)]}'
{
  "commit": "7ce8c8e9f8f8a0234f97bbd576072b1cdf756f92",
  "tree": "b430a0bbe93b1d1950fb2818d941165902f6301e",
  "parents": [
    "4de493af31e370ca2eb1bb590469ebbf76fc8d5b"
  ],
  "author": {
    "name": "MaheshRavishankar",
    "email": "1663364+MaheshRavishankar@users.noreply.github.com",
    "time": "Wed Jul 17 11:27:14 2024 -0700"
  },
  "committer": {
    "name": "GitHub",
    "email": "noreply@github.com",
    "time": "Wed Jul 17 11:27:14 2024 -0700"
  },
  "message": "[Preprocessing] Add a one-off pattern to fuse attention with transpose. (#17901)\n\nThe attention ops in SDXL models are usually followed by a\r\n`tensor.expand_shape` and a `transpose`. It is more natural to fold\r\nthese in with the attention for codegeneration. This is done as a\r\none-off pattern for now. Ideally the attention ops can be fused with any\r\nof its elementwise consumers when attention is handled natively by the\r\nbackend pass-pipelines.\r\nMore details are in https://github.com/iree-org/iree/issues/17673.\r\n\r\nSigned-off-by: MaheshRavishankar \u003cmahesh.ravishankar@gmail.com\u003e",
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