Fix memory profiling for memory.view ops #7925
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ATT Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/7925
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit c6e2441 with merge base d4a8f8f ( BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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ATT Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) cc Olivia-liu Jack-Khuu [ghstack-poisoned]
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ATT Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) cc Olivia-liu Jack-Khuu [ghstack-poisoned]
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Pull Request resolved: #7925 ATT ghstack-source-id: 263342054 @exported-using-ghexport Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) Co-authored-by: Kimish Patel <[email protected]>
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* Fix memory profiling for memory.view ops Pull Request resolved: #7925 ATT ghstack-source-id: 263342054 @exported-using-ghexport Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) * [ET][Memory planning] Improve greedy memory planning. Pull Request resolved: #7926 This diff replaces the old greedy algorithm. Older algorithm resulted in 35% worse compared to theoretical optimum. THis matter for long context even more since additional overhead can be few hundred MB. For example the theorical optimial for llama3_2 8B, 4-bit quantized modelw ith context length of 2k needs about 1G of memory. This theoretcial max can be observed by looking at the peaks in memory profile. Current agorithm resulted in about 1.6GB of planned memory. New algorithm reduce that to about 1.1G. ghstack-source-id: 263342052 @exported-using-ghexport Differential Revision: [D68448332](https://our.internmc.facebook.com/intern/diff/D68448332/) --------- Co-authored-by: Kimish Patel <[email protected]>
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Pull Request resolved: #7925 ATT ghstack-source-id: 263342054 @exported-using-ghexport Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) Co-authored-by: Kimish Patel <[email protected]>
YIWENX14
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* Fix memory profiling for memory.view ops Pull Request resolved: #7925 ATT ghstack-source-id: 263342054 @exported-using-ghexport Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) * [ET][Memory planning] Improve greedy memory planning. Pull Request resolved: #7926 This diff replaces the old greedy algorithm. Older algorithm resulted in 35% worse compared to theoretical optimum. THis matter for long context even more since additional overhead can be few hundred MB. For example the theorical optimial for llama3_2 8B, 4-bit quantized modelw ith context length of 2k needs about 1G of memory. This theoretcial max can be observed by looking at the peaks in memory profile. Current agorithm resulted in about 1.6GB of planned memory. New algorithm reduce that to about 1.1G. ghstack-source-id: 263342052 @exported-using-ghexport Differential Revision: [D68448332](https://our.internmc.facebook.com/intern/diff/D68448332/) --------- Co-authored-by: Kimish Patel <[email protected]>
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Pull Request resolved: pytorch#7925 ATT ghstack-source-id: 263342054 @exported-using-ghexport Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) Co-authored-by: Kimish Patel <[email protected]>
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* Fix memory profiling for memory.view ops Pull Request resolved: pytorch#7925 ATT ghstack-source-id: 263342054 @exported-using-ghexport Differential Revision: [D68448333](https://our.internmc.facebook.com/intern/diff/D68448333/) * [ET][Memory planning] Improve greedy memory planning. Pull Request resolved: pytorch#7926 This diff replaces the old greedy algorithm. Older algorithm resulted in 35% worse compared to theoretical optimum. THis matter for long context even more since additional overhead can be few hundred MB. For example the theorical optimial for llama3_2 8B, 4-bit quantized modelw ith context length of 2k needs about 1G of memory. This theoretcial max can be observed by looking at the peaks in memory profile. Current agorithm resulted in about 1.6GB of planned memory. New algorithm reduce that to about 1.1G. ghstack-source-id: 263342052 @exported-using-ghexport Differential Revision: [D68448332](https://our.internmc.facebook.com/intern/diff/D68448332/) --------- Co-authored-by: Kimish Patel <[email protected]>
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Differential Revision: D68448333
cc @Olivia-liu @Jack-Khuu