Improve performance of _to_dim_order_copy #11545
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/11545
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 9e82b26 with merge base 04710d4 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
swolchok
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We had a problem similar to the one motivating BroadcastIndexesRange: we were doing full coordinate recalcuation on every iteration of a loop. Thankfully, it is straightforward to use BroadcastIndexesRange (and the new support_noncontiguous_tensors option, which I realized should be renamed) to fix this. ghstack-source-id: 944a2d1 ghstack-comment-id: 2961146796 Pull-Request-resolved: #11545
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manuelcandales
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We had a problem similar to the one motivating BroadcastIndexesRange: we were doing full coordinate recalcuation on every iteration of a loop. Thankfully, it is straightforward to use BroadcastIndexesRange (and the new support_noncontiguous_tensors option, which I realized should be renamed) to fix this.