[inductor] Generalize pointless_cumsum_replacement pattern #108373
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The current pattern transforms:
```
ones([x, y]).cumsum(1) -> arange(1, 1 + y).expand([x, y])
```
but this generalizes it to
```
full(shape, fill_value).cumsum(d) ->
(fill_value * arange(1, 1 + shape[d])).view([1..., d, 1...]).expand(shape)
```
So we handle any fill value, any number of dimensions, and broadcasting to any dimension.
[ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/108373
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 948fddb with merge base 0e4752b ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
peterbell10
added a commit
that referenced
this pull request
Aug 31, 2023
The current pattern transforms:
```
ones([x, y]).cumsum(1) -> arange(1, 1 + y).expand([x, y])
```
but this generalizes it to
```
full(shape, fill_value).cumsum(d) ->
(fill_value * arange(1, 1 + shape[d])).view([1..., d, 1...]).expand(shape)
```
So we handle any fill value, any number of dimensions, and broadcasting to any dimension.
ghstack-source-id: 0a4bc2a
Pull Request resolved: #108373
lezcano
approved these changes
Sep 1, 2023
|
@pytorchbot merge |
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Stack from ghstack (oldest at bottom):
The current pattern transforms:
but this generalizes it to
So we handle any fill value, any number of dimensions, and broadcasting to any dimension.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @ipiszy @ngimel @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov