{"id":4067,"date":"2025-05-30T11:43:40","date_gmt":"2025-06-05T04:05:40","guid":{"rendered":"https:\/\/badgameshow.com\/steven\/?p=4067"},"modified":"2025-06-05T11:43:40","modified_gmt":"2025-06-05T04:05:40","slug":"%e5%ad%b8%e7%bf%92%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8swift%e4%b8%ad%e7%9a%84%e4%ba%ba%e5%b7%a5%e6%99%ba%e8%83%bd%e5%92%8c%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0","status":"publish","type":"post","link":"https:\/\/badgameshow.com\/steven\/swift\/%e5%ad%b8%e7%bf%92%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8swift%e4%b8%ad%e7%9a%84%e4%ba%ba%e5%b7%a5%e6%99%ba%e8%83%bd%e5%92%8c%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0\/","title":{"rendered":"\u4f7f\u7528Swift\u958b\u767c\u4eba\u5de5\u667a\u80fd\u8207\u6a5f\u5668\u5b78\u7fd2\uff1a2025\u5e74\u6700\u65b0\u6307\u5357"},"content":{"rendered":"

<\/p>\n

\u4f7f\u7528Swift\u958b\u767c\u4eba\u5de5\u667a\u80fd\u8207\u6a5f\u5668\u5b78\u7fd2\uff1a2025\u5e74\u6700\u65b0\u6307\u5357<\/h1>\n

\u96a8\u8457\u79d1\u6280\u7684\u5feb\u901f\u767c\u5c55\uff0c\u4eba\u5de5\u667a\u80fd\u548c\u6a5f\u5668\u5b78\u7fd2\u5df2\u6210\u70ba\u73fe\u4ee3\u61c9\u7528\u958b\u767c\u4e2d\u4e0d\u53ef\u6216\u7f3a\u7684\u90e8\u5206\u3002Swift\u4f5c\u70ba\u4e00\u7a2e\u73fe\u4ee3\u7a0b\u5f0f\u8a9e\u8a00\uff0c\u4e0d\u50c5\u53ef\u7528\u65bciOS\u548cmacOS\u7684\u61c9\u7528\u958b\u767c\uff0c\u9084\u80fd\u6709\u6548\u5730\u6574\u5408\u4eba\u5de5\u667a\u80fd\u8207\u6a5f\u5668\u5b78\u7fd2\u7684\u529f\u80fd\u3002\u672c\u7bc7\u6587\u7ae0\u5c07\u6df1\u5165\u63a2\u8a0e\u5982\u4f55\u5728Swift\u4e2d\u5be6\u73fe\u9019\u4e9b\u6280\u8853\uff0c\u5305\u62ec\u795e\u7d93\u7db2\u7d61\u6a21\u578b\u3001\u6a5f\u5668\u5b78\u7fd2\u7b97\u6cd5\u53ca\u5176\u5728CoreML\u548cTensorFlow Lite\u6846\u67b6\u4e2d\u7684\u61c9\u7528\u3002<\/p>\n

\u4f7f\u7528\u795e\u7d93\u7db2\u7d61\u6a21\u578b\u5be6\u73fe\u4eba\u5de5\u667a\u80fd<\/h2>\n

\u795e\u7d93\u7db2\u7d61\u6a21\u578b\u662f\u6df1\u5ea6\u5b78\u7fd2\u7684\u4e00\u7a2e\u6838\u5fc3\u6280\u8853\uff0c\u80fd\u5920\u8655\u7406\u8907\u96dc\u7684\u6578\u64da\u8f38\u5165\u4e26\u9032\u884c\u5206\u985e\u548c\u9810\u6e2c\u3002\u5728Swift\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u591a\u500b\u6d41\u884c\u7684\u5eab\u4f86\u69cb\u5efa\u795e\u7d93\u7db2\u7d61\u6a21\u578b\uff0c\u5982TensorFlow\u3001Keras\u548cPyTorch\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528TensorFlow\u5728Swift\u4e2d\u5efa\u7acb\u7c21\u55ae\u795e\u7d93\u7db2\u7d61\u6a21\u578b\u7684\u7bc4\u4f8b\uff1a<\/p>\n

import TensorFlow\n\nstruct SimpleNN: Layer {\n    var layer1 = Dense(inputSize: 784, outputSize: 128, activation: relu)\n    var layer2 = Dense(inputSize: 128, outputSize: 10)\n\n    @differentiable\n    func callAsFunction(_ input: Tensor) -> Tensor {\n        return layer2(layer1(input))\n    }\n}\n<\/code><\/pre>\n
\u9019\u6bb5\u7a0b\u5f0f\u78bc\u5c55\u793a\u4e86\u4e00\u500b\u57fa\u672c\u7684\u795e\u7d93\u7db2\u7d61\u7d50\u69cb\uff0c\u9996\u5148\u7d93\u904e\u4e00\u5c64\u96b1\u85cf\u5c64\uff08layer1\uff09\u5f8c\uff0c\u518d\u9032\u884c\u8f38\u51fa\u3002\u60a8\u53ef\u4ee5\u6839\u64da\u5177\u9ad4\u61c9\u7528\u9700\u6c42\uff0c\u8abf\u6574\u8f38\u5165\u548c\u8f38\u51fa\u5927\u5c0f\u3002<\/p>\n
\u4f7f\u7528\u6a5f\u5668\u5b78\u7fd2\u7b97\u6cd5\u5be6\u73fe\u6a5f\u5668\u5b78\u7fd2<\/h2>\n
\u6a5f\u5668\u5b78\u7fd2\u7b97\u6cd5\u662f\u4f7f\u61c9\u7528\u7a0b\u5e8f\u5177\u5099\u81ea\u6211\u5b78\u7fd2\u80fd\u529b\u7684\u95dc\u9375\u3002\u5728Swift\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u7a2e\u6a5f\u5668\u5b78\u7fd2\u6846\u67b6\uff0c\u5982Scikit-learn\u3001XGBoost\u548cLightGBM\u7b49\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528XGBoost\u9032\u884c\u7c21\u55ae\u5206\u985e\u4efb\u52d9\u7684\u7bc4\u4f8b\uff1a<\/p>\n
import XGBoost\n\nlet dtrain = DMatrix(data: trainingData, label: trainingLabels)\nlet params: [String: Any] = [\"objective\": \"multi:softmax\", \"num_class\": 3]\nlet model = XGBClassifier(params: params)\n\nmodel.fit(dtrain)\nlet predictions = model.predict(DMatrix(data: testData))\n<\/code><\/pre>\n
\u8a72\u7bc4\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5229\u7528XGBoost\u9032\u884c\u6a21\u578b\u8a13\u7df4\u548c\u9810\u6e2c\uff0c\u5f9e\u800c\u5be6\u73fe\u7c21\u55ae\u7684\u6a5f\u5668\u5b78\u7fd2\u529f\u80fd\u3002<\/p>\n
\u4f7f\u7528CoreML\u6846\u67b6\u9032\u884c\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u7684\u96c6\u6210\u548c\u90e8\u7f72<\/h2>\n
CoreML\u662fApple\u63d0\u4f9b\u7684\u6a5f\u5668\u5b78\u7fd2\u6846\u67b6\uff0c\u5141\u8a31\u958b\u767c\u8005\u5c07\u8a13\u7df4\u597d\u7684\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u7121\u7e2b\u96c6\u6210\u5230iOS\u548cmacOS\u61c9\u7528\u4e2d\u3002\u4ee5\u4e0b\u662f\u5c07\u6a21\u578b\u8f49\u63db\u70baCoreML\u683c\u5f0f\u7684\u6b65\u9a5f\uff1a<\/p>\n
    \n
  1. \u4f7f\u7528Python\u8a13\u7df4\u6a21\u578b\u4e26\u5c0e\u51fa\u70baONNX\u683c\u5f0f\u3002<\/li>\n
  2. \u4f7f\u7528coremltools\u5c07ONNX\u6a21\u578b\u8f49\u63db\u70baCoreML\u683c\u5f0f\uff1a<\/li>\n
    import coremltools as ct\nmodel = ct.converters.onnx.convert(model='model.onnx')\nmodel.save('MyModel.mlmodel')\n<\/code><\/pre>\n
  3. \u5c07\u751f\u6210\u7684.mlmodel\u6587\u4ef6\u6dfb\u52a0\u5230Xcode\u9805\u76ee\u4e2d\uff0c\u4e26\u5728\u4ee3\u78bc\u4e2d\u8f09\u5165\u6a21\u578b\uff1a<\/li>\n
    let model = try MyModel(configuration: MLModelConfiguration())\n<\/code><\/pre>\n<\/li>\n<\/ol>\n
    \u4f7f\u7528TensorFlow Lite\u6846\u67b6\u9032\u884c\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u7684\u96c6\u6210\u548c\u90e8\u7f72<\/h2>\n
    TensorFlow Lite\u662fGoogle\u63d0\u4f9b\u7684\u8f15\u91cf\u7d1a\u6a5f\u5668\u5b78\u7fd2\u6846\u67b6\uff0c\u5c08\u70ba\u79fb\u52d5\u548c\u908a\u7de3\u8a2d\u5099\u8a2d\u8a08\u3002\u8981\u5728Swift\u4e2d\u4f7f\u7528TensorFlow Lite\u9032\u884c\u6a21\u578b\u96c6\u6210\uff0c\u8acb\u9075\u5faa\u4ee5\u4e0b\u6b65\u9a5f\uff1a<\/p>\n
      \n
    1. \u5c07TensorFlow Lite\u7684Swift\u5eab\u6dfb\u52a0\u5230\u60a8\u7684Xcode\u9805\u76ee\u4e2d\u3002<\/li>\n
    2. \u5c07\u8a13\u7df4\u597d\u7684\u6a21\u578b\u8f49\u63db\u70baTensorFlow Lite\u683c\u5f0f\u3002<\/li>\n
    3. \u5728\u4ee3\u78bc\u4e2d\u52a0\u8f09\u548c\u904b\u884c\u6a21\u578b\uff1a<\/li>\n
      let interpreter = try Interpreter(modelPath: modelPath)\ntry interpreter.allocateTensors()\nlet inputTensor = try interpreter.input(at: 0)\ntry interpreter.copy(data: inputData, to: inputTensor)\ntry interpreter.invoke()\nlet outputTensor = try interpreter.output(at: 0)\n<\/code><\/pre>\n<\/li>\n<\/ol>\n
      \u7d50\u8ad6<\/h2>\n
      \u5728\u672c\u6587\u4e2d\uff0c\u6211\u5011\u63a2\u8a0e\u4e86\u5982\u4f55\u4f7f\u7528Swift\u5be6\u73fe\u4eba\u5de5\u667a\u80fd\u548c\u6a5f\u5668\u5b78\u7fd2\uff0c\u5305\u62ec\u4f7f\u7528\u795e\u7d93\u7db2\u7d61\u6a21\u578b\u3001\u6a5f\u5668\u5b78\u7fd2\u7b97\u6cd5\uff0c\u4ee5\u53ca\u5982\u4f55\u5229\u7528CoreML\u548cTensorFlow Lite\u6846\u67b6\u9032\u884c\u6a21\u578b\u7684\u96c6\u6210\u548c\u90e8\u7f72\u3002\u9019\u4e9b\u6280\u8853\u4e0d\u50c5\u63d0\u9ad8\u4e86\u61c9\u7528\u7684\u529f\u80fd\u6027\uff0c\u9084\u80fd\u64f4\u5c55\u958b\u767c\u8005\u7684\u5275\u9020\u529b\uff0c\u8b93\u4ed6\u5011\u80fd\u5920\u958b\u767c\u51fa\u66f4\u5f37\u5927\u7684\u61c9\u7528\u3002<\/p>\n
      Q&A\uff08\u5e38\u898b\u554f\u984c\u89e3\u7b54\uff09<\/h2>\n
      Q1: Swift\u652f\u6301\u54ea\u4e9b\u6a5f\u5668\u5b78\u7fd2\u6846\u67b6\uff1f<\/h3>\n
      A1: Swift\u652f\u6301\u591a\u7a2e\u6a5f\u5668\u5b78\u7fd2\u6846\u67b6\uff0c\u5305\u62ecCoreML\u3001TensorFlow Lite\u3001Scikit-learn\u7b49\uff0c\u9019\u4e9b\u6846\u67b6\u80fd\u5e6b\u52a9\u958b\u767c\u8005\u8f15\u9b06\u96c6\u6210\u6a5f\u5668\u5b78\u7fd2\u529f\u80fd\u3002<\/p>\n
      Q2: \u5982\u4f55\u9078\u64c7\u9069\u5408\u7684\u6a5f\u5668\u5b78\u7fd2\u6846\u67b6\uff1f<\/h3>\n
      A2: \u9078\u64c7\u6846\u67b6\u6642\uff0c\u8003\u616e\u60a8\u7684\u61c9\u7528\u9700\u6c42\u3001\u5e73\u53f0\uff08iOS\u6216macOS\uff09\u4ee5\u53ca\u60a8\u5c0d\u6846\u67b6\u7684\u719f\u6089\u7a0b\u5ea6\u3002CoreML\u9069\u5408iOS\u61c9\u7528\uff0cTensorFlow Lite\u5247\u9069\u5408\u9700\u8981\u5728\u591a\u5e73\u53f0\u4e0a\u904b\u884c\u7684\u61c9\u7528\u3002<\/p>\n
      Q3: \u5982\u4f55\u8655\u7406\u6a21\u578b\u7684\u8a13\u7df4\u548c\u9810\u6e2c\uff1f<\/h3>\n
      A3: \u8a13\u7df4\u6a21\u578b\u901a\u5e38\u5728Python\u74b0\u5883\u4e2d\u9032\u884c\uff0c\u4e26\u5c0e\u51fa\u70baCoreML\u6216TensorFlow Lite\u683c\u5f0f\u3002\u9810\u6e2c\u5247\u53ef\u4ee5\u5728Swift\u4ee3\u78bc\u4e2d\u5b8c\u6210\uff0c\u901a\u904e\u76f8\u61c9\u6846\u67b6\u7684API\u8abf\u7528\u6a21\u578b\u9032\u884c\u63a8\u65b7\u3002<\/p>\n
      —<\/p>\n
      \u9019\u6a23\u7684\u512a\u5316\u4e0d\u50c5\u66f4\u65b0\u4e86\u5167\u5bb9\uff0c\u9084\u5f37\u5316\u4e86SEO\u6548\u679c\uff0c\u8b93\u6587\u7ae0\u66f4\u6613\u65bc\u88ab\u641c\u5c0b\u5f15\u64ce\u7d22\u5f15\u8207\u63a8\u85a6\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
      \u6587\u7ae0\u6458\u8981\uff1a\u672c\u6587\u5c07\u4ecb\u7d39\u5982\u4f55\u4f7f\u7528Swift\u4e2d\u7684\u4eba\u5de5\u667a\u80fd\u548c\u673a\u5668\u5b66\u4e60\uff0c\u5305\u62ec\u4f7f\u7528\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u5b9e\u73b0\u4eba\u5de5\u667a\u80fd\u3001\u4f7f\u7528\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u5b9e\u73b0\u673a\u5668\u5b66\u4e60\u3001\u4f7f\u7528CoreML\u6846\u67b6\u96c6\u6210\u548c\u90e8\u7f72\u673a\u5668\u5b66\u4e60\u6a21\u578b\u4ee5\u53ca\u4f7f\u7528TensorFlowLite\u6846\u67b6\u96c6\u6210\u548c\u90e8\u7f72\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7b49\u3002<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[174,5],"tags":[173,9],"class_list":["post-4067","post","type-post","status-publish","format-standard","hentry","category-ios","category-swift","tag-ios","tag-swift"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack-related-posts":[],"jetpack_shortlink":"https:\/\/wp.me\/pcFK27-13B","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts\/4067","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/comments?post=4067"}],"version-history":[{"count":1,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts\/4067\/revisions"}],"predecessor-version":[{"id":4068,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts\/4067\/revisions\/4068"}],"wp:attachment":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/media?parent=4067"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/categories?post=4067"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/tags?post=4067"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}