)]}'
{
  "commit": "4606deb2beb818ce53fe291d1afce917498df181",
  "tree": "b709bdc6476c7553f49a654d35c83a95759236c5",
  "parents": [
    "d00579da938ecee18743ead0ee89fefa5e97b108"
  ],
  "author": {
    "name": "Hong Xu",
    "email": "hong@topbug.net",
    "time": "Sat Nov 09 09:09:50 2019 -0800"
  },
  "committer": {
    "name": "Facebook Github Bot",
    "email": "facebook-github-bot@users.noreply.github.com",
    "time": "Sat Nov 09 09:11:45 2019 -0800"
  },
  "message": "Migrate frac from TH to ATen (CUDA) (#28953)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/28953\n\nClose #24566\n\nBenchmark (Debian Buster, CUDA 9.2, Quadro P400, turbo off, Release, gcc\n7.4):\n\n```python\nimport timeit\n\nfor n, t in [(10_000, 20000),\n             (100_000, 20000)]:\n    for dtype in (\u0027torch.half\u0027, \u0027torch.float\u0027, \u0027torch.double\u0027):\n        print(f\u0027torch.frac(a) a.numel() \u003d\u003d {n} for {t} times {dtype}\u0027)\n        print(timeit.timeit(f\u0027torch.frac(a); torch.cuda.synchronize()\u0027, setup\u003df\u0027import torch; a\u003dtorch.arange({n}, dtype\u003d{dtype}, device\u003d\"cuda\")\u0027, number\u003dt))\n```\n\nBefore:\n\n```\ntorch.frac(a) a.numel() \u003d\u003d 10000 for 20000 times torch.half\n0.3608182370007853\ntorch.frac(a) a.numel() \u003d\u003d 10000 for 20000 times torch.float\n0.3647012189976522\ntorch.frac(a) a.numel() \u003d\u003d 10000 for 20000 times torch.double\n0.3889585220022127\ntorch.frac(a) a.numel() \u003d\u003d 100000 for 20000 times torch.half\n0.622635444997286\ntorch.frac(a) a.numel() \u003d\u003d 100000 for 20000 times torch.float\n0.9595754649999435\ntorch.frac(a) a.numel() \u003d\u003d 100000 for 20000 times torch.double\n1.5590267750012572\n```\n\nAfter:\n\n```\ntorch.frac(a) a.numel() \u003d\u003d 10000 for 20000 times torch.half\n0.3675256470014574\ntorch.frac(a) a.numel() \u003d\u003d 10000 for 20000 times torch.float\n0.3703597319981782\ntorch.frac(a) a.numel() \u003d\u003d 10000 for 20000 times torch.double\n0.372184894993552\ntorch.frac(a) a.numel() \u003d\u003d 100000 for 20000 times torch.half\n0.60767333900003\ntorch.frac(a) a.numel() \u003d\u003d 100000 for 20000 times torch.float\n0.9645607889979146\ntorch.frac(a) a.numel() \u003d\u003d 100000 for 20000 times torch.double\n1.5542530329985311\n```\n\nTest Plan: Imported from OSS\n\nDifferential Revision: D18302768\n\nPulled By: VitalyFedyunin\n\nfbshipit-source-id: 24198838dc903d455155f0819d0c7d58974aaecd\n",
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