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feat: update torch and modify cuda graphs #220

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merged 7 commits into from
Dec 19, 2022

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@pommedeterresautee pommedeterresautee commented Dec 14, 2022

fix #197

  • update PyTorch nightly to last version
  • rely on CUDA graph PyTorch wrapper (instead of our own)

@pommedeterresautee pommedeterresautee marked this pull request as draft December 14, 2022 21:19
@github-actions github-actions bot added feature and removed feature labels Dec 14, 2022
@@ -1,5 +1,5 @@
triton==2.0.0.dev20221202
torch==1.14.0.dev20221029+cu117
torch== 2.0.0.dev20221214+cu117
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note to remember: version in docker needs to be changed

@github-actions github-actions bot added feature and removed feature labels Dec 15, 2022
@pommedeterresautee pommedeterresautee self-assigned this Dec 15, 2022
@pommedeterresautee pommedeterresautee added the dependencies Pull requests that update a dependency file label Dec 15, 2022
@pommedeterresautee pommedeterresautee marked this pull request as ready for review December 15, 2022 12:38
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simple test pass

pytest test/test_torchdynamo.py

============================================================================================== 268 passed in 5296.85s (1:28:16) ==============================================================================================

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all tests pass

====================== 2849 passed in 9063.33s (2:31:03) =======================

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needs docker change

@@ -22,15 +22,11 @@
from kernl.optimizer.dynamo_backend import dynamo_backend_ofi


# single shared pool by default
_pool: (int, int) = torch.cuda.graph_pool_handle()
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should we open an issue to add pool back ?

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it will be covered here:

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@gaetansnl docker updated

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Comparison with pytorch 2.0
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