)]}'
{
  "commit": "b7c415254fe87b025bf4e8b671a37265ee831cb2",
  "tree": "78429f95214d4ec3028f30f76c6107d237391733",
  "parents": [
    "46326ef4b2bab02a9bda7e2eed810df08d8ca021"
  ],
  "author": {
    "name": "Kunwar Grover",
    "email": "groverkss@gmail.com",
    "time": "Sat Mar 09 18:49:50 2024 +0000"
  },
  "committer": {
    "name": "GitHub",
    "email": "noreply@github.com",
    "time": "Sat Mar 09 18:49:50 2024 +0000"
  },
  "message": "[LinalgExt] Add scaling to attention op (#16679)\n\nThis commit add support for a scale input to the attention\r\nop. This is to follow semantics of scaled dot product\r\nsemantics for attention like explained in\r\nhttps://paperswithcode.com/method/scaled\r\n\r\nRight now we only thread through the lower part of the\r\nstack, meaning linalg ext ops and its code generation.\r\nWe also need to eventually fix upper layers to get the\r\nscale from the input. For now we only support the PyTorch\r\ndefault scale case--rsqrt(d).\r\n\r\n---------\r\n\r\nCo-authored-by: Lei Zhang \u003cantiagainst@gmail.com\u003e",
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