u548c\u6807\u7b7e\uff0c\u4ee5\u53ca MLflow \u81ea\u52a8\u8bb0\u5f55\u7684\u7cfb\u7edf\u4fe1\u606f\uff0c\u5982\u8fd0\u884c\u7684\u5f00\u59cb\u548c\u7ed3\u675f\u65f6\u95f4\u3001\u6e90\u4ee3\u7801\u7248\u672c\u7b49\u3002<\/li>\n\n\n\n<li>\u5728\u8fd0\u884c\u8be6\u7ec6\u9875\u9762\u7684\u4e0b\u65b9\uff0c\u60a8\u53ef\u4ee5\u67e5\u770b\u8fd0\u884c\u7684\u5de5\u4ef6\u5217\u8868\u3002\u8fd9\u4e9b\u5de5\u4ef6\u53ef\u80fd\u5305\u62ec\u6a21\u578b\u6587\u4ef6\u3001\u8bad\u7ec3\u6570\u636e\u3001\u751f\u6210\u7684\u56fe\u7247\u7b49\u3002\u70b9\u51fb\u5de5\u4ef6\u540d\u79f0\uff0c\u60a8\u53ef\u4ee5\u4e0b\u8f7d\u6216\u9884\u89c8\u5de5\u4ef6\u3002<\/li>\n\n\n\n<li>\u5982\u679c\u60a8\u8bb0\u5f55\u4e86\u6307\u6807\u7684\u5386\u53f2\u6570\u636e\uff08\u4f8b\u5982\uff0c\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u7684\u6bcf\u4e2a\u6b65\u9aa4\uff09\uff0c\u60a8\u53ef\u4ee5\u5728\u8fd0\u884c\u8be6\u7ec6\u9875\u9762\u7684\u6307\u6807\u90e8\u5206\u67e5\u770b\u6307\u6807\u7684\u53d8\u5316\u8d8b\u52bf\u3002\u5c06\u9f20\u6807\u60ac\u505c\u5728\u6307\u6807\u56fe\u8868\u4e0a\uff0c\u60a8\u53ef\u4ee5\u770b\u5230\u5177\u4f53\u7684\u6570\u503c\u548c\u6b65\u9aa4\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u901a\u8fc7 MLflow UI\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u67e5\u770b\u3001\u6bd4\u8f83\u548c\u5206\u6790\u5b9e\u9a8c\u7ed3\u679c\uff0c\u627e\u5230\u6700\u4f73\u7684\u6a21\u578b\u914d\u7f6e\u3002\u6b64\u5916\uff0cMLflow UI \u8fd8\u63d0\u4f9b\u4e86\u5b9e\u9a8c\u548c\u8fd0\u884c\u7684\u5bfc\u5165\u548c\u5bfc\u51fa\u529f\u80fd\uff0c\u65b9\u4fbf\u60a8\u5c06\u5b9e\u9a8c\u6570\u636e\u4e0e\u56e2\u961f\u6210\u5458\u5206\u4eab\uff0c\u6216\u8005\u5c06\u5b9e\u9a8c\u6570\u636e\u8fc1\u79fb\u5230\u5176\u4ed6 MLflow \u5b9e\u4f8b\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u67e5\u8be2\u4e0e\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c<\/p>\n\n\n\n<p>\u5728 MLflow \u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 Python API \u548c Web \u7528\u6237\u754c\u9762\uff08UI\uff09\u67e5\u8be2\u548c\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u6267\u884c\u8fd9\u4e9b\u64cd\u4f5c\u7684\u8be6\u7ec6\u8bf4\u660e\uff1a<\/p>\n\n\n\n<p><strong>\u4f7f\u7528 Python API \u67e5\u8be2\u548c\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c\uff1a<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u9996\u5148\uff0c\u5bfc\u5165 <code>mlflow<\/code> \u5e93\uff0c\u5e76\u8bbe\u7f6e MLflow \u670d\u52a1\u5668\u7684 URI\u3002\u5728 Python \u811a\u672c\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1apythonCopy code<code>import mlflow mlflow.set_tracking_uri(\"http:\/\/your-mlflow-server-ip:your-mlflow-server-port\") <\/code>\u8bf7\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u66ff\u6362 <code>your-mlflow-server-ip<\/code> \u548c <code>your-mlflow-server-port<\/code>\u3002<\/li>\n\n\n\n<li>\u4f7f\u7528 <code>mlflow.search_runs<\/code> \u51fd\u6570\u67e5\u8be2\u5b9e\u9a8c\u7ed3\u679c\u3002\u8be5\u51fd\u6570\u63a5\u53d7\u4e00\u4e2a\u5b9e\u9a8c ID \u5217\u8868\uff0c\u4ee5\u53ca\u4e00\u4e2a\u53ef\u9009\u7684\u67e5\u8be2\u8868\u8fbe\u5f0f\uff0c\u53ef\u4ee5\u6839\u636e\u53c2\u6570\u3001\u6307\u6807\u548c\u6807\u7b7e\u7b49\u6761\u4ef6\u7b5b\u9009\u8fd0\u884c\uff1apythonCopy code<code>experiment = mlflow.get_experiment_by_name(\"your_experiment_name\") runs = mlflow.search_runs( experiment_ids=[experiment.experiment_id], filter_string=\"params.param_name &gt; 0.5 and metrics.metric_name &lt; 0.1\" ) <\/code><code>mlflow.search_runs<\/code> \u51fd\u6570\u8fd4\u56de\u4e00\u4e2a\u5305\u542b\u7b26\u5408\u6761\u4ef6\u7684\u8fd0\u884c\u4fe1\u606f\u7684 DataFrame\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528 Pandas \u7684\u529f\u80fd\u5bf9 DataFrame \u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5904\u7406\u548c\u5206\u6790\uff0c\u4f8b\u5982\uff0c\u627e\u5230\u5177\u6709\u6700\u4f73\u6307\u6807\u503c\u7684\u8fd0\u884c\uff1apythonCopy code<code>best_run = runs.loc[runs[\"metrics.metric_name\"].idxmin()]<\/code><\/li>\n<\/ol>\n\n\n\n<p><strong>\u4f7f\u7528 Web \u7528\u6237\u754c\u9762\u67e5\u8be2\u548c\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c\uff1a<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u4f7f\u7528\u6d4f\u89c8\u5668\u8bbf\u95ee MLflow UI\u3002\u8f93\u5165 MLflow \u670d\u52a1\u5668\u7684\u5730\u5740\uff0c\u683c\u5f0f\u4e3a\uff1a<code>http:\/\/your-mlflow-server-ip:your-mlflow-server-port<\/code>\u3002\u4f8b\u5982\uff0c\u5982\u679c MLflow \u670d\u52a1\u5668\u8fd0\u884c\u5728\u672c\u5730\uff0c\u9ed8\u8ba4\u5730\u5740\u4e3a\uff1a<code>http:\/\/localhost:5000<\/code>\u3002<\/li>\n\n\n\n<li>\u5728 MLflow UI \u4e2d\uff0c\u70b9\u51fb\u5b9e\u9a8c\u540d\u79f0\uff0c\u8fdb\u5165\u8be5\u5b9e\u9a8c\u7684\u8be6\u7ec6\u9875\u9762\u3002\u5728\u8fd9\u4e2a\u9875\u9762\u4e0a\uff0c\u60a8\u53ef\u4ee5\u770b\u5230\u4e00\u4e2a\u8868\u683c\uff0c\u663e\u793a\u4e86\u5b9e\u9a8c\u4e2d\u7684\u6240\u6709\u8fd0\u884c\uff0c\u4ee5\u53ca\u6bcf\u4e2a\u8fd0\u884c\u7684\u53c2\u6570\u3001\u6307\u6807\u3001\u7528\u6237\u3001\u8fd0\u884c\u65f6\u95f4\u7b49\u4fe1\u606f\u3002<\/li>\n\n\n\n<li>\u4f7f\u7528\u8868\u683c\u53f3\u4e0a\u89d2\u7684\u641c\u7d22\u6846\u5bf9\u8fd0\u884c\u8fdb\u884c\u7b5b\u9009\uff0c\u6839\u636e\u53c2\u6570\u3001\u6307\u6807\u3001\u6807\u7b7e\u7b49\u6761\u4ef6\u67e5\u627e\u7279\u5b9a\u7684\u8fd0\u884c\u3002\u4f8b\u5982\uff0c\u8981\u67e5\u627e\u53c2\u6570 <code>param_name<\/code> \u5927\u4e8e 0.5 \u4e14\u6307\u6807 <code>metric_name<\/code> \u5c0f\u4e8e 0.1 \u7684\u8fd0\u884c\uff0c\u60a8\u53ef\u4ee5\u8f93\u5165\u4ee5\u4e0b\u67e5\u8be2\u8868\u8fbe\u5f0f\uff1acsharpCopy code<code>params.param_name &gt; 0.5 and metrics.metric_name &lt; 0.1<\/code><\/li>\n\n\n\n<li>\u901a\u8fc7\u5355\u51fb\u8868\u5934\u4e0a\u7684\u5217\u540d\uff0c\u60a8\u53ef\u4ee5\u5bf9\u8fd0\u884c\u8fdb\u884c\u6392\u5e8f\uff0c\u5feb\u901f\u627e\u5230\u5177\u6709\u6700\u4f73\u6307\u6807\u503c\u7684\u8fd0\u884c\u3002<\/li>\n\n\n\n<li>\u8981\u6bd4\u8f83\u591a\u4e2a\u8fd0\u884c\uff0c\u9009\u4e2d\u8868\u683c\u5de6\u4fa7\u7684\u590d\u9009\u6846\uff0c\u7136\u540e\u70b9\u51fb\u8868\u683c\u4e0a\u65b9\u7684 \u201cCompare\u201d \u6309\u94ae\u3002\u5728\u6bd4\u8f83\u9875\u9762\u4e2d\uff0c\u60a8\u53ef\u4ee5\u67e5\u770b\u6240\u9009\u8fd0\u884c\u7684\u53c2\u6570\u3001\u6307\u6807\u548c\u6807\u7b7e\uff0c\u4ee5\u53ca MLflow \u81ea\u52a8\u8bb0\u5f55\u7684\u7cfb\u7edf\u4fe1\u606f\uff0c\u5982\u8fd0\u884c\u7684\u5f00\u59cb\u548c\u7ed3\u675f\u65f6\u95f4\u3001\u6e90\u4ee3\u7801\u7248\u672c\u7b49\u3002\u6b64\u5916\uff0c\u60a8\u8fd8\u53ef\u4ee5\u67e5\u770b\u6307\u6807<\/li>\n<\/ol>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u7684\u53d8\u5316\u8d8b\u52bf\u56fe\uff0c\u4ee5\u5206\u6790\u4e0d\u540c\u8fd0\u884c\u4e4b\u95f4\u7684\u6027\u80fd\u5dee\u5f02\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"6\">\n<li>\u5728\u6bd4\u8f83\u9875\u9762\u7684\u9876\u90e8\uff0c\u60a8\u53ef\u4ee5\u70b9\u51fb \u201cScatter Plot\u201d \u548c \u201cParallel Coordinates Plot\u201d \u6309\u94ae\uff0c\u67e5\u770b\u6240\u9009\u8fd0\u884c\u7684\u6563\u70b9\u56fe\u548c\u5e73\u884c\u5750\u6807\u56fe\u3002\u8fd9\u4e9b\u56fe\u8868\u53ef\u4ee5\u5e2e\u52a9\u60a8\u66f4\u76f4\u89c2\u5730\u5206\u6790\u591a\u4e2a\u8fd0\u884c\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u4f8b\u5982\uff0c\u67e5\u627e\u53c2\u6570\u548c\u6307\u6807\u4e4b\u95f4\u7684\u76f8\u5173\u6027\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u901a\u8fc7 MLflow Python API \u548c Web \u7528\u6237\u754c\u9762\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u67e5\u8be2\u548c\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c\uff0c\u627e\u5230\u6700\u4f73\u7684\u6a21\u578b\u914d\u7f6e\u3002\u8fd9\u4e9b\u529f\u80fd\u6709\u52a9\u4e8e\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u53ef\u7ef4\u62a4\u6027\uff0c\u540c\u65f6\u4e3a\u60a8\u7684\u56e2\u961f\u63d0\u4f9b\u66f4\u597d\u7684\u534f\u4f5c\u548c\u6570\u636e\u5171\u4eab\u652f\u6301\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u8bb0\u5f55\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6<\/p>\n\n\n\n<p>\u5728 MLflow \u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 Tracking API \u8bb0\u5f55\u5b9e\u9a8c\u7684\u53c2\u6570\uff08\u5982\u8d85\u53c2\u6570\uff09\u3001\u6307\u6807\uff08\u5982\u51c6\u786e\u7387\u3001\u635f\u5931\u7b49\uff09\u548c\u5de5\u4ef6\uff08\u5982\u6a21\u578b\u6587\u4ef6\u3001\u8bad\u7ec3\u6570\u636e\u3001\u751f\u6210\u7684\u56fe\u7247\u7b49\uff09\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u8bb0\u5f55\u8fd9\u4e9b\u4fe1\u606f\u7684\u8be6\u7ec6\u8bf4\u660e\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u9996\u5148\uff0c\u5bfc\u5165 <code>mlflow<\/code> \u5e93\uff0c\u5e76\u8bbe\u7f6e MLflow \u670d\u52a1\u5668\u7684 URI\u3002\u5728 Python \u811a\u672c\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1apythonCopy code<code>import mlflow mlflow.set_tracking_uri(\"http:\/\/your-mlflow-server-ip:your-mlflow-server-port\") <\/code>\u8bf7\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u66ff\u6362 <code>your-mlflow-server-ip<\/code> \u548c <code>your-mlflow-server-port<\/code>\u3002<\/li>\n\n\n\n<li>\u4f7f\u7528 <code>mlflow.start_run<\/code> \u4e0a\u4e0b\u6587\u7ba1\u7406\u5668\u5f00\u59cb\u4e00\u4e2a\u65b0\u7684\u8fd0\u884c\u3002\u5728 <code>with<\/code> \u8bed\u53e5\u5757\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow API \u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\uff0c\u5982\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u7b49\uff1apythonCopy code<code>with mlflow.start_run(): # \u8bb0\u5f55\u53c2\u6570 mlflow.log_param(\"param_name\", param_value) # \u8bb0\u5f55\u6307\u6807 mlflow.log_metric(\"metric_name\", metric_value) # \u8bb0\u5f55\u5de5\u4ef6\uff08\u5982\u6a21\u578b\u6587\u4ef6\u3001\u56fe\u7247\u7b49\uff09 mlflow.log_artifact(\"path\/to\/local\/file\", \"artifact_subfolder\")<\/code><\/li>\n<\/ol>\n\n\n\n<p><strong>\u8bb0\u5f55\u53c2\u6570\uff1a<\/strong><\/p>\n\n\n\n<p>\u4f7f\u7528 <code>mlflow.log_param(key, value)<\/code> \u51fd\u6570\u8bb0\u5f55\u53c2\u6570\u3002<code>key<\/code> \u662f\u53c2\u6570\u540d\u79f0\uff0c<code>value<\/code> \u662f\u53c2\u6570\u503c\u3002\u4f8b\u5982\uff0c\u8bb0\u5f55\u5b66\u4e60\u7387\u53c2\u6570\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>learning_rate = 0.01\nmlflow.log_param(\"learning_rate\", learning_rate)\n<\/code><\/pre>\n\n\n\n<p><strong>\u8bb0\u5f55\u6307\u6807\uff1a<\/strong><\/p>\n\n\n\n<p>\u4f7f\u7528 <code>mlflow.log_metric(key, value, step)<\/code> \u51fd\u6570\u8bb0\u5f55\u6307\u6807\u3002<code>key<\/code> \u662f\u6307\u6807\u540d\u79f0\uff0c<code>value<\/code> \u662f\u6307\u6807\u503c\uff0c<code>step<\/code> \u662f\u53ef\u9009\u53c2\u6570\uff0c\u8868\u793a\u8bad\u7ec3\u6216\u4f18\u5316\u8fc7\u7a0b\u4e2d\u7684\u6b65\u9aa4\u3002\u4f8b\u5982\uff0c\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u8bb0\u5f55\u6bcf\u4e2a epoch \u7684\u635f\u5931\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>for epoch in range(epochs):\n    # \u8bad\u7ec3\u6a21\u578b\u5e76\u8ba1\u7b97\u635f\u5931\n    loss = train_model()\n\n    # \u8bb0\u5f55\u635f\u5931\n    mlflow.log_metric(\"loss\", loss, step=epoch)\n<\/code><\/pre>\n\n\n\n<p><strong>\u8bb0\u5f55\u5de5\u4ef6\uff1a<\/strong><\/p>\n\n\n\n<p>\u4f7f\u7528 <code>mlflow.log_artifact(local_path, artifact_path)<\/code> \u51fd\u6570\u8bb0\u5f55\u5de5\u4ef6\u3002<code>local_path<\/code> \u662f\u672c\u5730\u6587\u4ef6\u6216\u76ee\u5f55\u7684\u8def\u5f84\uff0c<code>artifact_path<\/code> \u662f\u53ef\u9009\u53c2\u6570\uff0c\u8868\u793a\u5de5\u4ef6\u5728 MLflow \u670d\u52a1\u5668\u4e0a\u7684\u76f8\u5bf9\u8def\u5f84\u3002\u4f8b\u5982\uff0c\u8bb0\u5f55\u4e00\u4e2a\u751f\u6210\u7684\u56fe\u7247\u6587\u4ef6\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import matplotlib.pyplot as plt\n\n# \u521b\u5efa\u4e00\u5f20\u56fe\u7247\nplt.plot([0, 1, 2, 3, 4], [0, 1, 4, 9, 16])\nplt.savefig(\"plot.png\")\n\n# \u8bb0\u5f55\u56fe\u7247\u6587\u4ef6\nmlflow.log_artifact(\"plot.png\", \"plots\")\n<\/code><\/pre>\n\n\n\n<p>\u901a\u8fc7\u8bb0\u5f55\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u8ddf\u8e2a\u548c\u7ba1\u7406\u5b9e\u9a8c\u6570\u636e\uff0c\u4ece\u800c\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u53ef\u7ef4\u62a4\u6027\u3002MLflow \u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684 API \u548c\u53ef\u89c6\u5316\u754c\u9762\uff0c\u5e2e\u52a9\u60a8\u5feb\u901f\u627e\u5230\u6700\u4f73\u7684\u6a21\u578b\u914d\u7f6e\uff0c\u5b9e\u73b0\u66f4\u9ad8\u6548\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u521b\u5efa\u4e00\u4e2a MLflow \u9879\u76ee<\/p>\n\n\n\n<p>\u521b\u5efa\u4e00\u4e2a MLflow \u9879\u76ee\u4e3b\u8981\u6d89\u53ca\u5230\u51c6\u5907\u9879\u76ee\u6587\u4ef6\u3001\u5b9a\u4e49\u73af\u5883\u914d\u7f6e\u548c\u7f16\u5199\u6267\u884c\u5165\u53e3\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u521b\u5efa\u4e00\u4e2a MLflow \u9879\u76ee\u7684\u8be6\u7ec6\u8bf4\u660e\uff1a<\/p>\n\n\n\n<p><strong>1. \u51c6\u5907\u9879\u76ee\u6587\u4ef6<\/strong><\/p>\n\n\n\n<p>\u5728\u9879\u76ee\u76ee\u5f55\u4e2d\uff0c\u521b\u5efa\u4e00\u4e2a\u5305\u542b\u4ee5\u4e0b\u6587\u4ef6\u548c\u6587\u4ef6\u5939\u7684\u7ed3\u6784\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">luaCopy code<code>your_project\/\n|-- MLproject\n|-- conda.yaml\n|-- main.py\n|-- other_files\/\n<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>MLproject<\/code>: \u4e00\u4e2a\u63cf\u8ff0\u9879\u76ee\u5143\u6570\u636e\u7684 YAML \u6587\u4ef6\uff0c\u5982\u9879\u76ee\u540d\u79f0\u3001\u5165\u53e3\u70b9\u548c\u53c2\u6570\u7b49\u3002<\/li>\n\n\n\n<li><code>conda.yaml<\/code>: \u4e00\u4e2a\u63cf\u8ff0\u9879\u76ee\u4f9d\u8d56\u548c\u73af\u5883\u914d\u7f6e\u7684 Conda YAML \u6587\u4ef6\u3002<\/li>\n\n\n\n<li><code>main.py<\/code>: \u9879\u76ee\u7684\u4e3b\u8981\u6267\u884c\u5165\u53e3\uff0c\u5305\u542b\u9879\u76ee\u7684\u4e3b\u8981\u903b\u8f91\u548c MLflow API \u8c03\u7528\u3002<\/li>\n\n\n\n<li><code>other_files\/<\/code>: \u5176\u4ed6\u9879\u76ee\u76f8\u5173\u6587\u4ef6\uff0c\u5982\u6570\u636e\u6587\u4ef6\u3001\u6a21\u578b\u6587\u4ef6\u7b49\u3002<\/li>\n<\/ul>\n\n\n\n<p><strong>2. \u5b9a\u4e49 MLproject \u6587\u4ef6<\/strong><\/p>\n\n\n\n<p>\u5728 <code>MLproject<\/code> \u6587\u4ef6\u4e2d\uff0c\u5b9a\u4e49\u9879\u76ee\u540d\u79f0\u3001\u5165\u53e3\u70b9\u548c\u53c2\u6570\u7b49\u5143\u6570\u636e\u3002\u4f8b\u5982\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">yamlCopy code<code>name: your_project_name\n\nentry_points:\n  main:\n    parameters:\n      param1: {type: float, default: 0.1, description: \"Example parameter 1\"}\n      param2: {type: int, default: 10, description: \"Example parameter 2\"}\n    command: \"python main.py --param1 {param1} --param2 {param2}\"\n<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>name<\/code>: \u9879\u76ee\u540d\u79f0\u3002<\/li>\n\n\n\n<li><code>entry_points<\/code>: \u5b9a\u4e49\u9879\u76ee\u7684\u5165\u53e3\u70b9\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u6709\u4e00\u4e2a\u540d\u4e3a <code>main<\/code> \u7684\u5165\u53e3\u70b9\u3002<\/li>\n\n\n\n<li><code>parameters<\/code>: \u5b9a\u4e49\u5165\u53e3\u70b9\u6240\u9700\u7684\u53c2\u6570\u53ca\u5176\u7c7b\u578b\u3001\u9ed8\u8ba4\u503c\u548c\u63cf\u8ff0\u3002<\/li>\n\n\n\n<li><code>command<\/code>: \u5b9a\u4e49\u6267\u884c\u5165\u53e3\u70b9\u7684\u547d\u4ee4\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u547d\u4ee4\u662f\u8fd0\u884c <code>main.py<\/code> \u6587\u4ef6\uff0c\u5e76\u4f20\u9012 <code>param1<\/code> \u548c <code>param2<\/code> \u53c2\u6570\u3002<\/li>\n<\/ul>\n\n\n\n<p><strong>3. \u5b9a\u4e49 conda.yaml \u6587\u4ef6<\/strong><\/p>\n\n\n\n<p>\u5728 <code>conda.yaml<\/code> \u6587\u4ef6\u4e2d\uff0c\u5b9a\u4e49\u9879\u76ee\u7684\u4f9d\u8d56\u548c\u73af\u5883\u914d\u7f6e\u3002\u4f8b\u5982\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">yamlCopy code<code>name: your_project_env\nchannels:\n  - defaults\n  - conda-forge\ndependencies:\n  - python=3.8\n  - scikit-learn\n  - pandas\n  - mlflow\n  - pip:\n    - -r requirements.txt\n<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>name<\/code>: \u73af\u5883\u540d\u79f0\u3002<\/li>\n\n\n\n<li><code>channels<\/code>: Conda \u9891\u9053\u5217\u8868\uff0c\u7528\u4e8e\u641c\u7d22\u8f6f\u4ef6\u5305\u3002<\/li>\n\n\n\n<li><code>dependencies<\/code>: \u9879\u76ee\u6240\u9700\u7684\u8f6f\u4ef6\u5305\u548c\u7248\u672c\u3002<\/li>\n<\/ul>\n\n\n\n<p><strong>4. \u7f16\u5199 main.py \u6587\u4ef6<\/strong><\/p>\n\n\n\n<p>\u5728 <code>main.py<\/code> \u6587\u4ef6\u4e2d\uff0c\u7f16\u5199\u9879\u76ee\u7684\u4e3b\u8981\u903b\u8f91\u548c MLflow API \u8c03\u7528\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>argparse<\/code> \u5904\u7406\u547d\u4ee4\u884c\u53c2\u6570\uff0c\u7136\u540e\u4f7f\u7528 MLflow API \u8bb0\u5f55\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u7b49\u3002<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import argparse\nimport mlflow\n\ndef main(param1, param2):\n    # \u9879\u76ee\u903b\u8f91\uff0c\u5982\u8bad\u7ec3\u6a21\u578b\u3001\u8ba1\u7b97\u6307\u6807\u7b49\n    ...\n    with mlflow.start_run():\n        mlflow.log_param(\"param1\", param1)\n        mlflow.log_param(\"param2\", param2)\n        mlflow.log_metric(\"example_metric\", example_metric_value)\n        ...\n        mlflow.log_artifact(\"path\/to\/local\/file\", \"artifact_subfolder\")\n\nif __name__ == \"__main__\":\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--\n<\/code><\/pre>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>param1&#8243;, type=float, help=&#8221;Example parameter 1&#8243;) parser.add_argument(&#8220;&#8211;param2&#8243;, type=int, help=&#8221;Example parameter 2&#8221;) args = parser.parse_args()<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">cssCopy code<code>main(args.param1, args.param2)\n<\/code><\/pre>\n\n\n\n<pre class=\"wp-block-preformatted\">markdownCopy code<code>\n\u5728 `main.py` \u6587\u4ef6\u4e2d\uff1a\n\n- \u4f7f\u7528 `argparse.ArgumentParser()` \u5b9a\u4e49\u547d\u4ee4\u884c\u53c2\u6570\u3002\n- \u7f16\u5199 `main()` \u51fd\u6570\uff0c\u5305\u542b\u9879\u76ee\u7684\u4e3b\u8981\u903b\u8f91\u548c MLflow API \u8c03\u7528\u3002\n- \u5728 `if __name__ == \"__main__\":` \u4ee3\u7801\u5757\u4e2d\uff0c\u89e3\u6790\u547d\u4ee4\u884c\u53c2\u6570\uff0c\u5e76\u8c03\u7528 `main()` \u51fd\u6570\u3002\n\n**5. \u8fd0\u884c MLflow \u9879\u76ee**\n\n\u5728\u5b8c\u6210\u9879\u76ee\u6587\u4ef6\u51c6\u5907\u540e\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 `mlflow run` \u547d\u4ee4\u8fd0\u884c MLflow \u9879\u76ee\u3002\u5728\u9879\u76ee\u76ee\u5f55\u6240\u5728\u7684\u7ec8\u7aef\u4e2d\uff0c\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4\uff1a\n\n<\/code><\/pre>\n\n\n\n<p>mlflow run . -P param1=0.5 -P param2=20<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">markdownCopy code<code>\n- `mlflow run`: MLflow \u547d\u4ee4\uff0c\u7528\u4e8e\u8fd0\u884c\u9879\u76ee\u3002\n- `.`: \u9879\u76ee\u76ee\u5f55\u7684\u8def\u5f84\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u9879\u76ee\u4f4d\u4e8e\u5f53\u524d\u76ee\u5f55\u3002\n- `-P param1=0.5 -P param2=20`: \u4f20\u9012\u7ed9\u9879\u76ee\u5165\u53e3\u70b9\u7684\u53c2\u6570\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u4f20\u9012 `param1` \u548c `param2` \u53c2\u6570\u3002\n\n\u6b64\u547d\u4ee4\u5c06\u8fd0\u884c MLflow \u9879\u76ee\uff0c\u5e76\u4f7f\u7528\u6307\u5b9a\u7684\u53c2\u6570\u3002\u5728\u8fd0\u884c\u8fc7\u7a0b\u4e2d\uff0cMLflow \u5c06\u81ea\u52a8\u521b\u5efa\u548c\u6fc0\u6d3b Conda \u73af\u5883\uff0c\u5e76\u6267\u884c\u5b9a\u4e49\u5728 `MLproject` \u6587\u4ef6\u4e2d\u7684\u547d\u4ee4\u3002\n\n\u901a\u8fc7\u521b\u5efa\u4e00\u4e2a MLflow \u9879\u76ee\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\uff0c\u5b9e\u73b0\u8de8\u56e2\u961f\u7684\u534f\u4f5c\u548c\u5171\u4eab\u3002MLflow \u63d0\u4f9b\u4e86\u4e00\u79cd\u7b80\u5355\u7684\u65b9\u5f0f\u6765\u6253\u5305\u3001\u8fd0\u884c\u548c\u5206\u4eab\u673a\u5668\u5b66\u4e60\u9879\u76ee\uff0c\u4f7f\u5f97\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u91cd\u590d\u5b9e\u9a8c\u548c\u90e8\u7f72\u6a21\u578b\u3002\n<\/code><\/pre>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p><strong>6. \u5206\u4eab\u548c\u534f\u4f5c<\/strong><\/p>\n\n\n\n<p>\u5f53\u60a8\u7684 MLflow \u9879\u76ee\u51c6\u5907\u5c31\u7eea\u540e\uff0c\u60a8\u53ef\u4ee5\u4e0e\u56e2\u961f\u6210\u5458\u5171\u4eab\u9879\u76ee\uff0c\u4ee5\u4fbf\u8fdb\u884c\u534f\u4f5c\u3002\u4e3a\u4e86\u5b9e\u73b0\u8fd9\u4e00\u76ee\u6807\uff0c\u60a8\u53ef\u4ee5\u91c7\u53d6\u4ee5\u4e0b\u65b9\u6cd5\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>\u7248\u672c\u63a7\u5236<\/strong>\uff1a\u5c06\u9879\u76ee\u6258\u7ba1\u5728\u7248\u672c\u63a7\u5236\u7cfb\u7edf\uff08\u5982 Git\uff09\u4e0a\uff0c\u4ee5\u4fbf\u8ddf\u8e2a\u9879\u76ee\u5386\u53f2\u548c\u534f\u4f5c\u3002\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u514b\u9686\u4ed3\u5e93\uff0c\u5e76\u5728\u672c\u5730\u8fd0\u884c MLflow \u9879\u76ee\u3002<\/li>\n\n\n\n<li><strong>\u914d\u7f6e\u8fdc\u7a0b MLflow \u670d\u52a1\u5668<\/strong>\uff1a\u914d\u7f6e\u4e00\u4e2a\u8fdc\u7a0b MLflow \u670d\u52a1\u5668\uff0c\u4ee5\u4fbf\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u67e5\u770b\u548c\u5171\u4eab\u5b9e\u9a8c\u7ed3\u679c\u3002\u5728 Python \u811a\u672c\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 <code>mlflow.set_tracking_uri()<\/code> \u51fd\u6570\u8bbe\u7f6e\u8fdc\u7a0b\u670d\u52a1\u5668\u7684 URI\u3002<\/li>\n\n\n\n<li><strong>\u4f7f\u7528 MLflow \u6a21\u578b\u6ce8\u518c\u8868<\/strong>\uff1a\u5229\u7528 MLflow Model Registry \u7ba1\u7406\u548c\u5171\u4eab\u6a21\u578b\u3002\u60a8\u53ef\u4ee5\u5c06\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u6ce8\u518c\u5230\u6a21\u578b\u6ce8\u518c\u8868\u4e2d\uff0c\u5e76\u4e3a\u5176\u521b\u5efa\u4e0d\u540c\u7684\u7248\u672c\u3002\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u5728 MLflow UI \u4e0a\u67e5\u770b\u3001\u6bd4\u8f83\u548c\u90e8\u7f72\u4e0d\u540c\u7248\u672c\u7684\u6a21\u578b\u3002<\/li>\n<\/ul>\n\n\n\n<p>\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u60a8\u53ef\u4ee5\u4e0e\u56e2\u961f\u6210\u5458\u4e00\u8d77\u5de5\u4f5c\uff0c\u5171\u4eab\u5b9e\u9a8c\u6570\u636e\u3001\u6a21\u578b\u548c\u7ed3\u679c\uff0c\u4ece\u800c\u63d0\u9ad8\u56e2\u961f\u534f\u4f5c\u6548\u7387\uff0c\u52a0\u901f\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u5f00\u53d1\u548c\u90e8\u7f72\u3002<\/p>\n\n\n\n<p>\u603b\u4e4b\uff0c\u521b\u5efa\u4e00\u4e2a MLflow \u9879\u76ee\u53ef\u4ee5\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u3002\u901a\u8fc7\u5b9a\u4e49\u9879\u76ee\u6587\u4ef6\u3001\u73af\u5883\u914d\u7f6e\u548c\u6267\u884c\u5165\u53e3\uff0c\u60a8\u53ef\u4ee5\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u8f7b\u677e\u5730\u91cd\u590d\u5b9e\u9a8c\u548c\u90e8\u7f72\u6a21\u578b\u3002\u6b64\u5916\uff0cMLflow \u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u548c\u5de5\u5177\uff0c\u652f\u6301\u8de8\u56e2\u961f\u7684\u534f\u4f5c\u548c\u5171\u4eab\uff0c\u63d0\u9ad8\u4e86\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u5f00\u53d1\u6548\u7387\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u9879\u76ee\u4f9d\u8d56\u7ba1\u7406<\/p>\n\n\n\n<p>\u5728\u673a\u5668\u5b66\u4e60\u548c\u6570\u636e\u79d1\u5b66\u9879\u76ee\u4e2d\uff0c\u4f9d\u8d56\u7ba1\u7406\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u5b83\u53ef\u4ee5\u786e\u4fdd\u9879\u76ee\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u80fd\u591f\u7a33\u5b9a\u5730\u8fd0\u884c\uff0c\u540c\u65f6\u7b80\u5316\u4e86\u56e2\u961f\u534f\u4f5c\u548c\u6a21\u578b\u90e8\u7f72\u3002\u4ee5\u4e0b\u662f\u9879\u76ee\u4f9d\u8d56\u7ba1\u7406\u7684\u8be6\u7ec6\u8bf4\u660e\uff1a<\/p>\n\n\n\n<p><strong>1. \u4f7f\u7528\u865a\u62df\u73af\u5883<\/strong><\/p>\n\n\n\n<p>\u4e3a\u4e86\u786e\u4fdd\u9879\u76ee\u7684\u9694\u79bb\u6027\u548c\u53ef\u79fb\u690d\u6027\uff0c\u5efa\u8bae\u4e3a\u6bcf\u4e2a\u9879\u76ee\u521b\u5efa\u4e00\u4e2a\u865a\u62df\u73af\u5883\u3002\u865a\u62df\u73af\u5883\u662f\u4e00\u4e2a\u72ec\u7acb\u7684 Python \u89e3\u91ca\u5668\u548c\u5305\u5b89\u88c5\u4f4d\u7f6e\uff0c\u53ef\u4ee5\u9632\u6b62\u4e0d\u540c\u9879\u76ee\u4e4b\u95f4\u7684\u4f9d\u8d56\u51b2\u7a81\u3002\u5e38\u89c1\u7684\u865a\u62df\u73af\u5883\u5de5\u5177\u6709 <code>venv<\/code>\uff08Python \u81ea\u5e26\u7684\u865a\u62df\u73af\u5883\u5de5\u5177\uff09\u548c <code>conda<\/code>\uff08Anaconda \u63d0\u4f9b\u7684\u865a\u62df\u73af\u5883\u548c\u5305\u7ba1\u7406\u5de5\u5177\uff09\u3002<\/p>\n\n\n\n<p><strong>2. \u4f7f\u7528\u4f9d\u8d56\u6587\u4ef6<\/strong><\/p>\n\n\n\n<p>\u4e3a\u4e86\u65b9\u4fbf\u5730\u7ba1\u7406\u548c\u5171\u4eab\u9879\u76ee\u4f9d\u8d56\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4f9d\u8d56\u6587\u4ef6\u3002\u8fd9\u4e9b\u6587\u4ef6\u5305\u542b\u4e86\u9879\u76ee\u6240\u9700\u7684\u6240\u6709\u8f6f\u4ef6\u5305\u53ca\u5176\u7248\u672c\u4fe1\u606f\u3002\u5e38\u89c1\u7684\u4f9d\u8d56\u6587\u4ef6\u6709\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>requirements.txt<\/code>: \u9002\u7528\u4e8e <code>pip<\/code> \u7684\u4f9d\u8d56\u6587\u4ef6\u3002\u53ef\u4ee5\u4f7f\u7528 <code>pip freeze &gt; requirements.txt<\/code> \u751f\u6210\uff0c\u5e76\u4f7f\u7528 <code>pip install -r requirements.txt<\/code> \u5b89\u88c5\u3002<\/li>\n\n\n\n<li><code>conda.yaml<\/code> \u6216 <code>environment.yaml<\/code>: \u9002\u7528\u4e8e <code>conda<\/code> \u7684\u4f9d\u8d56\u6587\u4ef6\u3002\u53ef\u4ee5\u4f7f\u7528 <code>conda env export &gt; environment.yaml<\/code> \u751f\u6210\uff0c\u5e76\u4f7f\u7528 <code>conda env create -f environment.yaml<\/code> \u5b89\u88c5\u3002<\/li>\n<\/ul>\n\n\n\n<p>\u901a\u8fc7\u4f7f\u7528\u4f9d\u8d56\u6587\u4ef6\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u4f7f\u7528\u76f8\u540c\u7248\u672c\u7684\u8f6f\u4ef6\u5305\uff0c\u4ece\u800c\u907f\u514d\u6f5c\u5728\u7684\u517c\u5bb9\u6027\u95ee\u9898\u3002<\/p>\n\n\n\n<p><strong>3. \u5728 MLflow \u9879\u76ee\u4e2d\u7ba1\u7406\u4f9d\u8d56<\/strong><\/p>\n\n\n\n<p>\u5728 MLflow \u9879\u76ee\u4e2d\uff0c\u4f9d\u8d56\u7ba1\u7406\u662f\u901a\u8fc7 <code>conda.yaml<\/code> \u6587\u4ef6\u5b9e\u73b0\u7684\u3002\u8fd9\u4e2a\u6587\u4ef6\u63cf\u8ff0\u4e86\u9879\u76ee\u6240\u9700\u7684\u8f6f\u4ef6\u5305\u53ca\u5176\u7248\u672c\u4fe1\u606f\u3002\u5f53\u60a8\u4f7f\u7528 <code>mlflow run<\/code> \u547d\u4ee4\u8fd0\u884c MLflow \u9879\u76ee\u65f6\uff0cMLflow \u4f1a\u81ea\u52a8\u521b\u5efa\u548c\u6fc0\u6d3b\u4e00\u4e2a Conda \u73af\u5883\uff0c\u6839\u636e <code>conda.yaml<\/code> \u6587\u4ef6\u5b89\u88c5\u6240\u9700\u7684\u4f9d\u8d56\u3002<\/p>\n\n\n\n<p>\u4f8b\u5982\uff0c\u5728 <code>conda.yaml<\/code> \u6587\u4ef6\u4e2d\uff0c\u5b9a\u4e49\u4ee5\u4e0b\u4f9d\u8d56\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">yamlCopy code<code>name: your_project_env\nchannels:\n  - defaults\n  - conda-forge\ndependencies:\n  - python=3.8\n  - scikit-learn\n  - pandas\n  - mlflow\n  - pip:\n    - -r requirements.txt\n<\/code><\/pre>\n\n\n\n<p>\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0cMLflow \u786e\u4fdd\u9879\u76ee\u8fd0\u884c\u6240\u9700\u7684\u4f9d\u8d56\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u4fdd\u6301\u4e00\u81f4\u3002<\/p>\n\n\n\n<p>\u603b\u4e4b\uff0c\u5728\u673a\u5668\u5b66\u4e60\u548c\u6570\u636e\u79d1\u5b66\u9879\u76ee\u4e2d\uff0c\u4f9d\u8d56\u7ba1\u7406\u53ef\u4ee5\u786e\u4fdd\u9879\u76ee\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u7a33\u5b9a\u5730\u8fd0\u884c\uff0c\u7b80\u5316\u56e2\u961f\u534f\u4f5c\u548c\u6a21\u578b\u90e8\u7f72\u3002\u901a\u8fc7\u4f7f\u7528\u865a\u62df\u73af\u5883\u3001\u4f9d\u8d56\u6587\u4ef6\u548c MLflow \u9879\u76ee\uff0c\u60a8\u53ef\u4ee5\u9ad8\u6548\u5730\u7ba1\u7406\u9879\u76ee\u4f9d\u8d56\uff0c\u63d0\u9ad8\u9879\u76ee\u7684\u53ef\u7ef4\u62a4\u6027\u548c\u53ef\u79fb\u690d\u6027\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u4f7f\u7528 MLflow \u8fd0\u884c\u9879\u76ee<\/p>\n\n\n\n<p>\u4f7f\u7528 MLflow \u8fd0\u884c\u9879\u76ee\u975e\u5e38\u7b80\u5355\u3002\u5728\u60a8\u5df2\u7ecf\u521b\u5efa\u4e86\u4e00\u4e2a\u5305\u542b <code>MLproject<\/code> \u6587\u4ef6\u548c\u76f8\u5173\u4f9d\u8d56\u6587\u4ef6\u7684 MLflow \u9879\u76ee\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>mlflow run<\/code> \u547d\u4ee4\u6765\u8fd0\u884c\u9879\u76ee\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 MLflow \u8fd0\u884c\u9879\u76ee\u7684\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<p><strong>1. \u5b9a\u4f4d\u5230\u9879\u76ee\u76ee\u5f55<\/strong><\/p>\n\n\n\n<p>\u5728\u7ec8\u7aef\u4e2d\uff0c\u5bfc\u822a\u5230 MLflow \u9879\u76ee\u7684\u6839\u76ee\u5f55\u3002\u786e\u4fdd\u60a8\u7684\u9879\u76ee\u76ee\u5f55\u5305\u542b <code>MLproject<\/code> \u6587\u4ef6\u548c <code>conda.yaml<\/code>\uff08\u6216\u5176\u4ed6\u4f9d\u8d56\u6587\u4ef6\uff09\u3002<\/p>\n\n\n\n<p><strong>2. \u8fd0\u884c MLflow \u9879\u76ee<\/strong><\/p>\n\n\n\n<p>\u5728\u9879\u76ee\u76ee\u5f55\u6240\u5728\u7684\u7ec8\u7aef\u4e2d\uff0c\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">cssCopy code<code>mlflow run . -P param1=value1 -P param2=value2\n<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>mlflow run<\/code>: MLflow \u547d\u4ee4\uff0c\u7528\u4e8e\u8fd0\u884c\u9879\u76ee\u3002<\/li>\n\n\n\n<li><code>.<\/code>: \u9879\u76ee\u76ee\u5f55\u7684\u8def\u5f84\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u9879\u76ee\u4f4d\u4e8e\u5f53\u524d\u76ee\u5f55\u3002<\/li>\n\n\n\n<li><code>-P param1=value1 -P param2=value2<\/code>: \u4f20\u9012\u7ed9\u9879\u76ee\u5165\u53e3\u70b9\u7684\u53c2\u6570\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u4f20\u9012\u4e86 <code>param1<\/code> \u548c <code>param2<\/code> \u53c2\u6570\u3002\u8fd9\u4e9b\u53c2\u6570\u5e94\u4e0e <code>MLproject<\/code> \u6587\u4ef6\u4e2d\u5b9a\u4e49\u7684\u53c2\u6570\u76f8\u5bf9\u5e94\u3002<\/li>\n<\/ul>\n\n\n\n<p>\u6b64\u547d\u4ee4\u5c06\u8fd0\u884c MLflow \u9879\u76ee\uff0c\u5e76\u4f7f\u7528\u6307\u5b9a\u7684\u53c2\u6570\u3002\u5728\u8fd0\u884c\u8fc7\u7a0b\u4e2d\uff0cMLflow \u5c06\u6839\u636e <code>conda.yaml<\/code> \u6587\u4ef6\u81ea\u52a8\u521b\u5efa\u548c\u6fc0\u6d3b Conda \u73af\u5883\uff0c\u5e76\u6267\u884c\u5b9a\u4e49\u5728 <code>MLproject<\/code> \u6587\u4ef6\u4e2d\u7684\u547d\u4ee4\u3002<\/p>\n\n\n\n<p><strong>3. \u8fd0\u884c\u8fdc\u7a0b\u9879\u76ee<\/strong><\/p>\n\n\n\n<p>\u9664\u4e86\u8fd0\u884c\u672c\u5730\u9879\u76ee\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528 MLflow \u8fd0\u884c\u8fdc\u7a0b\u9879\u76ee\u3002\u4f8b\u5982\uff0c\u5982\u679c\u9879\u76ee\u6258\u7ba1\u5728 Git \u4ed3\u5e93\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u8fd0\u884c\u9879\u76ee\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">arduinoCopy code<code>mlflow run https:\/\/github.com\/your-username\/your-repo.git -P param1=value1 -P param2=value2\n<\/code><\/pre>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>https:\/\/github.com\/your-username\/your-repo.git<\/code>: Git \u4ed3\u5e93\u7684 URL\u3002<\/li>\n\n\n\n<li><code>-P param1=value1 -P param2=value2<\/code>: \u4f20\u9012\u7ed9\u9879\u76ee\u5165\u53e3\u70b9\u7684\u53c2\u6570\u3002<\/li>\n<\/ul>\n\n\n\n<p>\u5728\u8fd0\u884c\u8fdc\u7a0b\u9879\u76ee\u65f6\uff0cMLflow \u5c06\u81ea\u52a8\u514b\u9686 Git \u4ed3\u5e93\u5230\u672c\u5730\uff0c\u5e76\u6267\u884c\u76f8\u540c\u7684\u8fd0\u884c\u8fc7\u7a0b\u3002<\/p>\n\n\n\n<p>\u901a\u8fc7\u4f7f\u7528 <code>mlflow run<\/code> \u547d\u4ee4\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u8fd0\u884c MLflow \u9879\u76ee\uff0c\u65e0\u8bba\u662f\u672c\u5730\u8fd8\u662f\u8fdc\u7a0b\u3002\u8fd9\u79cd\u65b9\u5f0f\u786e\u4fdd\u4e86\u9879\u76ee\u4f9d\u8d56\u7684\u4e00\u81f4\u6027\u548c\u53ef\u79fb\u690d\u6027\uff0c\u7b80\u5316\u4e86\u5b9e\u9a8c\u7684\u91cd\u590d\u548c\u6a21\u578b\u90e8\u7f72\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u521b\u5efa MLflow Model<\/p>\n\n\n\n<p>\u5728 MLflow \u4e2d\uff0c\u6a21\u578b\u662f\u6307\u7528\u4e8e\u9884\u6d4b\u7684\u53ef\u90e8\u7f72\u7ec4\u4ef6\u3002MLflow Model \u7531\u6a21\u578b\u6587\u4ef6\u3001\u6a21\u578b\u5143\u6570\u636e\u548c\u6a21\u578b\u683c\u5f0f\u7ec4\u6210\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528 MLflow \u521b\u5efa\u6a21\u578b\u7684\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<p><strong>1. \u8bad\u7ec3\u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u9996\u5148\uff0c\u60a8\u9700\u8981\u8bad\u7ec3\u4e00\u4e2a\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u8fd9\u4e2a\u8fc7\u7a0b\u53d6\u51b3\u4e8e\u60a8\u4f7f\u7528\u7684\u5177\u4f53\u7b97\u6cd5\u548c\u5e93\u3002\u4f8b\u5982\uff0c\u4f7f\u7528 scikit-learn \u8bad\u7ec3\u4e00\u4e2a\u7ebf\u6027\u56de\u5f52\u6a21\u578b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import numpy as np\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.model_selection import train_test_split\n\n# \u521b\u5efa\u6570\u636e\u96c6\nX, y = np.random.rand(100, 1), np.random.rand(100, 1)\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n\n# \u8bad\u7ec3\u6a21\u578b\nmodel = LinearRegression()\nmodel.fit(X_train, y_train)\n<\/code><\/pre>\n\n\n\n<p><strong>2. \u4f7f\u7528 MLflow \u4fdd\u5b58\u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u5f53\u60a8\u7684\u6a21\u578b\u8bad\u7ec3\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528 MLflow API \u4fdd\u5b58\u6a21\u578b\u3002MLflow \u652f\u6301\u591a\u79cd\u6a21\u578b\u683c\u5f0f\uff0c\u5982 scikit-learn\u3001PyTorch\u3001TensorFlow \u7b49\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u6211\u4eec\u5c06\u4f7f\u7528 scikit-learn \u683c\u5f0f\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow.sklearn\n\n# \u4fdd\u5b58\u6a21\u578b\nmlflow.sklearn.save_model(model, \"model\")\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c<code>model<\/code> \u662f\u8bad\u7ec3\u597d\u7684 scikit-learn \u6a21\u578b\uff0c<code>\"model\"<\/code> \u662f\u4fdd\u5b58\u6a21\u578b\u7684\u76ee\u5f55\u3002MLflow \u4f1a\u5728\u6307\u5b9a\u76ee\u5f55\u4e2d\u521b\u5efa\u4e00\u4e2a\u540d\u4e3a <code>MLmodel<\/code> \u7684\u5143\u6570\u636e\u6587\u4ef6\uff0c\u8be5\u6587\u4ef6\u63cf\u8ff0\u4e86\u6a21\u578b\u7684\u683c\u5f0f\u3001\u7248\u672c\u7b49\u4fe1\u606f\u3002\u540c\u65f6\uff0cMLflow \u4f1a\u5c06\u6a21\u578b\u6587\u4ef6\uff08\u5982 scikit-learn \u6a21\u578b\u7684 <code>.pkl<\/code> \u6587\u4ef6\uff09\u4fdd\u5b58\u5728\u8be5\u76ee\u5f55\u4e2d\u3002<\/p>\n\n\n\n<p><strong>3. \u52a0\u8f7d\u5e76\u4f7f\u7528 MLflow Model<\/strong><\/p>\n\n\n\n<p>\u4fdd\u5b58 MLflow Model \u540e\uff0c\u60a8\u53ef\u4ee5\u5728\u5176\u4ed6 Python \u811a\u672c\u6216\u5e94\u7528\u7a0b\u5e8f\u4e2d\u4f7f\u7528 MLflow API \u52a0\u8f7d\u548c\u4f7f\u7528\u6a21\u578b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow.sklearn\n\n# \u52a0\u8f7d\u6a21\u578b\nloaded_model = mlflow.sklearn.load_model(\"model\")\n\n# \u4f7f\u7528\u6a21\u578b\u8fdb\u884c\u9884\u6d4b\npredictions = loaded_model.predict(X_test)\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c<code>\"model\"<\/code> \u662f\u4fdd\u5b58\u6a21\u578b\u7684\u76ee\u5f55\u3002\u4f7f\u7528 <code>mlflow.sklearn.load_model()<\/code> \u51fd\u6570\uff0c\u60a8\u53ef\u4ee5\u4ece\u6307\u5b9a\u76ee\u5f55\u52a0\u8f7d MLflow Model\u3002\u7136\u540e\uff0c\u60a8\u53ef\u4ee5\u50cf\u4f7f\u7528\u666e\u901a scikit-learn \u6a21\u578b\u4e00\u6837\u4f7f\u7528\u52a0\u8f7d\u7684\u6a21\u578b\u8fdb\u884c\u9884\u6d4b\u3002<\/p>\n\n\n\n<p>\u521b\u5efa MLflow Model \u7684\u8fc7\u7a0b\u975e\u5e38\u7b80\u5355\u3002\u901a\u8fc7\u4f7f\u7528 MLflow API \u4fdd\u5b58\u548c\u52a0\u8f7d\u6a21\u578b\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd\u6a21\u578b\u683c\u5f0f\u548c\u5143\u6570\u636e\u7684\u4e00\u81f4\u6027\uff0c\u7b80\u5316\u6a21\u578b\u90e8\u7f72\u548c\u5171\u4eab\u3002\u6b64\u5916\uff0cMLflow \u652f\u6301\u591a\u79cd\u6a21\u578b\u683c\u5f0f\uff0c\u65b9\u4fbf\u60a8\u5728\u4e0d\u540c\u7684\u673a\u5668\u5b66\u4e60\u5e93\u548c\u73af\u5883\u4e2d\u4f7f\u7528\u6a21\u578b\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u4f7f\u7528\u4e0d\u540c\u7684\u6a21\u578b\u683c\u5f0f\u4fdd\u5b58\u6a21\u578b<\/p>\n\n\n\n<p>MLflow \u652f\u6301\u591a\u79cd\u6a21\u578b\u683c\u5f0f\uff0c\u5982 scikit-learn\u3001TensorFlow\u3001PyTorch \u7b49\u3002\u5728\u4fdd\u5b58\u6a21\u578b\u65f6\uff0c\u60a8\u9700\u8981\u4f7f\u7528\u4e0e\u6a21\u578b\u5bf9\u5e94\u7684 MLflow \u5b50\u6a21\u5757\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528\u4e0d\u540c\u6a21\u578b\u683c\u5f0f\u4fdd\u5b58\u6a21\u578b\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<p><strong>1. \u4fdd\u5b58 scikit-learn \u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u5982\u679c\u60a8\u4f7f\u7528 scikit-learn \u8bad\u7ec3\u4e86\u4e00\u4e2a\u6a21\u578b\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>mlflow.sklearn<\/code> \u5b50\u6a21\u5757\u4fdd\u5b58\u6a21\u578b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow.sklearn\n\n# \u8bad\u7ec3\u4e00\u4e2a scikit-learn \u6a21\u578b\n# ...\n\n# \u4fdd\u5b58\u6a21\u578b\nmlflow.sklearn.save_model(model, \"model_sklearn\")\n<\/code><\/pre>\n\n\n\n<p><strong>2. \u4fdd\u5b58 TensorFlow \u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u5982\u679c\u60a8\u4f7f\u7528 TensorFlow \u8bad\u7ec3\u4e86\u4e00\u4e2a\u6a21\u578b\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>mlflow.tensorflow<\/code> \u5b50\u6a21\u5757\u4fdd\u5b58\u6a21\u578b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow.tensorflow\n\n# \u8bad\u7ec3\u4e00\u4e2a TensorFlow \u6a21\u578b\n# ...\n\n# \u4fdd\u5b58\u6a21\u578b\nmlflow.tensorflow.save_model(model, \"model_tensorflow\")\n<\/code><\/pre>\n\n\n\n<p>\u6ce8\u610f\uff1a\u5728\u4f7f\u7528 <code>mlflow.tensorflow<\/code> \u4e4b\u524d\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5 TensorFlow \u5e93\u3002<\/p>\n\n\n\n<p><strong>3. \u4fdd\u5b58 PyTorch \u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u5982\u679c\u60a8\u4f7f\u7528 PyTorch \u8bad\u7ec3\u4e86\u4e00\u4e2a\u6a21\u578b\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>mlflow.pytorch<\/code> \u5b50\u6a21\u5757\u4fdd\u5b58\u6a21\u578b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow.pytorch\n\n# \u8bad\u7ec3\u4e00\u4e2a PyTorch \u6a21\u578b\n# ...\n\n# \u4fdd\u5b58\u6a21\u578b\nmlflow.pytorch.save_model(model, \"model_pytorch\")\n<\/code><\/pre>\n\n\n\n<p>\u6ce8\u610f\uff1a\u5728\u4f7f\u7528 <code>mlflow.pytorch<\/code> \u4e4b\u524d\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5 PyTorch \u5e93\u3002<\/p>\n\n\n\n<p><strong>4. \u4fdd\u5b58\u5176\u4ed6\u6a21\u578b\u683c\u5f0f<\/strong><\/p>\n\n\n\n<p>MLflow \u652f\u6301\u5176\u4ed6\u8bb8\u591a\u6a21\u578b\u683c\u5f0f\uff0c\u5982 XGBoost\u3001LightGBM \u7b49\u3002\u8bf7\u53c2\u8003 MLflow \u6587\u6863\u4e86\u89e3\u5982\u4f55\u4f7f\u7528\u4e0d\u540c\u7684\u5b50\u6a21\u5757\u4fdd\u5b58\u8fd9\u4e9b\u6a21\u578b\u683c\u5f0f\uff1a<a href=\"https:\/\/www.mlflow.org\/docs\/latest\/models.html\">MLflow Models<\/a><\/p>\n\n\n\n<p>\u5728\u4fdd\u5b58\u6a21\u578b\u65f6\uff0c\u8bf7\u786e\u4fdd\u4f7f\u7528\u4e0e\u6a21\u578b\u5bf9\u5e94\u7684 MLflow \u5b50\u6a21\u5757\u3002\u8fd9\u6837\uff0cMLflow \u53ef\u4ee5\u6b63\u786e\u5730\u4fdd\u5b58\u6a21\u578b\u6587\u4ef6\u3001\u5143\u6570\u636e\u548c\u683c\u5f0f\u3002\u5f53\u60a8\u9700\u8981\u90e8\u7f72\u6216\u5171\u4eab\u6a21\u578b\u65f6\uff0cMLflow \u63d0\u4f9b\u4e86\u7edf\u4e00\u7684 API \u52a0\u8f7d\u548c\u4f7f\u7528\u4e0d\u540c\u683c\u5f0f\u7684\u6a21\u578b\uff0c\u7b80\u5316\u4e86\u6a21\u578b\u7ba1\u7406\u548c\u90e8\u7f72\u7684\u8fc7\u7a0b\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u90e8\u7f72 MLflow Model<\/p>\n\n\n\n<p>MLflow Model \u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u8fdb\u884c\u90e8\u7f72\uff0c\u5305\u62ec\u672c\u5730\u90e8\u7f72\u3001\u90e8\u7f72\u5230\u4e91\u670d\u52a1\u548c\u90e8\u7f72\u5230\u5bb9\u5668\u7b49\u3002\u5728\u8fd9\u91cc\uff0c\u6211\u4eec\u5c06\u4ecb\u7ecd\u5982\u4f55\u5728\u672c\u5730\u90e8\u7f72 MLflow Model\uff0c\u5e76\u5c06\u6a21\u578b\u4f5c\u4e3a REST API \u63d0\u4f9b\u670d\u52a1\u3002<\/p>\n\n\n\n<p><strong>\u90e8\u7f72 MLflow Model \u4f5c\u4e3a REST API<\/strong><\/p>\n\n\n\n<p>\u8981\u5c06 MLflow Model \u90e8\u7f72\u4e3a REST API\uff0c\u6211\u4eec\u5c06\u4f7f\u7528 MLflow \u81ea\u5e26\u7684\u6a21\u578b\u670d\u52a1\u5668\u3002\u4ee5\u4e0b\u662f\u90e8\u7f72\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u786e\u4fdd\u5b89\u88c5\u6240\u9700\u7684\u5e93<\/strong>\u9996\u5148\uff0c\u786e\u4fdd\u60a8\u5df2\u7ecf\u5b89\u88c5\u4e86 <code>mlflow<\/code> \u548c\u5176\u4ed6\u5fc5\u9700\u7684\u5e93\u3002\u5bf9\u4e8e\u67d0\u4e9b\u6a21\u578b\uff08\u4f8b\u5982 TensorFlow\u3001PyTorch \u7b49\uff09\uff0c\u60a8\u53ef\u80fd\u9700\u8981\u5b89\u88c5\u76f8\u5e94\u7684\u5e93\u3002\u4f7f\u7528 <code>pip<\/code> \u5b89\u88c5\u5e93\uff1abashCopy code<code>pip install mlflow<\/code><\/li>\n\n\n\n<li><strong>\u542f\u52a8 MLflow Model \u670d\u52a1\u5668<\/strong>\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u542f\u52a8 MLflow Model \u670d\u52a1\u5668\uff1abashCopy code<code>mlflow models serve -m \/path\/to\/your\/model -h 0.0.0.0 -p 1234 <\/code>\u5176\u4e2d\uff1a<ul><li><code>-m \/path\/to\/your\/model<\/code>\uff1a\u6307\u5b9a MLflow Model \u6240\u5728\u7684\u8def\u5f84\u3002<\/li><li><code>-h 0.0.0.0<\/code>\uff1a\u6307\u5b9a\u670d\u52a1\u5668\u7ed1\u5b9a\u7684 IP \u5730\u5740\u3002\u5728\u8fd9\u91cc\uff0c\u6211\u4eec\u4f7f\u7528 <code>0.0.0.0<\/code> \u4ee5\u5141\u8bb8\u4ece\u4efb\u4f55 IP \u5730\u5740\u8bbf\u95ee\u670d\u52a1\u5668\u3002<\/li><li><code>-p 1234<\/code>\uff1a\u6307\u5b9a\u670d\u52a1\u5668\u76d1\u542c\u7684\u7aef\u53e3\u53f7\u3002\u5728\u8fd9\u91cc\uff0c\u6211\u4eec\u4f7f\u7528 <code>1234<\/code> \u7aef\u53e3\u3002<\/li><\/ul>\u542f\u52a8\u670d\u52a1\u5668\u540e\uff0c\u60a8\u5c06\u5728\u63a7\u5236\u53f0\u770b\u5230\u7c7b\u4f3c\u7684\u8f93\u51fa\uff1ayamlCopy code<code>2023\/04\/16 12:34:56 INFO mlflow.models.cli: Selected backend for flavor 'python_function' 2023\/04\/16 12:34:56 INFO mlflow.pyfunc.backend: No conda environment specified. Using current python version. 2023\/04\/16 12:34:56 INFO mlflow.pyfunc.backend: No gunicorn_opts specified, defaulting gunicorn_opts to \"\". 2023\/04\/16 12:34:56 INFO mlflow.models.cli: Starting gunicorn server with command: gunicorn --timeout=60 -k gevent -b 0.0.0.0:1234 -w 1 wsgi:app 2023\/04\/16 12:34:56 [INFO] Starting gunicorn 20.1.0 2023\/04\/16 12:34:56 [INFO] Listening at: http:\/\/0.0.0.0:1234 (1) 2023\/04\/16 12:34:56 [INFO] Using worker: gevent 2023\/04\/16 12:34:56 [INFO] Booting worker with pid: 12345<\/code><\/li>\n\n\n\n<li><strong>\u53d1\u9001\u8bf7\u6c42\u5230 REST API<\/strong>MLflow Model \u670d\u52a1\u5668\u5c06\u5728\u6307\u5b9a\u7684 IP \u5730\u5740\u548c\u7aef\u53e3\u4e0a\u76d1\u542c\u8bf7\u6c42\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0c\u670d\u52a1\u5668\u5c06\u5728 <code>\/invocations<\/code> \u8def\u5f84\u4e0a\u63d0\u4f9b\u9884\u6d4b\u670d\u52a1\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528\u4efb\u4f55 HTTP \u5ba2\u6237\u7aef\u53d1\u9001\u8bf7\u6c42\uff0c\u4f8b\u5982 <code>curl<\/code>\u3001Postman \u6216 Python \u7684 <code>requests<\/code> \u5e93<\/li>\n<\/ol>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u7b49\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 Python <code>requests<\/code> \u5e93\u53d1\u9001\u8bf7\u6c42\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import json\nimport requests\n\n# \u51c6\u5907\u8f93\u5165\u6570\u636e\ninput_data = {\n    \"columns\": [\"feature1\", \"feature2\"],\n    \"data\": [[1.0, 2.0], [3.0, 4.0]]\n}\n\n# \u5c06\u8f93\u5165\u6570\u636e\u8f6c\u6362\u4e3a JSON \u683c\u5f0f\ninput_json = json.dumps(input_data)\n\n# \u53d1\u9001 POST \u8bf7\u6c42\u5230 MLflow Model \u670d\u52a1\u5668\nresponse = requests.post(\"http:\/\/0.0.0.0:1234\/invocations\", data=input_json, headers={\"Content-Type\": \"application\/json\"})\n\n# \u89e3\u6790\u670d\u52a1\u5668\u8fd4\u56de\u7684\u9884\u6d4b\u7ed3\u679c\npredictions = json.loads(response.text)\nprint(predictions)\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u51c6\u5907\u4e86\u8f93\u5165\u6570\u636e\uff0c\u7136\u540e\u5c06\u5176\u8f6c\u6362\u4e3a JSON \u683c\u5f0f\u3002\u63a5\u7740\uff0c\u6211\u4eec\u4f7f\u7528 <code>requests.post()<\/code> \u51fd\u6570\u53d1\u9001 POST \u8bf7\u6c42\u5230 MLflow Model \u670d\u52a1\u5668\u3002\u6700\u540e\uff0c\u6211\u4eec\u89e3\u6790\u670d\u52a1\u5668\u8fd4\u56de\u7684\u9884\u6d4b\u7ed3\u679c\u3002<\/p>\n\n\n\n<p>\u8fd9\u79cd\u90e8\u7f72\u65b9\u5f0f\u4f7f\u5f97 MLflow Model \u80fd\u591f\u4f5c\u4e3a REST API \u63d0\u4f9b\u670d\u52a1\uff0c\u65b9\u4fbf\u60a8\u5728\u5176\u4ed6\u5e94\u7528\u7a0b\u5e8f\u4e2d\u8c03\u7528\u6a21\u578b\u3002\u6b64\u5916\uff0c\u60a8\u8fd8\u53ef\u4ee5\u8003\u8651\u5c06 MLflow Model \u90e8\u7f72\u5230\u4e91\u670d\u52a1\uff08\u5982 AWS Sagemaker\u3001Azure ML \u7b49\uff09\u6216\u5bb9\u5668\uff08\u5982 Docker\u3001Kubernetes \u7b49\uff09\uff0c\u4ee5\u4fbf\u4e8e\u6a21\u578b\u7ba1\u7406\u548c\u6269\u5c55\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u4ecb\u7ecd\u4f7f\u7528 MLflow Model Registry \u7ba1\u7406\u6a21\u578b<\/p>\n\n\n\n<p>MLflow Model Registry \u662f\u4e00\u4e2a\u7528\u4e8e\u7ba1\u7406\u6a21\u578b\u751f\u547d\u5468\u671f\u7684\u96c6\u4e2d\u5f0f\u6a21\u578b\u5b58\u50a8\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u754c\u9762\uff0c\u8ba9\u60a8\u53ef\u4ee5\u8ddf\u8e2a\u6a21\u578b\u7684\u7248\u672c\u3001\u7ba1\u7406\u6a21\u578b\u7684\u9636\u6bb5\uff08\u5982\u5f00\u53d1\u3001\u751f\u4ea7\u7b49\uff09\u4ee5\u53ca\u4e0e\u56e2\u961f\u6210\u5458\u534f\u4f5c\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528 MLflow Model Registry \u7ba1\u7406\u6a21\u578b\u7684\u8be6\u7ec6\u4ecb\u7ecd\uff1a<\/p>\n\n\n\n<p><strong>1. \u6ce8\u518c\u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u8981\u5f00\u59cb\u4f7f\u7528 Model Registry\uff0c\u9996\u5148\u9700\u8981\u5c06\u8bad\u7ec3\u597d\u7684 MLflow Model \u6ce8\u518c\u5230\u5b58\u50a8\u5e93\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5c06\u6a21\u578b\u6ce8\u518c\u5230 Model Registry\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow\n\n# \u6ce8\u518c\u6a21\u578b\nmodel_uri = \"runs:\/&lt;run_id&gt;\/model\"  # \u5c06 &lt;run_id&gt; \u66ff\u6362\u4e3a\u5b9e\u9645\u7684\u8fd0\u884c ID\nregistered_model = mlflow.register_model(model_uri, \"MyModel\")\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u91cc\uff0c<code>model_uri<\/code> \u6307\u5b9a\u4e86\u8981\u6ce8\u518c\u7684\u6a21\u578b\u7684\u4f4d\u7f6e\uff0c\u683c\u5f0f\u4e3a <code>runs:\/&lt;run_id&gt;\/model<\/code>\u3002<code>\"MyModel\"<\/code> \u662f\u6ce8\u518c\u6a21\u578b\u7684\u540d\u79f0\u3002\u6ce8\u518c\u6a21\u578b\u540e\uff0cMLflow \u4f1a\u4e3a\u6a21\u578b\u521b\u5efa\u4e00\u4e2a\u7248\u672c\uff08\u9ed8\u8ba4\u4e3a\u7248\u672c 1\uff09\u3002<\/p>\n\n\n\n<p><strong>2. \u67e5\u770b\u6a21\u578b\u7248\u672c<\/strong><\/p>\n\n\n\n<p>\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u67e5\u770b Model Registry \u4e2d\u67d0\u4e2a\u6a21\u578b\u7684\u6240\u6709\u7248\u672c\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u67e5\u770b\u6a21\u578b\u7248\u672c\nmodel_versions = mlflow.search_model_versions(\"name='MyModel'\")\nfor mv in model_versions:\n    print(\"Version: {}\\nURI: {}\\n\".format(mv.version, mv.source))\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u6253\u5370\u51fa\u6a21\u578b &#8220;MyModel&#8221; \u7684\u6240\u6709\u7248\u672c\u4ee5\u53ca\u5b83\u4eec\u7684\u5b58\u50a8\u4f4d\u7f6e\u3002<\/p>\n\n\n\n<p><strong>3. \u66f4\u65b0\u6a21\u578b\u9636\u6bb5<\/strong><\/p>\n\n\n\n<p>\u6a21\u578b\u9636\u6bb5\u662f\u7528\u4e8e\u6807\u8bc6\u6a21\u578b\u5728\u751f\u547d\u5468\u671f\u4e2d\u7684\u5f53\u524d\u72b6\u6001\u3002\u4f8b\u5982\uff0c\u5f53\u4e00\u4e2a\u6a21\u578b\u5728\u5f00\u53d1\u9636\u6bb5\u65f6\uff0c\u53ef\u4ee5\u5c06\u5176\u9636\u6bb5\u8bbe\u7f6e\u4e3a &#8220;Staging&#8221;\u3002\u5f53\u6a21\u578b\u51c6\u5907\u597d\u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883\u65f6\uff0c\u53ef\u4ee5\u5c06\u5176\u9636\u6bb5\u8bbe\u7f6e\u4e3a &#8220;Production&#8221;\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u66f4\u65b0\u6a21\u578b\u9636\u6bb5\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u5c06\u6a21\u578b\u9636\u6bb5\u8bbe\u7f6e\u4e3a \"Staging\"\nmlflow.set_registered_model_tag(\"MyModel\", \"Staging\")\n\n# \u5c06\u6a21\u578b\u9636\u6bb5\u8bbe\u7f6e\u4e3a \"Production\"\nmlflow.set_registered_model_tag(\"MyModel\", \"Production\")\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528 <code>mlflow.set_registered_model_tag()<\/code> \u51fd\u6570\u5c06\u6a21\u578b &#8220;MyModel&#8221; \u7684\u9636\u6bb5\u5206\u522b\u8bbe\u7f6e\u4e3a &#8220;Staging&#8221; \u548c &#8220;Production&#8221;\u3002<\/p>\n\n\n\n<p><strong>4. \u5220\u9664\u6a21\u578b\u7248\u672c<\/strong><\/p>\n\n\n\n<p>\u5982\u679c\u60a8\u9700\u8981\u5220\u9664\u67d0\u4e2a\u6a21\u578b\u7684\u67d0\u4e2a\u7248\u672c\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u5220\u9664\u6a21\u578b\u7248\u672c\nmlflow.delete_model_version(\"MyModel\", 1)\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u5220\u9664\u6a21\u578b &#8220;MyModel&#8221; \u7684\u7248\u672c 1\u3002<\/p>\n\n\n\n<p><strong>5. \u83b7\u53d6\u751f\u4ea7\u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u5f53\u60a8\u9700\u8981\u83b7\u53d6\u5f53\u524d\u5904\u4e8e &#8220;Production&#8221; \u9636\u6bb5\u7684\u6a21\u578b\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u83b7\u53d6\u751f\u4ea7\u6a21\u578b\nproduction_model_version = mlflow.get_latest_versions(\"MyModel\", stages=[\"Production\"])[0]\nproduction_model_uri = production_model_version.source\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u8fd4\u56de\u6a21\u578b &#8220;MyModel&#8221; \u5f53\u524d\u5904\u4e8e &#8220;Production&#8221; \u9636\u6bb5\u7684\u6700\u65b0\u7248\u672c\u7684\u5b58\u50a8\u4f4d\u7f6e\u3002<\/p>\n\n\n\n<p>\u901a\u8fc7\u4f7f\u7528 MLflow Model<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>Registry\uff0c\u60a8\u53ef\u4ee5\u66f4\u8f7b\u677e\u5730\u7ba1\u7406\u6a21\u578b\u7684\u7248\u672c\u548c\u9636\u6bb5\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u989d\u5916\u7684\u529f\u80fd\uff0c\u53ef\u4ee5\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u7ba1\u7406\u6a21\u578b\uff1a<\/p>\n\n\n\n<p><strong>6. \u6bd4\u8f83\u6a21\u578b\u7248\u672c<\/strong><\/p>\n\n\n\n<p>\u60a8\u53ef\u4ee5\u5728 MLflow UI \u4e2d\u6bd4\u8f83 Model Registry \u4e2d\u4e0d\u540c\u6a21\u578b\u7248\u672c\u7684\u6307\u6807\u3001\u53c2\u6570\u548c\u5de5\u4ef6\u3002\u8fd9\u53ef\u4ee5\u5e2e\u52a9\u60a8\u4e86\u89e3\u6a21\u578b\u6027\u80fd\u7684\u53d8\u5316\uff0c\u5e76\u786e\u5b9a\u54ea\u4e2a\u7248\u672c\u6700\u9002\u5408\u90e8\u7f72\u3002\u8981\u6bd4\u8f83\u6a21\u578b\u7248\u672c\uff0c\u8bf7\u8f6c\u5230 Model Registry \u9875\u9762\uff0c\u9009\u62e9\u8981\u6bd4\u8f83\u7684\u6a21\u578b\u7248\u672c\uff0c\u7136\u540e\u70b9\u51fb &#8220;Compare&#8221; \u6309\u94ae\u3002<\/p>\n\n\n\n<p><strong>7. \u6dfb\u52a0\u63cf\u8ff0\u548c\u6807\u7b7e<\/strong><\/p>\n\n\n\n<p>\u4e3a\u4e86\u4fbf\u4e8e\u56e2\u961f\u6210\u5458\u4e86\u89e3\u6a21\u578b\u7684\u7528\u9014\u548c\u6027\u80fd\uff0c\u60a8\u53ef\u4ee5\u4e3a\u6a21\u578b\u7248\u672c\u6dfb\u52a0\u63cf\u8ff0\u548c\u6807\u7b7e\u3002\u63cf\u8ff0\u53ef\u4ee5\u5305\u62ec\u6a21\u578b\u7684\u8be6\u7ec6\u4fe1\u606f\uff0c\u5982\u7b97\u6cd5\u3001\u7279\u5f81\u9009\u62e9\u548c\u8d85\u53c2\u6570\u8c03\u6574\u7b49\u3002\u6807\u7b7e\u53ef\u4ee5\u7528\u4e8e\u5bf9\u6a21\u578b\u8fdb\u884c\u5206\u7c7b\uff0c\u4f8b\u5982 &#8220;\u56de\u5f52&#8221;\u3001&#8221;\u5206\u7c7b&#8221; \u6216 &#8220;\u63a8\u8350\u7cfb\u7edf&#8221; \u7b49\u3002\u8981\u6dfb\u52a0\u63cf\u8ff0\u548c\u6807\u7b7e\uff0c\u8bf7\u8f6c\u5230\u6a21\u578b\u7248\u672c\u7684\u8be6\u7ec6\u4fe1\u606f\u9875\u9762\uff0c\u7136\u540e\u70b9\u51fb &#8220;Edit&#8221; \u6309\u94ae\u3002<\/p>\n\n\n\n<p><strong>8. \u534f\u4f5c\u4e0e\u6743\u9650\u7ba1\u7406<\/strong><\/p>\n\n\n\n<p>MLflow Model Registry \u652f\u6301\u591a\u7528\u6237\u534f\u4f5c\u3002\u60a8\u53ef\u4ee5\u9080\u8bf7\u56e2\u961f\u6210\u5458\u52a0\u5165\u60a8\u7684 MLflow \u5b9e\u4f8b\uff0c\u5e76\u4e3a\u4ed6\u4eec\u5206\u914d\u89d2\u8272\u548c\u6743\u9650\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u5141\u8bb8\u67d0\u4e9b\u7528\u6237\u67e5\u770b\u6a21\u578b\u3001\u6ce8\u518c\u65b0\u6a21\u578b\u6216\u66f4\u6539\u6a21\u578b\u7684\u9636\u6bb5\u3002\u901a\u8fc7\u4f7f\u7528\u6743\u9650\u7ba1\u7406\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd\u56e2\u961f\u6210\u5458\u53ea\u80fd\u8bbf\u95ee\u548c\u66f4\u6539\u4ed6\u4eec\u9700\u8981\u7684\u6a21\u578b\u3002<\/p>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow Model Registry \u63d0\u4f9b\u4e86\u4e00\u79cd\u96c6\u4e2d\u5f0f\u7684\u65b9\u5f0f\u6765\u7ba1\u7406\u6a21\u578b\u7684\u751f\u547d\u5468\u671f\u3002\u901a\u8fc7\u4f7f\u7528 Model Registry\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u8ddf\u8e2a\u6a21\u578b\u7684\u7248\u672c\u3001\u7ba1\u7406\u6a21\u578b\u7684\u9636\u6bb5\u3001\u4e0e\u56e2\u961f\u6210\u5458\u534f\u4f5c\u4ee5\u53ca\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u60a8\u7684\u6a21\u578b\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u4ecb\u7ecdMLflow Model Registry\u6ce8\u518c\u6a21\u578b\u4e0e\u7248\u672c\u7ba1\u7406<\/p>\n\n\n\n<p>MLflow Model Registry \u662f\u4e00\u4e2a\u96c6\u4e2d\u5f0f\u6a21\u578b\u5b58\u50a8\u5e93\uff0c\u7528\u4e8e\u7ba1\u7406\u6a21\u578b\u53ca\u5176\u7248\u672c\u3002\u5b83\u5141\u8bb8\u60a8\u8ddf\u8e2a\u6a21\u578b\u7684\u7248\u672c\uff0c\u7ba1\u7406\u6a21\u578b\u7684\u9636\u6bb5\uff0c\u4e0e\u56e2\u961f\u6210\u5458\u534f\u4f5c\u5e76\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u6a21\u578b\u3002\u4ee5\u4e0b\u662f\u5173\u4e8e\u5982\u4f55\u4f7f\u7528 MLflow Model Registry \u6ce8\u518c\u6a21\u578b\u548c\u8fdb\u884c\u7248\u672c\u7ba1\u7406\u7684\u8be6\u7ec6\u4ecb\u7ecd\uff1a<\/p>\n\n\n\n<p><strong>\u6ce8\u518c\u6a21\u578b<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>\u5728\u8bad\u7ec3\u6a21\u578b\u5e76\u5c06\u5176\u4fdd\u5b58\u5230 MLflow \u4e2d\u540e\uff0c\u60a8\u9700\u8981\u5c06\u6a21\u578b\u6ce8\u518c\u5230 Model Registry\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u5f0f\u6ce8\u518c\u6a21\u578b\uff1a<\/li>\n<\/ol>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow\n\n# \u6ce8\u518c\u6a21\u578b\nmodel_uri = \"runs:\/&lt;run_id&gt;\/model\"  # \u5c06 &lt;run_id&gt; \u66ff\u6362\u4e3a\u5b9e\u9645\u7684\u8fd0\u884c ID\nregistered_model = mlflow.register_model(model_uri, \"MyModel\")\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u91cc\uff0c<code>model_uri<\/code> \u6307\u5b9a\u4e86\u8981\u6ce8\u518c\u7684\u6a21\u578b\u7684\u4f4d\u7f6e\uff0c\u683c\u5f0f\u4e3a <code>runs:\/&lt;run_id&gt;\/model<\/code>\u3002<code>\"MyModel\"<\/code> \u662f\u6ce8\u518c\u6a21\u578b\u7684\u540d\u79f0\u3002\u6ce8\u518c\u6a21\u578b\u540e\uff0cMLflow \u4f1a\u4e3a\u6a21\u578b\u521b\u5efa\u4e00\u4e2a\u7248\u672c\uff08\u9ed8\u8ba4\u4e3a\u7248\u672c 1\uff09\u3002<\/p>\n\n\n\n<p><strong>\u7248\u672c\u7ba1\u7406<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u67e5\u770b\u6a21\u578b\u7248\u672c<\/strong><\/li>\n<\/ol>\n\n\n\n<p>\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u67e5\u770b Model Registry \u4e2d\u67d0\u4e2a\u6a21\u578b\u7684\u6240\u6709\u7248\u672c\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u67e5\u770b\u6a21\u578b\u7248\u672c\nmodel_versions = mlflow.search_model_versions(\"name='MyModel'\")\nfor mv in model_versions:\n    print(\"Version: {}\\nURI: {}\\n\".format(mv.version, mv.source))\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u6253\u5370\u51fa\u6a21\u578b &#8220;MyModel&#8221; \u7684\u6240\u6709\u7248\u672c\u4ee5\u53ca\u5b83\u4eec\u7684\u5b58\u50a8\u4f4d\u7f6e\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"2\">\n<li><strong>\u521b\u5efa\u65b0\u7248\u672c<\/strong><\/li>\n<\/ol>\n\n\n\n<p>\u5982\u679c\u60a8\u5bf9\u6a21\u578b\u8fdb\u884c\u4e86\u6539\u8fdb\u5e76\u91cd\u65b0\u8bad\u7ec3\uff0c\u53ef\u4ee5\u4f7f\u7528\u76f8\u540c\u7684\u6a21\u578b\u540d\u79f0\u521b\u5efa\u65b0\u7248\u672c\u3002MLflow \u4f1a\u81ea\u52a8\u4e3a\u65b0\u6a21\u578b\u5206\u914d\u4e0b\u4e00\u4e2a\u53ef\u7528\u7684\u7248\u672c\u53f7\u3002\u4ee5\u4e0b\u662f\u521b\u5efa\u65b0\u6a21\u578b\u7248\u672c\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u521b\u5efa\u65b0\u6a21\u578b\u7248\u672c\nnew_model_uri = \"runs:\/&lt;new_run_id&gt;\/model\"  # \u5c06 &lt;new_run_id&gt; \u66ff\u6362\u4e3a\u65b0\u7684\u8fd0\u884c ID\nmlflow.register_model(new_model_uri, \"MyModel\")\n<\/code><\/pre>\n\n\n\n<ol class=\"wp-block-list\" start=\"3\">\n<li><strong>\u5220\u9664\u6a21\u578b\u7248\u672c<\/strong><\/li>\n<\/ol>\n\n\n\n<p>\u5982\u679c\u60a8\u9700\u8981\u5220\u9664\u67d0\u4e2a\u6a21\u578b\u7684\u67d0\u4e2a\u7248\u672c\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u5220\u9664\u6a21\u578b\u7248\u672c\nmlflow.delete_model_version(\"MyModel\", 1)\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u5220\u9664\u6a21\u578b &#8220;MyModel&#8221; \u7684\u7248\u672c 1\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"4\">\n<li><strong>\u6bd4\u8f83\u6a21\u578b\u7248\u672c<\/strong><\/li>\n<\/ol>\n\n\n\n<p>\u5728 MLflow UI \u4e2d\uff0c\u60a8\u53ef\u4ee5\u6bd4\u8f83 Model Registry \u4e2d\u4e0d\u540c\u6a21\u578b\u7248\u672c\u7684\u6307\u6807\u3001\u53c2\u6570\u548c\u5de5\u4ef6\u3002\u8fd9\u6709\u52a9\u4e8e\u4e86\u89e3\u6a21\u578b\u6027\u80fd\u7684\u53d8\u5316\u5e76\u786e\u5b9a\u54ea\u4e2a\u7248\u672c\u6700\u9002\u5408\u90e8\u7f72\u3002\u8981\u6bd4\u8f83\u6a21\u578b\u7248\u672c\uff0c\u8bf7\u8f6c\u5230 Model Registry \u9875\u9762\uff0c\u9009\u62e9\u8981\u6bd4\u8f83\u7684\u6a21\u578b\u7248\u672c\uff0c\u7136\u540e\u70b9\u51fb &#8220;Compare&#8221; \u6309\u94ae\u3002<\/p>\n\n\n\n<p>\u901a\u8fc7\u4f7f\u7528 MLflow Model Registry \u6ce8\u518c\u6a21\u578b\u548c\u8fdb\u884c\u7248\u672c\u7ba1\u7406\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u8ddf\u8e2a\u6a21\u578b\u7684\u6539\u8fdb\u548c\u6027\u80fd\u53d8\u5316\u3002\u8fd9\u6709\u52a9\u4e8e\u786e\u4fdd\u60a8\u59cb\u7ec8\u4f7f\u7528\u6700\u4f73\u6a21\u578b\u7248\u672c\uff0c\u5e76\u5141\u8bb8\u60a8\u968f\u65f6\u56de\u6eda\u5230\u5148\u524d\u7684\u6a21\u578b\u7248\u672c\u3002\u6b64\u5916\uff0cModel Registry \u652f\u6301\u4e0e\u56e2\u961f\u6210\u5458\u534f\u4f5c\uff0c\u4f7f\u5f97\u8de8<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u56e2\u961f\u5171\u4eab\u548c\u7ba1\u7406\u6a21\u578b\u53d8\u5f97\u66f4\u52a0\u65b9\u4fbf\u3002<\/p>\n\n\n\n<p><strong>\u6a21\u578b\u9636\u6bb5\u7ba1\u7406<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u66f4\u65b0\u6a21\u578b\u9636\u6bb5<\/strong><\/li>\n<\/ol>\n\n\n\n<p>\u6a21\u578b\u9636\u6bb5\u7528\u4e8e\u6807\u8bc6\u6a21\u578b\u5728\u751f\u547d\u5468\u671f\u4e2d\u7684\u5f53\u524d\u72b6\u6001\u3002\u4f8b\u5982\uff0c\u5f53\u4e00\u4e2a\u6a21\u578b\u5728\u5f00\u53d1\u9636\u6bb5\u65f6\uff0c\u53ef\u4ee5\u5c06\u5176\u9636\u6bb5\u8bbe\u7f6e\u4e3a &#8220;Staging&#8221;\u3002\u5f53\u6a21\u578b\u51c6\u5907\u597d\u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883\u65f6\uff0c\u53ef\u4ee5\u5c06\u5176\u9636\u6bb5\u8bbe\u7f6e\u4e3a &#8220;Production&#8221;\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u66f4\u65b0\u6a21\u578b\u9636\u6bb5\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u5c06\u6a21\u578b\u9636\u6bb5\u8bbe\u7f6e\u4e3a \"Staging\"\nmlflow.set_registered_model_tag(\"MyModel\", \"Staging\")\n\n# \u5c06\u6a21\u578b\u9636\u6bb5\u8bbe\u7f6e\u4e3a \"Production\"\nmlflow.set_registered_model_tag(\"MyModel\", \"Production\")\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528 <code>mlflow.set_registered_model_tag()<\/code> \u51fd\u6570\u5c06\u6a21\u578b &#8220;MyModel&#8221; \u7684\u9636\u6bb5\u5206\u522b\u8bbe\u7f6e\u4e3a &#8220;Staging&#8221; \u548c &#8220;Production&#8221;\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"2\">\n<li><strong>\u83b7\u53d6\u7279\u5b9a\u9636\u6bb5\u7684\u6a21\u578b<\/strong><\/li>\n<\/ol>\n\n\n\n<p>\u5f53\u60a8\u9700\u8981\u83b7\u53d6\u5904\u4e8e\u7279\u5b9a\u9636\u6bb5\u7684\u6a21\u578b\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code># \u83b7\u53d6\u751f\u4ea7\u6a21\u578b\nproduction_model_version = mlflow.get_latest_versions(\"MyModel\", stages=[\"Production\"])[0]\nproduction_model_uri = production_model_version.source\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u8fd4\u56de\u6a21\u578b &#8220;MyModel&#8221; \u5f53\u524d\u5904\u4e8e &#8220;Production&#8221; \u9636\u6bb5\u7684\u6700\u65b0\u7248\u672c\u7684\u5b58\u50a8\u4f4d\u7f6e\u3002<\/p>\n\n\n\n<p><strong>\u534f\u4f5c\u4e0e\u6743\u9650\u7ba1\u7406<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>MLflow Model Registry \u652f\u6301\u591a\u7528\u6237\u534f\u4f5c\u3002\u60a8\u53ef\u4ee5\u9080\u8bf7\u56e2\u961f\u6210\u5458\u52a0\u5165\u60a8\u7684 MLflow \u5b9e\u4f8b\uff0c\u5e76\u4e3a\u4ed6\u4eec\u5206\u914d\u89d2\u8272\u548c\u6743\u9650\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u5141\u8bb8\u67d0\u4e9b\u7528\u6237\u67e5\u770b\u6a21\u578b\u3001\u6ce8\u518c\u65b0\u6a21\u578b\u6216\u66f4\u6539\u6a21\u578b\u7684\u9636\u6bb5\u3002\u901a\u8fc7\u4f7f\u7528\u6743\u9650\u7ba1\u7406\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd\u56e2\u961f\u6210\u5458\u53ea\u80fd\u8bbf\u95ee\u548c\u66f4\u6539\u4ed6\u4eec\u9700\u8981\u7684\u6a21\u578b\u3002<\/li>\n\n\n\n<li>\u60a8\u8fd8\u53ef\u4ee5\u4e3a\u6a21\u578b\u7248\u672c\u6dfb\u52a0\u63cf\u8ff0\u548c\u6807\u7b7e\uff0c\u4ee5\u4fbf\u4e8e\u56e2\u961f\u6210\u5458\u4e86\u89e3\u6a21\u578b\u7684\u7528\u9014\u548c\u6027\u80fd\u3002\u63cf\u8ff0\u53ef\u4ee5\u5305\u62ec\u6a21\u578b\u7684\u8be6\u7ec6\u4fe1\u606f\uff0c\u5982\u7b97\u6cd5\u3001\u7279\u5f81\u9009\u62e9\u548c\u8d85\u53c2\u6570\u8c03\u6574\u7b49\u3002\u6807\u7b7e\u53ef\u4ee5\u7528\u4e8e\u5bf9\u6a21\u578b\u8fdb\u884c\u5206\u7c7b\uff0c\u4f8b\u5982 &#8220;\u56de\u5f52&#8221;\u3001&#8221;\u5206\u7c7b&#8221; \u6216 &#8220;\u63a8\u8350\u7cfb\u7edf&#8221; \u7b49\u3002\u8981\u6dfb\u52a0\u63cf\u8ff0\u548c\u6807\u7b7e\uff0c\u8bf7\u8f6c\u5230\u6a21\u578b\u7248\u672c\u7684\u8be6\u7ec6\u4fe1\u606f\u9875\u9762\uff0c\u7136\u540e\u70b9\u51fb &#8220;Edit&#8221; \u6309\u94ae\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow Model Registry \u63d0\u4f9b\u4e86\u4e00\u79cd\u96c6\u4e2d\u5f0f\u7684\u65b9\u5f0f\u6765\u7ba1\u7406\u6a21\u578b\u7684\u751f\u547d\u5468\u671f\u3002\u901a\u8fc7\u4f7f\u7528 Model Registry\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u8ddf\u8e2a\u6a21\u578b\u7684\u7248\u672c\u3001\u7ba1\u7406\u6a21\u578b\u7684\u9636\u6bb5\u3001\u4e0e\u56e2\u961f\u6210\u5458\u534f\u4f5c\u4ee5\u53ca\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u60a8\u7684\u6a21\u578b\u3002\u8fd9\u6709\u52a9\u4e8e\u786e\u4fdd\u60a8\u7684\u56e2\u961f\u80fd\u591f\u5171\u4eab\u548c\u7ba1\u7406\u6a21\u578b\uff0c\u4ece\u800c\u63d0\u9ad8\u6574\u4f53\u5de5\u4f5c\u6548\u7387\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u4ecb\u7ecdMLflow Model Registry\u6a21\u578b\u751f\u547d\u5468\u671f\u7ba1\u7406\u4e0e\u534f\u4f5c<\/p>\n\n\n\n<p>MLflow Model Registry \u63d0\u4f9b\u4e86\u4e00\u79cd\u96c6\u4e2d\u5f0f\u7684\u65b9\u5f0f\u6765\u7ba1\u7406\u6a21\u578b\u7684\u751f\u547d\u5468\u671f\uff0c\u5305\u62ec\u8ddf\u8e2a\u6a21\u578b\u7684\u7248\u672c\u3001\u7ba1\u7406\u6a21\u578b\u7684\u9636\u6bb5\u4ee5\u53ca\u4e0e\u56e2\u961f\u6210\u5458\u534f\u4f5c\u3002\u4ee5\u4e0b\u662f\u5173\u4e8e MLflow Model Registry \u6a21\u578b\u751f\u547d\u5468\u671f\u7ba1\u7406\u548c\u534f\u4f5c\u7684\u8be6\u7ec6\u4ecb\u7ecd\uff1a<\/p>\n\n\n\n<p><strong>\u6a21\u578b\u751f\u547d\u5468\u671f\u7ba1\u7406<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u6a21\u578b\u7248\u672c<\/strong>\uff1aModel Registry \u4f1a\u81ea\u52a8\u4e3a\u60a8\u7684\u6bcf\u4e2a\u6a21\u578b\u5206\u914d\u4e00\u4e2a\u7248\u672c\u53f7\uff0c\u4f7f\u60a8\u80fd\u591f\u8f7b\u677e\u8ddf\u8e2a\u6a21\u578b\u7684\u53d8\u5316\u3002\u60a8\u53ef\u4ee5\u521b\u5efa\u65b0\u7248\u672c\uff0c\u5220\u9664\u4e0d\u518d\u9700\u8981\u7684\u7248\u672c\uff0c\u6216\u8005\u6bd4\u8f83\u4e0d\u540c\u7248\u672c\u7684\u6027\u80fd\u3002<\/li>\n\n\n\n<li><strong>\u6a21\u578b\u9636\u6bb5<\/strong>\uff1a\u60a8\u53ef\u4ee5\u4e3a\u6a21\u578b\u5206\u914d\u9636\u6bb5\u6807\u7b7e\uff0c\u5982 &#8220;Development&#8221;\u3001&#8221;Staging&#8221; \u6216 &#8220;Production&#8221;\uff0c\u4ee5\u8868\u793a\u6a21\u578b\u5728\u751f\u547d\u5468\u671f\u4e2d\u7684\u5f53\u524d\u72b6\u6001\u3002\u8fd9\u6709\u52a9\u4e8e\u60a8\u4e86\u89e3\u54ea\u4e9b\u6a21\u578b\u5df2\u51c6\u5907\u597d\u90e8\u7f72\uff0c\u54ea\u4e9b\u6a21\u578b\u4ecd\u5728\u5f00\u53d1\u6216\u6d4b\u8bd5\u9636\u6bb5\u3002<\/li>\n<\/ol>\n\n\n\n<p><strong>\u56e2\u961f\u534f\u4f5c<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u591a\u7528\u6237\u652f\u6301<\/strong>\uff1aMLflow Model Registry \u652f\u6301\u591a\u7528\u6237\u534f\u4f5c\u3002\u60a8\u53ef\u4ee5\u9080\u8bf7\u56e2\u961f\u6210\u5458\u52a0\u5165\u60a8\u7684 MLflow \u5b9e\u4f8b\uff0c\u5e76\u4e3a\u4ed6\u4eec\u5206\u914d\u89d2\u8272\u548c\u6743\u9650\u3002\u8fd9\u4f7f\u5f97\u56e2\u961f\u6210\u5458\u80fd\u591f\u5171\u4eab\u6a21\u578b\u3001\u67e5\u770b\u6a21\u578b\u7684\u6027\u80fd\u4ee5\u53ca\u8ddf\u8e2a\u6a21\u578b\u7684\u53d8\u5316\u3002<\/li>\n\n\n\n<li><strong>\u6743\u9650\u7ba1\u7406<\/strong>\uff1a\u60a8\u53ef\u4ee5\u4e3a\u56e2\u961f\u6210\u5458\u5206\u914d\u4e0d\u540c\u7684\u6743\u9650\uff0c\u4f8b\u5982\u67e5\u770b\u6a21\u578b\u3001\u6ce8\u518c\u65b0\u6a21\u578b\u6216\u66f4\u6539\u6a21\u578b\u7684\u9636\u6bb5\u3002\u901a\u8fc7\u4f7f\u7528\u6743\u9650\u7ba1\u7406\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd\u56e2\u961f\u6210\u5458\u53ea\u80fd\u8bbf\u95ee\u548c\u66f4\u6539\u4ed6\u4eec\u9700\u8981\u7684\u6a21\u578b\uff0c\u4ece\u800c\u4fdd\u62a4\u6a21\u578b\u7684\u5b89\u5168\u548c\u5b8c\u6574\u6027\u3002<\/li>\n\n\n\n<li><strong>\u63cf\u8ff0\u548c\u6807\u7b7e<\/strong>\uff1a\u4e3a\u4e86\u4fbf\u4e8e\u56e2\u961f\u6210\u5458\u4e86\u89e3\u6a21\u578b\u7684\u7528\u9014\u548c\u6027\u80fd\uff0c\u60a8\u53ef\u4ee5\u4e3a\u6a21\u578b\u7248\u672c\u6dfb\u52a0\u63cf\u8ff0\u548c\u6807\u7b7e\u3002\u63cf\u8ff0\u53ef\u4ee5\u5305\u62ec\u6a21\u578b\u7684\u8be6\u7ec6\u4fe1\u606f\uff0c\u5982\u7b97\u6cd5\u3001\u7279\u5f81\u9009\u62e9\u548c\u8d85\u53c2\u6570\u8c03\u6574\u7b49\u3002\u6807\u7b7e\u53ef\u4ee5\u7528\u4e8e\u5bf9\u6a21\u578b\u8fdb\u884c\u5206\u7c7b\uff0c\u4f8b\u5982 &#8220;\u56de\u5f52&#8221;\u3001&#8221;\u5206\u7c7b&#8221; \u6216 &#8220;\u63a8\u8350\u7cfb\u7edf&#8221; \u7b49\u3002\u8fd9\u6709\u52a9\u4e8e\u63d0\u9ad8\u56e2\u961f\u6210\u5458\u4e4b\u95f4\u7684\u6c9f\u901a\u6548\u7387\uff0c\u4f7f\u4ed6\u4eec\u80fd\u591f\u5feb\u901f\u4e86\u89e3\u6a21\u578b\u7684\u5173\u952e\u4fe1\u606f\u3002<\/li>\n\n\n\n<li><strong>\u6bd4\u8f83\u6a21\u578b\u6027\u80fd<\/strong>\uff1aMLflow Model Registry \u4f7f\u60a8\u80fd\u591f\u6bd4\u8f83\u4e0d\u540c\u6a21\u578b\u7248\u672c\u7684\u6027\u80fd\uff0c\u5305\u62ec\u6307\u6807\u3001\u53c2\u6570\u548c\u5de5\u4ef6\u3002\u8fd9\u6709\u52a9\u4e8e\u60a8\u4e86\u89e3\u6a21\u578b\u6027\u80fd\u7684\u53d8\u5316\uff0c\u5e76\u786e\u5b9a\u54ea\u4e2a\u7248\u672c\u6700\u9002\u5408\u90e8\u7f72\u3002\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u5728 MLflow UI \u4e2d\u8f7b\u677e\u8fdb\u884c\u6a21\u578b\u6027\u80fd\u6bd4\u8f83\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow Model Registry \u63d0\u4f9b\u4e86\u4e00\u79cd\u96c6\u4e2d\u5f0f\u7684\u65b9\u5f0f\u6765\u7ba1\u7406\u6a21\u578b\u7684\u751f\u547d\u5468\u671f\u548c\u534f\u4f5c\u3002\u901a\u8fc7\u4f7f\u7528 Model Registry\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u8ddf\u8e2a\u6a21\u578b\u7684\u7248\u672c\u3001\u7ba1\u7406\u6a21\u578b\u7684\u9636\u6bb5\u3001\u4e0e\u56e2\u961f\u6210\u5458\u534f\u4f5c\u4ee5\u53ca\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u60a8\u7684\u6a21\u578b\u3002\u8fd9\u6709\u52a9\u4e8e\u786e\u4fdd\u60a8\u7684\u56e2\u961f\u80fd\u591f\u5171\u4eab\u548c<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u7ba1\u7406\u6a21\u578b\uff0c\u4ece\u800c\u63d0\u9ad8\u6574\u4f53\u5de5\u4f5c\u6548\u7387\u548c\u534f\u4f5c\u3002<\/p>\n\n\n\n<p><strong>\u6a21\u578b\u5ba1\u6279\u6d41\u7a0b<\/strong><\/p>\n\n\n\n<p>\u5728\u6a21\u578b\u5f00\u53d1\u8fc7\u7a0b\u4e2d\uff0c\u60a8\u53ef\u80fd\u9700\u8981\u9075\u5faa\u7279\u5b9a\u7684\u6a21\u578b\u5ba1\u6279\u6d41\u7a0b\u3002\u8fd9\u53ef\u4ee5\u786e\u4fdd\u56e2\u961f\u6210\u5458\u5728\u6a21\u578b\u90e8\u7f72\u4e4b\u524d\u5bf9\u5176\u8fdb\u884c\u5145\u5206\u7684\u5ba1\u67e5\u548c\u9a8c\u8bc1\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u53ef\u80fd\u7684\u6a21\u578b\u5ba1\u6279\u6d41\u7a0b\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u5f00\u53d1\u9636\u6bb5<\/strong>\uff1a\u6a21\u578b\u5f00\u53d1\u4eba\u5458\u8bad\u7ec3\u6a21\u578b\u5e76\u5c06\u5176\u4fdd\u5b58\u5230 MLflow\u3002\u63a5\u7740\uff0c\u4ed6\u4eec\u5c06\u6a21\u578b\u6ce8\u518c\u5230 Model Registry\uff0c\u5e76\u5c06\u6a21\u578b\u9636\u6bb5\u8bbe\u7f6e\u4e3a &#8220;Development&#8221;\u3002<\/li>\n\n\n\n<li><strong>\u8bc4\u5ba1\u9636\u6bb5<\/strong>\uff1a\u5f53\u6a21\u578b\u5f00\u53d1\u5b8c\u6210\u540e\uff0c\u5176\u4ed6\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u5bf9\u5176\u8fdb\u884c\u8bc4\u5ba1\u3002\u8bc4\u5ba1\u8005\u53ef\u4ee5\u67e5\u770b\u6a21\u578b\u7684\u6307\u6807\u3001\u53c2\u6570\u548c\u5de5\u4ef6\uff0c\u5e76\u4e0e\u5f00\u53d1\u4eba\u5458\u8ba8\u8bba\u6a21\u578b\u7684\u6027\u80fd\u548c\u6f5c\u5728\u6539\u8fdb\u3002\u5728\u6b64\u9636\u6bb5\uff0c\u8bc4\u5ba1\u4eba\u5458\u53ef\u4ee5\u51b3\u5b9a\u662f\u5426\u9700\u8981\u4fee\u6539\u6a21\u578b\u6216\u7ee7\u7eed\u8fdb\u884c\u6d4b\u8bd5\u3002<\/li>\n\n\n\n<li><strong>\u6d4b\u8bd5\u9636\u6bb5<\/strong>\uff1a\u5f53\u6a21\u578b\u901a\u8fc7\u8bc4\u5ba1\u540e\uff0c\u53ef\u4ee5\u5c06\u5176\u9636\u6bb5\u8bbe\u7f6e\u4e3a &#8220;Staging&#8221;\u3002\u5728\u8fd9\u4e2a\u9636\u6bb5\uff0c\u6a21\u578b\u5c06\u5728\u6d4b\u8bd5\u73af\u5883\u4e2d\u90e8\u7f72\u5e76\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u9a8c\u8bc1\u3002\u56e2\u961f\u6210\u5458\u53ef\u4ee5\u5728\u6b64\u9636\u6bb5\u786e\u5b9a\u6a21\u578b\u662f\u5426\u7b26\u5408\u9884\u671f\u7684\u6027\u80fd\u6307\u6807\u3002<\/li>\n\n\n\n<li><strong>\u751f\u4ea7\u9636\u6bb5<\/strong>\uff1a\u5f53\u6a21\u578b\u901a\u8fc7\u6d4b\u8bd5\u5e76\u88ab\u8ba4\u4e3a\u9002\u5408\u90e8\u7f72\u65f6\uff0c\u53ef\u4ee5\u5c06\u5176\u9636\u6bb5\u8bbe\u7f6e\u4e3a &#8220;Production&#8221;\u3002\u5728\u8fd9\u4e2a\u9636\u6bb5\uff0c\u6a21\u578b\u5c06\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72\u5e76\u5f00\u59cb\u4e3a\u5b9e\u9645\u7528\u6237\u63d0\u4f9b\u670d\u52a1\u3002<\/li>\n\n\n\n<li><strong>\u6301\u7eed\u76d1\u63a7\u4e0e\u7ef4\u62a4<\/strong>\uff1a\u5728\u751f\u4ea7\u9636\u6bb5\uff0c\u56e2\u961f\u6210\u5458\u9700\u8981\u6301\u7eed\u76d1\u63a7\u6a21\u578b\u7684\u6027\u80fd\uff0c\u786e\u4fdd\u5176\u59cb\u7ec8\u6ee1\u8db3\u9884\u671f\u7684\u6027\u80fd\u6307\u6807\u3002\u5982\u679c\u53d1\u73b0\u6027\u80fd\u4e0b\u964d\u6216\u5176\u4ed6\u95ee\u9898\uff0c\u53ef\u4ee5\u8fd4\u56de\u5230\u5f00\u53d1\u9636\u6bb5\u5bf9\u6a21\u578b\u8fdb\u884c\u4f18\u5316\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u901a\u8fc7\u9075\u5faa\u8fd9\u4e2a\u6a21\u578b\u5ba1\u6279\u6d41\u7a0b\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd\u6a21\u578b\u5728\u90e8\u7f72\u4e4b\u524d\u7ecf\u8fc7\u5145\u5206\u7684\u5ba1\u67e5\u548c\u9a8c\u8bc1\u3002\u6b64\u5916\uff0c\u8fd9\u4e5f\u6709\u52a9\u4e8e\u63d0\u9ad8\u56e2\u961f\u534f\u4f5c\uff0c\u4f7f\u56e2\u961f\u6210\u5458\u80fd\u591f\u5728\u6574\u4e2a\u6a21\u578b\u751f\u547d\u5468\u671f\u4e2d\u5171\u4eab\u77e5\u8bc6\u548c\u7ecf\u9a8c\u3002<\/p>\n\n\n\n<p>MLflow Model Registry \u529f\u80fd\u5f3a\u5927\uff0c\u53ef\u4ee5\u5e2e\u52a9\u60a8\u548c\u60a8\u7684\u56e2\u961f\u66f4\u9ad8\u6548\u5730\u7ba1\u7406\u6a21\u578b\u7684\u751f\u547d\u5468\u671f\u548c\u534f\u4f5c\u3002\u65e0\u8bba\u60a8\u662f\u5355\u72ec\u5f00\u53d1\u4eba\u5458\u8fd8\u662f\u591a\u4eba\u56e2\u961f\uff0cMLflow Model Registry \u90fd\u662f\u4e00\u4e2a\u6709\u4ef7\u503c\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u8ddf\u8e2a\u6a21\u578b\u7684\u53d8\u5316\u3001\u4e0e\u540c\u4e8b\u5171\u4eab\u77e5\u8bc6\u5e76\u786e\u4fdd\u60a8\u59cb\u7ec8\u90e8\u7f72\u6700\u4f73\u6a21\u578b\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u96c6\u6210 MLflow \u4e0e TensorFlow, PyTorch \u7b49\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6<\/p>\n\n\n\n<p>MLflow \u53ef\u4ee5\u4e0e\u5404\u79cd\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff08\u5982 TensorFlow \u548c PyTorch\uff09\u96c6\u6210\uff0c\u4f7f\u60a8\u80fd\u591f\u8f7b\u677e\u8bb0\u5f55\u548c\u7ba1\u7406\u6df1\u5ea6\u5b66\u4e60\u5b9e\u9a8c\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u5c06 MLflow \u4e0e TensorFlow \u548c PyTorch \u96c6\u6210\u7684\u8be6\u7ec6\u8bf4\u660e\uff1a<\/p>\n\n\n\n<p><strong>1. \u96c6\u6210 TensorFlow<\/strong><\/p>\n\n\n\n<p>\u8981\u5c06 MLflow \u4e0e TensorFlow \u96c6\u6210\uff0c\u60a8\u9700\u8981\u5b89\u88c5 TensorFlow \u548c MLflow \u7684 TensorFlow \u6a21\u5757\u3002\u9996\u5148\uff0c\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5 TensorFlow\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">Copy code<code>pip install tensorflow\n<\/code><\/pre>\n\n\n\n<p>\u7136\u540e\uff0c\u5b89\u88c5 MLflow \u7684 TensorFlow \u6a21\u5757\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">cssCopy code<code>pip install mlflow[tensorflow]\n<\/code><\/pre>\n\n\n\n<p>\u73b0\u5728\uff0c\u60a8\u53ef\u4ee5\u5728 TensorFlow \u4ee3\u7801\u4e2d\u4f7f\u7528 MLflow \u8bb0\u5f55\u5b9e\u9a8c\u7ed3\u679c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import tensorflow as tf\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Dense\nimport mlflow\nimport mlflow.tensorflow\n\n# \u5f00\u542f MLflow \u81ea\u52a8\u8bb0\u5f55\nmlflow.tensorflow.autolog()\n\n# \u51c6\u5907\u6570\u636e\n(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()\nx_train, x_test = x_train \/ 255.0, x_test \/ 255.0\n\n# \u6784\u5efa\u6a21\u578b\nmodel = Sequential([\n    tf.keras.layers.Flatten(input_shape=(28, 28)),\n    Dense(128, activation='relu'),\n    Dense(10, activation='softmax')\n])\n\n# \u7f16\u8bd1\u6a21\u578b\nmodel.compile(optimizer='adam',\n              loss='sparse_categorical_crossentropy',\n              metrics=['accuracy'])\n\n# \u8bad\u7ec3\u6a21\u578b\nmodel.fit(x_train, y_train, epochs=5)\n<\/code><\/pre>\n\n\n\n<p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528 <code>mlflow.tensorflow.autolog()<\/code> \u5f00\u542f\u4e86 MLflow \u7684\u81ea\u52a8\u8bb0\u5f55\u529f\u80fd\u3002\u7136\u540e\uff0c\u6211\u4eec\u6784\u5efa\u548c\u8bad\u7ec3\u4e86\u4e00\u4e2a\u7b80\u5355\u7684 TensorFlow \u6a21\u578b\u3002MLflow \u4f1a\u81ea\u52a8\u8bb0\u5f55\u5b9e\u9a8c\u7684\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u3002<\/p>\n\n\n\n<p><strong>2. \u96c6\u6210 PyTorch<\/strong><\/p>\n\n\n\n<p>\u8981\u5c06 MLflow \u4e0e PyTorch \u96c6\u6210\uff0c\u60a8\u9700\u8981\u5b89\u88c5 PyTorch \u548c MLflow \u7684 PyTorch \u6a21\u5757\u3002\u9996\u5148\uff0c\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5 PyTorch\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">Copy code<code>pip install torch torchvision\n<\/code><\/pre>\n\n\n\n<p>\u7136\u540e\uff0c\u5b89\u88c5 MLflow \u7684 PyTorch \u6a21\u5757\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">cssCopy code<code>pip install mlflow[pytorch]\n<\/code><\/pre>\n\n\n\n<p>\u63a5\u4e0b\u6765\uff0c\u60a8\u53ef\u4ee5\u5728 PyTorch \u4ee3\u7801\u4e2d\u4f7f\u7528 MLflow \u8bb0\u5f55\u5b9e\u9a8c\u7ed3\u679c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport torchvision\nimport torchvision.transforms as transforms\nimport mlflow\nimport mlflow.pytorch\n\n# \u51c6\u5907\u6570\u636e\ntransform = transforms.Compose([\n    transforms.ToTensor(),\n    transforms.Normalize((0.5,), (0.5,))\n])\n\ntrainset = torchvision.datasets.MNIST(root='.\/data', train=True, download=True, transform=transform)\ntrainloader = torch.utils.data.DataLoader(trainset, batch_size=100, shuffle=True)\n\n# \u6784\u5efa\u6a21\u578b\nclass Net(nn.Module):\n    def __init__(self):\n        super(Net, self).__init__()\n        self.fc1 = nn.Linear(28 * 28, 128)\n        self.fc2 = nn.Linear(128, 10)\n\n    def forward(self, x):\n        x = x.view(-1, 28 * 28)\n        x = torch.relu(self.fc1(x))\n       \n<\/code><\/pre>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">kotlinCopy code<code>    x = self.fc2(x)\n    return x\n<\/code><\/pre>\n\n\n\n<p>model = Net()<\/p>\n\n\n\n<h1 class=\"wp-block-heading\">\u5b9a\u4e49\u635f\u5931\u51fd\u6570\u548c\u4f18\u5316\u5668<\/h1>\n\n\n\n<p>criterion = nn.CrossEntropyLoss() optimizer = optim.Adam(model.parameters(), lr=0.001)<\/p>\n\n\n\n<h1 class=\"wp-block-heading\">\u8bad\u7ec3\u6a21\u578b<\/h1>\n\n\n\n<p>with mlflow.start_run(): for epoch in range(5): # 5\u4e2aepoch running_loss = 0.0 for i, data in enumerate(trainloader, 0): inputs, labels = data<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">scssCopy code<code>        optimizer.zero_grad()\n\n        outputs = model(inputs)\n        loss = criterion(outputs, labels)\n        loss.backward()\n        optimizer.step()\n\n        running_loss += loss.item()\n\n    # \u8ba1\u7b97\u5e76\u8bb0\u5f55\u6bcf\u4e2aepoch\u7684\u5e73\u5747\u635f\u5931\n    avg_loss = running_loss \/ (i + 1)\n    mlflow.log_metric(\"loss\", avg_loss, step=epoch)\n    print(f\"Epoch: {epoch + 1}, Loss: {avg_loss:.4f}\")\n\n# \u4fdd\u5b58 PyTorch \u6a21\u578b\nmlflow.pytorch.log_model(model, \"model\")\n<\/code><\/pre>\n\n\n\n<pre class=\"wp-block-preformatted\">goCopy code<code>\n\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528 `mlflow.start_run()` \u521b\u5efa\u4e86\u4e00\u4e2a\u65b0\u7684 MLflow \u8fd0\u884c\uff0c\u5e76\u5728\u8bad\u7ec3\u5faa\u73af\u5185\u90e8\u8bb0\u5f55\u4e86\u6bcf\u4e2a epoch \u7684\u635f\u5931\u3002\u5728\u8bad\u7ec3\u7ed3\u675f\u540e\uff0c\u6211\u4eec\u4f7f\u7528 `mlflow.pytorch.log_model()` \u5c06\u8bad\u7ec3\u597d\u7684 PyTorch \u6a21\u578b\u4fdd\u5b58\u5230 MLflow\u3002\n\n\u901a\u8fc7\u4ee5\u4e0a\u7684\u793a\u4f8b\uff0c\u60a8\u53ef\u4ee5\u4e86\u89e3\u5982\u4f55\u5c06 MLflow \u4e0e TensorFlow \u548c PyTorch \u96c6\u6210\u3002\u65e0\u8bba\u60a8\u4f7f\u7528\u54ea\u79cd\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0cMLflow \u90fd\u53ef\u4ee5\u5e2e\u52a9\u60a8\u8f7b\u677e\u8bb0\u5f55\u548c\u7ba1\u7406\u5b9e\u9a8c\u6570\u636e\uff0c\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002\n<\/code><\/pre>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u5728\u4e0a\u8ff0\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u5c55\u793a\u4e86\u5982\u4f55\u5c06 MLflow \u4e0e TensorFlow \u548c PyTorch \u96c6\u6210\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8ba8\u8bba\u5982\u4f55\u5229\u7528 MLflow \u7684\u5176\u4ed6\u7279\u6027\u6765\u63d0\u9ad8\u6df1\u5ea6\u5b66\u4e60\u9879\u76ee\u7684\u7ba1\u7406\u6548\u7387\u3002<\/p>\n\n\n\n<p><strong>1. \u7528 MLflow \u9879\u76ee\u7ba1\u7406\u6df1\u5ea6\u5b66\u4e60\u5b9e\u9a8c<\/strong><\/p>\n\n\n\n<p>\u4e0e TensorFlow \u548c PyTorch \u96c6\u6210\u540e\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow \u9879\u76ee\u6765\u7ba1\u7406\u6df1\u5ea6\u5b66\u4e60\u5b9e\u9a8c\u3002MLflow \u9879\u76ee\u662f\u4e00\u79cd\u7ec4\u7ec7\u548c\u8fd0\u884c\u4ee3\u7801\u7684\u6807\u51c6\u65b9\u6cd5\u3002\u901a\u8fc7\u4f7f\u7528 MLflow \u9879\u76ee\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd\u6240\u6709\u56e2\u961f\u6210\u5458\u4f7f\u7528\u76f8\u540c\u7684\u4f9d\u8d56\u9879\u3001\u53c2\u6570\u548c\u4ee3\u7801\u7ed3\u6784\uff0c\u4ece\u800c\u7b80\u5316\u5b9e\u9a8c\u7684\u590d\u73b0\u548c\u5171\u4eab\u3002<\/p>\n\n\n\n<p>\u521b\u5efa\u4e00\u4e2a MLflow \u9879\u76ee\u5f88\u7b80\u5355\u3002\u53ea\u9700\u5728\u9879\u76ee\u6839\u76ee\u5f55\u4e0b\u521b\u5efa\u4e00\u4e2a\u540d\u4e3a <code>MLproject<\/code> \u7684\u6587\u4ef6\uff0c\u5176\u4e2d\u5305\u542b\u9879\u76ee\u7684\u540d\u79f0\u3001\u73af\u5883\u914d\u7f6e\u548c\u5165\u53e3\u70b9\u3002\u4f8b\u5982\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">yamlCopy code<code>name: my-deep-learning-project\n\nconda_env: conda.yaml\n\nentry_points:\n  main:\n    parameters:\n      epochs: int\n      batch_size: int\n    command: \"python train.py --epochs {epochs} --batch_size {batch_size}\"\n<\/code><\/pre>\n\n\n\n<p>\u63a5\u4e0b\u6765\uff0c\u60a8\u53ef\u4ee5\u5c06\u6df1\u5ea6\u5b66\u4e60\u5b9e\u9a8c\u7684\u4ee3\u7801\u548c\u6570\u636e\u5b58\u50a8\u5728\u9879\u76ee\u6587\u4ef6\u5939\u4e2d\uff0c\u5e76\u4f7f\u7528 <code>mlflow run<\/code> \u547d\u4ee4\u8fd0\u884c\u9879\u76ee\u3002\u4f8b\u5982\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">cssCopy code<code>mlflow run . -P epochs=5 -P batch_size=100\n<\/code><\/pre>\n\n\n\n<p><strong>2. \u4f7f\u7528 MLflow Model Registry \u7ba1\u7406\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b<\/strong><\/p>\n\n\n\n<p>\u4e0e TensorFlow \u548c PyTorch \u96c6\u6210\u540e\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528 MLflow Model Registry \u6765\u7ba1\u7406\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3002MLflow Model Registry \u63d0\u4f9b\u4e86\u4e00\u4e2a\u4e2d\u5fc3\u5316\u7684\u4f4d\u7f6e\u6765\u5b58\u50a8\u3001\u7248\u672c\u63a7\u5236\u548c\u7ba1\u7406\u6a21\u578b\u3002\u901a\u8fc7\u4f7f\u7528 Model Registry\uff0c\u60a8\u53ef\u4ee5\u66f4\u8f7b\u677e\u5730\u8ddf\u8e2a\u6a21\u578b\u7684\u5386\u53f2\u8bb0\u5f55\u3001\u90e8\u7f72\u65b0\u7248\u672c\u7684\u6a21\u578b\u5e76\u534f\u4f5c\u3002<\/p>\n\n\n\n<p>\u8981\u5c06\u8bad\u7ec3\u597d\u7684\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u6ce8\u518c\u5230 MLflow Model Registry\uff0c\u53ea\u9700\u4f7f\u7528 <code>mlflow.register_model()<\/code> \u51fd\u6570\u3002\u4f8b\u5982\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>result = mlflow.register_model(\"runs:\/&lt;run_id&gt;\/model\", \"my-deep-learning-model\")\n<\/code><\/pre>\n\n\n\n<p>\u7136\u540e\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow Model Registry \u7684 Web UI \u6216 API \u6765\u67e5\u770b\u3001\u7ba1\u7406\u548c\u90e8\u7f72\u6a21\u578b\u3002<\/p>\n\n\n\n<p>\u603b\u4e4b\uff0cMLflow \u63d0\u4f9b\u4e86\u4e0e TensorFlow \u548c PyTorch \u7b49\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u96c6\u6210\u7684\u529f\u80fd\uff0c\u4f7f\u60a8\u80fd\u591f\u66f4\u8f7b\u677e\u5730\u8bb0\u5f55\u3001\u7ba1\u7406\u548c\u5171\u4eab\u6df1\u5ea6\u5b66\u4e60\u5b9e\u9a8c\u3002\u901a\u8fc7\u4f7f\u7528 MLflow \u9879\u76ee\u548c MLflow Model Registry\uff0c\u60a8\u53ef\u4ee5\u8fdb\u4e00\u6b65\u63d0\u9ad8\u6df1\u5ea6\u5b66\u4e60\u9879\u76ee\u7684\u7ba1\u7406\u6548\u7387\u548c\u534f\u4f5c\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u4f7f\u7528 MLflow \u4e0e Jupyter Notebook<\/p>\n\n\n\n<p>MLflow \u53ef\u4ee5\u4e0e Jupyter Notebook \u65e0\u7f1d\u96c6\u6210\uff0c\u4f7f\u60a8\u80fd\u591f\u5728\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u73af\u5883\u4e2d\u8f7b\u677e\u8bb0\u5f55\u548c\u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u5728 Jupyter Notebook \u4e2d\u4f7f\u7528 MLflow \u7684\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<p><strong>1. \u5b89\u88c5 Jupyter Notebook \u548c MLflow<\/strong><\/p>\n\n\n\n<p>\u786e\u4fdd\u60a8\u5df2\u7ecf\u5b89\u88c5\u4e86 Jupyter Notebook \u548c MLflow\u3002\u5982\u679c\u5c1a\u672a\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">Copy code<code>pip install jupyter\npip install mlflow\n<\/code><\/pre>\n\n\n\n<p><strong>2. \u542f\u52a8 Jupyter Notebook<\/strong><\/p>\n\n\n\n<p>\u5728\u60a8\u7684\u9879\u76ee\u76ee\u5f55\u4e2d\u542f\u52a8 Jupyter Notebook\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">Copy code<code>jupyter notebook\n<\/code><\/pre>\n\n\n\n<p>\u7136\u540e\uff0c\u521b\u5efa\u4e00\u4e2a\u65b0\u7684 Notebook\uff0c\u5e76\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow\nimport mlflow.sklearn\n<\/code><\/pre>\n\n\n\n<p><strong>3. \u4f7f\u7528 MLflow \u8bb0\u5f55\u5b9e\u9a8c\u7ed3\u679c<\/strong><\/p>\n\n\n\n<p>\u5728 Jupyter Notebook \u4e2d\uff0c\u60a8\u53ef\u4ee5\u50cf\u5728\u5e38\u89c4 Python \u811a\u672c\u4e2d\u4e00\u6837\u4f7f\u7528 MLflow\u3002\u4f8b\u5982\uff0c\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528 scikit-learn \u8fdb\u884c\u7b80\u5355\u7ebf\u6027\u56de\u5f52\u7684\u4f8b\u5b50\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import numpy as np\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.metrics import mean_squared_error\n\n# \u51c6\u5907\u6570\u636e\nX = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])\ny = np.dot(X, np.array([1, 2])) + 3\n\n# \u8bad\u7ec3\u6a21\u578b\nmodel = LinearRegression().fit(X, y)\n\n# \u9884\u6d4b\ny_pred = model.predict(X)\n\n# \u8ba1\u7b97\u6027\u80fd\u6307\u6807\nmse = mean_squared_error(y, y_pred)\n\n# \u4f7f\u7528 MLflow \u8bb0\u5f55\u5b9e\u9a8c\u7ed3\u679c\nwith mlflow.start_run():\n    mlflow.log_param(\"model_type\", \"LinearRegression\")\n    mlflow.log_metric(\"mse\", mse)\n    mlflow.sklearn.log_model(model, \"model\")\n<\/code><\/pre>\n\n\n\n<p><strong>4. \u542f\u52a8 MLflow UI<\/strong><\/p>\n\n\n\n<p>\u5728\u547d\u4ee4\u884c\u4e2d\uff0c\u5bfc\u822a\u5230\u60a8\u7684\u9879\u76ee\u76ee\u5f55\u5e76\u542f\u52a8 MLflow UI\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">Copy code<code>mlflow ui\n<\/code><\/pre>\n\n\n\n<p>\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0cMLflow UI \u5c06\u5728\u7aef\u53e3 5000 \u4e0a\u542f\u52a8\u3002\u5728\u6d4f\u89c8\u5668\u4e2d\u6253\u5f00 <code>http:\/\/localhost:5000<\/code> \u4ee5\u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c\u3002<\/p>\n\n\n\n<p><strong>5. \u67e5\u8be2\u5b9e\u9a8c\u7ed3\u679c<\/strong><\/p>\n\n\n\n<p>\u5728 Jupyter Notebook \u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 MLflow API \u67e5\u8be2\u5b9e\u9a8c\u7ed3\u679c\u3002\u4f8b\u5982\uff0c\u4ee5\u4e0b\u662f\u5982\u4f55\u68c0\u7d22\u6700\u4f73\u6a21\u578b\uff08\u57fa\u4e8e MSE\uff09\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">pythonCopy code<code>import mlflow\nimport mlflow.sklearn\n\n# \u67e5\u8be2\u5b9e\u9a8c\u7ed3\u679c\nbest_run = mlflow.search_runs(order_by=[\"metric.mse ASC\"]).iloc[0]\n\n# \u52a0\u8f7d\u6700\u4f73\u6a21\u578b\nbest_model = mlflow.sklearn.load_model(\"runs:\/{}\/model\".format(best_run.run_id))\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c31\u662f\u5728 Jupyter Notebook \u4e2d\u4f7f\u7528 MLflow \u7684\u57fa\u672c\u8fc7\u7a0b\u3002MLflow \u53ef\u4ee5\u8f7b\u677e\u5730\u4e0e Jupyter Notebook \u96c6\u6210\uff0c\u4f7f\u60a8\u80fd\u591f\u5728\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u73af\u5883\u4e2d\u8bb0\u5f55\u5b9e\u9a8c\u7ed3\u679c\u3001\u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c\u5e76\u52a0\u8f7d\u4fdd\u5b58\u7684\u6a21\u578b\u3002\u8fd9\u5c06\u6709\u52a9\u4e8e\u60a8\u66f4\u597d\u5730\u7ec4\u7ec7\u548c\u7ba1\u7406\u5b9e\u9a8c\uff0c\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u4e0e\u4e91\u670d\u52a1\u5546\u96c6\u6210\uff0c\u5982 AWS SageMaker, Azure ML \u7b49<\/p>\n\n\n\n<p>MLflow \u53ef\u4ee5\u4e0e\u5404\u79cd\u4e91\u670d\u52a1\u5546\u96c6\u6210\uff0c\u5982 AWS SageMaker \u548c Azure ML\uff0c\u4ece\u800c\u63d0\u4f9b\u66f4\u5b8c\u6574\u7684\u5de5\u4f5c\u6d41\u7a0b\u548c\u66f4\u5f3a\u5927\u7684\u90e8\u7f72\u9009\u9879\u3002\u5728\u672c\u8282\u4e2d\uff0c\u6211\u4eec\u5c06\u5206\u522b\u4ecb\u7ecd\u5982\u4f55\u5c06 MLflow \u4e0e AWS SageMaker \u548c Azure ML \u96c6\u6210\u3002<\/p>\n\n\n\n<p><strong>1. \u96c6\u6210 AWS SageMaker<\/strong><\/p>\n\n\n\n<p>AWS SageMaker \u662f\u4e00\u4e2a\u5b8c\u5168\u6258\u7ba1\u7684\u673a\u5668\u5b66\u4e60\u670d\u52a1\uff0c\u53ef\u7528\u4e8e\u6784\u5efa\u3001\u8bad\u7ec3\u548c\u90e8\u7f72 ML \u6a21\u578b\u3002\u901a\u8fc7\u5c06 MLflow \u4e0e AWS SageMaker \u96c6\u6210\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06 MLflow \u6a21\u578b\u90e8\u7f72\u5230 SageMaker \u4e0a\u3002\u4ee5\u4e0b\u662f\u5c06 MLflow \u6a21\u578b\u90e8\u7f72\u5230 SageMaker \u7684\u57fa\u672c\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86 <code>mlflow<\/code> \u548c <code>boto3<\/code>\uff08AWS SDK for Python\uff09\uff1aCopy code<code>pip install mlflow pip install boto3<\/code><\/li>\n\n\n\n<li>\u914d\u7f6e AWS \u8bbf\u95ee\u5bc6\u94a5\u3002\u60a8\u9700\u8981\u5728 AWS \u63a7\u5236\u53f0\u4e2d\u521b\u5efa\u4e00\u4e2a IAM \u7528\u6237\u5e76\u6388\u4e88\u9002\u5f53\u7684\u6743\u9650\u3002\u7136\u540e\uff0c\u5c06\u8bbf\u95ee\u5bc6\u94a5\u548c\u79d8\u5bc6\u8bbf\u95ee\u5bc6\u94a5\u8bbe\u7f6e\u4e3a\u73af\u5883\u53d8\u91cf\uff1aarduinoCopy code<code>export AWS_ACCESS_KEY_ID=&lt;your_access_key&gt; export AWS_SECRET_ACCESS_KEY=&lt;your_secret_key&gt;<\/code><\/li>\n\n\n\n<li>\u5728 Python \u811a\u672c\u6216 Jupyter Notebook \u4e2d\uff0c\u4f7f\u7528 <code>mlflow.sagemaker<\/code> \u6a21\u5757\u5c06\u6a21\u578b\u90e8\u7f72\u5230 SageMaker\uff1apythonCopy code<code>import mlflow.sagemaker as mfs # \u6307\u5b9a\u6a21\u578b\u7684 URI\uff08\u4f8b\u5982\uff1as3:\/\/your_bucket\/your_model_path\uff09 model_uri = \"runs:\/&lt;run_id&gt;\/model\" # \u90e8\u7f72\u6a21\u578b mfs.deploy(app_name=\"mlflow-sagemaker-example\", model_uri=model_uri, execution_role_arn=\"arn:aws:iam::&lt;account_id&gt;:role\/service-role\/AmazonSageMaker-ExecutionRole\", region_name=\"us-west-2\", mode=mfs.DeploymentMode.CREATE) <\/code>\u8fd9\u5c06\u5728 SageMaker \u4e0a\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u7ec8\u7aef\u8282\u70b9\u5e76\u90e8\u7f72\u60a8\u7684 MLflow \u6a21\u578b\u3002\u60a8\u53ef\u4ee5\u5728 AWS \u63a7\u5236\u53f0\u7684 SageMaker \u670d\u52a1\u4e2d\u67e5\u770b\u90e8\u7f72\u7684\u6a21\u578b\u548c\u7ec8\u7aef\u8282\u70b9\u3002<\/li>\n\n\n\n<li>\u8981\u8c03\u7528\u90e8\u7f72\u7684\u6a21\u578b\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 <code>boto3<\/code>\uff08AWS SDK for Python\uff09\uff1apythonCopy code<code>import boto3 # \u521b\u5efa SageMaker \u8fd0\u884c\u65f6\u5ba2\u6237\u7aef client = boto3.client(\"sagemaker-runtime\", region_name=\"us-west-2\") # \u51c6\u5907\u8f93\u5165\u6570\u636e input_data = ... # \u6309\u7167\u6a21\u578b\u6240\u9700\u683c\u5f0f\u51c6\u5907\u8f93\u5165\u6570\u636e # \u8c03\u7528\u6a21\u578b response = client.invoke_endpoint(EndpointName=\"mlflow-sagemaker-example\", ContentType=\"application\/json\", Body=input_data) # \u89e3\u6790\u8f93\u51fa\u7ed3\u679c output_data = response[\"Body\"].read().decode(\"utf-8\")<\/code><\/li>\n<\/ul>\n\n\n\n<p><strong>2. \u96c6\u6210 Azure ML<\/strong><\/p>\n\n\n\n<p>Azure ML \u662f\u4e00\u4e2a\u4e91\u4e0a\u7684\u673a\u5668\u5b66\u4e60\u670d\u52a1\uff0c\u63d0\u4f9b\u7528\u4e8e\u6784\u5efa\u3001\u8bad\u7ec3\u548c\u90e8\u7f72 ML \u6a21\u578b\u7684\u5de5\u5177\u548c\u670d\u52a1\u3002\u901a\u8fc7\u5c06 MLflow \u4e0e Azure ML \u96c6\u6210\uff0c\u60a8<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u53ef\u4ee5\u5728 Azure ML \u5de5\u4f5c\u533a\u4e2d\u8f7b\u677e\u7ba1\u7406\u548c\u90e8\u7f72 MLflow \u6a21\u578b\u3002\u4ee5\u4e0b\u662f\u5c06 MLflow \u6a21\u578b\u96c6\u6210\u5230 Azure ML \u7684\u57fa\u672c\u6b65\u9aa4\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86 <code>mlflow<\/code> \u548c <code>azureml-sdk<\/code>\uff1aCopy code<code>pip install mlflow pip install azureml-sdk<\/code><\/li>\n\n\n\n<li>\u5728 Azure \u95e8\u6237\u4e2d\u521b\u5efa\u4e00\u4e2a Azure ML \u5de5\u4f5c\u533a\u5e76\u83b7\u53d6\u8ba2\u9605 ID\u3001\u8d44\u6e90\u7ec4\u548c\u5de5\u4f5c\u533a\u540d\u79f0\u3002<\/li>\n\n\n\n<li>\u5728 Python \u811a\u672c\u6216 Jupyter Notebook \u4e2d\uff0c\u4f7f\u7528 <code>azureml.core<\/code> \u6a21\u5757\u8fde\u63a5\u5230 Azure ML \u5de5\u4f5c\u533a\uff1apythonCopy code<code>from azureml.core import Workspace subscription_id = \"&lt;your_subscription_id&gt;\" resource_group = \"&lt;your_resource_group&gt;\" workspace_name = \"&lt;your_workspace_name&gt;\" ws = Workspace.get(name=workspace_name, subscription_id=subscription_id, resource_group=resource_group)<\/code><\/li>\n\n\n\n<li>\u4f7f\u7528 <code>mlflow.azureml<\/code> \u6a21\u5757\u5c06 MLflow \u6a21\u578b\u6ce8\u518c\u5230 Azure ML\uff1apythonCopy code<code>import mlflow.azureml model_uri = \"runs:\/&lt;run_id&gt;\/model\" model_name = \"my_mlflow_model\" registered_model = mlflow.azureml.register_model(ws, model_name=model_name, model_uri=model_uri, description=\"MLflow model example\") <\/code>\u8fd9\u5c06\u5728 Azure ML \u5de5\u4f5c\u533a\u4e2d\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u6ce8\u518c\u6a21\u578b\u3002\u60a8\u53ef\u4ee5\u5728 Azure \u95e8\u6237\u7684 Azure ML \u670d\u52a1\u4e2d\u67e5\u770b\u6ce8\u518c\u7684\u6a21\u578b\u3002<\/li>\n\n\n\n<li>\u8981\u5728 Azure Kubernetes Service\uff08AKS\uff09\u6216 Azure Container Instances\uff08ACI\uff09\u4e0a\u90e8\u7f72\u6ce8\u518c\u7684 MLflow \u6a21\u578b\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 <code>azureml.core<\/code> \u548c <code>azureml.mlflow<\/code> \u6a21\u5757\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u90e8\u7f72\u5230 ACI \u7684\u793a\u4f8b\uff1apythonCopy code<code>from azureml.core import Environment from azureml.core.webservice import AciWebservice, Webservice from azureml.core.model import InferenceConfig, Model from azureml.mlflow import get_mlflow import mlflow.azureml # \u521b\u5efa\u63a8\u7406\u73af\u5883 env = get_mlflow(ws, model_name) # \u521b\u5efa\u63a8\u7406\u914d\u7f6e inference_config = InferenceConfig(entry_script=\"score.py\", environment=env) # \u914d\u7f6e\u90e8\u7f72\u76ee\u6807\uff08\u5728\u672c\u4f8b\u4e2d\u4e3a ACI\uff09 deployment_config = AciWebservice.deploy_configuration(cpu_cores=1, memory_gb=1) # \u90e8\u7f72\u6a21\u578b service = Model.deploy(ws, \"my-aci-service\", [registered_model], inference_config, deployment_config) service.wait_for_deployment(show_output=True) <\/code>\u8fd9\u5c06\u5728 Azure ML \u4e2d\u90e8\u7f72\u60a8\u7684 MLflow \u6a21\u578b\u3002\u60a8\u53ef\u4ee5\u5728 Azure \u95e8\u6237\u7684 Azure ML \u670d\u52a1\u4e2d\u67e5\u770b\u90e8\u7f72\u7684\u6a21\u578b\u548c Web \u670d\u52a1\u3002<\/li>\n\n\n\n<li>\u8981\u8c03\u7528\u90e8\u7f72\u7684\u6a21\u578b\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 <code>azureml.core.webservice<\/code> \u6a21\u5757\uff1apythonCopy code<code>import json # \u51c6\u5907\u8f93\u5165\u6570\u636e input_data = ... # \u6309\u7167\u6a21\u578b\u6240\u9700\u683c\u5f0f\u51c6\u5907\u8f93\u5165\u6570\u636e input_json = json.dumps({\"data\": input_data}) # \u8c03\u7528\u6a21\u578b output_json = service.run(input_json) # \u89e3\u6790\u8f93\u51fa\u7ed3\u679c output_data = json.loads(output_json)<\/code><\/li>\n<\/ul>\n\n\n\n<p>\u901a\u8fc7\u5c06 MLflow<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u4e0e AWS SageMaker \u548c Azure ML \u96c6\u6210\uff0c\u60a8\u53ef\u4ee5\u5145\u5206\u5229\u7528\u4e91\u670d\u52a1\u5546\u63d0\u4f9b\u7684\u5f3a\u5927\u529f\u80fd\uff0c\u5982\u81ea\u52a8\u5316\u7684\u6a21\u578b\u90e8\u7f72\u3001\u6269\u5c55\u548c\u7ba1\u7406\u3002\u8fd9\u4f7f\u5f97\u60a8\u80fd\u591f\u5c06\u6ce8\u610f\u529b\u96c6\u4e2d\u5728\u6784\u5efa\u548c\u4f18\u5316\u6a21\u578b\u4e0a\uff0c\u800c\u4e0d\u662f\u5728\u5e95\u5c42\u7684\u57fa\u7840\u8bbe\u65bd\u548c\u90e8\u7f72\u4e0a\u3002<\/p>\n\n\n\n<p>\u6b64\u5916\uff0cMLflow \u4e5f\u53ef\u4ee5\u4e0e\u5176\u4ed6\u4e91\u670d\u52a1\u5546\u96c6\u6210\uff0c\u5982 Google Cloud AI Platform \u7b49\u3002\u60a8\u53ef\u4ee5\u53c2\u8003 MLflow \u6587\u6863\u548c\u4e91\u670d\u52a1\u5546\u7684\u6587\u6863\u4ee5\u83b7\u5f97\u66f4\u591a\u5173\u4e8e\u5982\u4f55\u5c06 MLflow \u96c6\u6210\u5230\u60a8\u6240\u9009\u7684\u4e91\u670d\u52a1\u5546\u7684\u8be6\u7ec6\u4fe1\u606f\u3002<\/p>\n\n\n\n<p>\u603b\u4e4b\uff0c\u96c6\u6210 MLflow \u4e0e\u4e91\u670d\u52a1\u5546\u4f7f\u60a8\u53ef\u4ee5\u66f4\u8f7b\u677e\u5730\u5728\u4e91\u4e0a\u7ba1\u7406\u3001\u90e8\u7f72\u548c\u6269\u5c55\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u8fd9\u79cd\u96c6\u6210\u6709\u52a9\u4e8e\u7b80\u5316\u6a21\u578b\u7ba1\u7406\u548c\u90e8\u7f72\u7684\u5de5\u4f5c\u6d41\u7a0b\uff0c\u63d0\u9ad8\u60a8\u7684\u5de5\u4f5c\u6548\u7387\uff0c\u5e76\u52a0\u901f\u6a21\u578b\u4ece\u5b9e\u9a8c\u5230\u751f\u4ea7\u7684\u8fc7\u7a0b\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u5c06 MLflow Model \u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883<\/p>\n\n\n\n<p>\u5c06 MLflow Model \u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883\u6d89\u53ca\u5c06\u6a21\u578b\u4ece\u8bad\u7ec3\u548c\u5b9e\u9a8c\u9636\u6bb5\u8f6c\u79fb\u5230\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u4ee5\u4fbf\u5728\u5b9e\u9645\u6570\u636e\u4e0a\u8fdb\u884c\u9884\u6d4b\u3002\u90e8\u7f72 MLflow Model \u53ef\u4ee5\u91c7\u7528\u4e0d\u540c\u7684\u65b9\u5f0f\uff0c\u8fd9\u91cc\u6211\u4eec\u5c06\u4ecb\u7ecd\u4e00\u4e9b\u5e38\u7528\u7684\u90e8\u7f72\u65b9\u6cd5\uff1a<\/p>\n\n\n\n<p><strong>1. \u4f7f\u7528 MLflow \u81ea\u5e26\u7684\u90e8\u7f72\u5de5\u5177<\/strong><\/p>\n\n\n\n<p>MLflow \u63d0\u4f9b\u4e86\u4e00\u4e9b\u5185\u7f6e\u7684\u90e8\u7f72\u5de5\u5177\uff0c\u53ef\u4ee5\u5c06\u6a21\u578b\u90e8\u7f72\u4e3a REST API \u670d\u52a1\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 MLflow \u7684 <code>mlflow models serve<\/code> \u547d\u4ee4\u90e8\u7f72\u6a21\u578b\u7684\u7b80\u5355\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">javascriptCopy code<code>mlflow models serve -m runs:\/&lt;run_id&gt;\/model -p 1234\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u5728\u7aef\u53e3 1234 \u4e0a\u542f\u52a8\u4e00\u4e2a REST API \u670d\u52a1\u3002\u60a8\u53ef\u4ee5\u901a\u8fc7\u53d1\u9001 POST \u8bf7\u6c42\u5230 <code>http:\/\/&lt;server_url&gt;:1234\/invocations<\/code> \u6765\u8c03\u7528\u8be5\u670d\u52a1\u3002\u8bf7\u6ce8\u610f\uff0c\u6b64\u65b9\u6cd5\u4ec5\u9002\u7528\u4e8e\u5c0f\u89c4\u6a21\u90e8\u7f72\u548c\u6d4b\u8bd5\uff0c\u4e0d\u5efa\u8bae\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528\u3002<\/p>\n\n\n\n<p><strong>2. \u4f7f\u7528 Docker \u90e8\u7f72<\/strong><\/p>\n\n\n\n<p>MLflow \u652f\u6301\u5c06\u6a21\u578b\u6253\u5305\u6210 Docker \u5bb9\u5668\uff0c\u4ece\u800c\u53ef\u4ee5\u5728\u4efb\u4f55\u652f\u6301 Docker \u7684\u73af\u5883\u4e2d\u8fd0\u884c\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 MLflow \u7684 <code>mlflow models build-docker<\/code> \u547d\u4ee4\u5c06\u6a21\u578b\u6253\u5305\u6210 Docker \u5bb9\u5668\u7684\u793a\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">javascriptCopy code<code>mlflow models build-docker -m runs:\/&lt;run_id&gt;\/model -n my_mlflow_model\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u751f\u6210\u4e00\u4e2a\u540d\u4e3a <code>my_mlflow_model<\/code> \u7684 Docker \u955c\u50cf\u3002\u7136\u540e\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fd0\u884c Docker \u5bb9\u5668\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">arduinoCopy code<code>docker run -p 1234:8080 my_mlflow_model\n<\/code><\/pre>\n\n\n\n<p>\u8fd9\u5c06\u5728\u7aef\u53e3 1234 \u4e0a\u542f\u52a8\u4e00\u4e2a REST API \u670d\u52a1\u3002\u60a8\u53ef\u4ee5\u50cf\u4e4b\u524d\u90a3\u6837\u901a\u8fc7\u53d1\u9001 POST \u8bf7\u6c42\u5230 <code>http:\/\/&lt;server_url&gt;:1234\/invocations<\/code> \u6765\u8c03\u7528\u8be5\u670d\u52a1\u3002<\/p>\n\n\n\n<p><strong>3. \u90e8\u7f72\u5230\u4e91\u670d\u52a1\u5546<\/strong><\/p>\n\n\n\n<p>\u5982\u524d\u9762\u63d0\u5230\u7684\uff0cMLflow \u53ef\u4ee5\u4e0e\u4e91\u670d\u52a1\u5546\uff08\u5982 AWS SageMaker\u3001Azure ML \u548c Google Cloud AI Platform\uff09\u96c6\u6210\u3002\u8fd9\u4e9b\u670d\u52a1\u901a\u5e38\u63d0\u4f9b\u4e86\u5b8c\u5168\u6258\u7ba1\u7684\u90e8\u7f72\u89e3\u51b3\u65b9\u6848\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u5c06 MLflow \u6a21\u578b\u90e8\u7f72\u4e3a\u53ef\u6269\u5c55\u7684 REST API \u670d\u52a1\u3002\u8bf7\u53c2\u8003\u524d\u9762\u7684\u56de\u7b54\u4ee5\u4e86\u89e3\u5982\u4f55\u5c06 MLflow \u6a21\u578b\u90e8\u7f72\u5230 AWS SageMaker \u548c Azure ML\u3002<\/p>\n\n\n\n<p><strong>4. \u90e8\u7f72\u5230 Kubernetes<\/strong><\/p>\n\n\n\n<p>\u5c06 MLflow \u6a21\u578b\u90e8\u7f72\u5230 Kubernetes \u53ef\u4ee5\u5b9e\u73b0\u9ad8\u5ea6\u53ef\u6269\u5c55\u548c\u7075\u6d3b\u7684\u90e8\u7f72\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5316\u7684\u90e8\u7f72\u6d41\u7a0b\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u4f7f\u7528 <code>mlflow models build-docker<\/code> \u547d\u4ee4\u521b\u5efa Docker \u955c\u50cf\uff08\u5982\u4e0a\u6240\u8ff0\uff09\u3002<\/li>\n\n\n\n<li>\u5c06 Docker \u955c\u50cf\u63a8\u9001\u5230\u5bb9\u5668\u955c\u50cf\u4ed3\u5e93\uff08\u5982 Docker Hub\u3001Google Container Registry \u6216 AWS Elastic Container Registry\uff09\u3002<\/li>\n\n\n\n<li>\u521b\u5efa\u4e00\u4e2a Kubernetes \u90e8\u7f72\u548c\u670d\u52a1\u8d44\u6e90\uff0c\u6307\u5b9a\u5bb9\u5668\u955c\u50cf\u548c\u9002\u5f53\u7684\u7aef\u53e3\u6620\u5c04\u3002<\/li>\n\n\n\n<li>\u4f7f\u7528 <code>kubectl apply<\/code> \u547d\u4ee4\u90e8\u7f72 Kubernetes \u8d44\u6e90\u3002<\/li>\n<\/ul>\n\n\n\n<p>\u90e8\u7f72<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u90e8\u7f72 MLflow \u6a21\u578b\u5230\u751f\u4ea7\u73af\u5883\u65f6\uff0c\u8fd8\u9700\u8981\u8003\u8651\u4ee5\u4e0b\u56e0\u7d20\uff1a<\/p>\n\n\n\n<p><strong>1. \u6027\u80fd\u548c\u53ef\u6269\u5c55\u6027<\/strong><\/p>\n\n\n\n<p>\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72 MLflow \u6a21\u578b\u65f6\uff0c\u9700\u8981\u786e\u4fdd\u6a21\u578b\u80fd\u591f\u6ee1\u8db3\u6027\u80fd\u8981\u6c42\u5e76\u5177\u6709\u826f\u597d\u7684\u53ef\u6269\u5c55\u6027\u3002\u9009\u62e9\u5408\u9002\u7684\u786c\u4ef6\u8d44\u6e90\u3001\u90e8\u7f72\u65b9\u5f0f\u4ee5\u53ca\u4f18\u5316\u6a21\u578b\u548c\u4ee3\u7801\u53ef\u4ee5\u5e2e\u52a9\u63d0\u9ad8\u6027\u80fd\u3002\u8003\u8651\u4f7f\u7528\u4e91\u670d\u52a1\u5546\u6216 Kubernetes \u7b49\u5bb9\u5668\u7f16\u6392\u5de5\u5177\uff0c\u4ee5\u4fbf\u6839\u636e\u9700\u8981\u52a8\u6001\u5730\u6269\u5c55\u6216\u7f29\u5c0f\u670d\u52a1\u3002<\/p>\n\n\n\n<p><strong>2. \u76d1\u63a7\u548c\u65e5\u5fd7\u8bb0\u5f55<\/strong><\/p>\n\n\n\n<p>\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72 MLflow \u6a21\u578b\u65f6\uff0c\u76d1\u63a7\u548c\u65e5\u5fd7\u8bb0\u5f55\u81f3\u5173\u91cd\u8981\u3002\u786e\u4fdd\u60a8\u7684\u90e8\u7f72\u65b9\u6848\u652f\u6301\u6536\u96c6\u5173\u952e\u6307\u6807\uff08\u5982\u8bf7\u6c42\u5ef6\u8fdf\u3001\u9519\u8bef\u7387\u548c\u541e\u5410\u91cf\uff09\u4ee5\u53ca\u6a21\u578b\u548c\u670d\u52a1\u7684\u65e5\u5fd7\u3002\u8fd9\u5c06\u5e2e\u52a9\u60a8\u53ca\u65f6\u53d1\u73b0\u5e76\u89e3\u51b3\u6f5c\u5728\u95ee\u9898\uff0c\u4ee5\u786e\u4fdd\u826f\u597d\u7684\u670d\u52a1\u8d28\u91cf\u3002<\/p>\n\n\n\n<p><strong>3. \u5b89\u5168\u6027<\/strong><\/p>\n\n\n\n<p>\u786e\u4fdd\u6a21\u578b\u90e8\u7f72\u7684\u5b89\u5168\u6027\u5bf9\u4e8e\u751f\u4ea7\u73af\u5883\u81f3\u5173\u91cd\u8981\u3002\u6839\u636e\u60a8\u7684\u5177\u4f53\u9700\u6c42\uff0c\u60a8\u53ef\u80fd\u9700\u8981\u5b9e\u65bd\u5982\u8eab\u4efd\u9a8c\u8bc1\u3001\u6388\u6743\u3001\u6570\u636e\u52a0\u5bc6\u7b49\u5b89\u5168\u63aa\u65bd\u3002\u6b64\u5916\uff0c\u5408\u89c4\u6027\u8981\u6c42\uff08\u5982 GDPR\u3001HIPAA \u7b49\uff09\u4e5f\u53ef\u80fd\u5f71\u54cd\u60a8\u7684\u90e8\u7f72\u7b56\u7565\u548c\u5b9e\u8df5\u3002<\/p>\n\n\n\n<p><strong>4. \u7248\u672c\u63a7\u5236\u548c\u6301\u7eed\u96c6\u6210\/\u6301\u7eed\u90e8\u7f72\uff08CI\/CD\uff09<\/strong><\/p>\n\n\n\n<p>\u4e3a\u786e\u4fdd\u60a8\u7684 MLflow \u6a21\u578b\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u59cb\u7ec8\u4fdd\u6301\u6700\u65b0\u72b6\u6001\uff0c\u5efa\u8bae\u5c06\u6a21\u578b\u4e0e\u7248\u672c\u63a7\u5236\u7cfb\u7edf\uff08\u5982 Git\uff09\u96c6\u6210\uff0c\u5e76\u4f7f\u7528\u6301\u7eed\u96c6\u6210\/\u6301\u7eed\u90e8\u7f72\uff08CI\/CD\uff09\u5de5\u5177\uff08\u5982 Jenkins\u3001Travis CI\u3001GitHub Actions \u7b49\uff09\u81ea\u52a8\u5316\u90e8\u7f72\u8fc7\u7a0b\u3002\u8fd9\u6837\u53ef\u4ee5\u786e\u4fdd\u6a21\u578b\u66f4\u65b0\u7684\u53ca\u65f6\u6027\u548c\u4e00\u81f4\u6027\uff0c\u51cf\u5c11\u4eba\u4e3a\u9519\u8bef\u7684\u53ef\u80fd\u6027\u3002<\/p>\n\n\n\n<p>\u603b\u4e4b\uff0c\u5c06 MLflow \u6a21\u578b\u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883\u6d89\u53ca\u591a\u4e2a\u65b9\u9762\u7684\u8003\u8651\u3002\u9009\u62e9\u5408\u9002\u7684\u90e8\u7f72\u65b9\u5f0f\u3001\u786e\u4fdd\u6027\u80fd\u548c\u53ef\u6269\u5c55\u6027\u3001\u5173\u6ce8\u5b89\u5168\u6027\u548c\u76d1\u63a7\uff0c\u5e76\u5229\u7528\u7248\u672c\u63a7\u5236\u548c CI\/CD \u5de5\u5177\uff0c\u5c06\u6709\u52a9\u4e8e\u60a8\u6210\u529f\u5730\u5c06 MLflow \u6a21\u578b\u5e94\u7528\u4e8e\u5b9e\u9645\u4e1a\u52a1\u573a\u666f\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91caMLflow \u5728\u751f\u4ea7\u73af\u5883\u4e2d\u7684\u6700\u4f73\u5b9e\u8df5<\/p>\n\n\n\n<p>\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528 MLflow \u7684\u6700\u4f73\u5b9e\u8df5\u53ef\u4ee5\u5e2e\u52a9\u60a8\u66f4\u6709\u6548\u5730\u7ba1\u7406\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u7a0b\u5e76\u786e\u4fdd\u670d\u52a1\u8d28\u91cf\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u91cd\u8981\u7684\u6700\u4f73\u5b9e\u8df5\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u6a21\u578b\u7248\u672c\u63a7\u5236\u548c\u8ddf\u8e2a<\/strong>\uff1a\u4f7f\u7528 MLflow Model Registry \u7ba1\u7406\u6a21\u578b\u7248\u672c\u548c\u751f\u547d\u5468\u671f\u3002\u786e\u4fdd\u4e3a\u6bcf\u4e2a\u6a21\u578b\u521b\u5efa\u5355\u72ec\u7684\u6ce8\u518c\u8868\u6761\u76ee\uff0c\u5e76\u4e3a\u6bcf\u4e2a\u91cd\u8981\u66f4\u65b0\u521b\u5efa\u65b0\u7684\u7248\u672c\u3002\u4f7f\u7528 Model Registry \u53ef\u4ee5\u5e2e\u52a9\u60a8\u8ddf\u8e2a\u4e0d\u540c\u6a21\u578b\u7248\u672c\u7684\u6027\u80fd\u6307\u6807\uff0c\u5e76\u5728\u9700\u8981\u65f6\u56de\u6eda\u5230\u65e7\u7248\u672c\u3002<\/li>\n\n\n\n<li><strong>\u6e05\u6670\u7684\u5b9e\u9a8c\u7ec4\u7ec7<\/strong>\uff1a\u5728 MLflow \u4e2d\u7ec4\u7ec7\u5b9e\u9a8c\uff0c\u786e\u4fdd\u6bcf\u4e2a\u5b9e\u9a8c\u6709\u660e\u786e\u7684\u76ee\u6807\u548c\u8303\u56f4\u3002\u5c3d\u91cf\u907f\u514d\u6df7\u5408\u4e0d\u540c\u7c7b\u578b\u7684\u6a21\u578b\u548c\u4efb\u52a1\u3002\u4e3a\u5b9e\u9a8c\u6dfb\u52a0\u63cf\u8ff0\u6027\u6807\u7b7e\uff0c\u4ee5\u4fbf\u4e8e\u56e2\u961f\u6210\u5458\u7406\u89e3\u548c\u67e5\u627e\u3002<\/li>\n\n\n\n<li><strong>\u8bb0\u5f55\u548c\u67e5\u8be2\u5b8c\u6574\u7684\u5b9e\u9a8c\u4fe1\u606f<\/strong>\uff1a\u8bb0\u5f55\u6a21\u578b\u7684\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\uff0c\u786e\u4fdd\u5b9e\u9a8c\u7684\u53ef\u91cd\u590d\u6027\u3002\u5728\u67e5\u8be2\u5b9e\u9a8c\u65f6\uff0c\u5229\u7528 MLflow \u63d0\u4f9b\u7684 API \u7b5b\u9009\u5e76\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c\uff0c\u4ee5\u4fbf\u4e8e\u627e\u5230\u6700\u4f18\u6a21\u578b\u3002<\/li>\n\n\n\n<li><strong>\u4ee3\u7801\u7248\u672c\u63a7\u5236<\/strong>\uff1a\u5c06 MLflow \u9879\u76ee\u7684\u4ee3\u7801\u6258\u7ba1\u5728\u7248\u672c\u63a7\u5236\u7cfb\u7edf\uff08\u5982 Git\uff09\u4e2d\uff0c\u786e\u4fdd\u4ee3\u7801\u7684\u53ef\u8ffd\u6eaf\u6027\u548c\u534f\u4f5c\u6027\u3002\u5c06\u4ee3\u7801\u548c\u6a21\u578b\u7684\u7248\u672c\u4fdd\u6301\u540c\u6b65\uff0c\u4ee5\u4fbf\u4e8e\u8ddf\u8e2a\u548c\u8c03\u8bd5\u3002<\/li>\n\n\n\n<li><strong>\u6301\u7eed\u96c6\u6210\/\u6301\u7eed\u90e8\u7f72\uff08CI\/CD\uff09<\/strong>\uff1a\u5c06 MLflow \u4e0e CI\/CD \u5de5\u5177\uff08\u5982 Jenkins\u3001Travis CI\u3001GitHub Actions \u7b49\uff09\u96c6\u6210\uff0c\u4ee5\u81ea\u52a8\u5316\u6784\u5efa\u3001\u6d4b\u8bd5\u548c\u90e8\u7f72\u8fc7\u7a0b\u3002\u8fd9\u53ef\u4ee5\u786e\u4fdd\u6a21\u578b\u7684\u53ca\u65f6\u66f4\u65b0\u548c\u4e00\u81f4\u6027\uff0c\u51cf\u5c11\u4eba\u4e3a\u9519\u8bef\u7684\u53ef\u80fd\u6027\u3002<\/li>\n\n\n\n<li><strong>\u73af\u5883\u9694\u79bb\u548c\u4f9d\u8d56\u7ba1\u7406<\/strong>\uff1a\u4f7f\u7528\u865a\u62df\u73af\u5883\uff08\u5982 Conda\u3001virtualenv\uff09\u6216\u5bb9\u5668\u6280\u672f\uff08\u5982 Docker\uff09\u786e\u4fdd\u5b9e\u9a8c\u548c\u90e8\u7f72\u73af\u5883\u7684\u9694\u79bb\u3002\u4f7f\u7528 MLflow Projects \u7ba1\u7406\u9879\u76ee\u4f9d\u8d56\uff0c\u5e76\u5728 <code>conda.yaml<\/code> \u6216 <code>requirements.txt<\/code> \u6587\u4ef6\u4e2d\u6307\u5b9a\u4f9d\u8d56\u7248\u672c\uff0c\u4ee5\u786e\u4fdd\u73af\u5883\u7684\u4e00\u81f4\u6027\u3002<\/li>\n\n\n\n<li><strong>\u4f7f\u7528\u6807\u51c6\u7684\u6a21\u578b\u683c\u5f0f<\/strong>\uff1a\u5728\u4fdd\u5b58\u6a21\u578b\u65f6\uff0c\u4f7f\u7528\u6807\u51c6\u7684\u6a21\u578b\u683c\u5f0f\uff08\u5982 ONNX\u3001PMML\u3001TensorFlow SavedModel \u7b49\uff09\uff0c\u4ee5\u4fbf\u4e8e\u6a21\u578b\u5728\u4e0d\u540c\u73af\u5883\u548c\u5e73\u53f0\u4e4b\u95f4\u7684\u4e92\u64cd\u4f5c\u6027\u3002<\/li>\n\n\n\n<li><strong>\u6027\u80fd\u548c\u53ef\u6269\u5c55\u6027<\/strong>\uff1a\u4f18\u5316\u6a21\u578b\u548c\u4ee3\u7801\u4ee5\u63d0\u9ad8\u6027\u80fd\uff0c\u5e76\u786e\u4fdd\u6a21\u578b\u5177\u6709\u826f\u597d\u7684\u53ef\u6269\u5c55\u6027\u3002\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72\u65f6\uff0c\u9009\u62e9\u5408\u9002\u7684\u786c\u4ef6\u8d44\u6e90\u548c\u90e8\u7f72\u65b9\u5f0f\uff0c\u4ee5\u6ee1\u8db3\u6027\u80fd\u8981\u6c42\u3002<\/li>\n\n\n\n<li><strong>\u5b89\u5168\u6027\u548c\u5408\u89c4\u6027<\/strong>\uff1a\u786e\u4fdd\u6a21\u578b\u90e8\u7f72\u7684\u5b89\u5168\u6027\uff0c\u5b9e\u65bd\u9002\u5f53\u7684\u8eab\u4efd\u9a8c\u8bc1\u3001<\/li>\n<\/ol>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u6388\u6743\u548c\u6570\u636e\u52a0\u5bc6\u63aa\u65bd\u3002\u6839\u636e\u60a8\u7684\u884c\u4e1a\u548c\u5730\u533a\uff0c\u9075\u5faa\u76f8\u5173\u7684\u6cd5\u89c4\u548c\u5408\u89c4\u6027\u8981\u6c42\uff08\u5982 GDPR\u3001HIPAA \u7b49\uff09\u3002\u5728\u90e8\u7f72 MLflow \u6a21\u578b\u65f6\uff0c\u52a1\u5fc5\u5173\u6ce8\u6570\u636e\u9690\u79c1\u548c\u5b89\u5168\u6027\u3002<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"10\">\n<li><strong>\u76d1\u63a7\u548c\u65e5\u5fd7\u8bb0\u5f55<\/strong>\uff1a\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72 MLflow \u6a21\u578b\u65f6\uff0c\u786e\u4fdd\u76d1\u63a7\u5173\u952e\u6307\u6807\uff08\u5982\u8bf7\u6c42\u5ef6\u8fdf\u3001\u9519\u8bef\u7387\u548c\u541e\u5410\u91cf\uff09\u4ee5\u53ca\u6536\u96c6\u6a21\u578b\u548c\u670d\u52a1\u7684\u65e5\u5fd7\u3002\u8fd9\u5c06\u5e2e\u52a9\u60a8\u53ca\u65f6\u53d1\u73b0\u5e76\u89e3\u51b3\u6f5c\u5728\u95ee\u9898\uff0c\u786e\u4fdd\u826f\u597d\u7684\u670d\u52a1\u8d28\u91cf\u3002\u5c06 MLflow \u4e0e\u65e5\u5fd7\u8bb0\u5f55\u548c\u76d1\u63a7\u5de5\u5177\uff08\u5982 Elasticsearch\u3001Kibana\u3001Grafana \u7b49\uff09\u96c6\u6210\uff0c\u4ee5\u5b9e\u73b0\u96c6\u4e2d\u5f0f\u65e5\u5fd7\u548c\u6307\u6807\u7ba1\u7406\u3002<\/li>\n\n\n\n<li><strong>\u6a21\u578b\u9a8c\u8bc1\u548c\u6d4b\u8bd5<\/strong>\uff1a\u5728\u90e8\u7f72\u6a21\u578b\u4e4b\u524d\uff0c\u5bf9\u6a21\u578b\u8fdb\u884c\u8be6\u7ec6\u7684\u9a8c\u8bc1\u548c\u6d4b\u8bd5\u3002\u9664\u4e86\u9a8c\u8bc1\u6a21\u578b\u5728\u8bad\u7ec3\u548c\u9a8c\u8bc1\u6570\u636e\u96c6\u4e0a\u7684\u6027\u80fd\u4e4b\u5916\uff0c\u8fd8\u8981\u6d4b\u8bd5\u6a21\u578b\u5728\u5404\u79cd\u8fb9\u7f18\u60c5\u51b5\u4e0b\u7684\u8868\u73b0\u3002\u8fd9\u53ef\u4ee5\u5e2e\u52a9\u60a8\u63d0\u524d\u53d1\u73b0\u6f5c\u5728\u95ee\u9898\uff0c\u964d\u4f4e\u751f\u4ea7\u73af\u5883\u4e2d\u7684\u98ce\u9669\u3002<\/li>\n\n\n\n<li><strong>\u56e2\u961f\u534f\u4f5c\u548c\u77e5\u8bc6\u5171\u4eab<\/strong>\uff1a\u786e\u4fdd\u56e2\u961f\u6210\u5458\u80fd\u591f\u8f7b\u677e\u5730\u8bbf\u95ee\u548c\u5171\u4eab MLflow \u5b9e\u9a8c\u548c\u6a21\u578b\u3002\u4f7f\u7528\u5171\u4eab\u7684 MLflow \u670d\u52a1\u5668\u4ee5\u4fbf\u4e8e\u56e2\u961f\u6210\u5458\u67e5\u770b\u5b9e\u9a8c\u7ed3\u679c\u548c\u6a21\u578b\u6027\u80fd\u3002\u5728\u56e2\u961f\u4e2d\u63a8\u5e7f MLflow \u7684\u4f7f\u7528\uff0c\u4ee5\u4fbf\u4e8e\u8de8\u9879\u76ee\u548c\u90e8\u95e8\u7684\u77e5\u8bc6\u5171\u4eab\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u603b\u4e4b\uff0c\u9075\u5faa\u4e0a\u8ff0\u6700\u4f73\u5b9e\u8df5\u5c06\u6709\u52a9\u4e8e\u60a8\u66f4\u6709\u6548\u5730\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528 MLflow\u3002\u4ece\u6a21\u578b\u7248\u672c\u63a7\u5236\u3001\u5b9e\u9a8c\u7ec4\u7ec7\u5230\u73af\u5883\u7ba1\u7406\u548c\u76d1\u63a7\uff0c\u8fd9\u4e9b\u5b9e\u8df5\u5c06\u786e\u4fdd\u60a8\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u7a0b\u66f4\u52a0\u5065\u58ee\u3001\u53ef\u6269\u5c55\u4e14\u5b89\u5168\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u8be6\u7ec6\u89e3\u91camlflow\u5b89\u5168\u4e0e\u6027\u80fd\u4f18\u5316<\/p>\n\n\n\n<p>\u5728\u4f7f\u7528 MLflow \u65f6\uff0c\u786e\u4fdd\u5b89\u5168\u6027\u548c\u4f18\u5316\u6027\u80fd\u81f3\u5173\u91cd\u8981\u3002\u4ee5\u4e0b\u662f\u6709\u5173 MLflow \u5b89\u5168\u6027\u548c\u6027\u80fd\u4f18\u5316\u7684\u8be6\u7ec6\u89e3\u91ca\uff1a<\/p>\n\n\n\n<p><strong>\u5b89\u5168\u6027<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u8eab\u4efd\u9a8c\u8bc1\u548c\u6388\u6743<\/strong>\uff1a\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72 MLflow \u65f6\uff0c\u9700\u8981\u5b9e\u65bd\u8eab\u4efd\u9a8c\u8bc1\u548c\u6388\u6743\u63aa\u65bd\u3002\u4f8b\u5982\uff0c\u901a\u8fc7\u4f7f\u7528 OAuth2\u3001LDAP \u6216\u5176\u4ed6\u8eab\u4efd\u9a8c\u8bc1\u7cfb\u7edf\uff0c\u786e\u4fdd\u53ea\u6709\u6388\u6743\u7528\u6237\u624d\u80fd\u8bbf\u95ee MLflow \u670d\u52a1\u3002<\/li>\n\n\n\n<li><strong>\u6570\u636e\u52a0\u5bc6<\/strong>\uff1a\u4e3a\u4e86\u4fdd\u62a4\u6570\u636e\u9690\u79c1\uff0c\u5e94\u5bf9\u4f20\u8f93\u4e2d\u7684\u6570\u636e\uff08\u5982 HTTPS\uff09\u548c\u5b58\u50a8\u4e2d\u7684\u6570\u636e\uff08\u5982\u670d\u52a1\u5668\u7aef\u52a0\u5bc6\u7684\u5bf9\u8c61\u5b58\u50a8\uff09\u8fdb\u884c\u52a0\u5bc6\u3002<\/li>\n\n\n\n<li><strong>\u7f51\u7edc\u5b89\u5168<\/strong>\uff1a\u786e\u4fdd MLflow \u670d\u52a1\u4e0e\u5176\u4ed6\u5173\u952e\u670d\u52a1\uff08\u5982\u6570\u636e\u5e93\u3001\u5b58\u50a8\u7b49\uff09\u4e4b\u95f4\u7684\u901a\u4fe1\u53d7\u5230\u4fdd\u62a4\u3002\u53ef\u4ee5\u4f7f\u7528\u7f51\u7edc\u7b56\u7565\u3001\u9632\u706b\u5899\u89c4\u5219\u7b49\u6765\u9650\u5236\u8bbf\u95ee\u6743\u9650\uff0c\u9632\u6b62\u672a\u7ecf\u6388\u6743\u7684\u8bbf\u95ee\u3002<\/li>\n\n\n\n<li><strong>\u5408\u89c4\u6027<\/strong>\uff1a\u6839\u636e\u60a8\u6240\u5728\u7684\u884c\u4e1a\u548c\u5730\u533a\uff0c\u9075\u5faa\u76f8\u5173\u7684\u6cd5\u89c4\u548c\u5408\u89c4\u6027\u8981\u6c42\uff08\u5982 GDPR\u3001HIPAA \u7b49\uff09\u3002\u786e\u4fdd MLflow \u7684\u4f7f\u7528\u548c\u90e8\u7f72\u7b26\u5408\u8fd9\u4e9b\u8981\u6c42\u3002<\/li>\n<\/ol>\n\n\n\n<p><strong>\u6027\u80fd\u4f18\u5316<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u786c\u4ef6\u8d44\u6e90<\/strong>\uff1a\u6839\u636e\u6a21\u578b\u7684\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u786c\u4ef6\u8d44\u6e90\uff08\u5982 CPU\u3001GPU\u3001\u5185\u5b58\u7b49\uff09\uff0c\u4ee5\u6ee1\u8db3\u6027\u80fd\u8981\u6c42\u3002\u53ef\u4ee5\u6839\u636e\u6027\u80fd\u6307\u6807\uff08\u5982\u541e\u5410\u91cf\u3001\u5ef6\u8fdf\u7b49\uff09\u8c03\u6574\u8d44\u6e90\u5206\u914d\u3002<\/li>\n\n\n\n<li><strong>\u4ee3\u7801\u4f18\u5316<\/strong>\uff1a\u4f18\u5316\u673a\u5668\u5b66\u4e60\u4ee3\u7801\uff0c\u4ee5\u63d0\u9ad8\u8bad\u7ec3\u548c\u63a8\u7406\u6027\u80fd\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u77e2\u91cf\u5316\u64cd\u4f5c\u3001\u5e76\u884c\u8ba1\u7b97\u7b49\u6280\u672f\u52a0\u901f\u8ba1\u7b97\uff0c\u51cf\u5c11\u4e0d\u5fc5\u8981\u7684\u8ba1\u7b97\u5f00\u9500\u3002<\/li>\n\n\n\n<li><strong>\u6a21\u578b\u4f18\u5316<\/strong>\uff1a\u6839\u636e\u5177\u4f53\u573a\u666f\uff0c\u5bf9\u6a21\u578b\u8fdb\u884c\u4f18\u5316\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u6a21\u578b\u538b\u7f29\u6280\u672f\uff08\u5982\u91cf\u5316\u3001\u526a\u679d\u7b49\uff09\u964d\u4f4e\u6a21\u578b\u5927\u5c0f\u548c\u8ba1\u7b97\u590d\u6742\u5ea6\uff0c\u4ece\u800c\u63d0\u9ad8\u63a8\u7406\u6027\u80fd\u3002<\/li>\n\n\n\n<li><strong>\u8d1f\u8f7d\u5747\u8861<\/strong>\uff1a\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u90e8\u7f72 MLflow \u6a21\u578b\u65f6\uff0c\u4f7f\u7528\u8d1f\u8f7d\u5747\u8861\u5668\u5206\u53d1\u6d41\u91cf\uff0c\u4ee5\u786e\u4fdd\u670d\u52a1\u7684\u7a33\u5b9a\u6027\u548c\u53ef\u6269\u5c55\u6027\u3002<\/li>\n\n\n\n<li><strong>\u53ef\u6269\u5c55\u6027<\/strong>\uff1a\u4f7f\u7528\u4e91\u670d\u52a1\u5546\u6216\u5bb9\u5668\u7f16\u6392\u5de5\u5177\uff08\u5982 Kubernetes\uff09\u52a8\u6001\u6269\u5c55\u6216\u7f29\u5c0f\u670d\u52a1\uff0c\u4ee5\u6ee1\u8db3\u4e0d\u65ad\u53d8\u5316\u7684\u9700\u6c42\u3002\u8fd9\u5c06\u6709\u52a9\u4e8e\u786e\u4fdd\u670d\u52a1\u5177\u6709\u826f\u597d\u7684\u53ef\u6269\u5c55\u6027\uff0c\u4ee5\u5e94\u5bf9\u4e0d\u540c\u7684\u8d1f\u8f7d\u9700\u6c42\u3002<\/li>\n\n\n\n<li><strong>\u7f13\u5b58\u548c\u6279\u5904\u7406<\/strong>\uff1a\u5728\u9002\u5f53\u7684\u60c5\u51b5\u4e0b\uff0c\u4f7f\u7528\u7f13\u5b58\u548c\u6279\u5904\u7406\u6280\u672f\u51cf\u5c11\u5ef6\u8fdf\u548c\u63d0\u9ad8\u541e\u5410\u91cf\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u7f13\u5b58\u5e38\u7528\u7684\u8ba1\u7b97\u7ed3\u679c\uff0c\u4ee5\u51cf\u5c11\u91cd\u590d\u8ba1\u7b97\u7684\u5f00\u9500\uff1b\u901a\u8fc7\u6279\u5904\u7406\u63a8\u7406\u8bf7\u6c42\uff0c\u4ee5\u63d0\u9ad8 GPU \u5229\u7528\u7387\u548c\u541e\u5410\u91cf<\/li>\n<\/ol>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<ol class=\"wp-block-list\" start=\"7\">\n<li><strong>\u76d1\u63a7\u6027\u80fd\u6307\u6807<\/strong>\uff1a\u5b9a\u671f\u76d1\u63a7\u5173\u952e\u6027\u80fd\u6307\u6807\uff0c\u5982\u5ef6\u8fdf\u3001\u541e\u5410\u91cf\u3001\u8d44\u6e90\u5229\u7528\u7387\u7b49\uff0c\u4ee5\u4fbf\u5728\u51fa\u73b0\u6027\u80fd\u74f6\u9888\u65f6\u53ca\u65f6\u53d1\u73b0\u5e76\u91c7\u53d6\u76f8\u5e94\u63aa\u65bd\u3002\u53ef\u4ee5\u4f7f\u7528\u76d1\u63a7\u5de5\u5177\uff08\u5982 Prometheus\u3001Grafana \u7b49\uff09\u5b9e\u73b0\u5b9e\u65f6\u76d1\u63a7\u548c\u53ef\u89c6\u5316\u3002<\/li>\n\n\n\n<li><strong>\u5f02\u6b65\u5904\u7406<\/strong>\uff1a\u5728\u9002\u5f53\u7684\u573a\u666f\u4e0b\uff0c\u4f7f\u7528\u5f02\u6b65\u5904\u7406\u6280\u672f\u6765\u63d0\u9ad8\u7cfb\u7edf\u6027\u80fd\u3002\u4f8b\u5982\uff0c\u5728\u5904\u7406\u8017\u65f6\u8f83\u957f\u7684\u63a8\u7406\u8bf7\u6c42\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u6d88\u606f\u961f\u5217\uff08\u5982 RabbitMQ\u3001Kafka \u7b49\uff09\u5c06\u8bf7\u6c42\u653e\u5165\u961f\u5217\uff0c\u5f02\u6b65\u5904\u7406\u5e76\u8fd4\u56de\u7ed3\u679c\u3002<\/li>\n\n\n\n<li><strong>\u5206\u5e03\u5f0f\u8bad\u7ec3<\/strong>\uff1a\u5728\u8bad\u7ec3\u5927\u89c4\u6a21\u6a21\u578b\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528 MLflow \u4e0e\u5206\u5e03\u5f0f\u8bad\u7ec3\u6846\u67b6\uff08\u5982 Horovod\u3001TensorFlow \u5206\u5e03\u5f0f\u8bad\u7ec3\u7b49\uff09\u96c6\u6210\uff0c\u4ee5\u52a0\u901f\u8bad\u7ec3\u8fc7\u7a0b\u5e76\u63d0\u9ad8\u8d44\u6e90\u5229\u7528\u7387\u3002<\/li>\n\n\n\n<li><strong>\u6301\u7eed\u96c6\u6210\/\u6301\u7eed\u90e8\u7f72\uff08CI\/CD\uff09<\/strong>\uff1a\u5c06 MLflow \u4e0e CI\/CD \u5de5\u5177\uff08\u5982 Jenkins\u3001Travis CI\u3001GitHub Actions \u7b49\uff09\u96c6\u6210\uff0c\u4ee5\u81ea\u52a8\u5316\u6784\u5efa\u3001\u6d4b\u8bd5\u548c\u90e8\u7f72\u8fc7\u7a0b\u3002\u8fd9\u53ef\u4ee5\u786e\u4fdd\u6a21\u578b\u7684\u53ca\u65f6\u66f4\u65b0\u548c\u4e00\u81f4\u6027\uff0c\u51cf\u5c11\u4eba\u4e3a\u9519\u8bef\u7684\u53ef\u80fd\u6027\u3002<\/li>\n\n\n\n<li><strong>\u5065\u5eb7\u68c0\u67e5\u548c\u6545\u969c\u6062\u590d<\/strong>\uff1a\u5b9e\u65bd\u5065\u5eb7\u68c0\u67e5\u673a\u5236\uff0c\u4ee5\u76d1\u63a7 MLflow \u670d\u52a1\u7684\u8fd0\u884c\u72b6\u51b5\u3002\u5728\u670d\u52a1\u51fa\u73b0\u6545\u969c\u65f6\uff0c\u81ea\u52a8\u89e6\u53d1\u6062\u590d\u6d41\u7a0b\uff0c\u4f8b\u5982\u91cd\u542f\u670d\u52a1\u6216\u5207\u6362\u5230\u5907\u4efd\u5b9e\u4f8b\uff0c\u4ee5\u786e\u4fdd\u670d\u52a1\u7684\u9ad8\u53ef\u7528\u6027\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u9075\u5faa\u4e0a\u8ff0\u7b56\u7565\u53ef\u4ee5\u5e2e\u52a9\u60a8\u63d0\u9ad8 MLflow \u5728\u751f\u4ea7\u73af\u5883\u4e2d\u7684\u5b89\u5168\u6027\u548c\u6027\u80fd\u3002\u901a\u8fc7\u5b9e\u65bd\u9002\u5f53\u7684\u5b89\u5168\u63aa\u65bd\u3001\u4f18\u5316\u4ee3\u7801\u548c\u6a21\u578b\u3001\u76d1\u63a7\u6027\u80fd\u6307\u6807\u4ee5\u53ca\u786e\u4fdd\u9ad8\u53ef\u7528\u6027\uff0c\u60a8\u53ef\u4ee5\u786e\u4fdd MLflow \u6ee1\u8db3\u751f\u4ea7\u73af\u5883\u7684\u9700\u6c42\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u505a\u4e2a\u672c\u8bfe\u7a0b\u7684\u56de\u987e\u4e0e\u603b\u7ed3<\/p>\n\n\n\n<p>\u5728\u672c\u8bfe\u7a0b\u4e2d\uff0c\u6211\u4eec\u6df1\u5165\u63a2\u8ba8\u4e86 MLflow \u53ca\u5176\u5728\u673a\u5668\u5b66\u4e60\u9879\u76ee\u4e2d\u7684\u5e94\u7528\u3002\u4ee5\u4e0b\u662f\u5173\u952e\u6982\u5ff5\u548c\u4e3b\u9898\u7684\u56de\u987e\u4e0e\u603b\u7ed3\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>MLflow \u7b80\u4ecb<\/strong>\uff1a\u6211\u4eec\u4ecb\u7ecd\u4e86 MLflow \u7684\u80cc\u666f\u3001\u76ee\u7684\u548c\u76ee\u6807\uff0c\u4ee5\u53ca\u4e3a\u4ec0\u4e48\u9009\u62e9 MLflow \u4f5c\u4e3a\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u7ba1\u7406\u5de5\u5177\u3002<\/li>\n\n\n\n<li><strong>MLflow \u4f18\u52bf\u548c\u7279\u70b9<\/strong>\uff1a\u6211\u4eec\u8ba8\u8bba\u4e86 MLflow \u7684\u4e3b\u8981\u4f18\u52bf\uff0c\u5305\u62ec\u5176\u6a21\u5757\u5316\u3001\u53ef\u6269\u5c55\u6027\u3001\u6613\u7528\u6027\u7b49\u7279\u70b9\u3002<\/li>\n\n\n\n<li><strong>MLflow \u7ec4\u4ef6\u4e0e\u67b6\u6784<\/strong>\uff1a\u6211\u4eec\u6df1\u5165\u7814\u7a76\u4e86 MLflow \u7684\u56db\u4e2a\u4e3b\u8981\u7ec4\u4ef6\uff1aTracking\u3001Projects\u3001Models \u548c Model Registry\uff0c\u5e76\u89e3\u91ca\u4e86\u5b83\u4eec\u5728 MLflow \u67b6\u6784\u4e2d\u7684\u89d2\u8272\u3002<\/li>\n\n\n\n<li><strong>\u5b89\u88c5\u4e0e\u914d\u7f6e<\/strong>\uff1a\u6211\u4eec\u4ecb\u7ecd\u4e86\u5982\u4f55\u5b89\u88c5 MLflow \u4ee5\u53ca\u5982\u4f55\u914d\u7f6e\u73af\u5883\u548c\u540e\u7aef\u5b58\u50a8\u3002<\/li>\n\n\n\n<li><strong>MLflow Tracking<\/strong>\uff1a\u6211\u4eec\u8be6\u7ec6\u8ba8\u8bba\u4e86 MLflow Tracking \u7684\u529f\u80fd\u548c\u7528\u6cd5\uff0c\u5305\u62ec\u8bb0\u5f55\u5b9e\u9a8c\u6570\u636e\u3001\u67e5\u8be2\u548c\u6bd4\u8f83\u5b9e\u9a8c\u7ed3\u679c\u3001\u8bb0\u5f55\u53c2\u6570\u3001\u6307\u6807\u548c\u5de5\u4ef6\u7b49\u3002<\/li>\n\n\n\n<li><strong>MLflow Projects<\/strong>\uff1a\u6211\u4eec\u4ecb\u7ecd\u4e86\u5982\u4f55\u521b\u5efa\u3001\u7ba1\u7406\u548c\u8fd0\u884c MLflow \u9879\u76ee\uff0c\u4ee5\u53ca\u9879\u76ee\u4f9d\u8d56\u7ba1\u7406\u3002<\/li>\n\n\n\n<li><strong>MLflow Models<\/strong>\uff1a\u6211\u4eec\u8ba8\u8bba\u4e86\u5982\u4f55\u521b\u5efa\u3001\u4fdd\u5b58\u3001\u90e8\u7f72\u548c\u4f7f\u7528\u4e0d\u540c\u6a21\u578b\u683c\u5f0f\u7684 MLflow \u6a21\u578b\u3002<\/li>\n\n\n\n<li><strong>MLflow Model Registry<\/strong>\uff1a\u6211\u4eec\u4ecb\u7ecd\u4e86 MLflow Model Registry \u7684\u529f\u80fd\uff0c\u5305\u62ec\u6ce8\u518c\u6a21\u578b\u3001\u7248\u672c\u7ba1\u7406\u3001\u6a21\u578b\u751f\u547d\u5468\u671f\u7ba1\u7406\u548c\u534f\u4f5c\u7b49\u3002<\/li>\n\n\n\n<li><strong>\u6846\u67b6\u96c6\u6210\u4e0e\u4e91\u670d\u52a1\u5546\u96c6\u6210<\/strong>\uff1a\u6211\u4eec\u8ba8\u8bba\u4e86\u5982\u4f55\u5c06 MLflow \u96c6\u6210\u5230 TensorFlow\u3001PyTorch \u7b49\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u4ee5\u53ca\u5982\u4f55\u4e0e AWS SageMaker\u3001Azure ML \u7b49\u4e91\u670d\u52a1\u5546\u96c6\u6210\u3002<\/li>\n\n\n\n<li><strong>Jupyter Notebook \u4e0e MLflow<\/strong>\uff1a\u6211\u4eec\u4ecb\u7ecd\u4e86\u5982\u4f55\u5728 Jupyter Notebook \u4e2d\u4f7f\u7528 MLflow\u3002<\/li>\n\n\n\n<li><strong>\u751f\u4ea7\u73af\u5883\u90e8\u7f72\u4e0e\u6700\u4f73\u5b9e\u8df5<\/strong>\uff1a\u6211\u4eec\u8ba8\u8bba\u4e86\u5982\u4f55\u5c06 MLflow Model \u90e8\u7f72\u5230\u751f\u4ea7\u73af\u5883\uff0c\u5e76\u5206\u4eab\u4e86\u4e00\u4e9b\u751f\u4ea7\u73af\u5883\u4e2d\u7684\u6700\u4f73\u5b9e\u8df5\uff0c\u5305\u62ec\u5b89\u5168\u6027\u548c\u6027\u80fd\u4f18\u5316\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u901a\u8fc7\u672c\u8bfe\u7a0b\uff0c\u60a8\u5e94\u8be5\u5df2\u7ecf\u638c\u63e1\u4e86 MLflow \u7684\u6838\u5fc3\u6982\u5ff5\u548c\u529f\u80fd\uff0c\u5e76\u4e86\u89e3\u4e86\u5982\u4f55\u5c06\u5176\u5e94\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u9879\u76ee\u7684\u5b9e\u9645\u573a\u666f\u3002\u5e0c\u671b\u60a8\u80fd\u591f\u5145\u5206\u5229\u7528 MLflow \u7684\u5f3a\u5927\u529f\u80fd\uff0c\u6709\u6548\u5730\u7ba1\u7406\u548c\u4f18\u5316\u60a8\u7684\u673a\u5668\u5b66\u4e60\u5de5\u4f5c\u6d41\u7a0b\u3002<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u4ecb\u7ecd\u4e00\u4e0bmlfow\u7684\u793e\u533a\u548c\u8d44\u6e90<\/p>\n\n\n\n<p>MLflow \u793e\u533a\u662f\u4e00\u4e2a\u6d3b\u8dc3\u4e14\u4e0d\u65ad\u53d1\u5c55\u7684\u751f\u6001\u7cfb\u7edf\uff0c\u4e3a\u7528\u6237\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u8d44\u6e90\u3001\u652f\u6301\u548c\u5408\u4f5c\u673a\u4f1a\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u4e0e MLflow \u793e\u533a\u548c\u8d44\u6e90\u76f8\u5173\u7684\u4fe1\u606f\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>GitHub \u4ed3\u5e93<\/strong>\uff1aMLflow \u7684\u6e90\u4ee3\u7801\u6258\u7ba1\u5728 GitHub \u4e0a\u3002\u60a8\u53ef\u4ee5\u5728\u6b64\u627e\u5230\u6e90\u4ee3\u7801\u3001\u95ee\u9898\u8ddf\u8e2a\u3001\u8d21\u732e\u6307\u5357\u7b49\u4fe1\u606f\u3002GitHub \u4ed3\u5e93\u5730\u5740\uff1a<a href=\"https:\/\/github.com\/mlflow\/mlflow\">https:\/\/github.com\/mlflow\/mlflow<\/a><\/li>\n\n\n\n<li><strong>\u5b98\u65b9\u6587\u6863<\/strong>\uff1aMLflow \u5b98\u65b9\u6587\u6863\u63d0\u4f9b\u4e86\u8be6\u7ec6\u7684\u7528\u6237\u6307\u5357\u3001API \u53c2\u8003\u3001\u5f00\u53d1\u4eba\u5458\u6307\u5357\u7b49\u8d44\u6e90\u3002\u6587\u6863\u5730\u5740\uff1a<a href=\"https:\/\/www.mlflow.org\/docs\/latest\/index.html\">https:\/\/www.mlflow.org\/docs\/latest\/index.html<\/a><\/li>\n\n\n\n<li><strong>\u5b98\u65b9\u535a\u5ba2<\/strong>\uff1aMLflow \u5b98\u65b9\u535a\u5ba2\u53d1\u5e03\u5173\u4e8e\u9879\u76ee\u65b0\u529f\u80fd\u3001\u6848\u4f8b\u7814\u7a76\u3001\u4e8b\u4ef6\u7b49\u65b9\u9762\u7684\u6587\u7ae0\u3002\u535a\u5ba2\u5730\u5740\uff1a<a href=\"https:\/\/medium.com\/mlflow\">https:\/\/medium.com\/mlflow<\/a><\/li>\n\n\n\n<li><strong>\u90ae\u4ef6\u5217\u8868<\/strong>\uff1aMLflow \u793e\u533a\u6709\u4e00\u4e2a Google Group \u90ae\u4ef6\u5217\u8868\uff0c\u60a8\u53ef\u4ee5\u5728\u6b64\u8ba2\u9605\u4ee5\u83b7\u53d6\u6700\u65b0\u4fe1\u606f\u3001\u63d0\u95ee\u548c\u8ba8\u8bba\u3002\u90ae\u4ef6\u5217\u8868\u5730\u5740\uff1a<a href=\"https:\/\/groups.google.com\/a\/databricks.com\/forum\/#!forum\/mlflow-users\">https:\/\/groups.google.com\/a\/databricks.com\/forum\/#!forum\/mlflow-users<\/a><\/li>\n\n\n\n<li><strong>Slack<\/strong>\uff1aMLflow \u793e\u533a\u5728 Slack \u4e0a\u6709\u4e00\u4e2a\u4e13\u95e8\u7684\u9891\u9053\uff0c\u60a8\u53ef\u4ee5\u52a0\u5165\u8be5\u9891\u9053\u4e0e\u5176\u4ed6\u7528\u6237\u548c\u5f00\u53d1\u4eba\u5458\u4ea4\u6d41\u3002Slack \u9891\u9053\u5730\u5740\uff1a<a href=\"https:\/\/tinyurl.com\/y8msy8tb\">https:\/\/tinyurl.com\/y8msy8tb<\/a><\/li>\n\n\n\n<li><strong>Stack Overflow<\/strong>\uff1a\u5728 Stack Overflow \u4e0a\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528 <code>mlflow<\/code> \u6807\u7b7e\u63d0\u95ee\u548c\u5bfb\u6c42\u5e2e\u52a9\u3002\u8bb8\u591a\u95ee\u9898\u5df2\u7ecf\u6709\u4e86\u8be6\u7ec6\u7684\u89e3\u7b54\u3002Stack Overflow \u6807\u7b7e\u5730\u5740\uff1a<a href=\"https:\/\/stackoverflow.com\/questions\/tagged\/mlflow\">https:\/\/stackoverflow.com\/questions\/tagged\/mlflow<\/a><\/li>\n\n\n\n<li><strong>\u793e\u533a\u8d21\u732e<\/strong>\uff1aMLflow \u793e\u533a\u6b22\u8fce\u4efb\u4f55\u4eba\u4e3a\u9879\u76ee\u505a\u51fa\u8d21\u732e\uff0c\u65e0\u8bba\u662f\u4fee\u590d bug\u3001\u589e\u52a0\u65b0\u529f\u80fd\uff0c\u8fd8\u662f\u5b8c\u5584\u6587\u6863\u3002\u60a8\u53ef\u4ee5\u67e5\u770b GitHub \u4ed3\u5e93\u4e2d\u7684\u201c\u8d21\u732e\u201d\u90e8\u5206\u4ee5\u4e86\u89e3\u5982\u4f55\u53c2\u4e0e\u9879\u76ee\uff1a<a href=\"https:\/\/github.com\/mlflow\/mlflow\/blob\/main\/CONTRIBUTING.rst\">https:\/\/github.com\/mlflow\/mlflow\/blob\/main\/CONTRIBUTING.rst<\/a><\/li>\n\n\n\n<li><strong>\u6848\u4f8b\u7814\u7a76\u4e0e\u6559\u7a0b<\/strong>\uff1a\u9664\u4e86\u5b98\u65b9\u8d44\u6e90\uff0c\u8fd8\u6709\u8bb8\u591a\u6765\u81ea\u793e\u533a\u7684\u6559\u7a0b\u3001\u6848\u4f8b\u7814\u7a76\u548c\u6f14\u793a\uff0c\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5404\u79cd\u573a\u666f\u4e2d\u4f7f\u7528 MLflow\u3002\u8fd9\u4e9b\u8d44\u6e90\u53ef\u4ee5\u5728\u535a\u5ba2\u3001GitHub \u4ed3\u5e93\u3001YouTube \u89c6\u9891\u7b49\u5e73\u53f0\u627e\u5230\u3002<\/li>\n<\/ol>\n\n\n\n<p>\u901a\u8fc7\u53c2\u4e0e MLflow \u793e\u533a\u548c\u5229\u7528\u8fd9\u4e9b\u8d44\u6e90\uff0c\u60a8\u53ef\u4ee5\u66f4\u597d\u5730\u4e86\u89e3 MLflow \u7684\u6700\u65b0\u52a8\u6001\uff0c\u89e3\u51b3\u9047\u5230\u7684\u95ee\u9898\uff0c\u5e76\u4e0e\u5176\u4ed6\u7528\u6237\u548c\u5f00\u53d1\u4eba\u5458\u8fdb\u884c\u4ea4\u6d41\u3002\u540c\u65f6\uff0c\u60a8<\/p>\n\n\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/chat.openai.com\/_next\/image?url=https%3A%2F%2Flh3.googleusercontent.com%2Fa%2FAGNmyxbwVdnTP0E2eBqDrujRQjV-wFP12Thr4vFgysVv5A%3Ds96-c&amp;w=64&amp;q=75\" alt=\"gun tei\"\/><\/figure>\n\n\n\n<p>\u8bf7\u7ee7\u7eed<\/p>\n\n\n\n<p>\u7684\u8d21\u732e\u4e5f\u53ef\u4ee5\u5e2e\u52a9\u4e0d\u65ad\u5b8c\u5584\u548c\u53d1\u5c55 MLflow \u793e\u533a\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5efa\u8bae\u7684\u53c2\u4e0e\u65b9\u5f0f\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u63d0\u51fa\u95ee\u9898\u548c\u5efa\u8bae<\/strong>\uff1a\u5728 GitHub \u4ed3\u5e93\u4e2d\u63d0\u4ea4 issue \u53ef\u4ee5\u5e2e\u52a9\u793e\u533a\u53d1\u73b0 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