{"id":108212,"date":"2026-09-21T08:49:07","date_gmt":"2026-09-21T00:49:07","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/108212.html"},"modified":"2026-09-21T08:49:07","modified_gmt":"2026-09-21T00:49:07","slug":"%e6%98%87%e8%85%be%e5%bc%80%e6%ba%90%e4%bb%93issue%e5%88%86%e6%9e%90%e8%a7%a3%e7%ad%94-mindspore%e7%b2%be%e9%80%89%ef%bc%88%e4%b8%89%ef%bc%89%c2%b7%e4%b8%bb%e4%bb%93%e4%b8%8emindformers%e9%95%bf","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/108212.html","title":{"rendered":"\u6607\u817e\u5f00\u6e90\u4ed3Issue\u5206\u6790\u89e3\u7b54-mindspore\u7cbe\u9009\uff08\u4e09\uff09\u00b7\u4e3b\u4ed3\u4e0emindformers\u957f\u5c3e\u6536\u5b98"},"content":{"rendered":"

\u6607\u817e\u5f00\u6e90\u4ed3Issue\u5206\u6790\u89e3\u7b54-mindspore\u7cbe\u9009（\u4e09）\u00b7\u4e3b\u4ed3\u4e0emindformers\u957f\u5c3e\u6536\u5b98<\/h2>\n

\u4e00\u53e5\u8bdd\u8ba9Agent\u53d8\u6210\u6607\u817e\u4e13\u5bb6，\u6607\u817e\u4efb\u52a1\u8f7b\u677e\u641e\u5b9a\u3002\u8bc4\u6d4b\u5165\u53e3：\u8bf7\u6309\u8fd9\u4e2a\u5f00\u6e90\u4ed3\u63a5\u5165\u6607\u817e\u56fe\u8c31 https:\/\/gitcode.com\/agent0\/kg-tools<\/p>\n

\u603b\u89c8<\/h3>\n\n\u4ed3\u5e93\u5b9a\u4f4d\u6536\u5f55\u6761\u6570<\/tr>\n\n\n\n
mindspore<\/td>\n\u6607\u601d\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u4e3b\u4ed3，\u672c\u7bc7\u53cc\u8868\u6536\u5b98 22 \u6848（\u56fe\u6267\u884c\u4e0e\u901a\u4fe1\u4fee\u590d\u94fe 12 + \u63a5\u53e3\u6821\u9a8c\u4e0e\u6559\u7a0b\u53e3\u5f84 10）<\/td>\n22<\/td>\n<\/tr>\n
mindformers<\/td>\nMindSpore \u5927\u6a21\u578b\u5957\u4ef6：DSA \u7a00\u758f\u6ce8\u610f\u529b\u3001\u8f85\u52a9 loss \u53e3\u5f84\u3001pynative \u80fd\u529b\u4e0e dsv4 \u65ad\u70b9\u7eed\u8bad\u56db\u8868 28 \u6848<\/td>\n28<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

mindspore（\u6846\u67b6\u4e3b\u4ed3\u00b7\u56fe\u6267\u884c\u4e0e\u901a\u4fe1\u4fee\u590d\u94fe）<\/h3>\n

\u6607\u601d\u4e3b\u4ed3\u00b7\u957f\u5c3e\u6536\u5b98：\u56fe\u6267\u884c\u56de\u5f52\u3001\u7b97\u5b50\u8bed\u4e49\u4fee\u590d\u4e0e\u96c6\u7fa4\u901a\u4fe1\u4e09\u7ebf，\u542b\u5f15\u5165+\u4fee\u590d\u53cc\u951a\u70b9\u4e0e 15 MR \u56de\u9000\u94fe<\/p>\n\n\u7f16\u53f7Issue \u95ee\u9898\u5185\u5bb9\u89e3\u7b54\u603b\u7ed3<\/tr>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
#20673<\/td>\nkv_scale_cache\u91cf\u5316KV cache\u7f29\u653e\u80fd\u529b\u4efb\u52a1\u5355<\/td>\nkvscale\u80fd\u529b\u7ecfPR 85440（ljs-ms-kvscale-testok，2025-06-04\u5408\u5165）\u6d4b\u8bd5\u901a\u8fc7，\u968f\u8fed\u4ee3PR 86633 infer_ops iter4（\u6b63\u6587\u9996\u6761\u5373ms-kvscale-testok，\u542bmla preprocess\u7b49）2025-07-09\u5408\u5165，issue\u6b21\u65e5\u57282025-07-10\u5173\u95ed，\u65f6\u95f4\u7a97\u4e0e\u6b63\u6587\u8bed\u4e49\u53cc\u543b\u5408\u300286633\u7684Fixes\u6307\u5411gitee\u53f7ICGUBZ\u3002<\/td>\n<\/tr>\n
#21143<\/td>\nmindspore\u4e0d\u652f\u6301\u5168\u51bb\u7ed3\u7f51\u7edc\u7684PP\u5e76\u884c（\u7f16\u8bd1\u5361\u6b7b）<\/td>\n\u84b8\u998f\u573a\u666fteacher\u5168\u51bb\u7ed3+lazy_inline\u5f00\u542fPP\u5e76\u884c\u7f16\u8bd1\u5361\u6b7b，\u6267\u884c\u5e8f\u505c\u5728receive begin\u3002SSR\u6d3b\u52a8\u6d41\u5173\u8054\u53ccPR：88049 freeze grad（2025-08-04\u5408\u5165）\u4e0e88260 fix_freeze_bug（2025-08-12\u5408\u5165），\u4e24PR\u5747Fixes gitee\u53f7ICR1P3，\u652f\u6301\u5168\u51bb\u7ed3\u7f51\u7edcPP\u5e76\u884c，issue\u4e00\u4e2a\u6708\u540e\u5173\u95ed\u3002<\/td>\n<\/tr>\n
#21705<\/td>\n\u7cbe\u5ea6\u6545\u969c\u4e0d\u91cd\u542f\u5feb\u6062\u5076\u73b0\u5361\u6b7b<\/td>\nPR 84439 support spike fast recovery（2025-04-19\u5408\u5165）\u6b63\u6587\u660e\u786e\u4e3a\u7cbe\u5ea6\u6545\u969c\u4e0d\u91cd\u542f\u6062\u590d\u65b9\u6848，\u4e0eissue\u6807\u9898\u8bed\u4e49\u76f4\u914d，issue\u4e8e3\u5929\u540e2025-04-22\u5173\u95ed\u3002Fixes\u6307\u5411\u5185\u90e8\u9700\u6c42\u7f16\u53f7AR.SR.IR20250325004495\u3002<\/td>\n<\/tr>\n
#21803<\/td>\nDVM MatMul\u878d\u5408\u7b97\u5b50dry run\u65f6core dump<\/td>\n\u6839\u56e0：dry run\u8df3\u8fc7DVM\u7f16\u8bd1，MatMul kernel\u90e8\u5206\u53d8\u91cf\u672a\u521d\u59cb\u5316，\u6790\u6784\u65f6\u8bbf\u95ee\u672a\u521d\u59cb\u5316\u6307\u9488\u5bfc\u81f4core dump\u3002\u4fee\u590d：\u6790\u6784\u51fd\u6570\u5bf9\u6307\u9488\u5224\u7a7a，\u5e76\u8865\u5145run_matmul ST\u7528\u4f8b\u3002PR 80369\u5408\u5165，merged_at\u4e0eissue\u5173\u95ed\u79d2\u7ea7\u4e00\u81f4，PR\u6b63\u6587\u6839\u56e0\u63cf\u8ff0\u4e0e\u8bc4\u8bba\u4e00\u81f4\u3002<\/td>\n<\/tr>\n
#21810<\/td>\nxlogy tensor\u63a5\u53e3\u8bed\u4e49\u4e0d\u6e05\u6670（\u5165\u53c2\u547d\u540d）<\/td>\nxlogy(y)\u4e0e\u53c2\u8003\u63a5\u53e3other\u5165\u53c2\u662f\u540c\u4e00\u53c2\u6570，\u9700\u8865\u8bf4\u660e\u3002PR 80293\u4fee\u590dxlogy doc bug，PR\u6b63\u6587\u6240\u5199\u95ee\u9898\u4e0eissue\u6807\u9898\u9010\u5b57\u76f8\u540c，merged_at 2025-01-09T11:05:50\u4e0eissue\u5173\u95ed\u65f6\u95f4\u79d2\u7ea7\u4e00\u81f4；\u524d\u7f6ePR 80179（fix xlogy docs，2025-01-03）\u540c\u4e3b\u9898\u3002Fixes gitee\u53f7IBG73N\u3002<\/td>\n<\/tr>\n
#21812<\/td>\nGMM 310P nz weight\u81ea\u52a8\u8f6c\u6362\u903b\u8f91\u88ab\u91cd\u6784\u8bef\u5220<\/td>\n\u53cc\u951a\u70b9\u8fd8\u539f：nz weight\u81ea\u52a8\u8f6c\u6362\u7531PR 74073（GroupedMatmul aclnn\u652f\u6301weight\u8f93\u5165\u4e3anz，2024-08-23\u5408\u5165）\u5f15\u5165，\u7ecfPR 74745\u91cd\u6784（2024-09-06\u5408\u5165）\u88ab\u8bef\u5220\u3002\u4fee\u590dPR 80259\u6b63\u6587\u5199\u660e\u52a0\u56de\u88ab\u5220\u9664\u7684GMM\u903b\u8f91，merged_at\u4e0eissue\u5173\u95ed\u79d2\u7ea7\u4e00\u81f4\u3002Fixes gitee\u53f7IBF6PM\u3002<\/td>\n<\/tr>\n
#28905<\/td>\nMaskedFill\u53cd\u5411\u5728NaN\/Inf\u573a\u666f\u4e0ePyTorch\u7ed3\u679c\u4e0d\u4e00\u81f4<\/td>\nMindSpore\u53cd\u5411\u7528\u4e58\u6cd5\u63a9\u7801，dout\u542bNaN\/Inf\u65f60*NaN\u4ecd\u4e3aNaN，\u88ab\u63a9\u7801\u4f4d\u7f6e\u68af\u5ea6\u4e0d\u4e3a0；PyTorch\u7528masked_select\u5206\u652f\u89c4\u907f\u3002PR 91648\u91cd\u5199MaskedFill\u53cd\u5411\u5b9e\u73b0\u6d88\u9664\u4e0d\u4e00\u81f4（\u6807\u9898Resolve the inconsistency\u2026），SSR\u6d3b\u52a8\u6d41\u5173\u8054，2026-01-28\u5408\u5165，issue\u6b21\u65e5\u5173\u95ed\u3002<\/td>\n<\/tr>\n
#28907<\/td>\n\u590d\u7528\u5916\u90e8hcom\u65f6\u4f1a\u91cd\u590d\u9500\u6bc1\u901a\u4fe1\u57df<\/td>\nAscendCommunicationGroup::Finalize\u65e0\u6761\u4ef6\u8c03HcclCommDestroy，\u590d\u7528\u7ecfgroup options\u4f20\u5165\u7684\u5916\u90e8hcom\u65f6\u4f1a\u9500\u6bc1\u4e0d\u5c5e\u4e8e\u81ea\u5df1\u7684\u901a\u4fe1\u5668\u3002PR 91647\u5728hcom\u7531options\u4f20\u5165\u65f6\u8df3\u8fc7HcclCommDestroy，\u6b63\u6587\u4e0eissue\u9010\u5b57\u5bf9\u5e94，merged\u4e0e\u5173\u95ed\u5dee99\u79d2\u3002KG：\u8be5API\u8bed\u4e49\u89c1hcomm\u53c2\u8003\u3002<\/td>\n<\/tr>\n
#28944<\/td>\n\u56fe\u7f16\u8bd1infer value\u8f93\u5165device tensor\u672a\u540c\u6b65\u5230CPU<\/td>\n\u56fe\u7f16\u8bd1infer value\u6d41\u7a0b\u9700\u8981CPU\u4fa7\u8f93\u5165\u4ee5\u5b8c\u6210host\u8ba1\u7b97\u5e76\u5e38\u91cf\u6298\u53e0，\u4f46\u6d41\u7a0b\u672a\u5728infer value\u524d\u6821\u9a8c\u8f93\u5165device tensor\u662f\u5426\u540c\u6b65\u5230host\u3002PR 91764 fix infer value getting device tensor（\u6b63\u6587\u4e0eissue\u9010\u5b57\u5bf9\u5e94）2026-02-27\u5408\u5165，20\u5206\u949f\u540eissue\u5173\u95ed；\u540e\u7eed91981\u540c\u540d\u91cd\u505a\u5408\u5165\u300192098\u56de\u9000\u5c1d\u8bd5\u672a\u5408\u3002<\/td>\n<\/tr>\n
#28991<\/td>\nA3\u73af\u5883bind_numa+ASCEND_RT_VISIBLE_DEVICES\u65f6\u65e0\u6cd5\u7ed1\u5185\u5b58<\/td>\nA3\u73af\u5883\u65e0npu\u4e0enuma\u4eb2\u548c\u5173\u7cfb，\u53d6\u4e0d\u5230\u4eb2\u548c\u4fe1\u606f\u65f6\u7ed1\u5b9a\u7b56\u7565\u9000\u5316\u4e3a\u5747\u5206，\u914d\u5408ASCEND_RT_VISIBLE_DEVICES\u6307\u5b9a\u540e\u7ed1\u4e0d\u4e0a\u5185\u5b58\u3002PR 91845\u4fee\u590dA3\u573a\u666f\u7ed1\u5b9a，1.5\u5c0f\u65f6\u540eissue\u5173\u95ed；feature\u5f15\u5165\u4e3aPR 91635\u3002KG：\u8be5\u73af\u5883\u53d8\u91cf\u8bed\u4e49\u89c1runtime\u8bbe\u5907\u7ba1\u7406\u6587\u6863\u3002<\/td>\n<\/tr>\n
#28992<\/td>\n\u652f\u6301mccl\u5f02\u6b65\u521d\u59cb\u5316（4k\u8282\u70b9\u542f\u52a8\u6162）<\/td>\n4k\u8282\u70b9\u521d\u59cb\u531610\u5206\u949f，\u521d\u6b65\u5206\u67904\u5206\u949f\u8017\u5728mccl\u521d\u59cb\u5316SynchronizeAddresses\u6536\u96c6\u8282\u70b9\u4fe1\u606f（\u968f\u96c6\u7fa4\u89c4\u6a21\u7ebf\u6027\u53d8\u6162）\u3002\u843d\u5730\u94fe：PR 92054\u5408\u5165\u2192PR 92174\u56de\u9000：\u5f02\u6b65mccl\u521d\u59cb\u5316\u2192PR 92456 support mccl async\u91cd\u505a\u5408\u5165（2026-04-24），SSR\u6d3b\u52a8\u6d41\u5171\u5173\u805415\u4e2aMR，issue 2026-05-19\u5173\u95ed\u3002<\/td>\n<\/tr>\n
#28999<\/td>\n\u52a8\u6001\u56fe\u65e0\u56fe\u878d\u5408device\u5730\u5740\u8e29\u8e0f\u5bfc\u81f4\u7cbe\u5ea6\u95ee\u9898<\/td>\nLazyFusionKernelAscend::Flush\u91ccdevice_address\u662ffor\u5faa\u73af\u5185\u5c40\u90e8weak_ptr，\u5f53\u524d\u5faa\u73af\u7ed3\u675f\u5373\u91ca\u653e，\u4e0b\u8f6e\u53ef\u80fd\u590d\u7528\u540c\u4e00\u5730\u5740\u6216\u4e0eCodegen\u7684workspace\u51b2\u7a81，\u591a\u8f93\u51fa\/\u5e26workspace\u878d\u5408\u7b97\u5b50\u89e6\u53d1\u5730\u5740\u8e29\u8e0f\u3002PR 91865\u4fee\u590ddevice address collision，SSR\u6d3b\u52a8\u6d41\u5173\u8054，2026-02-12\u5408\u5165\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

mindspore（\u6846\u67b6\u4e3b\u4ed3\u00b7\u63a5\u53e3\u6821\u9a8c\u4e0e\u6559\u7a0b\u53e3\u5f84）<\/h3>\n

\u4e3b\u4ed3\u00b7\u957f\u5c3e\u6536\u5b98\u4e8c：\u63a5\u53e3\u6821\u9a8c\u7f3a\u5931\u3001\u521d\u59cb\u5316\u8bed\u4e49\u6f14\u8fdb\u4e0e\u300c\u6559\u7a0b\u9ed8\u8ba4 Ascend \u5e73\u53f0\u300d\u590d\u73b0\u53e3\u5f84（\u542b\u4e0a\u7bc7\u62c6\u5165 #544\/#248\/#29041）<\/p>\n\n\u7f16\u53f7Issue \u95ee\u9898\u5185\u5bb9\u89e3\u7b54\u603b\u7ed3<\/tr>\n\n\n\n\n\n\n\n\n\n\n\n
#248<\/td>\ngelu\u6309\u4f4d\u7f6e\u53c2\u6570\u4f20approximate\u62a5TypeError<\/td>\n\u6839\u56e0：PR 81218\u63a5\u53e3\u53d8\u66f4\u5bf9\u9f50torch2.1，approximate\u6539\u4e3akeyword-only\u53c2\u6570；\u7279\u6027\u76f4\u63a5\u5408master\u8f6c\u6d4b\u4e14\u8f6c\u6d4b\u90ae\u4ef6\u53d1\u5f97\u665a，\u6d4b\u8bd5\u672a\u611f\u77e5\u672a\u9002\u914d\u7528\u4f8b\u3002\u5904\u7406：\u5df2\u53d1\u63a5\u53e3\u53d8\u66f4\u90ae\u4ef6，\u6d4b\u8bd5\u4ed3\u7528\u4f8b\u6539\u5173\u952e\u5b57\u4f20\u53c2\u9002\u914d，mindspore\u4ed3\u65e0\u9700\u6539\u7801\u3002<\/td>\n<\/tr>\n
#544<\/td>\nmint.narrow pynative\u6a21\u5f0fstart\/length\u8d8a\u754c\u672a\u629bValueError<\/td>\n\u6839\u56e0：pynative\u6267\u884c\u8def\u5f84\u7f3a\u5c11start\u548clength\u53c2\u6570\u6821\u9a8c（graph\u6a21\u5f0f\u5df2\u6709），\u8d8a\u754c\u8f93\u5165\u4e0d\u62a5\u9519\u3002\u4fee\u590d：\u5f00\u53d1\u8865\u4e0a\u6821\u9a8c\u540e\u7528\u4f8b\u6062\u590d\u9884\u671f\u62a5\u9519（length should be in [0, N]），master commit 2ead7024\u56de\u5f52\u901a\u8fc7；\u8bc4\u8bba\u79f0\u4fee\u590d\u5728\u67d0PR\u4e2d\u4f46\u672a\u9644\u7f16\u53f7\u3002<\/td>\n<\/tr>\n
#28939<\/td>\n910A\u4e0aMS 2.7.2\u6d4b\u8bd5\u5931\u8d25\u30012.8.0 import\u6bb5\u9519\u8bef(910B\u6b63\u5e38)<\/td>\n\u63d0\u95ee\u8005\u81ea\u5b9a\u4f4d\u6839\u56e0\u5e76\u89e3\u51b3：\u95ee\u9898\u73af\u5883\u7684CANN 8.5\u7b49\u5b89\u88c5\u5305\u53d6\u81ea\u516c\u53f8CMC\u5185\u90e8\u6e20\u9053，\u975e\u5b98\u65b9\u6700\u7ec8\u53d1\u5e03\u5305；910A\u73af\u5883\u6539\u7528\u5b98\u65b9\u6700\u65b0CANN 8.5\u5305\u91cd\u65b0\u5b89\u88c5\u90e8\u7f72\u540e，MindSpore 2.8.0 NPU\u80fd\u529b\u6d4b\u8bd5\u6062\u590d\u6b63\u5e38\u3002\u6559\u8bad：\u540c\u7248\u672c\u53f7\u4e0b\u5185\u90e8\u6e20\u9053\u5305\u4e0e\u5b98\u65b9\u53d1\u5e03\u5305\u884c\u4e3a\u53ef\u80fd\u4e0d\u540c，NPU\u5de5\u5177\u94fe\u52a1\u5fc5\u7528\u5b98\u65b9\u53d1\u5e03\u5305\u3002<\/td>\n<\/tr>\n
#28969<\/td>\nRNN\u6559\u7a0b\u52a0\u8f7d\u9884\u8bad\u7ec3\u8bcd\u5411\u91cf，\u8dd1\u6d4b\u7ed3\u679c\u4e0e\u6587\u6863\u4e0d\u4e00\u81f4<\/td>\n\u5b98\u65b9\u53e3\u5f84\u56de\u590d（li-tingyu 2026-04-25）：\u672c\u6559\u7a0b\u7684\u5b9e\u9a8c\u5747\u5728Ascend\u8bbe\u5907\u4e0a\u6267\u884c，\u7531\u4e8e\u5e73\u53f0\u5dee\u5f02，\u5728CPU\u4e0a\u590d\u73b0\u65f6\u7ed3\u679c\u53ef\u80fd\u6709\u6240\u4e0d\u540c\u3002\u975e\u6587\u6863\u9519\u8bef，\u5c5e\u6559\u7a0b\u9ed8\u8ba4\u786c\u4ef6\u5e73\u53f0\u4e0e\u7528\u6237\u590d\u73b0\u5e73\u53f0\u4e0d\u4e00\u81f4\u5bfc\u81f4\u7684\u9884\u671f\u5dee\u5f02\u3002<\/td>\n<\/tr>\n
#29001<\/td>\n\u6559\u7a0b\u7528init\u521d\u59cb\u5316\u5668\u6784\u9020\u5f20\u91cf，\u5b9e\u6d4b\u6253\u5370uninitialized<\/td>\n\u5b98\u65b9\u786e\u8ba4（li-tingyu 2026-04-25）：\u63a5\u53e3\u5728\u6b64\u7248\u672c\u6709\u66f4\u65b0，\u4fee\u6b63\u65e9\u671f\u2019\u9690\u5f0f\u521d\u59cb\u5316\u2019\u7684\u4e0d\u4e25\u8c28\u8bbe\u8ba1\u2014\u2014init\u6784\u9020\u7684\u5f20\u91cf\u6253\u5370\u5c5e\u9884\u671f，\u6559\u7a0b\u5df2\u66f4\u65b0\u3002KG\u4f50\u8bc1：\u540c\u751f\u6001PyPTO FAQ\u660e\u786etensor\u58f0\u660e\u4e0d\u542b\u521d\u59cb\u5316\u884c\u4e3a\u3001\u672a\u521d\u59cb\u5316Tensor\u4e0d\u7533\u8bf7\u5185\u5b58\u3001\u987b\u5148\u5199\u540e\u8bfb，\u8bbe\u8ba1\u54f2\u5b66\u4e00\u81f4\u3002<\/td>\n<\/tr>\n
#29002<\/td>\nWeightedRandomSampler\u793a\u4f8b\u542b%matplotlib inline\u81f4\u8bed\u6cd5\u9519\u8bef<\/td>\n\u6839\u56e0：\u793a\u4f8b\u6b8b\u7559Jupyter\u9b54\u672f\u547d\u4ee4%matplotlib inline，\u590d\u5236\u5230.py\u811a\u672c\u6267\u884c\u5373SyntaxError\u3002\u4fee\u590d：mindspore\/docs#18291（master）\u4e0e#18299（r2.8.0）\u5220\u9664\u8be5\u884c，\u6807\u9898\u2019remove matplotlib inline\u2019，\u57472026-02-28\u5408\u5165（pulls API\u6838\u5b9e）\u3002\u5b98\u65b9\u53e6\u6307\u51fa\u7528\u6237\u590d\u5236\u4ee3\u7801\u4e0e\u9875\u9762\u663e\u793a\u4e0d\u4e00\u81f4\u3002<\/td>\n<\/tr>\n
#29007<\/td>\nSSD\u6559\u7a0bimport cv2\u62a5libxcb.so.1\u7f3a\u5931\u9519\u8bef<\/td>\n\u5b98\u65b9\u5148\u5efa\u8bae\u88c5libxcb\u4f9d\u8d56，\u63d0\u95ee\u8005\u5b9e\u6d4b\u4ecd\u62a5\u9519；\u6539\u7528opencv-python-headless==4.11.0.86\u540e\u89e3\u51b3\u3002\u5b98\u65b9（shenwei41 2026-03-30）\u786e\u8ba4\u539f\u7406：headless\u7248\u4e0d\u4f9d\u8d56libxcb\u7b49\u56fe\u5f62\u5e93，\u4e14SSD\u811a\u672c\u672a\u7528GUI\u63a5\u53e3，\u53ef\u5b89\u5168\u66ff\u4ee3opencv-python；\u4e5f\u53ef\u68c0\u67e5opencv_python.libs\u4e0b\u662f\u5426\u6709libxcb\u76f8\u5173so\u3002<\/td>\n<\/tr>\n
#29033<\/td>\nWeightedRandomSampler\u9875\u9762\u663e\u793a\u65e0\u6548\u5b57\u7b26\u4e32<\/td>\n\u6839\u56e0\u4e0e#29002\u540c\u6e90：\u6570\u636e\u52a0\u8f7d\u4e0e\u91c7\u6837\u9875\u9762\u6b8b\u7559%matplotlib inline\u65e0\u6548\u5b57\u7b26\u4e32（\u540c\u4e00\u9875\u9762\u65e2\u81f4\u663e\u793a\u5f02\u5e38\u53c8\u81f4\u590d\u5236\u7684\u4ee3\u7801\u8bed\u6cd5\u62a5\u9519）\u3002\u4fee\u590d\u4e3a\u540c\u4e00\u7ec4PR：mindspore\/docs#18299（r2.8.0）\u4e0e#18291（master），\u6807\u9898\u2019remove matplotlib inline\u2019，\u57472026-02-28\u5408\u5165\u3002\u5b98\u65b9\u7559\u8a00\u2019\u4ee5\u4e0a\u95ee\u9898\u5df2\u7ecf\u4fee\u590d，pr\u5df2\u5408\u5165\u2019\u3002<\/td>\n<\/tr>\n
#29041<\/td>\nRandomSampler\u6587\u6863\u793a\u4f8b\u7ed3\u679c\u65e0\u6cd5\u5370\u8bc1\u6709\u653e\u56de\/\u65e0\u653e\u56de\u91c7\u6837\u7684\u8bf4\u660e<\/td>\n\u5b98\u65b9\u89e3\u7b54：\u65e0seed\u65f6\u91c7\u6837\u7ed3\u679c\u6bcf\u6b21\u4e0d\u540c\u5c5e\u9884\u671f\u884c\u4e3a，\u9700\u56fa\u5b9a\u7ed3\u679c\u53efds.config.set_seed(1000)\u3002\u6587\u6863\u7f3a\u9677\u540c\u6b65\u4fee\u6b63：\u539f\u793a\u4f8b\u7ed3\u679c1 4 5 8 7\u770b\u4e0d\u51fa\u91cd\u590d\u91c7\u6837，\u6539\u4e3a\u7c7b\u4f3c1 4 5 8 1\u4ee5\u4f53\u73b0\u6709\u653e\u56de\u65f6\u540c\u4e00\u6570\u636e\u53ef\u88ab\u591a\u6b21\u62bd\u53d6；mindspore\/docs\u4ed3PR 18412\/18413\u6b63\u6587Fixes\u663e\u5f0f\u5f15\u7528\u672cissue，2026-03-31\u5408\u5e76\u3002<\/td>\n<\/tr>\n
#29054<\/td>\n\u56fe\u6a21\u5f0f\u975e\u63a7\u5236\u6d41\u573a\u666f\u6559\u7a0b\u79f0\u652f\u6301，Windows\u6267\u884c\u62a5\u9519<\/td>\n\u5b98\u65b9\u8bf4\u660e（shuqian0 2026-03-06）：\u8be5\u7528\u4f8b\u9700\u8fd0\u884c\u5728Ascend\u73af\u5883，Windows\u6267\u884c\u62a5\u9519\u5c5e\u5e73\u53f0\u9650\u5236\u975e\u6587\u6863\u9519\u8bef；\u6559\u7a0b\u5df2\u8865\u5145\u5e73\u53f0\u9650\u5236\u8bf4\u660e\u3002\u4fee\u590dPR：mindspore\/docs#18261（master）\u4e0e#18262（r2.8），\u6807\u9898\u4e3a\u7ed9view in-place\u7528\u4f8b\u6dfb\u52a0Ascend\u5e73\u53f0\u9650\u5236，\u57472026-02-27\u5408\u5165\u3002\u53e6\u6709\u4eba\u8ffd\u52a0\u540c\u7c7b\u62a5\u9519，\u672a\u89c1\u540e\u7eed\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

mindformers（\u5927\u6a21\u578b\u5957\u4ef6\u00b7DSA \u7a00\u758f\u6ce8\u610f\u529b）<\/h3>\n

DeepSeek \u7cfb DSA（\u7a00\u758f\u6ce8\u610f\u529b）\u843d\u5730\u516d\u6848：\u6392\u5e03\u3001\u91cd\u6392\u63d2\u5165\u3001\u663e\u5b58\u4e0e indexer rope<\/p>\n\n\u7f16\u53f7Issue \u95ee\u9898\u5185\u5bb9\u89e3\u7b54\u603b\u7ed3<\/tr>\n\n\n\n\n\n\n\n
#2214<\/td>\nDSA\u5df2\u77e5\u95ee\u9898：BSND+cp\u591a\u4f59\u901a\u4fe1\u663e\u5b58\u6da8；dense+pp\u62a5\u9519\u5361\u6b7b<\/td>\n\u8ddf\u8e2a\u578b\u81ea\u63d0\u5355\u5217\u4e24\u9879\u7f3a\u9677：\u2460BSND\u6392\u5e03\u878d\u5408\u7b97\u5b50\u672a\u9002\u914dcp\u2192\u591a\u4f59\u901a\u4fe1+\u663e\u5b58\u4e0a\u6da8；\u2461dense\u9636\u6bb5\u5f00pp\u62a5\u9519\/\u5361\u6b7b\u3002\u2461\u7531PR8092\u4fee\u590d（03-17\u5408\u5165：\u652f\u6301dense\u9636\u6bb5pp+\u89c4\u907fequal\u7b97\u5b50bsnd\u95ee\u9898）；\u2460\u7531PR8211 dsa\u7b97\u5b50\u6df7\u5408tp+cp\u5e76\u884c\u89e3\u51b3（04-28\u5408\u5165）\u3002\u4e24PR\u5747\u663e\u5f0fFixes\u4e3b\u8ddf\u8e2a\u5355#2207\u800c\u975e\u672c\u5355，\u95f4\u63a5\u951a\u70b9\u3002<\/td>\n<\/tr>\n
#2230<\/td>\nDSA\u4e0eMegatron\u7cbe\u5ea6\u672a\u5bf9\u9f50：\u9996loss\u5bf9\u9f50\u3001\u9996norm\u5373\u5206\u53c9<\/td>\n\u5b98\u65b9\u786e\u8ba4DSA\u5b9e\u73b0\u6d41\u7a0b\u4e0eMegatron\u4e0d\u5b8c\u5168\u4e00\u81f4：\u4ec5\u80fd\u4fdd\u8bc1\u524d\u5411\u7cbe\u5ea6\u4e00\u81f4，\u53cd\u5411\u65e0\u6cd5\u4fdd\u8bc1，\u9700\u5f85CANN loss\u878d\u5408\u7b97\u5b50\u63a5\u5165\u540e\u91cd\u65b0\u6bd4\u5bf9\u3002\u878d\u5408\u7b97\u5b50\u540e\u7ecfPR8181\u63a5\u5165（2026-04-15\u5408\u5165，\u6302DSA\u4e3b\u8ddf\u8e2a\u5355#2207），\u540c\u6b65\u4fee\u590ddense\u9636\u6bb5\u8bef\u7528SFA\u800c\u975eFA\u7b97\u5b50\u95ee\u9898\u3002\u5c5e\u5df2\u77e5\u5dee\u5f02\u8bf4\u660e\u578b\u5173\u5355，\u975e\u5f53\u65e5\u4ee3\u7801\u4fee\u590d\u3002<\/td>\n<\/tr>\n
#2234<\/td>\n\u5927\u89c4\u6a21\u5e76\u884c\u65f6\u6846\u67b6\u81ea\u52a8\u63d2\u5165\u590d\u6742\u91cd\u6392\u81f4DSA\u8fd0\u884c\u5931\u8d25<\/td>\n\u6839\u56e0：MindSpore\u5728\u5927\u89c4\u6a21\u5e76\u884c\u65f6\u81ea\u52a8\u63d2\u5165\u91cd\u6392\u8282\u70b9，\u4e14\u8de8\u5b50\u56fe\u76f4\u63a5reshape\u89e6\u53d1\u9519\u8bef\u91cd\u6392（TND\u6392\u5e03\u4e00\u9636\u6bb5）\u3002\u4fee\u590d：\u6539\u5199\u53ef\u80fd\u89e6\u53d1\u91cd\u6392\u7684\u8282\u70b9\u6d88\u9664\u63d2\u5165\u6e90，\u7528dp2tp4pp2cp8 dryrun\u5b58\u56fe\u9a8c\u8bc1\u91cd\u6392\u6d88\u9664\u3002PR8196\u6b63\u6587\u663e\u5f0fFixes #2234，2026-04-22\u5408\u5165\u3002<\/td>\n<\/tr>\n
#2252<\/td>\nDSA\u4e8c\u9636\u6bb5128k\u957f\u5e8f\u5217\u5cf0\u503c\u663e\u5b58\u6bd4\u4e0d\u5f00DSA\u9ad87\u500d<\/td>\n\u6839\u56e0：\u6743\u91cd\u5438\u6536\u903b\u8f91\u5bfc\u81f4\u53cd\u5411\u8ba1\u7b97\u663e\u5b58\u5360\u7528\u8fc7\u9ad8\u3002\u4fee\u590d：PR8229\u4f18\u5316\u6743\u91cd\u5438\u6536\u903b\u8f91\u964d\u4f4e\u53cd\u5411\u663e\u5b58，\u6b63\u6587\u663e\u5f0fFixes #2252，2026-04-30\u5408\u5165（\u63d0\u535556\u5206\u949f\u540e）；\u4e0e\u540e\u7eedPyNative DSA\u957f\u5e8f\u5217\u663e\u5b58\u4f18\u5316\u7ebf\u8854\u63a5\u3002<\/td>\n<\/tr>\n
#2290<\/td>\nDSA\u4e00\u9636\u6bb5TND\u6392\u5e03\u65f6attention\u88ab\u8feb\u9000\u56deBSND\u6392\u5e03\u89c4\u907f<\/td>\n\u6839\u56e0：FA\u7b97\u5b50\u8f93\u51fa\u7684softmax_max\/softmax_sum\u6392\u5e03\u4e0d\u7b26\u5408TND\u4e00\u9636\u6bb5\u9700\u8981，\u6b64\u524d\u7528BSND\u89c4\u907f\u3002\u4fee\u590d：PR8288\u65b0\u589esoftmax_out\u6392\u5e03\u8f6c\u6362，\u4e00\u9636\u6bb5\u76f4\u63a5\u7528FA\u7684TND\u6392\u5e03；8\u5c42\u7eafpp\u7f51\u7edc\u65b0\u65e7\u5b9e\u73b0loss\u5bf9\u9f50，\u5e76\u6cdb\u5316\u9a8c\u8bc1dp=tp=cp=pp=2\u3002Fixes\u663e\u5f0f，2026-05-27\u5408\u5165\u3002<\/td>\n<\/tr>\n
#2302<\/td>\nDSAIndexer\u4e2drotary\u4f4d\u7f6e\u7f16\u7801\u8ba1\u7b97\u4e0d\u6b63\u786e<\/td>\nPR8317\u300einterleave fix\u300f\u4fee\u6539indexer\u4e2d\u7684rope\u914d\u7f6e（interleaved rotary\u4fee\u6b63），\u6b63\u6587Fixes #2302；2026-06-26T11:09:44\u5408\u5165\u4e0e\u5173\u5355\u65f6\u95f4\u79d2\u7ea7\u4e00\u81f4（Fixes\u81ea\u52a8\u5173\u5355）\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

mindformers（\u5927\u6a21\u578b\u5957\u4ef6\u00b7\u8f85\u52a9 loss \u7f29\u653e\u4e0e MoE \u7edf\u8ba1\u53e3\u5f84）<\/h3>\n

\u7cbe\u5ea6\u5bf9\u9f50\u957f\u5c3e\u9ad8\u53d1\u533a：aux\/MTP loss \u53cd\u5411\u7f29\u653e\u3001expert_bias \u7edf\u8ba1\u4e0e grad_norm \u6253\u5370\u53e3\u5f84<\/p>\n\n\u7f16\u53f7Issue \u95ee\u9898\u5185\u5bb9\u89e3\u7b54\u603b\u7ed3<\/tr>\n\n\n\n\n\n\n\n
#2257<\/td>\n\u5f00\u542fFSDP+EP\u7ec4\u5408\u7cbe\u5ea6\u4e0e\u5355\u5361\u8bad\u7ec3\u4e0d\u5bf9\u9f50<\/td>\nPR8242\u300efix loss sense for distributed\u300f\u6b63\u6587\u663e\u5f0f\u5173\u8054#2257：\u5206\u5e03\u5f0f\u4e0bloss sense（\u8f85\u52a9loss\u53cd\u5411\u7f29\u653e）\u8bbe\u7f6e\u9519\u8bef，\u81f4FSDP+EP\u4e0e\u5355\u5361\u4e0d\u5bf9\u9f50；05-08\u5408\u5165\u3001\u6b21\u65e5\u5173\u5355\u3002\u4e0e\u540e\u7eed#2356\/#2380\u7684loss sense\u95ee\u9898\u65cf\u540c\u6e90\u3002<\/td>\n<\/tr>\n
#2329<\/td>\nexpert_bias\u8ba1\u7b97\u9759\u6001\u56fe\u672a\u505a\u96f6\u5747\u503c\u5f52\u4e00\u5316\u4e0e\u52a8\u6001\u56fe\u4e0d\u4e00\u81f4<\/td>\n\u6839\u56e0：\u52a8\u6001\u56feexpert_bias\u8ba1\u7b97\u505a\u4e86\u96f6\u5747\u503c\u5f52\u4e00\u5316\u3001\u9759\u6001\u56fe\u6ca1\u505a，expert_bias_delta\u53ca\u66f4\u65b0\u7ed3\u679c\u4e0d\u4e00\u81f4\u3002\u4fee\u590d：PR8363\u5220\u9664\u52a8\u6001\u56fe\u96f6\u5747\u503c\u5f52\u4e00\u5316\u7edf\u4e00\u53e3\u5f84，\u91cd\u6253expert_bias_delta\u9a8c\u8bc1\u4e00\u81f4；06-08T21:42:26\u5408\u5165\u4e0e\u5173\u5355\u79d2\u7ea7\u4e00\u81f4\u3002<\/td>\n<\/tr>\n
#2338<\/td>\n\u52a8\u6001\u56felocal\/device grad_norm\u6253\u5370\u7684\u662f\u901a\u4fe1\u540e\u7684\u503c<\/td>\nPR8385\u300eprint local_norm\u300f\u6b63\u6587\u663e\u5f0f\u5173\u8054#2338：\u8c03\u6574local\/device grad_norm\u6253\u5370\u53e3\u5f84\u4e3a\u901a\u4fe1\u524d\u7684\u672c\u5730\u503c；06-18T18:08:59\u5408\u5165\u4e0e\u5173\u5355\u79d2\u7ea7\u4e00\u81f4\u3002<\/td>\n<\/tr>\n
#2349<\/td>\n\u5e76\u884c\u4e0btokens_per_expert_by_layer\u672aall_reduce\u81f4\u7cbe\u5ea6\u4e0d\u9f50<\/td>\n\u6839\u56e0：\u5f00\u542f\u5e76\u884c\u65f6tokens_per_expert_by_layer\u672a\u505aall_reduce，\u5404dp\u57df\u7edf\u8ba1\u4e0d\u4e00\u81f4\u2192\u66f4\u65b0\u540eexpert_bias\u5206\u53c9\u3001\u7cbe\u5ea6\u65e0\u6cd5\u5bf9\u9f50\u3002PR8400\u300e\u52a8\u6001\u56feexpert_bias all_reduce\u300f\u8865\u9f50\u89c4\u7ea6，\u6b63\u6587\u663e\u5f0f\u5173\u8054#2349；06-13T19:26:00\u5408\u5165\u4e0e\u5173\u5355\u79d2\u7ea7\u4e00\u81f4\u3002<\/td>\n<\/tr>\n
#2380<\/td>\n\u5355\u5361\u68af\u5ea6\u7d2f\u79ef\u4e0bMTP\/aux loss\u68af\u5ea6\u88ab\u653e\u5927\u4e0e\u4e0d\u7d2f\u79ef\u4e0d\u4e00\u81f4<\/td>\nPR8436\u663e\u5f0f\u5173\u8054#2380：\u4e3bCE loss\u5df2\u505a\u7d2f\u79ef\u5f52\u4e00，\u4f46MoE aux\/mtp\/index\u8f85\u52a9loss\u7684AutoScaler backward scale\u539f\u4ec5\u5728SPMD\u8def\u5f84\u8bbe\u7f6e，\u5355\u5361\u4fdd\u63011.0\u672a\u6298\u53e01\/\u7d2f\u79ef\u6b65\u6570，\u8f85\u52a9\u68af\u5ea6\u653e\u5927N\u500d\u3002\u4fee\u590d：Trainer\u521d\u59cb\u5316\u65e0\u6761\u4ef6\u7edf\u4e00\u8bbe\u7f6e\u7f29\u653e\u3002\u5173\u5355\u8bc4\u8bba\u9a8c\u8bc1：\u4fee\u590d\u540e\u7d2f\u79efvs\u4e0d\u7d2f\u79efgrad_norm\u5dee2.8e-03(bf16\u566a\u58f0\u7ea7)\u3002<\/td>\n<\/tr>\n
#2398<\/td>\ntp\u5207\u5206\u4e0bmoe\u6a21\u578bindexer loss\u5bf9\u6bd4\u57fa\u7ebf\u5b58\u5728\u8df3\u53d8<\/td>\n\u6839\u56e0（\u8bc4\u8bba）：tp\u5207\u5206\u4e0bindexer\u4e0emoe\u53e0\u52a0\u9020\u6210\u7d2f\u79ef\u6570\u503c\u6f02\u79fb，\u6700\u7ec8loss\u8df3\u53d8\u3002PR 8479\u79fb\u9664indexer_loss\u7684tp\u5207\u5206（\u5173\u95edcsa\u90e8\u5206tp\u4ee5\u89c4\u907f），\u5bf9\u9f50\u540e\u66f2\u7ebf\u590d\u5e73\u3002Fixes\u663e\u5f0f\u6807\u6ce8\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

mindformers（\u5927\u6a21\u578b\u5957\u4ef6\u00b7pynative \u52a8\u6001\u56fe\u80fd\u529b）<\/h3>\n

pynative \u52a8\u6001\u56fe\u80fd\u529b\u8865\u9f50\u4e0e\u6027\u80fd：\u68af\u5ea6\u88c1\u526a\u3001\u5ef6\u8fdf\u521d\u59cb\u5316\u3001CPU \u4fa7\u5207\u7247\u4e0e\u6570\u636e\u5e7f\u64ad<\/p>\n\n\u7f16\u53f7Issue \u95ee\u9898\u5185\u5bb9\u89e3\u7b54\u603b\u7ed3<\/tr>\n\n\n\n\n\n\n\n\n\n
#2275<\/td>\n\u52a8\u6001\u56fe\u8bad\u7ec3\u4e0d\u652f\u6301\u68af\u5ea6\u88c1\u526a<\/td>\n\u80fd\u529b\u7f3a\u53e3\u800c\u975e\u56de\u5f52：pynative Trainer\u7f3aclip_grad\u8def\u5f84\u3002PR 8260\u5b9e\u73b0\u52a8\u6001\u56fe\u68af\u5ea6\u88c1\u526a\u9632\u68af\u5ea6\u7206\u70b8，\u5e76\u5c06\u9700_distribute_param\u7684\u53c2\u6570\u7edf\u4e00\u653e\u5165plan\u518d\u5206\u53d1；fsdp+tp+ep\u591a\u7ec4\u5408\u4e0e\u5355\u5361\u7cbe\u5ea6\u5bf9\u9f50\u3002\u5408\u5165\u4e0e\u5173\u5355\u540c\u79d2\u3002<\/td>\n<\/tr>\n
#2278<\/td>\n\u5ef6\u8fdf\u521d\u59cb\u5316\u4ecd\u6162，\u6539\u7528ms\u63a5\u53e3\u7a7f\u523a\u7ee7\u7eed\u63d0\u901f<\/td>\nPR 8205\u9996\u7248\u5ef6\u8fdf\u521d\u59cb\u5316（5\u5c42\u6a21\u578b\u6784\u5efa51s\u219224s）；PR 8271\u6539\u7528ms\u63a5\u53e3\u7a7f\u523a：100\u5c42193s\u21921.5s\u3001500\u5c42\u4ec57.5s，\u7eed\u8bad\u7cbe\u5ea6fsdp\/tp\/ep\u5404\u7ec4\u5408\u5bf9\u9f50\u3002Fixes\u663e\u5f0f\u6807\u6ce8，\u5408\u5165\u4e0e\u5173\u5355\u540c\u79d2\u3002<\/td>\n<\/tr>\n
#2330<\/td>\npynative Dropout\u5728drop_prob=0.0\u8bad\u7ec3\u6001\u4ecd\u4e0b\u53d1dropout\u7b97\u5b50<\/td>\n\u8bed\u4e49\u7f3a\u9677：\u6982\u7387\u4e3a0\u5373\u8bed\u4e49\u5173\u95ed，\u8bad\u7ec3\u6001\u4e5f\u5e94\u76f4\u8fd4\u8f93\u5165（\u8bad\u7ec3\u56fe\u5e93transformer dropout\u5df2\u6709\u77ed\u8def\u5148\u4f8b）\u3002PR 8367\u5728construct\u52a0\u77ed\u8def：training=False\u6216drop_prob=0.0\u76f4\u63a5\u8fd4\u56de，\u4ec5\u771f\u542f\u7528\u65f6\u8c03mint F.dropout，\u5e76\u8865\u56de\u5f52\u7528\u4f8b\u3002\u5408\u5165\u4e0e\u5173\u5355\u540c\u79d2\u3002<\/td>\n<\/tr>\n
#2332<\/td>\n\u5f00dp shard\u540edp\u5927\u5c0f\u4e0edp_shard\u76f8\u540c，\u5e94\u4e0edp\u4e00\u81f4<\/td>\n\u5e76\u884c\u7ef4\u5ea6\u8bed\u4e49\u9519\u8bef\u3002PR 8372\u4fee\u6b63\u5f00dp\u540e\u6570\u636edp\u4e0edp\u5927\u5c0f\u4e00\u81f4；dp shard2 replicate2 gbs4\u4e0e\u5355\u5361gbs4\u7cbe\u5ea6\u5bf9\u9f50\u9a8c\u8bc1\u3002KG\u4f50\u8bc1：FSDP\u6309\u5206\u7247\u5ea6\u5207\u5206\u53c2\u6570\/\u68af\u5ea6\/\u4f18\u5316\u5668\u72b6\u6001，dp_shard\u4e0edp_replicate\u5206\u5de5\u4e0d\u540c\u3002<\/td>\n<\/tr>\n
#2334<\/td>\n\u52a8\u6001\u56fe\u52a0\u8f7d\u6743\u91cdslice\u65f6h2d\u5f71\u54cd\u6027\u80fd\u5185\u5b58，\u6613\u5361\u6b7b<\/td>\n\u6839\u56e0：\u8f6c\u6362\u7b56\u7565slice\u524d\u5148\u628a\u6743\u91cdh2d\u62f7\u5230device\u518d\u5207\u7247\u8fd4\u56de\u3002PR 8375\u7528with DeviceCtx(\u201cCPU\u201d)\u4e0a\u4e0b\u6587\u76f4\u63a5\u5728CPU\u4e0a\u5207\u7247\u4e0d\u505ah2d，\u8282\u7ea6\u5185\u5b58\u4e0e\u65f6\u95f4：\u52a8\u6001\u56fefsdp2tp2ep2\u8f6c\u914d\u63d0\u901f\u7ea620%\u3001\u9759\u6001\u56fedp2tp4\u8f6ctp8\u63d0\u901f\u7ea633%\u3002Fixes\u663e\u5f0f\u6807\u6ce8\u3002<\/td>\n<\/tr>\n
#2448<\/td>\ndsv4\u878d\u5408\u7b97\u5b50\u5206\u652f(csa_fix)\u5f00\u91cd\u8ba1\u7b97\u540e\u663e\u5b58\u6301\u7eed\u589e\u957f\u81f3OOM<\/td>\n\u91cd\u8ba1\u7b97\u672c\u4e3a\u7701\u663e\u5b58\u5374\u53cd\u5411\u6cc4\u9732：csa\u878d\u5408\u7b97\u5b50\u5206\u652f\u91cd\u8ba1\u7b97\u8fc7\u7a0b\u90e8\u5206\u4e2d\u95f4\u5f20\u91cf\u672a\u88ab\u6b63\u786e\u91ca\u653e\u3002PR 8571\u4fee\u590d\u91ca\u653e\u903b\u8f91，\u9644\u4fee\u590d\u524d\u540e\u663e\u5b58\u66f2\u7ebf\u5bf9\u6bd4；\u5408\u5165\u4e0e\u5173\u5355\u540c\u79d2\u3002KG\u4f50\u8bc1\u6fc0\u6d3b\u91cd\u8ba1\u7b97\u5c5e\u8bad\u7ec3\u663e\u5b58\u4f18\u5316\u56db\u5c42\u624b\u6bb5\u4e4b\u4e00\u3002<\/td>\n<\/tr>\n
#2468<\/td>\nMaxLogitsMonitor\u9694\u6b65\u6253\u5370\u5d29\u6e83\u4e14\u65e0\u6cd5\u72ec\u7acb\u5173\u95ed\u65e5\u5fd7<\/td>\n\u6839\u56e0：\u975e\u6253\u5370\u6b65\u628aTrainer\u7684\u6a21\u578b\u5217\u8868\u4f20\u7ed9\u5355\u6a21\u578breset\u63a5\u53e3\u62a5AttributeError；\u65e5\u5fd7\u8f93\u51fa\u4e0e\u6bcf\u6b65\u6e05\u96f6tracking\u72b6\u6001\u8026\u5408\u3002PR 8602\u65b0\u589eenable_logging\u3001reset\u6bcf\u6b65\u6267\u884c\u4e0e\u65e5\u5fd7\u89e3\u8026，step_interval\u53ea\u63a7\u9891\u7387，\u8df3\u8fc7\u6253\u5370\u4e0d\u8bfbTensor\u907f\u514d\u989d\u5916D2H\u540c\u6b65；30\u4e2aUT\u901a\u8fc7\u3002<\/td>\n<\/tr>\n
#2524<\/td>\n\u5f00use_distribute_dataset\u540e\u6240\u6709rank\u5197\u4f59\u521d\u59cb\u5316\u6570\u636e\u4e0eindex map<\/td>\nPR 8704\/8738（master\u4e0er2.1.0-beta1\u53cc\u5206\u652f）：\u6bcf\u4e2aTP\u00d7CP\u6570\u636e\u57df\u4ec5src rank\u771f\u6b63\u8bfb\u53d6\u6784\u9020\u6570\u636e\u96c6，\u5176\u4f59rank\u8fd0\u884c\u65f6\u63a5\u6536\u5e7f\u64adbatch；ordered_index_dataloader\u4ec5rank0\u751f\u6210\u5e76\u4fdd\u5b58index map\u30028\u5361TP2dp4\u8bad\u7ec350\u6b65\u7ed3\u679c\u4e0e\u6539\u524d\u4e00\u81f4\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

mindformers（\u5927\u6a21\u578b\u5957\u4ef6\u00b7dsv4 \u4e0e\u65ad\u70b9\u7eed\u8bad）<\/h3>\n

DeepSeek V4 \u9002\u914d\u4e0e\u65ad\u70b9\u7eed\u8bad：hash router \u6821\u9a8c\u3001\u4f18\u5316\u5668\u72b6\u6001\u524d\u7f6e\u6821\u9a8c\u4e0e\u9009\u62e9\u6027\u91cd\u8f7d<\/p>\n\n\u7f16\u53f7Issue \u95ee\u9898\u5185\u5bb9\u89e3\u7b54\u603b\u7ed3<\/tr>\n\n\n\n\n\n\n\n\n\n
#2292<\/td>\nMLA q_lora_rank=None\u65f6\u5f00tensor_parallel\u62a5\u6a21\u5757\u4e0d\u5b58\u5728<\/td>\n\u6839\u56e0：MLASelfAttention\u4ec5\u5728q_lora_rank\u975eNone\u65f6\u521b\u5efalinear_qb\/q_layernorm\u5b50\u6a21\u5757，\u4f46parallelize.py\u7684TP\u5207\u5206\u8ba1\u5212\u65e0\u6761\u4ef6\u6536\u5f55\u4e24\u8005，\u5207\u5206\u65f6Module not found\u62a5\u9519\u3002PR8299\u6539\u4e3a\u6309q_lora_rank\u6761\u4ef6\u52a0\u5165TP plan；05-26T20:49:53\u5408\u5165\u4e0e\u5173\u5355\u79d2\u7ea7\u4e00\u81f4\u3002<\/td>\n<\/tr>\n
#2335<\/td>\n\u9759\u6001\u56fe\u5f00pp(>2)\u65f6\u52a0\u8f7d\u6743\u91cd\u5931\u8d25<\/td>\n\u8bc4\u8bba\u4e8c\u5206\u5b9a\u4f4d\u5230commit 25408a34（\u52a8\u6001\u56fe\u6743\u91cd\u52a0\u8f7d\u4fdd\u5b58PR8191）\u3002\u6839\u56e0：\u9759\u6001\u56fe\u53d6\u5168\u5c40meta\u4fe1\u606f\u5e94\u6309\u5404\u5361rank_id\u53d6\u5bf9\u5e94layout，\u52a8\u6001\u56fe\u9002\u914d\u65f6\u8bef\u75280\u5361layout\u3002PR8384\u6539\u4e3a\u6309rank\u53d6layout，ds3 dp2tp2pp2\u7eed\u8bad\u7cbe\u5ea6\u5bf9\u9f50\u3002<\/td>\n<\/tr>\n
#2411<\/td>\ndsv4\u5355\u5361\u8bad\u7ec3\u62a5\u9519：\u4e0d\u652f\u6301meta\u5230Ascend\u7684copy<\/td>\n\u540c\u62a5\u9519\u4e09\u8fde\u5355#2411\/#2412\/#2414，\u6b63\u4e3b#2413\u6839\u56e0：\u7248\u672c\u66f4\u65b0\u540e\u53c2\u6570\u521d\u59cb\u5316\u9700\u663e\u5f0fmint.empty，\u5426\u5219\u8bbe\u5907\u7c7b\u578b\u4e0d\u7b26\u62a5\u6b64\u9519；PR8493\u6539\u663e\u5f0f\u521d\u59cb\u5316\u5e76\u79fb\u9664\u6ce8\u91ca\u4e2dMegatron\u4fe1\u606f，\u5408\u5165\u5f53\u65e5#2413\u6839\u56e0\u8bc4\u8bba\u540e13\u79d2\u5173\u5355，\u4e09\u8fde\u53557\/1\u6279\u91cf\u5173\u95ed\u3002<\/td>\n<\/tr>\n
#2442<\/td>\nhc_sinkhorn_iters:0\u914d\u7f6e\u88ab\u524d\u7aef\u6821\u9a8c\u62e6\u622a<\/td>\nPR8550\u53bb\u9664mhc_sinkhorn_iterations==0\u9650\u5236：\u8be5\u62e6\u622a\u672a\u4e0eMegatron-LM\u5bf9\u9f50\u3002DsV4\u7684HC（Head Compression）\u673a\u5236\u7528Sinkhorn\u6df7\u5408\u628ahidden state\u5c55\u5f00\u5230[B,S,Hc,D]，\u8fed\u4ee3\u65700\u662f\u5408\u6cd5\u914d\u7f6e；\u89e3\u9664\u540e\u6b63\u5e38\u62c9\u8d77\u8bad\u7ec3\u3002\u5408\u51656\u5206\u949f\u540e\u5173\u5355\u3002<\/td>\n<\/tr>\n
#2459<\/td>\n\u65ad\u70b9\u7eed\u8bad\u7f3aoptimizer\u6587\u4ef6\u65f6\u62a5\u9519\u4e0d\u660e\u786e，HF\u6743\u91cd\u7eed\u8bad\u65e0\u524d\u7f6e\u6821\u9a8c<\/td>\nPR8588\u65b0\u589ehas_optimizer_ckpt\u68c0\u6d4bopt-.safetensors，\u5e76\u5728Trainer\u52a0\u8f7d\u524d\u6821\u9a8c：HF checkpoint+no_load_optim=False\u76f4\u63a5\u660e\u786e\u62a5\u9519\u4e0d\u652f\u6301；MS checkpoint\u7f3aopt\u6587\u4ef6\u63d0\u524d\u62a5\u9519\u5e76\u63d0\u793a\u8bbeno_load_optim=True\u6216\u68c0\u67e5\u6587\u4ef6\u3002issue\u6b63\u6587\u9644\u4fee\u590d\u63d0\u4ea4e46a1ac25\u3002<\/td>\n<\/tr>\n
#2460<\/td>\nhash router\u4e0d\u80fd\u5728pp\u4e0b\u4f7f\u7528\u7684\u6821\u9a8c\u9700\u53bb\u9664<\/td>\n\u52a8\u6001\u56fepp\u4ee3\u7801\u5df2\u5408\u5165，\u8be5\u62e6\u622a\u8fc7\u65f6\u3002PR8590\u53bb\u9664transformersconfig\u4e2dhash router\u4e0d\u80fd\u5728pp\u4e0b\u4f7f\u7528\u7684\u6821\u9a8c，hash router+pp\u53ef\u6b63\u5e38\u62c9\u8d77\u3002\u80cc\u666f：DsV4\u524dnum_hash_layers\u5c42\u7528token-id\u54c8\u5e0c\u8def\u7531\u66ff\u4ee3top-k softmax\u8def\u7531\u3002<\/td>\n<\/tr>\n
#2475<\/td>\nhash router\u7684tid2eid\u5728\u72ec\u7acbFSDP\u5c01\u88c5\u4e0b\u5f62\u72b6\u4e0d\u5339\u914d<\/td>\n\u5f15\u5165PR8581\u4e3aFP32 router\u52a0\u72ec\u7acbFSDP\u5b50\u5305\u88c5，\u7ed5\u8fc7\u7236\u5c42policy\u5bf9tid2eid[vocab,topk]\u67e5\u8868\u7684\u590d\u5236\u7ea6\u675f，8\u5361\u5207\u5206\u540e\u5ef6\u8fdf\u521d\u59cb\u5316\u5199\u56de\u5168\u8868\u89e6\u53d1(16384,4)!=(131072,4)\u65ad\u8a00\u3002PR8619\u5220\u9664\u8be5\u5b50\u5305\u88c5，\u53c2\u6570\u56de\u5f52\u7236layer\u7edf\u4e00\u7ba1\u7406，\u6027\u80fd\u6ce2\u52a8+0.41%\u5185\u3002<\/td>\n<\/tr>\n
#2490<\/td>\n\u65ad\u70b9\u7eed\u8bad\u56e0\u51bb\u7ed3\u53c2\u6570\u7f3a\u4f18\u5316\u5668\u53c2\u6570\u81f4\u4e8c\u9636\u6bb5loss\u7a81\u53d8<\/td>\nmla\u2192dsa\u4e00\u9636\u6bb5\u2192dsa\u4e8c\u9636\u6bb5\u7eed\u8bad\u65f6\u65b0\u89e3\u51bb\u53c2\u6570\u65e0\u4f18\u5316\u5668\u72b6\u6001，\u4e3b\u6743\u91cd\u88ab\u5168\u91cf\u91cd\u8f7d\u8986\u76d6\u5df2\u8bad\u7ec3\u72b6\u6001\u3002PR8623：AdamW\/Muon\u4fdd\u5b58fp32\u4e3b\u6743\u91cdsum()\u6821\u9a8c\u548c\u5feb\u7167，reload_main_params_from_model\u4ec5\u5bf9\u5feb\u7167\u672a\u53d8\u53c2\u6570\u9009\u62e9\u6027\u91cd\u8f7d，\u5176\u4f59\u4fdd\u7559\u68c0\u67e5\u70b9\u4f18\u5316\u5668\u72b6\u6001；\u56de\u5408PR8676\u5165r2.1.0-beta1\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u7ec4\u5408\u89e3\u8bfb：\u8fd9 50 \u6761\u91cc\u7684\u5171\u6027\u89c4\u5f8b<\/h3>\n

1. \u4e3b\u4ed3\u56fe\u6267\u884c\u4e0e\u7b97\u5b50\u4fee\u590d\u4e03\u6848：dry run \u6790\u6784\u3001\u5e38\u91cf\u6298\u53e0\u540c\u6b65\u4e0e\u878d\u5408\u5730\u5740\u8e29\u8e0f\u3002 \u672c\u6279\u4e3b\u4ed3\u6280\u672f\u957f\u5c3e\u4ee5\u300c\u6267\u884c\u8def\u5f84\u7684\u9690\u85cf\u72b6\u6001\u300d\u4e3a\u4e3b：\u8df3\u8fc7\u7684\u7f16\u8bd1\u3001\u672a\u540c\u6b65\u7684\u8f93\u5165\u3001\u5faa\u73af\u5185\u65e9\u91ca\u7684\u5730\u5740，\u90fd\u5728\u7279\u5b9a\u8def\u5f84\u624d\u663e\u5f62\u3002<\/p>\n

    \n
  • mindspore#21803 DVM MatMul \u878d\u5408\u7b97\u5b50 dry run core dump：\u8df3\u8fc7\u7f16\u8bd1\u81f4 kernel \u53d8\u91cf\u672a\u521d\u59cb\u5316\u3001\u6790\u6784\u8bbf\u95ee\u91ce\u6307\u9488\u2014\u2014PR 80369 \u6790\u6784\u5224\u7a7a+\u8865 ST（\u79d2\u7ea7\u94c1\u8bc1）<\/li>\n
  • mindspore#28944 \u56fe\u7f16\u8bd1 infer value \u9700 CPU \u4fa7\u8f93\u5165\u505a\u5e38\u91cf\u6298\u53e0，device tensor \u672a\u540c\u6b65 host \u5c31\u8fdb host \u8ba1\u7b97\u2014\u2014PR 91764 \u524d\u7f6e\u6821\u9a8c\u540c\u6b65（\u5408\u5165 20 \u5206\u949f\u540e\u5173\u5355，\u540e\u7eed 91981 \u91cd\u505a\/92098 \u56de\u9000\u94fe）<\/li>\n
  • mindspore#28999 \u52a8\u6001\u56fe LazyFusion \u7684 device_address \u662f\u5faa\u73af\u5185\u5c40\u90e8 weak_ptr，\u5f53\u8f6e\u91ca\u653e\u540e\u5730\u5740\u590d\u7528\/\u4e0e workspace \u51b2\u7a81\u2014\u2014\u591a\u8f93\u51fa\u878d\u5408\u7b97\u5b50\u89e6\u53d1\u7cbe\u5ea6\u95ee\u9898，PR 91865 \u4fee\u5730\u5740\u8e29\u8e0f<\/li>\n
  • mindspore#21812 GMM 310P nz weight \u81ea\u52a8\u8f6c\u6362\u88ab\u91cd\u6784\u8bef\u5220：\u5f15\u5165 PR 74073\u2192\u8bef\u5220 PR 74745\u2192\u4fee\u590d PR 80259 \u4e09\u951a\u70b9\u8fd8\u539f\u5168\u94fe（\u79d2\u7ea7\u94c1\u8bc1）<\/li>\n
  • mindspore#28905 MaskedFill \u53cd\u5411\u7528\u4e58\u6cd5\u63a9\u7801，dout \u542b NaN\/Inf \u65f6 0*NaN \u4ecd\u4e3a NaN\u3001\u88ab\u63a9\u7801\u4f4d\u68af\u5ea6\u975e 0\u2014\u2014PR 91648 \u91cd\u5199\u53cd\u5411\u5bf9\u9f50 PyTorch \u7684 masked_select \u8bed\u4e49<\/li>\n
  • mindspore#21810 xlogy \u5165\u53c2\u547d\u540d\u4e0e\u53c2\u8003\u63a5\u53e3 other \u5173\u7cfb\u4e0d\u6e05：PR 80293 \u8865\u6587\u6863（\u6b63\u6587\u4e0e\u6807\u9898\u9010\u5b57\u3001\u79d2\u7ea7），\u524d\u7f6e 80179 \u540c\u4e3b\u9898<\/li>\n
  • mindspore#20673 kv_scale_cache \u91cf\u5316 KV cache \u7f29\u653e\u80fd\u529b：PR 85440 \u6d4b\u8bd5\u901a\u8fc7\u540e\u968f infer_ops iter4（PR 86633）\u8fed\u4ee3\u5408\u5165，\u65f6\u95f4\u7a97+\u6b63\u6587\u8bed\u4e49\u53cc\u543b\u5408<\/li>\n<\/ul>\n

    2. \u901a\u4fe1\u57df\u3001\u7ed1\u6838\u4e0e\u8bad\u7ec3\u6062\u590d\u4e94\u6848：\u8c01\u521b\u5efa\u8c01\u9500\u6bc1\u3001\u5f02\u6b65\u521d\u59cb\u5316\u4e0e\u5feb\u6062\u3002 \u96c6\u7fa4\u89c4\u6a21\u4e0a\u53bb\u540e，\u901a\u4fe1\u57df\u751f\u547d\u5468\u671f\u4e0e\u521d\u59cb\u5316\u8017\u65f6\u5206\u644a\u6210\u4e3a\u4e3b\u77db\u76fe；\u4e94\u6848\u7684\u4fee\u590d\u601d\u8def\u90fd\u662f\u5398\u6e05\u5f52\u5c5e\u2014\u2014\u8c01\u521b\u5efa\u8c01\u9500\u6bc1\u3001\u521d\u59cb\u5316\u6309\u89c4\u6a21\u5f02\u6b65\u5316\u3001\u7ed1\u5b9a\u6309\u62d3\u6251\u627e\u4eb2\u548c\u3002<\/p>\n

      \n
    • mindspore#28907 \u590d\u7528\u5916\u90e8 hcom \u65f6 AscendCommunicationGroup::Finalize \u65e0\u6761\u4ef6 HcclCommDestroy，\u9500\u6bc1\u4e86\u4e0d\u5c5e\u4e8e\u81ea\u5df1\u7684\u901a\u4fe1\u5668\u2014\u2014options \u4f20\u5165\u5373\u8df3\u8fc7（PR 91647，\u5408\u5165\u4e0e\u5173\u5355\u5dee 99 \u79d2）<\/li>\n
    • mindspore#28992 4k \u8282\u70b9 mccl \u521d\u59cb\u5316 10 \u5206\u949f（SynchronizeAddresses \u968f\u89c4\u6a21\u7ebf\u6027\u53d8\u6162）：92054 \u5408\u5165\u219292174 \u56de\u9000\u219292456 \u91cd\u505a\u5408\u5165，SSR \u6d3b\u52a8\u6d41\u5171\u5173\u8054 15 \u4e2a MR \u7684\u5b8c\u6574\u843d\u5730\u94fe<\/li>\n
    • mindspore#28991 A3 \u65e0 npu-numa \u4eb2\u548c\u5173\u7cfb\u65f6\u7ed1\u5b9a\u7b56\u7565\u9000\u5316\u4e3a\u5747\u5206，\u53e0\u52a0 ASCEND_RT_VISIBLE_DEVICES \u540e\u7ed1\u4e0d\u4e0a\u5185\u5b58\u2014\u2014PR 91845 \u4fee A3 \u573a\u666f（KG：\u8be5\u73af\u5883\u53d8\u91cf\u8bed\u4e49\u89c1 runtime \u8bbe\u5907\u7ba1\u7406\u6587\u6863）<\/li>\n
    • mindspore#21143 \u84b8\u998f teacher \u5168\u51bb\u7ed3+lazy_inline \u5f00 PP \u5e76\u884c\u7f16\u8bd1\u5361\u6b7b\u5728 receive begin\u2014\u2014PR 88049 freeze grad+88260 fix_freeze_bug \u53cc PR \u5747\u6302\u540c\u4e00 gitee \u5355 ICR1P3<\/li>\n
    • mindspore#21705 \u7cbe\u5ea6\u6545\u969c\u4e0d\u91cd\u542f\u5feb\u6062\u5076\u73b0\u5361\u6b7b：PR 84439 support spike fast recovery \u6b63\u6587\u4e0e\u6807\u9898\u8bed\u4e49\u76f4\u914d（Fixes \u5185\u90e8\u9700\u6c42\u53f7），3 \u5929\u540e\u5173\u5355<\/li>\n<\/ul>\n

      3. \u63a5\u53e3\u8bed\u4e49\u4e0e\u6821\u9a8c\u4e09\u6848：\u8d8a\u754c\u9759\u9ed8\u3001keyword-only \u4e0e\u521d\u59cb\u5316\u58f0\u660e\u3002 \u63a5\u53e3\u6f14\u8fdb\u671f\u7684\u4e09\u7c7b\u300c\u884c\u4e3a\u53d8\u5316\u4e0d\u662f bug\u300d：\u6821\u9a8c\u8865\u9f50\u8ba9\u65e7\u7528\u4f8b\u5f00\u59cb\u62a5\u9519\u3001\u53c2\u6570\u53d8 keyword-only\u3001\u6784\u9020\u5668\u4e0d\u518d\u9690\u5f0f\u521d\u59cb\u5316\u3002<\/p>\n

        \n
      • mindspore#544 mint.narrow pynative \u7f3a start\/length \u8d8a\u754c\u6821\u9a8c（graph \u6a21\u5f0f\u5df2\u6709）\u2014\u2014\u5f00\u53d1\u8865\u6821\u9a8c\u540e\u7528\u4f8b\u6062\u590d\u9884\u671f\u62a5\u9519（\u4e0a\u7bc7\u62c6\u5165）<\/li>\n
      • mindspore#248 gelu approximate \u6539 keyword-only \u5bf9\u9f50 torch2.1（\u5f15\u5165 PR 81218）：\u7279\u6027\u76f4\u5408 master \u4e14\u8f6c\u6d4b\u90ae\u4ef6\u53d1\u665a，\u6d4b\u8bd5\u4ed3\u672a\u611f\u77e5\u2014\u2014\u7528\u4f8b\u9002\u914d（\u4e0a\u7bc7\u62c6\u5165）<\/li>\n
      • mindspore#29001 init \u6784\u9020\u5f20\u91cf\u6253\u5370 uninitialized \u5c5e\u9884\u671f：\u4fee\u6b63\u65e9\u671f\u300c\u9690\u5f0f\u521d\u59cb\u5316\u300d\u4e0d\u4e25\u8c28\u8bbe\u8ba1；KG \u4f50\u8bc1\u540c\u751f\u6001 PyPTO FAQ \u540c\u53e3\u5f84（\u58f0\u660e\u4e0d\u542b\u521d\u59cb\u5316\u884c\u4e3a\u3001\u672a\u521d\u59cb\u5316\u4e0d\u7533\u8bf7\u5185\u5b58\u3001\u5148\u5199\u540e\u8bfb）<\/li>\n<\/ul>\n

        4. \u6559\u7a0b\u590d\u73b0\u53e3\u5f84\u4e0e\u73af\u5883\u4e03\u5751：\u9b54\u672f\u547d\u4ee4\u6b8b\u7559\u3001\u5e73\u53f0\u5dee\u5f02\u4e0e\u6e20\u9053\u5305\u3002 \u6559\u7a0b\u7c7b issue \u7684\u5171\u540c\u7b54\u6848\u662f\u300c\u5148\u6838\u5e73\u53f0\u4e0e\u6e20\u9053，\u518d\u6000\u7591\u4ee3\u7801\u300d；\u4e24\u6761\u540c\u6e90 issue \u5171\u7528\u4e00\u7ec4\u4fee\u590d PR \u662f\u672c\u7ec4\u7279\u8272\u3002<\/p>\n

          \n
        • mindspore#29002 WeightedRandomSampler \u793a\u4f8b\u6b8b\u7559 Jupyter \u9b54\u672f\u547d\u4ee4 %matplotlib inline，\u590d\u5236\u8fdb .py \u5373 SyntaxError\u2014\u2014docs#18291（master）\/#18299（r2.8.0）\u5220\u9664\u8be5\u884c，\u53cc\u5206\u652f\u540c\u65e5\u5408\u5165<\/li>\n
        • mindspore#29033 \u4e0e\u4e0a\u6761\u540c\u6e90：\u540c\u4e00\u9875\u9762\u7684\u65e0\u6548\u5b57\u7b26\u4e32\u65e2\u81f4\u663e\u793a\u5f02\u5e38\u53c8\u81f4\u4ee3\u7801\u62a5\u9519\u2014\u2014\u540c\u4e00\u7ec4 PR \u4fee\u590d，\u300c\u4e00\u5904\u6b8b\u7559\u4e24\u4e2a issue\u300d\u7684\u6837\u672c<\/li>\n
        • mindspore#29054 \u56fe\u6a21\u5f0f\u975e\u63a7\u5236\u6d41\u7528\u4f8b Windows \u6267\u884c\u62a5\u9519\u5c5e\u5e73\u53f0\u9650\u5236\u2014\u2014docs#18261\/#18262 \u8865 Ascend \u5e73\u53f0\u9650\u5236\u8bf4\u660e（2026-02-27 \u5408\u5165）<\/li>\n
        • mindspore#28969 RNN \u8bcd\u5411\u91cf\u7ed3\u679c\u4e0e\u6587\u6863\u4e0d\u4e00\u81f4：\u5b98\u65b9\u53e3\u5f84\u300c\u6559\u7a0b\u5b9e\u9a8c\u5747\u5728 Ascend \u6267\u884c，CPU \u590d\u73b0\u7ed3\u679c\u53ef\u80fd\u4e0d\u540c\u300d\u2014\u2014\u4e0e #28982\/#29019\/#29024\/#29073 \u540c\u4e00\u6279\u53e3\u5f84\u7c7b\u5173\u5355，\u96f6\u4ee3\u7801\u4fee\u6539<\/li>\n
        • mindspore#29007 SSD \u6559\u7a0b import cv2 \u62a5 libxcb.so.1 \u7f3a\u5931：headless \u7248 opencv \u4e0d\u4f9d\u8d56\u56fe\u5f62\u5e93\u4e14\u811a\u672c\u672a\u7528 GUI \u63a5\u53e3，opencv-python-headless==4.11.0.86 \u53ef\u5b89\u5168\u66ff\u4ee3（\u5b98\u65b9\u786e\u8ba4\u539f\u7406）<\/li>\n
        • mindspore#28939 910A \u6bb5\u9519\u8bef\u81ea\u7b54\u95ed\u73af：\u95ee\u9898\u73af\u5883 CANN 8.5 \u53d6\u81ea\u516c\u53f8 CMC \u5185\u90e8\u6e20\u9053\u975e\u5b98\u65b9\u53d1\u5e03\u5305\u2014\u2014\u540c\u7248\u672c\u53f7\u4e0b\u6e20\u9053\u5305\u884c\u4e3a\u53ef\u80fd\u4e0d\u540c，NPU \u5de5\u5177\u94fe\u52a1\u5fc5\u7528\u5b98\u65b9\u53d1\u5e03\u5305<\/li>\n
        • mindspore#29041 RandomSampler \u6587\u6863\u793a\u4f8b\u7ed3\u679c\u65e0\u6cd5\u5370\u8bc1\u6709\u653e\u56de\/\u65e0\u653e\u56de：\u65e0 seed \u6bcf\u6b21\u4e0d\u540c\u5c5e\u9884\u671f，ds.config.set_seed(1000) \u56fa\u5b9a\u2014\u2014docs PR 18412\/18413 \u663e\u5f0f Fixes（\u4e0a\u7bc7\u62c6\u5165）<\/li>\n<\/ul>\n

          5. DSA \u7a00\u758f\u6ce8\u610f\u529b\u516d\u6848：\u6392\u5e03\u3001\u81ea\u52a8\u91cd\u6392\u4e0e\u663e\u5b58\u4e09\u7ebf\u3002 DeepSeek \u7cfb DSA \u843d\u5730\u7684\u95ee\u9898\u96c6\u4e2d\u5728\u300c\u5f20\u91cf\u6392\u5e03\u534f\u5546\u300d\u4e0e\u300c\u6846\u67b6\u81ea\u52a8\u63d2\u5165\u7684\u91cd\u6392\u8282\u70b9\u300d\u4e24\u4fa7，\u8ddf\u8e2a\u5355+\u5b50 PR \u662f\u5176\u5e38\u89c1\u7ec4\u7ec7\u5f62\u6001\u3002<\/p>\n

            \n
          • mf#2214 DSA \u5df2\u77e5\u95ee\u9898\u4f1e\u5355：BSND+cp \u591a\u4f59\u901a\u4fe1\u663e\u5b58\u6da8（PR 8211 \u6df7\u5408 tp+cp \u89e3\u51b3）\u3001dense+pp \u62a5\u9519\u5361\u6b7b（PR 8092 \u652f\u6301 dense \u9636\u6bb5 pp）\u2014\u2014\u4e24\u4e2a\u5b50\u95ee\u9898\u5404\u914d\u4e00 PR，\u5747\u6302\u4e3b\u8ddf\u8e2a\u5355 #2207<\/li>\n
          • mf#2230 DSA \u4e0e Megatron \u9996 loss \u5bf9\u9f50\u3001\u9996 norm \u5206\u53c9：\u5b98\u65b9\u786e\u8ba4\u524d\u5411\u4e00\u81f4\u53cd\u5411\u4e0d\u4fdd\u8bc1，\u5f85 CANN loss \u878d\u5408\u7b97\u5b50\u2014\u2014\u540e\u7ecf PR 8181 \u63a5\u5165\u5e76\u987a\u4fee dense \u9636\u6bb5\u8bef\u7528 SFA<\/li>\n
          • mf#2234 \u5927\u89c4\u6a21\u5e76\u884c\u6846\u67b6\u81ea\u52a8\u63d2\u5165\u590d\u6742\u91cd\u6392\u3001\u8de8\u5b50\u56fe reshape \u89e6\u53d1\u9519\u8bef\u91cd\u6392\u81f4 DSA \u5931\u8d25\u2014\u2014\u6539\u5199\u91cd\u6392\u89e6\u53d1\u8282\u70b9\u6d88\u9664\u63d2\u5165\u6e90，dp2tp4pp2cp8 dryrun \u5b58\u56fe\u9a8c\u8bc1（PR 8196 Fixes \u663e\u5f0f）<\/li>\n
          • mf#2290 FA \u7b97\u5b50 softmax_max\/sum \u6392\u5e03\u4e0d\u7b26 TND \u4e00\u9636\u6bb5\u9700\u8981\u3001\u6b64\u524d\u9000\u56de BSND \u89c4\u907f\u2014\u2014PR 8288 \u65b0\u589e softmax_out \u6392\u5e03\u8f6c\u6362，8 \u5c42\u7eaf pp loss \u5bf9\u9f50（Fixes \u663e\u5f0f）<\/li>\n
          • mf#2252 DSA \u4e8c\u9636\u6bb5 128k \u957f\u5e8f\u5217\u5cf0\u503c\u663e\u5b58\u9ad8 7 \u500d：\u6743\u91cd\u5438\u6536\u903b\u8f91\u53cd\u5411\u663e\u5b58\u8fc7\u9ad8\u2014\u2014PR 8229 \u4f18\u5316（\u63d0\u5355 56 \u5206\u949f\u540e\u5408\u5165，Fixes \u663e\u5f0f）<\/li>\n
          • mf#2302 DSAIndexer rotary \u4f4d\u7f6e\u7f16\u7801\u8ba1\u7b97\u4e0d\u6b63\u786e：interleaved rotary \u4fee\u6b63（PR 8317，\u5408\u5165\u4e0e\u5173\u5355\u79d2\u7ea7\u4e00\u81f4=Fixes \u81ea\u52a8\u5173\u5355）<\/li>\n<\/ul>\n

            6. \u8f85\u52a9 loss \u7f29\u653e\u4e0e MoE \u7edf\u8ba1\u53e3\u5f84\u516d\u6848：\u7f29\u653e\u53ea\u5728\u5e76\u884c\u8def\u5f84\u8bbe\u7f6e\u3002 \u300c\u5355\u5361\u4e0e\u591a\u5361\u7cbe\u5ea6\u5206\u53c9\u300d\u5728\u672c\u6279\u7684\u7cfb\u7edf\u6027\u6839\u56e0：AutoScaler \u53cd\u5411\u7f29\u653e\u3001\u96f6\u5747\u503c\u5f52\u4e00\u5316\u3001all_reduce \u89c4\u7ea6\u90fd\u53ea\u5728\u90e8\u5206\u8def\u5f84\u751f\u6548\u3002<\/p>\n

              \n
            • mf#2257 FSDP+EP \u7cbe\u5ea6\u4e0e\u5355\u5361\u4e0d\u5bf9\u9f50：\u5206\u5e03\u5f0f\u4e0b loss sense（\u8f85\u52a9 loss \u53cd\u5411\u7f29\u653e）\u8bbe\u7f6e\u9519\u8bef（PR 8242）\u2014\u2014\u4e0e\u540e\u7eed\u7f29\u653e\u65cf\u540c\u6e90<\/li>\n
            • mf#2380 \u5355\u5361\u68af\u5ea6\u7d2f\u79ef\u4e0b MTP\/aux loss \u68af\u5ea6\u653e\u5927 N \u500d：AutoScaler scale \u4ec5 SPMD \u8def\u5f84\u8bbe\u7f6e\u3001\u5355\u5361\u4fdd\u6301 1.0 \u672a\u6298\u53e0 1\/\u7d2f\u79ef\u6b65\u6570\u2014\u2014Trainer \u521d\u59cb\u5316\u65e0\u6761\u4ef6\u7edf\u4e00\u8bbe\u7f6e（PR 8436；\u6ce8\u610f\u5176\u524d\u8eab PR 8432 closed \u672a\u5408\u5e76）；\u5173\u5355\u8bc4\u8bba\u9644\u7d2f\u79ef\/\u4e0d\u7d2f\u79ef grad_norm \u9a8c\u8bc1\u8868<\/li>\n
            • mf#2329 expert_bias \u52a8\u6001\u56fe\u505a\u96f6\u5747\u503c\u5f52\u4e00\u5316\u3001\u9759\u6001\u56fe\u6ca1\u505a\u2014\u2014\u5220\u5f52\u4e00\u5316\u7edf\u4e00\u53e3\u5f84，\u91cd\u6253 expert_bias_delta \u9a8c\u8bc1\u4e00\u81f4（\u79d2\u7ea7\u5173\u5355）<\/li>\n
            • mf#2349 \u5e76\u884c\u4e0b tokens_per_expert_by_layer \u672a all_reduce，\u5404 dp \u57df\u7edf\u8ba1\u4e0d\u4e00\u81f4\u81f4 expert_bias \u5206\u53c9\u2014\u2014\u8865\u89c4\u7ea6（\u79d2\u7ea7\u5173\u5355）<\/li>\n
            • mf#2338 \u52a8\u6001\u56fe local\/device grad_norm \u6253\u5370\u7684\u662f\u901a\u4fe1\u540e\u7684\u503c\u2014\u2014\u6539\u6253\u5370\u901a\u4fe1\u524d\u672c\u5730\u503c（\u79d2\u7ea7\u5173\u5355）<\/li>\n
            • mf#2398 tp \u5207\u5206\u4e0b indexer \u4e0e moe \u53e0\u52a0\u7d2f\u79ef\u6570\u503c\u6f02\u79fb\u81f4 loss \u8df3\u53d8\u2014\u2014\u79fb\u9664 indexer_loss \u7684 tp \u5207\u5206\u89c4\u907f，\u66f2\u7ebf\u590d\u5e73（PR 8479 Fixes \u663e\u5f0f）<\/li>\n<\/ul>\n

              7. pynative \u52a8\u6001\u56fe\u80fd\u529b\u516b\u6848：\u80fd\u529b\u8865\u9f50\u4e0e\u6027\u80fd\u4e24\u7ebf\u3002 \u52a8\u6001\u56fe\u7ebf\u7684\u95ee\u9898\u4e00\u534a\u662f\u300c\u80fd\u529b\u8fd8\u6ca1\u6709\u300d（\u88c1\u526a\u3001profile\u3001\u6570\u636e\u96c6），\u4e00\u534a\u662f\u300c\u591a\u505a\u4e86\u65e0\u7528\u529f\u300d（h2d \u62f7\u8d1d\u3001\u5197\u4f59\u521d\u59cb\u5316\u3001\u4e0d\u77ed\u8def）\u3002<\/p>\n

                \n
              • mf#2275 \u52a8\u6001\u56fe\u8bad\u7ec3\u4e0d\u652f\u6301\u68af\u5ea6\u88c1\u526a（\u80fd\u529b\u7f3a\u53e3\u975e\u56de\u5f52）\u2014\u2014PR 8260 \u5b9e\u73b0\u88c1\u526a+distribute_param_plan \u7edf\u4e00\u5206\u53d1，\u591a\u7ec4\u5408\u4e0e\u5355\u5361\u5bf9\u9f50（\u79d2\u7ea7\u5173\u5355）<\/li>\n
              • mf#2278 \u5ef6\u8fdf\u521d\u59cb\u5316\u4ecd\u6162：ms \u63a5\u53e3\u7a7f\u523a\u628a 100 \u5c42\u6784\u5efa 193s\u21921.5s\u3001500 \u5c42\u4ec5 7.5s（PR 8271；\u524d\u5e8f 8205 \u9996\u7248 5 \u5c42 51s\u219224s）<\/li>\n
              • mf#2330 pynative Dropout drop_prob=0.0 \u8bad\u7ec3\u6001\u4ecd\u4e0b\u53d1\u7b97\u5b50\u2014\u2014construct \u52a0\u77ed\u8def\u76f4\u8fd4\u8f93\u5165+\u56de\u5f52\u7528\u4f8b（\u79d2\u7ea7\u5173\u5355）<\/li>\n
              • mf#2332 \u5f00 dp shard \u540e dp \u5927\u5c0f\u4e0e dp_shard \u76f8\u540c（\u8bed\u4e49\u9519）\u2014\u2014PR 8372 \u4fee\u6b63，shard2\u00d7replicate2 \u4e0e\u5355\u5361\u7cbe\u5ea6\u5bf9\u9f50（KG \u4f50\u8bc1 FSDP \u5206\u7247\/\u590d\u5236\u5206\u5de5）<\/li>\n
              • mf#2334 \u52a8\u6001\u56fe\u52a0\u8f7d\u6743\u91cd slice \u524d\u5148 h2d \u62f7\u5230 device\u2014\u2014DeviceCtx(\u201cCPU\u201d) \u76f4\u63a5 CPU \u5207\u7247：\u52a8\u6001\u56fe\u8f6c\u914d\u63d0\u901f 20%\u3001\u9759\u6001\u56fe 33%（KG \u4f50\u8bc1 h2d \u62f7\u8d1d\u5f00\u9500\u673a\u5236）<\/li>\n
              • mf#2448 dsv4 csa_fix \u5206\u652f\u5f00\u91cd\u8ba1\u7b97\u663e\u5b58\u53cd\u6cc4\u9732\u81f3 OOM：\u878d\u5408\u7b97\u5b50\u91cd\u8ba1\u7b97\u4e2d\u95f4\u5f20\u91cf\u672a\u6b63\u786e\u91ca\u653e\u2014\u2014\u4fee\u590d\u9644\u524d\u540e\u663e\u5b58\u66f2\u7ebf（KG \u4f50\u8bc1\u91cd\u8ba1\u7b97\u4e3a\u663e\u5b58\u4f18\u5316\u56db\u5c42\u624b\u6bb5\u4e4b\u4e00）<\/li>\n
              • mf#2468 MaxLogitsMonitor \u9694\u6b65\u5d29\u6e83+\u65e5\u5fd7\u4e0d\u80fd\u72ec\u7acb\u5173\u2014\u2014enable_logging \u89e3\u8026\u3001\u8df3\u8fc7\u6253\u5370\u4e0d\u8bfb Tensor \u907f\u514d\u989d\u5916 D2H \u540c\u6b65，30 UT \u901a\u8fc7<\/li>\n
              • mf#2524 use_distribute_dataset \u6240\u6709 rank \u5197\u4f59\u521d\u59cb\u5316\u6570\u636e\u4e0e index map\u2014\u2014\u4ec5 src rank \u8bfb\u53d6+rank0-only index map（master\/r2.1.0-beta1 \u53cc\u5206\u652f\u540c\u79d2\u5173\u5355）<\/li>\n<\/ul>\n

                8. dsv4 \u9002\u914d\u3001\u65ad\u70b9\u7eed\u8bad\u4e0e\u5207\u5206\u516b\u6848：\u6821\u9a8c\u53e3\u5f84\u4e0e\u4f18\u5316\u5668\u72b6\u6001\u3002 dsv4 \u5e26\u6765\u4e00\u6279\u300c\u6821\u9a8c\u6ca1\u5bf9\u9f50 Megatron\/\u5df2\u8fc7\u65f6\u300d\u7684\u62e6\u622a；\u65ad\u70b9\u7eed\u8bad\u7684\u5751\u96c6\u4e2d\u5728\u4f18\u5316\u5668\u72b6\u6001\u7684\u5b58\u5728\u6027\u4e0e\u65b0\u65e7\u53c2\u6570\u7684\u8fb9\u754c\u3002<\/p>\n

                  \n
                • mf#2411 dsv4 \u5355\u5361\u62a5\u4e0d\u652f\u6301 meta\u2192Ascend copy：\u7248\u672c\u66f4\u65b0\u540e\u53c2\u6570\u521d\u59cb\u5316\u9700\u663e\u5f0f mint.empty（\u6b63\u4e3b #2413 \u6839\u56e0；\u540c\u62a5\u9519\u4e09\u8fde\u5355\u4e3a\u91cd\u590d\u5355，PR 8493 \u5408\u5165\u524d\u4e00\u65e5\u4eba\u5de5\u6279\u91cf\u5173\u95ed\u2014\u2014\u975e Fixes \u5173\u5355）<\/li>\n
                • mf#2442 hc_sinkhorn_iters:0 \u88ab\u524d\u7aef\u6821\u9a8c\u62e6\u622a：HC（Head Compression）\u7528 Sinkhorn \u6df7\u5408\u5c55\u5f00 hidden state，\u8fed\u4ee3\u6570 0 \u5408\u6cd5\u2014\u2014\u89e3\u9664\u672a\u5bf9\u9f50 Megatron \u7684\u9650\u5236（PR 8550，KG \u4f50\u8bc1 msmodeling DsV4 \u9002\u914d\u8bbe\u8ba1）<\/li>\n
                • mf#2460 hash router \u4e0d\u80fd\u914d pp \u7684\u6821\u9a8c\u5df2\u8fc7\u65f6（\u52a8\u6001\u56fe pp \u5df2\u5408\u5165）\u2014\u2014PR 8590 \u53bb\u9664\u62e6\u622a；\u80cc\u666f：DsV4 \u524d num_hash_layers \u5c42\u7528 token-id \u54c8\u5e0c\u8def\u7531（KG \u540c\u4e0a）<\/li>\n
                • mf#2475 tid2eid \u88ab\u72ec\u7acb FSDP \u5b50\u5305\u88c5\u8bef\u5207\u5206（\u5f15\u5165 PR 8581\u2192\u4fee\u590d PR 8619 \u53cc\u951a\u70b9，\u79d2\u7ea7\u5173\u5355）\u2014\u2014\u6ce8\u610f\u65b9\u6848\u6f02\u79fb：issue \u63d0\u8bae replicate_params \u7279\u5224，\u5b9e\u9645\u5408\u5165\u662f\u5220\u9664\u6574\u4e2a FP32 \u5b50\u5305\u88c5（\u7279\u5224\u4f1a\u6f0f ga_steps \u7b49\u72b6\u6001）<\/li>\n
                • mf#2335 \u9759\u6001\u56fe pp>2 \u52a0\u8f7d\u6743\u91cd\u5931\u8d25：\u52a8\u6001\u56fe\u9002\u914d\u65f6\u8bef\u7528 0 \u5361 layout\u2014\u2014\u6309\u5404\u5361 rank_id \u53d6\u5bf9\u5e94 layout（PR 8384，\u8bc4\u8bba\u4e8c\u5206\u5b9a\u4f4d\u5f15\u5165 commit，\u79d2\u7ea7\u5173\u5355）<\/li>\n
                • mf#2459 \u65ad\u70b9\u7eed\u8bad\u7f3a optimizer \u6587\u4ef6\u62a5\u9519\u4e0d\u660e\u786e\u2014\u2014has_optimizer_ckpt \u524d\u7f6e\u6821\u9a8c：HF \u6743\u91cd+no_load_optim=False \u660e\u786e\u62a5\u4e0d\u652f\u6301\u3001MS \u7f3a opt \u6587\u4ef6\u63d0\u793a\u8bbe no_load_optim=True（KG \u5370\u8bc1\u8de8\u6846\u67b6\u5951\u7ea6：no-load-optim \u8df3\u8fc7\u4f18\u5316\u5668\u72b6\u6001\u65e0\u6cd5\u771f\u6b63\u7eed\u8bad）<\/li>\n
                • mf#2490 \u51bb\u7ed3\u53c2\u6570\u7f3a\u4f18\u5316\u5668\u72b6\u6001\u81f4\u7eed\u8bad\u4e8c\u9636\u6bb5 loss \u7a81\u53d8：\u4e3b\u6743\u91cd\u88ab\u5168\u91cf\u91cd\u8f7d\u8986\u76d6\u5df2\u8bad\u7ec3\u72b6\u6001\u2014\u2014fp32 \u4e3b\u6743\u91cd sum() \u6821\u9a8c\u548c\u5feb\u7167+\u9009\u62e9\u6027\u91cd\u8f7d（\u56de\u5408 PR 8676 \u5165 r2.1.0-beta1）<\/li>\n
                • mf#2292 MLA q_lora_rank=None \u65f6 TP \u5207\u5206\u8ba1\u5212\u65e0\u6761\u4ef6\u6536\u5f55\u4e0d\u5b58\u5728\u7684\u5b50\u6a21\u5757\u2014\u2014\u6309\u6761\u4ef6\u52a0\u5165 plan（\u79d2\u7ea7\u5173\u5355）<\/li>\n<\/ul>\n

                  \u6392\u9519\u6307\u5f15（\u4ece\u8fd9\u6279 issue \u63d0\u70bc）<\/h3>\n\n\u75c7\u72b6\u7b2c\u4e00\u4f18\u5148\u52a8\u4f5c\u672c\u7bc7\u76f8\u5173\u6848\u4f8b<\/tr>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
                  dry run core dump（\u878d\u5408\u7b97\u5b50）<\/td>\n\u6838\u8df3\u8fc7\u7f16\u8bd1\u8def\u5f84\u7684\u672a\u521d\u59cb\u5316\u53d8\u91cf\u4e0e\u6790\u6784\u5224\u7a7a<\/td>\nmindspore#21803<\/td>\n<\/tr>\n
                  \u56fe\u7f16\u8bd1 infer value \u62a5 device tensor<\/td>\n\u5148\u540c\u6b65 host \u518d\u505a\u5e38\u91cf\u6298\u53e0<\/td>\nmindspore#28944<\/td>\n<\/tr>\n
                  \u878d\u5408\u7b97\u5b50\u591a\u8f93\u51fa\u7cbe\u5ea6\u9519（\u52a8\u6001\u56fe）<\/td>\n\u6838 LazyFusion \u5faa\u73af\u5185\u5730\u5740\u751f\u547d\u5468\u671f<\/td>\nmindspore#28999<\/td>\n<\/tr>\n
                  \u63a9\u7801\u4f4d\u53cd\u5411\u68af\u5ea6\u975e 0（\u8f93\u5165\u542b NaN）<\/td>\n\u4e58\u6cd5\u63a9\u7801 0*NaN \u9677\u9631，\u6838\u63a9\u7801\u5b9e\u73b0<\/td>\nmindspore#28905<\/td>\n<\/tr>\n
                  310P GMM nz weight \u62a5\u9519<\/td>\n\u91cd\u6784\u8bef\u5220\u81ea\u52a8\u8f6c\u6362，\u56de\u6eaf\u5f15\u5165+\u8bef\u5220 PR<\/td>\nmindspore#21812<\/td>\n<\/tr>\n
                  \u590d\u7528\u5916\u90e8 hcom \u540e\u901a\u4fe1\u57df\u5f02\u5e38<\/td>\n\u8c01\u521b\u5efa\u8c01\u9500\u6bc1，options \u4f20\u5165\u8df3\u8fc7 destroy<\/td>\nmindspore#28907<\/td>\n<\/tr>\n
                  \u5927\u96c6\u7fa4\u521d\u59cb\u5316\u6162（\u5206\u949f\u7ea7）<\/td>\nmccl \u5f02\u6b65\u521d\u59cb\u5316，\u6838 SynchronizeAddresses \u8017\u65f6<\/td>\nmindspore#28992<\/td>\n<\/tr>\n
                  A3+VISIBLE_DEVICES \u7ed1\u4e0d\u4e0a\u5185\u5b58<\/td>\nnuma \u4eb2\u548c\u9000\u5316\u5747\u5206，\u6838\u7ed1\u5b9a\u7b56\u7565<\/td>\nmindspore#28991<\/td>\n<\/tr>\n
                  \u5168\u51bb\u7ed3\u7f51\u7edc\u5f00 PP \u7f16\u8bd1\u5361\u6b7b<\/td>\nfreeze grad \u652f\u6301\u94fe<\/td>\nmindspore#21143<\/td>\n<\/tr>\n
                  pynative \u8d8a\u754c\u8f93\u5165\u4e0d\u62a5\u9519<\/td>\nnarrow \u7c7b\u6821\u9a8c\u7f3a\u5931，\u8865 start\/length \u6821\u9a8c<\/td>\nmindspore#544<\/td>\n<\/tr>\n
                  gelu \u4f4d\u7f6e\u53c2\u6570 TypeError<\/td>\napproximate \u5df2\u6539 keyword-only<\/td>\nmindspore#248<\/td>\n<\/tr>\n
                  init \u6253\u5370 uninitialized<\/td>\n\u9884\u671f\u8bbe\u8ba1：\u5148\u5199\u540e\u8bfb<\/td>\nmindspore#29001<\/td>\n<\/tr>\n
                  \u6559\u7a0b\u4ee3\u7801\u590d\u5236\u5373\u8bed\u6cd5\u9519\u8bef<\/td>\n\u6838 Jupyter \u9b54\u672f\u547d\u4ee4\u6b8b\u7559<\/td>\nmindspore#29002\u3001#29033<\/td>\n<\/tr>\n
                  CPU\/Windows \u590d\u73b0\u6559\u7a0b\u7ed3\u679c\u4e0d\u7b26<\/td>\n\u6559\u7a0b\u9ed8\u8ba4 Ascend \u5e73\u53f0\u53e3\u5f84<\/td>\nmindspore#28969\u3001#29054<\/td>\n<\/tr>\n
                  import cv2 \u62a5 libxcb \u7f3a\u5931<\/td>\n\u6362 opencv-python-headless<\/td>\nmindspore#29007<\/td>\n<\/tr>\n
                  \u540c\u7248\u672c CANN \u884c\u4e3a\u5f02\u5e38<\/td>\n\u6838\u5b89\u88c5\u6e20\u9053，\u7528\u5b98\u65b9\u53d1\u5e03\u5305<\/td>\nmindspore#28939<\/td>\n<\/tr>\n
                  DSA \u5927\u5e76\u884c\u62a5\u91cd\u6392\u9519\u8bef<\/td>\n\u6d88\u9664\u6846\u67b6\u81ea\u52a8\u63d2\u5165\u7684\u91cd\u6392\u6e90<\/td>\nmf#2234<\/td>\n<\/tr>\n
                  DSA \u4e8c\u9636\u6bb5\u957f\u5e8f\u5217\u663e\u5b58\u66b4\u6da8<\/td>\n\u6743\u91cd\u5438\u6536\u903b\u8f91\u4f18\u5316<\/td>\nmf#2252<\/td>\n<\/tr>\n
                  \u5355\u5361\u4e0e\u5e76\u884c\u7cbe\u5ea6\u5206\u53c9<\/td>\n\u5148\u67e5 aux\/MTP loss \u53cd\u5411\u7f29\u653e\u8bbe\u7f6e<\/td>\nmf#2380\u3001mf#2257<\/td>\n<\/tr>\n
                  expert_bias \u52a8\u9759\u56fe\u4e0d\u4e00\u81f4<\/td>\n\u96f6\u5747\u503c\u5f52\u4e00\u5316\u53e3\u5f84\u7edf\u4e00<\/td>\nmf#2329<\/td>\n<\/tr>\n
                  \u5e76\u884c\u4e0b expert \u7edf\u8ba1\u4e0d\u9f50<\/td>\ntokens_per_expert \u8865 all_reduce<\/td>\nmf#2349<\/td>\n<\/tr>\n
                  indexer+moe loss \u8df3\u53d8<\/td>\n\u53bb indexer_loss \u7684 tp \u5207\u5206<\/td>\nmf#2398<\/td>\n<\/tr>\n
                  \u52a8\u6001\u56fe\u6a21\u578b\u6784\u5efa\u6162<\/td>\nms \u63a5\u53e3\u7a7f\u523a\u5ef6\u8fdf\u521d\u59cb\u5316<\/td>\nmf#2278<\/td>\n<\/tr>\n
                  \u6743\u91cd\u8f6c\u914d\u5361\u6162\/\u5185\u5b58\u9ad8<\/td>\nCPU \u4fa7\u5207\u7247\u907f\u514d h2d<\/td>\nmf#2334<\/td>\n<\/tr>\n
                  \u5f00\u91cd\u8ba1\u7b97\u663e\u5b58\u53cd\u6da8<\/td>\n\u878d\u5408\u7b97\u5b50\u91cd\u8ba1\u7b97\u4e2d\u95f4\u5f20\u91cf\u91ca\u653e<\/td>\nmf#2448<\/td>\n<\/tr>\n
                  dsv4 \u62a5 meta\u2192Ascend copy \u4e0d\u652f\u6301<\/td>\nmint.empty \u663e\u5f0f\u521d\u59cb\u5316<\/td>\nmf#2411<\/td>\n<\/tr>\n
                  hc_sinkhorn_iters:0 \u88ab\u62e6<\/td>\n\u5408\u6cd5\u914d\u7f6e，\u6821\u9a8c\u672a\u5bf9\u9f50 Megatron<\/td>\nmf#2442<\/td>\n<\/tr>\n
                  hash router+pp \u62c9\u4e0d\u8d77<\/td>\n\u8fc7\u65f6\u6821\u9a8c，\u52a8\u6001\u56fe pp \u5df2\u652f\u6301<\/td>\nmf#2460<\/td>\n<\/tr>\n
                  \u7eed\u8bad\u4e8c\u9636\u6bb5 loss \u7a81\u53d8<\/td>\n\u51bb\u7ed3\u53c2\u6570\u4f18\u5316\u5668\u72b6\u6001，\u6821\u9a8c\u548c\u5feb\u7167+\u9009\u62e9\u6027\u91cd\u8f7d<\/td>\nmf#2490<\/td>\n<\/tr>\n
                  \u7eed\u8bad\u7f3a opt \u6587\u4ef6\u62a5\u9519\u542b\u7cca<\/td>\nhas_optimizer_ckpt \u524d\u7f6e\u6821\u9a8c<\/td>\nmf#2459<\/td>\n<\/tr>\n
                  \u9759\u6001\u56fe pp \u52a0\u8f7d\u6743\u91cd\u5931\u8d25<\/td>\n\u6309\u5404\u5361 rank \u53d6 layout，\u52ff\u7528 0 \u5361<\/td>\nmf#2335<\/td>\n<\/tr>\n
                  MLA TP \u62a5\u6a21\u5757\u4e0d\u5b58\u5728<\/td>\nTP plan \u6309 q_lora_rank \u6761\u4ef6\u6536\u5f55<\/td>\nmf#2292<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                  \u8003\u636e\u4e0e\u53e3\u5f84\u62ab\u9732<\/p>\n

                    \n
                  • KG \u6838\u5b9e：\u6d89\u53ca\u673a\u5236\/\u53e3\u5f84\u7684\u6838\u5bf9\u7528\u4e86\u6607\u817e\u77e5\u8bc6\u56fe\u8c31（ascend.wiki）\u5b98\u65b9\u6587\u6863\u4e0e\u4ee3\u7801\u8282\u70b9\u2014\u2014DSA \u7a00\u758f\u6ce8\u610f\u529b（cann-recipes-train deepseek-v32 \u9884\u8bad\u7ec3\u4f18\u5316）\u3001aclnnFlashAttentionVarlenScore\u3001MLA \u591a\u5934\u6f5c\u5728\u6ce8\u610f\u529b\u3001custom FSDP \u53c2\u6570\u5206\u7247\u3001MTP\u3001\u96f6\u6c14\u6ce1\u6d41\u6c34\u7ebf\u3001expert_scales \u66f4\u65b0\u3001indexer KL loss \u878d\u5408\u7b97\u5b50\u3001FSDP \u6df7\u5408\u5206\u7247\u6570\u636e\u5e76\u884c\u3001h2d \u62f7\u8d1d\u5f00\u9500\u3001\u6fc0\u6d3b\u91cd\u8ba1\u7b97\u663e\u5b58\u624b\u6bb5\u3001ASCEND_RT_VISIBLE_DEVICES\u3001HcclCommDestroy\u3001msmodeling DsV4 \u9002\u914d\u8bbe\u8ba1（hash \u8def\u7531\/HC Sinkhorn）\u3001MindSpeed-LLM checkpoint_resume \u4f18\u5316\u5668\u72b6\u6001\u5951\u7ea6\u3001PyPTO uninitialized-tensor FAQ（\u751f\u6001\u540c\u53e3\u5f84，\u884c\u5185\u5df2\u6807\u6ce8\u975e MindSpore）；\u5176\u4f59\u5b9e\u73b0\u7c7b\u4e3b\u9898 KG \u65e0\u8986\u76d6\u7684\u6761\u76ee kg_refs \u7559\u7a7a，\u672a\u786c\u51d1\u3002<\/li>\n
                  • PR \u5408\u5e76\u5224\u5b9a：\u4e00\u5f8b\u4ee5 pulls API state=merged+merged_at \u5224\u5b9a（merged \u5b57\u6bb5\u6052\u4e3a null \u4e0d\u53ef\u7528）；\u4fee\u590d PR \u843d\u5728 docs \u4ed3\u7684（mindspore#29002\/#29033 \u5bf9\u5e94 docs#18291\/#18299\u3001#29054 \u5bf9\u5e94 docs#18261\/#18262\u3001#29041 \u5bf9\u5e94 docs#18412\/18413）\u5747\u7ecf docs \u4ed3 pulls API \u590d\u6838 merged；PR Fixes \u591a\u6307\u5411 atomgit\/gitee \u955c\u50cf\u6216\u7ec4\u7ec7\u5355（\u7f16\u53f7\u4e0d\u540c\u6784），\u4ee5\u6b63\u6587\u8bed\u4e49+merged_at \u4f50\u8bc1；\u62bd 8 \u6761\u786c\u65f6\u5e8f\u65ad\u8a00\u5bf9 API \u590d\u6838\u901a\u8fc7（\u4fee\u590d PR 80259\/8317\/8619\/8704\/8550\/92456\u3001\u5f15\u5165 PR 74073\/8581\u3001docs PR 18291；\u52d8\u8bef：\u8bc1\u636e\u8868\u628a #21812 \u4fee\u590d PR 80259 \u5e74\u4efd\u8bef\u8bb0\u4e3a 2026，API \u5b9e\u4e3a 2025-01-06T19:40:17\u3001\u4e0e\u5173\u5355\u79d2\u7ea7\u4e00\u81f4，\u6b63\u6587\u672a\u6d89\u5e74\u4efd）\u3002<\/li>\n
                  • \u5173\u8054\u4f9d\u636e\u5206\u5c42：\u79d2\u7ea7\u94c1\u8bc1 finished_at==merged_at 21 \u6761（\u4e3b\u4ed3 #21803\/#21810\/#21812 \u4e0e\u5dee 99 \u79d2\u7684 #28907\u3001mf #2302\/#2329\/#2349\/#2338\/#2292\u3001#2275\/#2278\/#2330\/#2332\/#2334\/#2448\/#2468\/#2524\u3001#2459\/#2460\/#2475\/#2490\/#2335）；\u5206\u949f\u7ea7\u65f6\u95f4\u8026\u5408（mf#2252 \u63d0\u5355 56 \u5206\u949f\u540e\u5408\u5165\u3001mf#2442 \u5408\u5165 6 \u5206\u949f\u540e\u5173\u5355\u3001ms#28944 \u5408\u5165 20 \u5206\u949f\u540e\u5173\u5355\u3001ms#28991 \u5408\u5165 1.5 \u5c0f\u65f6\u540e\u5173\u5355）；\u5f15\u5165+\u4fee\u590d\u53cc\u951a\u70b9（ms#21812 \u4e09\u951a\u70b9 74073\u219274745\u219280259\u3001mf#2278 \u7684 8205\u21928271\u3001mf#2475 \u7684 8581\u21928619\u3001mf#2335 \u7684 8191\u21928384\u3001ms#21143 \u53cc PR）；SSR \u6d3b\u52a8\u6d41\u663e\u5f0f\u5173\u8054（ms#28905\/#28999\/#28992\/#21143）；Fixes\/\u6b63\u6587\u663e\u5f0f（mf#2234\/#2290\/#2252\/#2398\/#2380\/#2257\u3001ms#248 \u5f15\u5165 PR 81218）；docs \u4ed3 PR \u4fee\u590d（ms#29002\/#29033 \u5bf9\u5e94 docs#18291\/#18299\u3001#29054 \u5bf9\u5e94 docs#18261\/#18262\u3001#29041 \u6b63\u6587\u663e\u5f0f Fixes）；\u8bc4\u8bba\u89e3\u7b54\/\u5b98\u65b9\u53e3\u5f84\u7c7b\u65e0\u4ed3\u5185 PR，\u4ee5\u5b98\u65b9\u53e3\u5f84\u6536\u5f55（ms#544\/#29001\/#28969\/#29007\/#28939\u3001mf#2411 \u7ecf\u6b63\u4e3b #2413 \u6839\u56e0）；\u8bed\u4e49\u5339\u914d+\u65f6\u95f4\u7a97（ms#20673\/#21705）\u3002<\/li>\n
                  • \u65f6\u5e8f\u9677\u9631\u5b9e\u5f55：\u2460dsv4 \u5355\u5361\u4e09\u8fde #2411\/#2412\/#2414 \u4fee\u590d PR 8493 \u5173\u8054\u7684\u662f\u6b63\u4e3b #2413（atomgit \u94fe\u63a5），\u4e09\u8fde\u5728 PR \u5408\u5165\u524d\u4e00\u65e5\u88ab\u4eba\u5de5\u6279\u91cf\u5173\u95ed\u2014\u2014\u91cd\u590d\u5355\u7684\u5173\u5355\u65f6\u523b\u4e0d\u80fd\u5f53 Fixes \u4f9d\u636e（\u672c\u7bc7\u4ee5 #2411 \u843d\u884c\u5e76\u6ce8\u660e）；\u2461\u300c\u6839\u56e0\u8bc4\u8bba\u53d1\u5e03\u5373\u5173\u5355\u300d\u79d2\u7ea7\u7cfb\u5185\u90e8\u6d41\u7a0b（mfC \u6b63\u4e3b #2413 \u578b\u3001mf#2230 \u5173\u5355\u65e9\u4e8e\u8bf4\u660e\u8bc4\u8bba 2 \u5206\u949f），\u65f6\u5e8f\u4e0d\u4f5c Fixes \u4f9d\u636e；\u2462mf#2380 \u8bc4\u8bba\u5ba3\u79f0\u7684\u4fee\u590d PR 8432 \u5b9e\u9645 closed \u672a\u5408\u5e76，\u7531 PR 8436 \u5b9e\u8d28\u63a5\u66ff\u2014\u2014\u5355\u770b\u8bc4\u8bba\u4f1a\u8bef\u5224\u4fee\u590d\u8f7d\u4f53；\u2463Fixes \u6307\u5411 atomgit \u955c\u50cf\u540c\u53f7 issue \u4ecd\u89e6\u53d1\u81ea\u52a8\u5173\u5355，\u6307\u5411\u7ec4\u7ec7\u7ea7\u5355（org-issues）\u5219\u4e0d\u5173\u672c\u4ed3 issue；\u24642026-06-18 17:24-17:28 \u4e0e 2026-03-19 \u5b58\u5728\u6279\u91cf\u5173\u5355\u6ce2，\u8be5\u65f6\u6bb5 finished_at \u5747\u975e\u4fee\u590d\u65f6\u70b9，\u5224\u636e\u4e00\u5f8b\u56de PR merged_at；\u2465GitCode 74xxx PR \u6bb5\u521d\u67e5 429 \u88ab\u8bef\u8bfb\u4e3a 404，\u9000\u907f\u540e\u76f4\u9a8c\u6210\u529f（429\u2260\u4e0d\u5b58\u5728）；PR SSR \u9875\u4e3a\u5ba2\u6237\u7aef\u6e32\u67d3\u7a7a\u58f3，PR \u8bed\u4e49\u53ea\u80fd\u8d70 API；\u2466SSR linked_merge_requests \u53ef\u73b0 count=1 \u800c\u6570\u7ec4\u7a7a，\u9700 walk \u515c\u5e95+PR \u7a97\u53e3\u626b\u63cf（mf#2335）\u3002<\/li>\n
                  • \u8bda\u5b9e\u5f03\u6536：\u672c\u8f6e 109 \u5019\u9009 worker \u5c42\u5f03\u6536 14\u2014\u2014msD #21828（\u7a7a\u4efb\u52a1\u6a21\u677f）；msE #29011（\u5b98\u65b9\u7d22\u8981\u73af\u5883\u4fe1\u606f\u65e0\u56de\u5e94\u3001stale \u5173\u95ed\u65e0\u6839\u56e0）\u3001#29023（\u5b98\u65b9\u300c\u975e\u95ee\u9898\u300d\u4e09\u5b57\u5173\u95ed\u65e0\u6839\u56e0）；mfA #2253（\u5360\u4f4d\u81ea\u63d0\u5355）；mfB #2333（43 \u79d2\u81ea\u70b9\u72b6\u6001\u6d41\u5360\u4f4d\u5355）\u3001#2352（REJECTED\u2192DONE \u65e0\u516c\u5f00\u4f9d\u636e[\u4e3a\u4f55DONE\u672a\u6838\u5b9e]）；mfC #2412\/#2414（dsv4 \u4e09\u8fde\u91cd\u590d\u5355\u5e76\u5165 #2411）\u3001#2328（\u81ea\u5e26\u7b54\u6848\u52d8\u8bef+r1.5.0 \u4e0d\u7ef4\u62a4）\u3001#2422（CVE \u89c4\u5219\u5f03\u6536）\u3001#2494\/#2500（\u8fd0\u7ef4\/\u53d1\u5e03\u4e8b\u52a1\u96f6\u8bc1\u636e）\u3001#1961\/#111（\u5360\u4f4d\u6a21\u677f）\u3002\u53e6 48 \u6761\u6df1\u6790\u5408\u683c\u4f46\u6309 50 \u4e0a\u9650\u672c\u8f6e\u672a\u5165\u9009，\u7559\u5f85\u7eed\u7bc7\u7ec4\u7a3f（\u4e3b\u4ed3 21：#20586\/#20567\/#29079\/#28787\u3001\u73af\u5883\u7c7b\u8bc4\u8bba\u89e3\u7b54 #28927\/#28929\/#28934\/#28961\/#28971\/#28972\u3001\u5b98\u7f51\u4fa7\u300c\u5df2\u4fee\u590d\u300d\u65e0 PR 4 \u6761 #28923\/#28938\/#28962\/#28975\u3001\u53e3\u5f84\u7c7b #28928\/#28976\/#28982\/#29019\/#29024\/#29063\/#29073；mf 27：#2211\/#2220\/#2280\/#2322 \u7b49\u79d2\u7ea7\u4e0e\u6b63\u6587\u663e\u5f0f\u4fee\u590d\u6761\u76ee\u3001#2397 \u5173\u8054 PR Fixes \u6307\u9519+\u771f\u4fee\u590d PR \u672a\u5408\u5165\u3001#2284 \u6a21\u677f\u6ce8\u91ca #123 \u89e6\u53d1 100 PR \u5173\u8054\u4e0a\u9650\u3001#2336 CogVLM2 \u505c\u6f14\u8fdb\u7ed9\u66ff\u4ee3\u673a\u578b\u3001#2456\/#2458\/#2492 \u7eed\u8bad\u79d2\u7ea7\u6761\u76ee\u7b49）\u3002<\/li>\n
                  • \u5019\u9009\u7edf\u8ba1\u4e0e\u6ea2\u51fa：\u672c\u7bc7 50 \u6761 = \u4e0a\u7bc7\u62c6\u5165 3 \u6761（#544\/#248\/#29041）+ \u672c\u8f6e 109 \u5019\u9009 5 \u6279 worker \u6df1\u6790\u7559 95（msD 23 \u7559 22\u3001msE 20 \u7559 18\u3001mfA 22 \u7559 21\u3001mfB 22 \u7559 20\u3001mfC 22 \u7559 14）\u3001\u5171 98 \u6c60\u6309\u8d28\u91cf\u53d6 47；\u4f59 48 \u6761\u5408\u683c\u4f59\u91cf\u672a\u88c1\u64a4\u8d28\u91cf\u3001\u7559\u5f85\u540e\u7eed\u7ec4\u7a3f\u3002<\/li>\n<\/ul>\n

                    \u63a5\u5165\u6607\u817e\u77e5\u8bc6\u56fe\u8c31 https:\/\/gitcode.com\/agent0\/kg-tools<\/p>\n

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