{"id":62141,"date":"2026-01-19T12:18:10","date_gmt":"2026-01-19T04:18:10","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/62141.html"},"modified":"2026-01-19T12:18:10","modified_gmt":"2026-01-19T04:18:10","slug":"ai%e5%bc%80%e5%8f%91%e7%8e%af%e5%a2%83%e6%90%ad%e5%bb%ba%ef%bc%88%e4%b8%89%ef%bc%89%ef%bc%9apytorch-tensorflow%e9%85%8d%e7%bd%ae%e4%b8%8e%e7%94%b5%e7%a7%91%e9%87%91%e4%bb%93-kes-python-%e8%bf%9e","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/62141.html","title":{"rendered":"AI\u5f00\u53d1\u73af\u5883\u642d\u5efa\uff08\u4e09\uff09\uff1aPyTorch\/TensorFlow\u914d\u7f6e\u4e0e\u7535\u79d1\u91d1\u4ed3 KES-Python \u8fde\u63a5\u5b9e\u6218"},"content":{"rendered":"

\u73af\u5883\u642d\u5efa（\u4e09）：PyTorch\/TensorFlow\u914d\u7f6e\u4e0e\u7535\u79d1\u91d1\u4ed3 KES-Python \u8fde\u63a5\u5b9e\u6218<\/h2>\n

\u54b1\u4eec\u8fd9 100 \u5929\u7684 AI \u5f81\u7a0b，\u524d\u51e0\u5929\u7b97\u662f\u628a\u5730\u57fa\u6253\u597d\u4e86\u3002\u4eca\u5929\u7b2c 6 \u5929，\u54b1\u4eec\u8981\u5e72\u4ef6\u5927\u4e8b：\u628a AI \u7684\u201c\u53d1\u52a8\u673a\u201d（PyTorch\/TensorFlow）\u548c\u201c\u6cb9\u7bb1\u201d（\u7535\u79d1\u91d1\u4ed3 KingbaseES）\u6b63\u5f0f\u4e32\u8054\u8d77\u6765\u3002<\/p>\n

\u4f5c\u4e3a\u67b6\u6784\u5e08，\u6211\u6700\u6015\u770b\u5230\u7684\u5c31\u662f\u201c\u5b9e\u9a8c\u5ba4\u4ee3\u7801\u201d\u2014\u2014\u5728\u672c\u5730\u5237\u4e2a\u5206\u5f88\u6f02\u4eae，\u4e00\u4e0a\u7ebf\u53d1\u73b0\u6570\u636e\u8bfb\u4e0d\u52a8，\u6a21\u578b\u5582\u4e0d\u9971\u3002\u4eca\u5929，\u6211\u4eec\u5c31\u6765\u4e00\u6b21\u6b63\u89c4\u519b\u7684\u914d\u7f6e\u5b9e\u6218\u3002<\/p>\n

\n

\u58f9：\u9009\u53d1\u52a8\u673a\u8fd8\u662f\u9009\u53d8\u901f\u7bb1？PyTorch \u4e0e TensorFlow<\/h3>\n

\u5728\u67b6\u6784\u9009\u578b\u4e0a，PyTorch \u5c31\u50cf\u662f\u4e00\u8f86\u624b\u52a8\u6321\u7684\u8d8a\u91ce\u8f66，\u903b\u8f91\u900f\u660e，\u8c03\u8bd5\u8d77\u6765\u5982\u6307\u638c，\u662f\u73b0\u5728\u79d1\u7814\u548c\u4e3b\u6d41\u5927\u6a21\u578b\u7684\u9996\u9009；TensorFlow \u5219\u66f4\u50cf\u662f\u4e00\u8f86\u91cd\u578b\u5de5\u4e1a\u5361\u8f66，\u867d\u7136\u5b66\u4e60\u66f2\u7ebf\u9661\u4e00\u70b9，\u4f46\u5728\u5de5\u4e1a\u7ea7\u90e8\u7f72\u4e0a\u975e\u5e38\u624e\u5b9e\u3002<\/p>\n

\u65e0\u8bba\u4f60\u9009\u54ea\u4e2a，\u6838\u5fc3\u903b\u8f91\u662f\u4e00\u6837\u7684：\u8ba9\u6846\u67b6\u80fd\u591f\u9ad8\u6548\u5730\u4ece\u6570\u636e\u5e93\u91cc\u201c\u5438\u201d\u6570\u636e\u3002<\/p>\n

\n

\u8d30：Conda \u73af\u5883\u4e0b\u7684\u201c\u519b\u68b0\u5e93\u201d\u914d\u7f6e<\/h3>\n

\u54b1\u4eec\u7ee7\u7eed\u5728\u4e4b\u524d\u7684 KES_AI_Lab \u73af\u5883\u91cc\u64cd\u4f5c\u3002\u522b\u5728\u7cfb\u7edf\u73af\u5883\u91cc\u4e71\u641e，\u90a3\u662f\u5bf9\u81ea\u5df1\u67b6\u6784\u751f\u547d\u7684\u8d1f\u8d23\u3002<\/p>\n

\u914d\u7f6e\u7684\u6838\u5fc3\u6b65\u9aa4\u5982\u4e0b：<\/p>\n

  • \u5b89\u88c5\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6：\u5efa\u8bae\u6839\u636e\u4f60\u7684\u663e\u5361（CUDA）\u7248\u672c\u9009\u62e9\u5bf9\u5e94\u7684 PyTorch\u3002<\/li>\n
  • \u786e\u8ba4\u6570\u636e\u5e93\u9a71\u52a8：\u518d\u6b21\u68c0\u67e5 ksycopg2 \u662f\u5426\u5c31\u7eea\u3002\u5982\u679c\u6ca1\u88c5，\u8d76\u7d27\u53bb\u7535\u79d1\u91d1\u4ed3\u9a71\u52a8\u4e0b\u8f7d\u9875\u9762\u627e\u5bf9\u5e94\u7684\u5305\u3002<\/li>\n
    \n

    \u53c1：\u5b9e\u6218：\u628a KES \u7684\u6570\u636e\u5582\u7ed9\u795e\u7ecf\u7f51\u7edc<\/h3>\n

    \u5f88\u591a\u65b0\u624b\u4e60\u60ef\u628a\u6570\u636e\u5e93\u6570\u636e\u5bfc\u6210 CSV \u518d\u8bfb\u53d6，\u90a3\u662f\u201c\u5c0f\u519c\u7ecf\u6d4e\u201d\u3002\u771f\u6b63\u7684\u67b6\u6784\u601d\u7ef4\u662f\u6d41\u5f0f\u8bfb\u53d6\u6216\u8005\u5206\u6279\u52a0\u8f7d\u3002<\/p>\n

    \u4e0b\u9762\u8fd9\u6bb5\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u4ece \u7535\u79d1\u91d1\u4ed3 KES \u4e2d\u8bfb\u53d6\u5b58\u50a8\u7684\u7279\u5f81\u6570\u636e，\u5e76\u5c06\u5176\u8f6c\u5316\u4e3a PyTorch \u80fd\u591f\u8bc6\u522b\u7684 Tensor \u683c\u5f0f\u3002\u8fd9\u624d\u662f AI \u5de5\u4e1a\u5316\u7684\u7b2c\u4e00\u6b65\u3002<\/p>\n

    # -*- coding: utf-8 -*-<\/span>
    \nimport<\/span> ksycopg2
    \nimport<\/span> torch
    \nimport<\/span> numpy as<\/span> np<\/p>\n

    def<\/span> bridge_kes_to_pytorch<\/span>(<\/span>)<\/span>:<\/span>
    \n print<\/span>(<\/span>"— [\u7535\u79d1\u91d1\u4ed3] AI \u6570\u636e\u94fe\u8def\u8054\u8c03 —"<\/span>)<\/span><\/p>\n

    # \u9a71\u52a8\u4e0b\u8f7d\u4e0e\u914d\u7f6e\u53c2\u8003：https:\/\/www.kingbase.com.cn\/download.html#drive<\/span>
    \n conn_params =<\/span> "dbname=test user=username password=123456 host=127.0.0.1 port=54321"<\/span><\/p>\n

    try<\/span>:<\/span>
    \n # 1. \u4ece KES \u83b7\u53d6\u6570\u636e<\/span>
    \n conn =<\/span> ksycopg2.<\/span>connect(<\/span>conn_params)<\/span>
    \n cur =<\/span> conn.<\/span>cursor(<\/span>)<\/span><\/p>\n

    # \u5047\u8bbe\u6211\u4eec\u8868\u91cc\u5b58\u7684\u662f\u4e00\u4e9b\u4f20\u611f\u5668\u7279\u5f81\u6570\u636e<\/span>
    \n cur.<\/span>execute(<\/span>"SELECT id, name FROM test_ksy LIMIT 5"<\/span>)<\/span>
    \n rows =<\/span> cur.<\/span>fetchall(<\/span>)<\/span><\/p>\n

    # 2. \u6570\u636e\u8f6c\u5316：\u5c06\u6570\u636e\u5e93\u7684 Row \u8f6c\u5316\u4e3a NumPy \u6570\u7ec4，\u518d\u8f6c\u4e3a Tensor<\/span>
    \n # \u4e3a\u4e86\u6f14\u793a，\u6211\u4eec\u63d0\u53d6 ID \u5217\u4f5c\u4e3a\u6a21\u62df\u7279\u5f81<\/span>
    \n raw_data =<\/span> [<\/span>row[<\/span>0<\/span>]<\/span> for<\/span> row in<\/span> rows]<\/span>
    \n np_data =<\/span> np.<\/span>array(<\/span>raw_data,<\/span> dtype=<\/span>np.<\/span>float32)<\/span><\/p>\n

    # 3. \u8f6c\u5316\u4e3a PyTorch Tensor<\/span>
    \n feature_tensor =<\/span> torch.<\/span>from_numpy(<\/span>np_data)<\/span><\/p>\n

    print<\/span>(<\/span>f"\u4ece KES \u8bfb\u53d6\u5230\u7684\u539f\u59cb\u6570\u636e: <\/span>{<\/span>raw_data}<\/span><\/span>"<\/span><\/span>)<\/span>
    \n print<\/span>(<\/span>f"\u6210\u529f\u8f6c\u5316\u4e3a PyTorch Tensor: \\\\n<\/span>{<\/span>feature_tensor}<\/span><\/span>"<\/span><\/span>)<\/span>
    \n print<\/span>(<\/span>f"Tensor \u8bbe\u5907\u7c7b\u578b: <\/span>{<\/span>feature_tensor.<\/span>device}<\/span><\/span>"<\/span><\/span>)<\/span><\/p>\n

    cur.<\/span>close(<\/span>)<\/span>
    \n conn.<\/span>close(<\/span>)<\/span>
    \n print<\/span>(<\/span>"— \u94fe\u8def\u95ed\u73af\u6d4b\u8bd5\u5b8c\u6210 —"<\/span>)<\/span><\/p>\n

    except<\/span> Exception as<\/span> e:<\/span>
    \n print<\/span>(<\/span>f"\u94fe\u8def\u6545\u969c\u6392\u67e5: <\/span>{<\/span>e}<\/span><\/span>"<\/span><\/span>)<\/span><\/p>\n

    if<\/span> __name__ ==<\/span> "__main__"<\/span>:<\/span>
    \n bridge_kes_to_pytorch(<\/span>)<\/span><\/p>\n

    \n

    \u8086：\u67b6\u6784\u5e08\u7684\u788e\u788e\u5ff5<\/h3>\n

    \u6280\u672f\u548c\u4eba\u6587\u540c\u6e90，\u5c31\u5728\u4e8e\u8fd9\u79cd\u201c\u8fde\u63a5\u201d\u7684\u827a\u672f\u3002<\/p>\n

    \u6570\u636e\u5e93\u91cc\u7684\u6570\u636e\u662f\u51b0\u51b7\u7684\u7b26\u53f7，\u795e\u7ecf\u7f51\u7edc\u91cc\u7684 Tensor \u662f\u590d\u6742\u7684\u6982\u7387\u3002\u800c\u6211\u4eec\u4f5c\u4e3a\u67b6\u6784\u5e08，\u8981\u505a\u7684\u90a3\u5ea7\u6865\u6881，\u5fc5\u987b\u65e2\u80fd\u627f\u8f7d\u6d77\u91cf\u6570\u636e\u7684\u51b2\u51fb，\u53c8\u8981\u4fdd\u8bc1\u6bcf\u4e00\u6761\u4fe1\u606f\u5728\u6d41\u8f6c\u8fc7\u7a0b\u4e2d\u4e0d\u4e22\u5931\u7cbe\u5ea6\u7684\u201c\u6e29\u6da6\u201d\u3002<\/p>\n

    \u4eca\u5929\u54b1\u4eec\u6253\u901a\u4e86\u94fe\u8def，\u660e\u5929\u7b2c 7 \u5929，\u54b1\u4eec\u5c31\u8981\u6b63\u5f0f\u8fdb\u5165 Python \u6570\u636e\u79d1\u5b66\u57fa\u7840，\u53bb\u770b\u770b\u5982\u4f55\u7528 NumPy \u5728\u5185\u5b58\u91cc\u73a9\u8f6c\u8fd9\u4e9b\u4ece \u7535\u79d1\u91d1\u4ed3 KES \u91cc\u53d6\u51fa\u6765\u7684\u201c\u5b9d\u8d1d\u201d\u3002<\/p>\n

    ** \u54b1\u4eec\u7b2c 7 \u5929\u89c1\u3002**<\/p>\n

    \n

    \u4e0b\u671f\u9884\u544a： \u7b2c7\u5929：Python\u6570\u636e\u79d1\u5b66\u57fa\u7840：NumPy\u6570\u7ec4\u521b\u5efa\u4e0e\u57fa\u672c\u8fd0\u7b97\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

    \u73af\u5883\u642d\u5efa（\u4e09）：PyTorch\/TensorFlow\u914d\u7f6e\u4e0e\u7535\u79d1\u91d1\u4ed3 KES-Python \u8fde\u63a5\u5b9e\u6218
    \n\u54b1\u4eec\u8fd9 100 \u5929\u7684 AI \u5f81\u7a0b，\u524d\u51e0\u5929\u7b97\u662f\u628a\u5730\u57fa\u6253\u597d\u4e86\u3002\u4eca\u5929\u7b2c 6 \u5929，\u54b1\u4eec\u8981\u5e72\u4ef6\u5927\u4e8b：\u628a AI \u7684\u201c\u53d1\u52a8\u673a\u201d（PyTorch\/TensorFlow）\u548c\u201c\u6cb9\u7bb1\u201d（\u7535\u79d1\u91d1\u4ed3 KingbaseES）\u6b63\u5f0f\u4e32\u8054\u8d77\u6765\u3002
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