{"id":1112644,"date":"2025-01-08T17:40:26","date_gmt":"2025-01-08T09:40:26","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1112644.html"},"modified":"2025-01-08T17:40:29","modified_gmt":"2025-01-08T09:40:29","slug":"%e5%a6%82%e4%bd%95%e5%af%bc%e5%87%bapython%e4%b8%ad%e7%9a%84%e6%a8%a1%e5%9e%8b%e5%8f%82%e6%95%b0%e8%ae%be%e7%bd%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1112644.html","title":{"rendered":"\u5982\u4f55\u5bfc\u51fapython\u4e2d\u7684\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25074556\/5f4f1e79-4efa-42f1-b9dc-038a67832272.webp\" alt=\"\u5982\u4f55\u5bfc\u51fapython\u4e2d\u7684\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e\" \/><\/p>\n<p><p> <strong>\u5bfc\u51faPython\u4e2d\u7684\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e<\/strong>\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528pickle\u6a21\u5757\u3001\u4f7f\u7528joblib\u6a21\u5757\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u4fdd\u5b58\u51fd\u6570\u3001\u4f7f\u7528\u4e13\u95e8\u7684<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u5e93\u5982TensorFlow\u6216PyTorch\u81ea\u5e26\u7684\u4fdd\u5b58\u51fd\u6570\u3002<strong>\u63a8\u8350\u7684\u65b9\u6cd5\u662f\u4f7f\u7528pickle\u6a21\u5757\uff0c\u56e0\u4e3a\u5b83\u662fPython\u6807\u51c6\u5e93\u7684\u4e00\u90e8\u5206\uff0c\u4f7f\u7528\u7b80\u5355\u4e14\u529f\u80fd\u5f3a\u5927<\/strong>\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528pickle\u6a21\u5757<\/h3>\n<\/p>\n<p><p>pickle\u6a21\u5757\u662fPython\u6807\u51c6\u5e93\u4e2d\u7528\u4e8e\u5e8f\u5217\u5316\u548c\u53cd\u5e8f\u5217\u5316Python\u5bf9\u8c61\u7684\u6a21\u5757\u3002\u5e8f\u5217\u5316\u662f\u5c06\u5bf9\u8c61\u8f6c\u6362\u4e3a\u5b57\u8282\u6d41\u7684\u8fc7\u7a0b\uff0c\u53cd\u5e8f\u5217\u5316\u5219\u662f\u5c06\u5b57\u8282\u6d41\u8f6c\u6362\u56de\u5bf9\u8c61\u7684\u8fc7\u7a0b\u3002\u4f7f\u7528pickle\u53ef\u4ee5\u975e\u5e38\u65b9\u4fbf\u5730\u4fdd\u5b58\u548c\u52a0\u8f7dPython\u5bf9\u8c61\uff0c\u5305\u62ec\u6a21\u578b\u7684\u53c2\u6570\u8bbe\u7f6e\u3002<\/p>\n<\/p>\n<p><p><strong>\u6b65\u9aa4\u5982\u4e0b\uff1a<\/strong><\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u5bfc\u5165pickle\u6a21\u5757<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pickle<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4fdd\u5b58\u6a21\u578b\u53c2\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">with open(&#39;model_parameters.pkl&#39;, &#39;wb&#39;) as file:<\/p>\n<p>    pickle.dump(model_parameters, file)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u91cc\uff0c<code>model_parameters<\/code>\u662f\u4f60\u8981\u4fdd\u5b58\u7684\u6a21\u578b\u53c2\u6570\u5bf9\u8c61\uff0c<code>&#39;model_parameters.pkl&#39;<\/code>\u662f\u4fdd\u5b58\u7684\u6587\u4ef6\u540d\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u52a0\u8f7d\u6a21\u578b\u53c2\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">with open(&#39;model_parameters.pkl&#39;, &#39;rb&#39;) as file:<\/p>\n<p>    model_parameters = pickle.load(file)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u6837\u5c31\u53ef\u4ee5\u5c06\u4fdd\u5b58\u7684\u6a21\u578b\u53c2\u6570\u52a0\u8f7d\u56de\u6765\uff0c\u4f9b\u540e\u7eed\u4f7f\u7528\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n<p><h3>\u4e8c\u3001\u4f7f\u7528joblib\u6a21\u5757<\/h3>\n<\/p>\n<p><p>joblib\u662f\u4e13\u95e8\u7528\u4e8e\u5904\u7406\u5927\u6570\u636e\u548c\u5927\u578bPython\u5bf9\u8c61\u7684\u6a21\u5757\u3002\u5b83\u5728\u5904\u7406\u5927\u6570\u636e\u96c6\u65f6\u6bd4pickle\u66f4\u9ad8\u6548\uff0c\u7279\u522b\u662f\u5bf9\u4e8enumpy\u6570\u7ec4\u548cscipy\u7a00\u758f\u77e9\u9635\u3002<\/p>\n<\/p>\n<p><p><strong>\u6b65\u9aa4\u5982\u4e0b\uff1a<\/strong><\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u5bfc\u5165joblib\u6a21\u5757<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import joblib<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4fdd\u5b58\u6a21\u578b\u53c2\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">joblib.dump(model_parameters, &#39;model_parameters.pkl&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u52a0\u8f7d\u6a21\u578b\u53c2\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">model_parameters = joblib.load(&#39;model_parameters.pkl&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n<p><h3>\u4e09\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u4fdd\u5b58\u51fd\u6570<\/h3>\n<\/p>\n<p><p>\u5982\u679c\u4f60\u7684\u6a21\u578b\u53c2\u6570\u662f\u4e00\u4e2a\u81ea\u5b9a\u4e49\u7684Python\u5bf9\u8c61\uff0c\u4f60\u4e5f\u53ef\u4ee5\u7f16\u5199\u81ea\u5b9a\u4e49\u7684\u4fdd\u5b58\u548c\u52a0\u8f7d\u51fd\u6570\uff0c\u4f7f\u7528Python\u7684\u6587\u4ef6\u64cd\u4f5c\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><p><strong>\u6b65\u9aa4\u5982\u4e0b\uff1a<\/strong><\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u7f16\u5199\u4fdd\u5b58\u51fd\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def save_parameters(parameters, filename):<\/p>\n<p>    with open(filename, &#39;w&#39;) as file:<\/p>\n<p>        file.write(str(parameters))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u7f16\u5199\u52a0\u8f7d\u51fd\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def load_parameters(filename):<\/p>\n<p>    with open(filename, &#39;r&#39;) as file:<\/p>\n<p>        parameters = eval(file.read())<\/p>\n<p>    return parameters<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u4fdd\u5b58\u548c\u52a0\u8f7d\u53c2\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">save_parameters(model_parameters, &#39;model_parameters.txt&#39;)<\/p>\n<p>model_parameters = load_parameters(&#39;model_parameters.txt&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n<p><h3>\u56db\u3001\u4f7f\u7528\u673a\u5668\u5b66\u4e60\u5e93\u81ea\u5e26\u7684\u4fdd\u5b58\u51fd\u6570<\/h3>\n<\/p>\n<p><p>\u4e00\u4e9b\u5e38\u7528\u7684\u673a\u5668\u5b66\u4e60\u5e93\u5982TensorFlow\u548cPyTorch\u81ea\u5e26\u4e86\u4fdd\u5b58\u548c\u52a0\u8f7d\u6a21\u578b\u53c2\u6570\u7684\u51fd\u6570\uff0c\u8fd9\u4e9b\u51fd\u6570\u901a\u5e38\u66f4\u52a0\u9ad8\u6548\u548c\u65b9\u4fbf\u3002<\/p>\n<\/p>\n<p><p><strong>\u4ee5TensorFlow\u4e3a\u4f8b\uff1a<\/strong><\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u5bfc\u5165TensorFlow<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import tensorflow as tf<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4fdd\u5b58\u6a21\u578b\u53c2\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">model.save(&#39;model_parameters.h5&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u52a0\u8f7d\u6a21\u578b\u53c2\u6570<\/strong>\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">model = tf.keras.models.load_model(&#39;model_parameters.h5&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n<p><h3>\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u5bfc\u51faPython\u4e2d\u7684\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e\uff0c\u5305\u62ec\u4f7f\u7528pickle\u6a21\u5757\u3001joblib\u6a21\u5757\u3001\u81ea\u5b9a\u4e49\u4fdd\u5b58\u51fd\u6570\u4ee5\u53ca\u673a\u5668\u5b66\u4e60\u5e93\u81ea\u5e26\u7684\u4fdd\u5b58\u51fd\u6570\u3002<strong>\u63a8\u8350\u4f7f\u7528pickle\u6a21\u5757\uff0c\u56e0\u4e3a\u5b83\u662fPython\u6807\u51c6\u5e93\u7684\u4e00\u90e8\u5206\uff0c\u4f7f\u7528\u7b80\u5355\u4e14\u529f\u80fd\u5f3a\u5927<\/strong>\u3002\u65e0\u8bba\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\uff0c\u90fd\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u548c\u4f7f\u7528\u573a\u666f\u8fdb\u884c\u9009\u62e9\uff0c\u786e\u4fdd\u6a21\u578b\u53c2\u6570\u80fd\u591f\u65b9\u4fbf\u5730\u4fdd\u5b58\u548c\u52a0\u8f7d\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u6df1\u5165\u5206\u6790\u4e0e\u5bf9\u6bd4<\/h3>\n<\/p>\n<p><h4>Pickle\u6a21\u5757\u7684\u4f18\u70b9\u4e0e\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u6807\u51c6\u5e93\u652f\u6301<\/strong>\uff1a\u65e0\u9700\u989d\u5916\u5b89\u88c5\uff0cPython\u81ea\u5e26\u3002<\/li>\n<li><strong>\u7b80\u5355\u6613\u7528<\/strong>\uff1a\u4ee3\u7801\u7b80\u6d01\uff0c\u5bb9\u6613\u4e0a\u624b\u3002<\/li>\n<li><strong>\u901a\u7528\u6027\u5f3a<\/strong>\uff1a\u9002\u7528\u4e8e\u5927\u591a\u6570Python\u5bf9\u8c61\u3002<\/li>\n<\/ol>\n<p><p><strong>\u7f3a\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u5b89\u5168\u6027\u95ee\u9898<\/strong>\uff1a\u52a0\u8f7dpickle\u6587\u4ef6\u65f6\uff0c\u5982\u679c\u6587\u4ef6\u88ab\u6076\u610f\u7be1\u6539\uff0c\u53ef\u80fd\u4f1a\u6267\u884c\u4efb\u610f\u4ee3\u7801\u3002<\/li>\n<li><strong>\u6548\u7387\u95ee\u9898<\/strong>\uff1a\u5bf9\u4e8e\u5927\u578b\u6570\u636e\u96c6\uff0c\u5e8f\u5217\u5316\u548c\u53cd\u5e8f\u5217\u5316\u901f\u5ea6\u8f83\u6162\u3002<\/li>\n<\/ol>\n<p><h4>Joblib\u6a21\u5757\u7684\u4f18\u70b9\u4e0e\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u9ad8\u6548<\/strong>\uff1a\u5bf9\u5927\u6570\u636e\u548c\u5927\u578b\u5bf9\u8c61\u7684\u5904\u7406\u66f4\u52a0\u9ad8\u6548\u3002<\/li>\n<li><strong>\u5e76\u884c\u8ba1\u7b97\u652f\u6301<\/strong>\uff1a\u652f\u6301\u5e76\u884c\u8ba1\u7b97\uff0c\u9002\u5408\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u3002<\/li>\n<\/ol>\n<p><p><strong>\u7f3a\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u7b2c\u4e09\u65b9\u5e93<\/strong>\uff1a\u9700\u8981\u989d\u5916\u5b89\u88c5\uff0c\u4e0d\u5982pickle\u65b9\u4fbf\u3002<\/li>\n<li><strong>\u901a\u7528\u6027\u7565\u4f4e<\/strong>\uff1a\u4e3b\u8981\u9488\u5bf9numpy\u6570\u7ec4\u548cscipy\u7a00\u758f\u77e9\u9635\uff0c\u5176\u4ed6\u5bf9\u8c61\u652f\u6301\u8f83\u5f31\u3002<\/li>\n<\/ol>\n<p><h4>\u81ea\u5b9a\u4e49\u4fdd\u5b58\u51fd\u6570\u7684\u4f18\u70b9\u4e0e\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u7075\u6d3b\u6027\u9ad8<\/strong>\uff1a\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u81ea\u5b9a\u4e49\u4fdd\u5b58\u548c\u52a0\u8f7d\u903b\u8f91\u3002<\/li>\n<li><strong>\u5b89\u5168\u6027\u9ad8<\/strong>\uff1a\u53ef\u4ee5\u907f\u514dpickle\u7684\u5b89\u5168\u6027\u95ee\u9898\u3002<\/li>\n<\/ol>\n<p><p><strong>\u7f3a\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u590d\u6742\u5ea6\u9ad8<\/strong>\uff1a\u9700\u8981\u7f16\u5199\u81ea\u5b9a\u4e49\u51fd\u6570\uff0c\u589e\u52a0\u4e86\u4ee3\u7801\u590d\u6742\u5ea6\u3002<\/li>\n<li><strong>\u901a\u7528\u6027\u5dee<\/strong>\uff1a\u53ea\u9002\u7528\u4e8e\u7279\u5b9a\u7c7b\u578b\u7684\u5bf9\u8c61\uff0c\u4e0d\u5982pickle\u548cjoblib\u901a\u7528\u3002<\/li>\n<\/ol>\n<p><h4>\u673a\u5668\u5b66\u4e60\u5e93\u81ea\u5e26\u51fd\u6570\u7684\u4f18\u70b9\u4e0e\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u9ad8\u6548<\/strong>\uff1a\u9488\u5bf9\u7279\u5b9a\u5e93\u4f18\u5316\uff0c\u901f\u5ea6\u5feb\uff0c\u6548\u7387\u9ad8\u3002<\/li>\n<li><strong>\u7b80\u6d01<\/strong>\uff1a\u4ee3\u7801\u7b80\u6d01\uff0c\u4f7f\u7528\u65b9\u4fbf\u3002<\/li>\n<li><strong>\u517c\u5bb9\u6027\u597d<\/strong>\uff1a\u4e0e\u5e93\u5185\u5176\u4ed6\u529f\u80fd\u517c\u5bb9\u6027\u597d\uff0c\u6613\u4e8e\u96c6\u6210\u3002<\/li>\n<\/ol>\n<p><p><strong>\u7f3a\u70b9<\/strong>\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u5c40\u9650\u6027<\/strong>\uff1a\u53ea\u80fd\u7528\u4e8e\u7279\u5b9a\u7684\u673a\u5668\u5b66\u4e60\u5e93\uff0c\u901a\u7528\u6027\u5dee\u3002<\/li>\n<li><strong>\u4f9d\u8d56\u6027\u5f3a<\/strong>\uff1a\u4f9d\u8d56\u4e8e\u7279\u5b9a\u7684\u673a\u5668\u5b66\u4e60\u5e93\uff0c\u4e0d\u9002\u7528\u4e8e\u5176\u4ed6\u573a\u666f\u3002<\/li>\n<\/ol>\n<p><h3>\u516d\u3001\u5b9e\u6218\u6848\u4f8b<\/h3>\n<\/p>\n<p><h4>\u6848\u4f8b\u4e00\uff1a\u4f7f\u7528Pickle\u4fdd\u5b58\u548c\u52a0\u8f7d\u6a21\u578b\u53c2\u6570<\/h4>\n<\/p>\n<p><p>\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u7b80\u5355\u7684\u7ebf\u6027\u56de\u5f52\u6a21\u578b\uff0c\u6211\u4eec\u5e0c\u671b\u4fdd\u5b58\u548c\u52a0\u8f7d\u8be5\u6a21\u578b\u7684\u53c2\u6570\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pickle<\/p>\n<p>from sklearn.linear_model import LinearRegression<\/p>\n<h2><strong>\u521b\u5efa\u7ebf\u6027\u56de\u5f52\u6a21\u578b<\/strong><\/h2>\n<p>model = LinearRegression()<\/p>\n<h2><strong>\u8bad\u7ec3\u6a21\u578b<\/strong><\/h2>\n<p>X_tr<a href=\"https:\/\/docs.pingcode.com\/blog\/59162.html\" target=\"_blank\">AI<\/a>n = [[1], [2], [3], [4]]<\/p>\n<p>y_train = [1, 2, 3, 4]<\/p>\n<p>model.fit(X_train, y_train)<\/p>\n<h2><strong>\u83b7\u53d6\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>model_parameters = model.get_params()<\/p>\n<h2><strong>\u4fdd\u5b58\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>with open(&#39;linear_regression_parameters.pkl&#39;, &#39;wb&#39;) as file:<\/p>\n<p>    pickle.dump(model_parameters, file)<\/p>\n<h2><strong>\u52a0\u8f7d\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>with open(&#39;linear_regression_parameters.pkl&#39;, &#39;rb&#39;) as file:<\/p>\n<p>    loaded_parameters = pickle.load(file)<\/p>\n<h2><strong>\u8bbe\u7f6e\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>model.set_params(loaded_parameters)<\/p>\n<h2><strong>\u9a8c\u8bc1\u6a21\u578b\u53c2\u6570\u662f\u5426\u6b63\u786e\u52a0\u8f7d<\/strong><\/h2>\n<p>print(model.get_params())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u6848\u4f8b\u4e8c\uff1a\u4f7f\u7528Joblib\u4fdd\u5b58\u548c\u52a0\u8f7d\u6a21\u578b\u53c2\u6570<\/h4>\n<\/p>\n<p><pre><code class=\"language-python\">import joblib<\/p>\n<p>from sklearn.linear_model import LinearRegression<\/p>\n<h2><strong>\u521b\u5efa\u7ebf\u6027\u56de\u5f52\u6a21\u578b<\/strong><\/h2>\n<p>model = LinearRegression()<\/p>\n<h2><strong>\u8bad\u7ec3\u6a21\u578b<\/strong><\/h2>\n<p>X_train = [[1], [2], [3], [4]]<\/p>\n<p>y_train = [1, 2, 3, 4]<\/p>\n<p>model.fit(X_train, y_train)<\/p>\n<h2><strong>\u83b7\u53d6\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>model_parameters = model.get_params()<\/p>\n<h2><strong>\u4fdd\u5b58\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>joblib.dump(model_parameters, &#39;linear_regression_parameters.pkl&#39;)<\/p>\n<h2><strong>\u52a0\u8f7d\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>loaded_parameters = joblib.load(&#39;linear_regression_parameters.pkl&#39;)<\/p>\n<h2><strong>\u8bbe\u7f6e\u6a21\u578b\u53c2\u6570<\/strong><\/h2>\n<p>model.set_params(loaded_parameters)<\/p>\n<h2><strong>\u9a8c\u8bc1\u6a21\u578b\u53c2\u6570\u662f\u5426\u6b63\u786e\u52a0\u8f7d<\/strong><\/h2>\n<p>print(model.get_params())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e03\u3001\u6700\u4f73\u5b9e\u8df5<\/h3>\n<\/p>\n<ol>\n<li><strong>\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5<\/strong>\uff1a\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0cpickle\u9002\u7528\u4e8e\u4e00\u822c\u573a\u666f\uff0cjoblib\u9002\u7528\u4e8e\u5927\u6570\u636e\u96c6\uff0c\u81ea\u5b9a\u4e49\u51fd\u6570\u9002\u7528\u4e8e\u7279\u6b8a\u9700\u6c42\uff0c\u673a\u5668\u5b66\u4e60\u5e93\u81ea\u5e26\u51fd\u6570\u9002\u7528\u4e8e\u7279\u5b9a\u5e93\u3002<\/li>\n<li><strong>\u5b89\u5168\u6027\u8003\u8651<\/strong>\uff1a\u907f\u514d\u4f7f\u7528\u4e0d\u53ef\u4fe1\u7684pickle\u6587\u4ef6\uff0c\u786e\u4fdd\u6587\u4ef6\u6765\u6e90\u5b89\u5168\u3002\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u6216joblib\u4ee5\u63d0\u9ad8\u5b89\u5168\u6027\u3002<\/li>\n<li><strong>\u6027\u80fd\u4f18\u5316<\/strong>\uff1a\u5bf9\u4e8e\u5927\u6570\u636e\u96c6\uff0c\u4f18\u5148\u9009\u62e9\u6027\u80fd\u66f4\u9ad8\u7684joblib\u6a21\u5757\u3002\u5bf9\u4e8e\u7279\u5b9a\u673a\u5668\u5b66\u4e60\u5e93\uff0c\u4f7f\u7528\u5e93\u81ea\u5e26\u7684\u4fdd\u5b58\u51fd\u6570\u3002<\/li>\n<li><strong>\u7248\u672c\u63a7\u5236<\/strong>\uff1a\u4fdd\u5b58\u548c\u52a0\u8f7d\u6a21\u578b\u53c2\u6570\u65f6\uff0c\u6ce8\u610f\u7248\u672c\u517c\u5bb9\u6027\u95ee\u9898\u3002\u4e0d\u540c\u7248\u672c\u7684\u5e93\u53ef\u80fd\u5b58\u5728\u4e0d\u517c\u5bb9\u60c5\u51b5\uff0c\u786e\u4fdd\u4fdd\u5b58\u548c\u52a0\u8f7d\u65f6\u4f7f\u7528\u76f8\u540c\u7248\u672c\u7684\u5e93\u3002<\/li>\n<li><strong>\u6587\u6863\u548c\u6ce8\u91ca<\/strong>\uff1a\u5728\u4ee3\u7801\u4e2d\u6dfb\u52a0\u8be6\u7ec6\u7684\u6ce8\u91ca\u548c\u6587\u6863\uff0c\u8bf4\u660e\u4fdd\u5b58\u548c\u52a0\u8f7d\u6a21\u578b\u53c2\u6570\u7684\u65b9\u6cd5\u548c\u6ce8\u610f\u4e8b\u9879\uff0c\u65b9\u4fbf\u540e\u7eed\u7ef4\u62a4\u548c\u4f7f\u7528\u3002<\/li>\n<\/ol>\n<p><h3>\u516b\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u672c\u6587\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u5bfc\u51faPython\u4e2d\u7684\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e\uff0c\u5305\u62ec\u4f7f\u7528pickle\u6a21\u5757\u3001joblib\u6a21\u5757\u3001\u81ea\u5b9a\u4e49\u4fdd\u5b58\u51fd\u6570\u4ee5\u53ca\u673a\u5668\u5b66\u4e60\u5e93\u81ea\u5e26\u7684\u4fdd\u5b58\u51fd\u6570\u3002\u901a\u8fc7\u5bf9\u6bd4\u4e0d\u540c\u65b9\u6cd5\u7684\u4f18\u7f3a\u70b9\uff0c\u63a8\u8350\u4f7f\u7528pickle\u6a21\u5757\uff0c\u56e0\u4e3a\u5b83\u662fPython\u6807\u51c6\u5e93\u7684\u4e00\u90e8\u5206\uff0c\u4f7f\u7528\u7b80\u5355\u4e14\u529f\u80fd\u5f3a\u5927\u3002\u5728\u5177\u4f53\u5b9e\u8df5\u4e2d\uff0c\u6839\u636e\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u5e76\u6ce8\u610f\u5b89\u5168\u6027\u548c\u6027\u80fd\u4f18\u5316\uff0c\u786e\u4fdd\u6a21\u578b\u53c2\u6570\u80fd\u591f\u65b9\u4fbf\u3001\u5b89\u5168\u5730\u4fdd\u5b58\u548c\u52a0\u8f7d\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u4fdd\u5b58\u548c\u5bfc\u51fa\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u5bfc\u51fa\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e\u901a\u5e38\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528pickle\u6216joblib\u5e93\u6765\u5b9e\u73b0\u3002\u8fd9\u4e9b\u5e93\u5141\u8bb8\u4f60\u5c06\u6a21\u578b\u53ca\u5176\u53c2\u6570\u5e8f\u5217\u5316\u4e3a\u6587\u4ef6\uff0c\u4fbf\u4e8e\u540e\u7eed\u52a0\u8f7d\u548c\u4f7f\u7528\u3002\u4f7f\u7528\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<pre><code class=\"language-python\">import pickle\n\n# \u5047\u8bbe\u6a21\u578b\u662f\u4e00\u4e2a\u8bad\u7ec3\u597d\u7684scikit-learn\u6a21\u578b\nmodel = ...  # \u4f60\u7684\u6a21\u578b\nwith open(&#39;model_parameters.pkl&#39;, &#39;wb&#39;) as file:\n    pickle.dump(model, file)\n<\/code><\/pre>\n<p>\u6b64\u5916\uff0cTensorFlow\u548cPyTorch\u7b49\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u4e5f\u63d0\u4f9b\u4e86\u5185\u7f6e\u7684\u6a21\u578b\u4fdd\u5b58\u529f\u80fd\uff0c\u65b9\u4fbf\u4f60\u5bfc\u51fa\u6a21\u578b\u53ca\u5176\u6743\u91cd\u3002<\/p>\n<p><strong>\u5bfc\u51fa\u7684\u6a21\u578b\u53c2\u6570\u53ef\u4ee5\u5728\u4e0d\u540c\u73af\u5883\u4e2d\u4f7f\u7528\u5417\uff1f<\/strong><br \/>\u662f\u7684\uff0c\u5bfc\u51fa\u7684\u6a21\u578b\u53c2\u6570\u53ef\u4ee5\u5728\u4e0d\u540c\u7684Python\u73af\u5883\u4e2d\u4f7f\u7528\uff0c\u53ea\u8981\u786e\u4fdd\u6240\u4f7f\u7528\u7684\u5e93\u7248\u672c\u4e00\u81f4\u3002\u8fd9\u610f\u5473\u7740\uff0c\u5982\u679c\u4f60\u5728\u4e00\u4e2a\u73af\u5883\u4e2d\u8bad\u7ec3\u5e76\u4fdd\u5b58\u4e86\u6a21\u578b\u53c2\u6570\uff0c\u4fbf\u53ef\u4ee5\u5728\u53e6\u4e00\u4e2a\u73af\u5883\u4e2d\u52a0\u8f7d\u8fd9\u4e9b\u53c2\u6570\uff0c\u53ea\u9700\u786e\u4fdd\u5e93\u7684\u517c\u5bb9\u6027\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u76f8\u540c\u7248\u672c\u7684scikit-learn\u6216TensorFlow\u53ef\u4ee5\u786e\u4fdd\u6a21\u578b\u7684\u5b8c\u6574\u6027\u3002<\/p>\n<p><strong>\u5982\u4f55\u68c0\u67e5\u5bfc\u51fa\u7684\u6a21\u578b\u53c2\u6570\u662f\u5426\u5b8c\u6574\uff1f<\/strong><br \/>\u5bfc\u51fa\u7684\u6a21\u578b\u53c2\u6570\u53ef\u4ee5\u901a\u8fc7\u52a0\u8f7d\u6a21\u578b\u540e\u8fdb\u884c\u7b80\u5355\u7684\u9a8c\u8bc1\u6765\u68c0\u67e5\u5176\u5b8c\u6574\u6027\u3002\u53ef\u4ee5\u5c1d\u8bd5\u8fdb\u884c\u9884\u6d4b\u5e76\u4e0e\u539f\u59cb\u6a21\u578b\u7684\u8f93\u51fa\u8fdb\u884c\u6bd4\u8f83\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<pre><code class=\"language-python\"># \u52a0\u8f7d\u6a21\u578b\nwith open(&#39;model_parameters.pkl&#39;, &#39;rb&#39;) as file:\n    loaded_model = pickle.load(file)\n\n# \u6bd4\u8f83\u9884\u6d4b\u7ed3\u679c\noriginal_prediction = model.predict(X_test)\nloaded_prediction = loaded_model.predict(X_test)\n\n# \u68c0\u67e5\u662f\u5426\u76f8\u540c\nassert (original_prediction == loaded_prediction).all(), &quot;\u6a21\u578b\u53c2\u6570\u4e0d\u4e00\u81f4&quot;\n<\/code><\/pre>\n<p>\u8fd9\u79cd\u65b9\u5f0f\u80fd\u591f\u786e\u4fdd\u5bfc\u51fa\u7684\u53c2\u6570\u5728\u52a0\u8f7d\u540e\u4ecd\u7136\u4fdd\u6301\u6709\u6548\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5bfc\u51faPython\u4e2d\u7684\u6a21\u578b\u53c2\u6570\u8bbe\u7f6e\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528pickle\u6a21\u5757\u3001\u4f7f\u7528joblib\u6a21\u5757\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u4fdd\u5b58 [&hellip;]","protected":false},"author":3,"featured_media":1112650,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1112644"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1112644"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1112644\/revisions"}],"predecessor-version":[{"id":1112656,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1112644\/revisions\/1112656"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1112650"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1112644"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1112644"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1112644"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}