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实现代码","currentQuestion":"2 · 精确搜索：模型给分，评价定义相关 · 实现代码","sourceSlides":[],"knowledgeBlock":null,"formulas":[],"previousBlock":"b-afb04bcafbd1659a30206a97","nextBlock":"b-6acb624d6c60545b83e33dad","prerequisites":[{"id":"b-7ba0ecfaf1340d1a84e398d9","url":"#b-7ba0ecfaf1340d1a84e398d9","role":"section-title"},{"id":"b-2a1d7ecf6d04b924af79cd65","url":"#b-2a1d7ecf6d04b924af79cd65","role":"problem-context"}],"relatedBlocks":[]},{"id":"b-6acb624d6c60545b83e33dad","type":"pre","scope":"document","url":"https://codingai-lec03.pages.dev/course/notebook-blocks/e05d4164e12144fea000c0bf4d6b7e2f.html#b-6acb624d6c60545b83e33dad","content":"```\nX,Q=a['gallery'],a['queries']\nassert np.allclose(np.linalg.norm(X,axis=1),1,atol=2e-6)\nlabels=np.array([r['label'] for r in manifest['gallery']])\ntruth=[r['label'] for r in manifest['queries']]\nS=Q@X.T\nexact=np.stack([cr.stable_rank(row,k=3) for row in S])\nfor i,row in enumerate(exact):\n    print(manifest['queries'][i]['text'],'->',[(manifest['gallery'][j]['id'],round(float(S[i,j]),4)) for j in row])\nhit3=np.mean([any(labels[j]==truth[i] for j in row) for i,row in enumerate(exact)])\nprint('exact semantic Hit@3:',hit3)\n# 反方向：每张图对 12 条文字排序。每类有两条同义候选。\ni2t=np.stack([cr.stable_rank(row,k=1) for row in S.T])\nprint('image-to-text Hit@1:',np.mean([truth[row[0]]==labels[i] for i,row in enumerate(i2t)]))\n\n```","sha256":"00533db81ffa311ed8f37086e435877c01dd22b52775e5759abb88c9252bc0aa","chapter":{"id":"course","title":"2 · 精确搜索：模型给分，评价定义相关 · 实现代码"},"unit":{"id":"notebook-blocks/e05d4164e12144fea000c0bf4d6b7e2f","title":"2 · 精确搜索：模型给分，评价定义相关 · 实现代码"},"page":{"id":"reading-opening","title":"2 · 精确搜索：模型给分，评价定义相关 · 实现代码","number":1},"sectionTitle":"2 · 精确搜索：模型给分，评价定义相关 · 实现代码","currentQuestion":"2 · 精确搜索：模型给分，评价定义相关 · 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