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实现代码"},"page":{"id":"reading-opening","title":"运行准备与结果身份 · 实现代码","number":1},"sectionTitle":"运行准备与结果身份 · 实现代码","currentQuestion":"运行准备与结果身份 · 实现代码","sourceSlides":[],"knowledgeBlock":null,"formulas":[],"previousBlock":"b-af6f1737f51ba490a0cf33ea","nextBlock":"b-8cb5c7356bbf91bd01a0a9cf","prerequisites":[{"id":"b-0a5453390dff4e8827f70b64","url":"#b-0a5453390dff4e8827f70b64","role":"section-title"},{"id":"b-322ca5a656785eb94ef612a0","url":"#b-322ca5a656785eb94ef612a0","role":"problem-context"}],"relatedBlocks":[]},{"id":"b-8cb5c7356bbf91bd01a0a9cf","type":"pre","scope":"document","url":"https://codingai-lec03.pages.dev/course/notebook-blocks/e9570c227f07476e8290b9418319a6f2.html#b-8cb5c7356bbf91bd01a0a9cf","content":"```\n\"\"\"CPU image contrastive experiment. No class/color label enters pretraining.\"\"\"\nfrom pathlib import Path\nimport copy, hashlib, json, os, platform, time\nimport numpy as np\nimport torch\nfrom torch import nn\nfrom torch.nn import functional as F\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.preprocessing import StandardScaler\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\ntorch.set_num_threads(2)\nSEED=20260922\n\nSOURCE_SHA256='09bbb32bb5502db3535d89efec2045ffcd85c249b49f622390f12875060845d4'\nprint(\"source\",SOURCE_SHA256,\"torch\",torch.__version__)\n```","sha256":"1c09502a0af88ecc992c812ee8a92c14817a2fea125b3fe51e4382a22823aad0","chapter":{"id":"course","title":"运行准备与结果身份 · 实现代码"},"unit":{"id":"notebook-blocks/e9570c227f07476e8290b9418319a6f2","title":"运行准备与结果身份 · 实现代码"},"page":{"id":"reading-opening","title":"运行准备与结果身份 · 实现代码","number":1},"sectionTitle":"运行准备与结果身份 · 实现代码","currentQuestion":"运行准备与结果身份 · 实现代码","sourceSlides":[],"knowledgeBlock":null,"formulas":[],"previousBlock":"b-bfb710fa3a20416f9090d063","nextBlock":null,"prerequisites":[{"id":"b-0a5453390dff4e8827f70b64","url":"#b-0a5453390dff4e8827f70b64","role":"section-title"},{"id":"b-322ca5a656785eb94ef612a0","url":"#b-322ca5a656785eb94ef612a0","role":"problem-context"}],"relatedBlocks":[]}]}