)]}'
{
  "commit": "0fe0ca8f7c7daf9af6e6da1df995bdd1098a8c9c",
  "tree": "622cd8da8d264e21f6d747073db7ee531d08d8d8",
  "parents": [
    "d62d69b27352204b026883498be964e0606c0eec"
  ],
  "author": {
    "name": "Keshav Vinayak Jha",
    "email": "31160700+keshavvinayak01@users.noreply.github.com",
    "time": "Fri May 08 03:05:33 2026 +0530"
  },
  "committer": {
    "name": "GitHub",
    "email": "noreply@github.com",
    "time": "Fri May 08 03:05:33 2026 +0530"
  },
  "message": "[Torch][LinalgExt] Support GQA in torch.hop_flex_attention lowering (#24313)\n\nThis PR adds grouped-query attention support to the\ntorch.hop_flex_attention lowering in IREE’s Torch input pipeline.\n\nWhen query, key, and value have different head counts, the lowering now\nexpands key and value heads to match the query head count before\nemitting `iree_linalg_ext.online_attention`.\n\nThis is similar to how the torch-mlir \u003d\u003e TMTensor lowering handles this\ncase.\n\n---------\n\nSigned-off-by: Keshav Vinayak Jha \u003ckeshavvinayakjha@gmail.com\u003e\nCo-authored-by: GPT-5 Codex \u003cnoreply@openai.com\u003e",
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