[TensorExpr] TensorExprKernel: don't do any compilation or lowering in run().#37948
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ZolotukhinM wants to merge 4 commits intogh/ZolotukhinM/239/basefrom
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[TensorExpr] TensorExprKernel: don't do any compilation or lowering in run().#37948ZolotukhinM wants to merge 4 commits intogh/ZolotukhinM/239/basefrom
ZolotukhinM wants to merge 4 commits intogh/ZolotukhinM/239/basefrom
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…n run(). The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. [ghstack-poisoned]
… lowering in run()." The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. [ghstack-poisoned]
ZolotukhinM
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May 6, 2020
…n run(). The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. ghstack-source-id: e1fc41c Pull Request resolved: #37948
💊 CI failures summary and remediationsAs of commit de9aeb5 (more details on the Dr. CI page):
ci.pytorch.org: 1 failedThis comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions on the GitHub issue tracker. This comment has been revised 7 times. |
… lowering in run()." The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. Differential Revision: [D21432145](https://our.internmc.facebook.com/intern/diff/D21432145) [ghstack-poisoned]
ZolotukhinM
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May 12, 2020
…n run(). The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. ghstack-source-id: 90856fa Pull Request resolved: #37948
… lowering in run()." The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. Differential Revision: [D21432145](https://our.internmc.facebook.com/intern/diff/D21432145) [ghstack-poisoned]
ZolotukhinM
pushed a commit
that referenced
this pull request
May 13, 2020
…n run(). The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. ghstack-source-id: a8ccf12 Pull Request resolved: #37948
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@ZolotukhinM , does this work with the multigpu tests in test_jit_fuser_te.py? |
Author
All tests pass with this change. |
protonu
approved these changes
May 13, 2020
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@ZolotukhinM merged this pull request in 6e13146. |
laurentdupin
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Apr 24, 2026
…n run(). (pytorch#37948) Summary: Pull Request resolved: pytorch#37948 The input JIT graph has all the information we need to perform the entire compilation at the construction time. We don't need to postpone any steps until the execution time. Also, from the graph we always know what device we will be executing on and thus we don't need to have a CodeGen cache in TensorExprKernel - we always have one and only one CodeGen. Test Plan: Imported from OSS Reviewed By: protonu Differential Revision: D21432145 Pulled By: ZolotukhinM fbshipit-source-id: 8dc86b891713056b2c62f30170cd4a168912f027
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Stack from ghstack:
The input JIT graph has all the information we need to perform the
entire compilation at the construction time. We don't need to postpone
any steps until the execution time. Also, from the graph we always know
what device we will be executing on and thus we don't need to have a
CodeGen cache in TensorExprKernel - we always have one and only one
CodeGen.
Differential Revision: D21432145