[ET-VK][ez] Allow logit linear layer to be lowered to Vulkan #9918
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/) [ghstack-poisoned]
pytorch-bot
bot
added
the
module: vulkan
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9918
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 22fdb0b with merge base 6adff9c ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
SS-JIA
added a commit
that referenced
this pull request
Apr 4, 2025
## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/) ghstack-source-id: 276219519 Pull Request resolved: #9918
facebook-github-bot
added
the
CLA Signed
|
This pull request was exported from Phabricator. Differential Revision: D72480177 |
## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/) cc manuelcandales cbilgin [ghstack-poisoned]
SS-JIA
added a commit
that referenced
this pull request
Apr 4, 2025
Pull Request resolved: #9918 ## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/) ghstack-source-id: 276235672
|
This pull request was exported from Phabricator. Differential Revision: D72480177 |
## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/) cc manuelcandales cbilgin [ghstack-poisoned]
SS-JIA
added a commit
that referenced
this pull request
Apr 7, 2025
Pull Request resolved: #9918 ## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan ghstack-source-id: 276549534 Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/)
|
This pull request was exported from Phabricator. Differential Revision: D72480177 |
nathanaelsee
approved these changes
Apr 7, 2025
## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/) cc manuelcandales cbilgin [ghstack-poisoned]
SS-JIA
added a commit
that referenced
this pull request
Apr 7, 2025
Pull Request resolved: #9918 ## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan ghstack-source-id: 276566114 Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/)
|
This pull request was exported from Phabricator. Differential Revision: D72480177 |
facebook-github-bot
merged commit 73f2c97
into
gh/SS-JIA/208/base
87 of 90 checks passed
facebook-github-bot
had a problem deploying
to
cherry-pick-bot
GitHub Actions
Failure
kirklandsign
pushed a commit
that referenced
this pull request
Apr 7, 2025
Pull Request resolved: #9918 ## Context Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate. However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan. ## Changes * Remove limit from `VkInt4WeightOnlyQuantizer` that was causing it to ignore the logit layer of the transformer * Do not apply XNNPACK partitioner and quantizer when lowering with Vulkan ghstack-source-id: 276566114 Differential Revision: [D72480177](https://our.internmc.facebook.com/intern/diff/D72480177/)
facebook-github-bot
had a problem deploying
to
cherry-pick-bot
GitHub Actions
Failure
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Stack from ghstack (oldest at bottom):
Context
Due to poor performance of Vulkan's int4 linear operator, the final logit layer of the transformer model was not being delegated to vulkan, and was instead quantized and executed with the XNNPACK delegate.
However, with D72412950 / #9883 decent performance can now be achieved with Vulkan/s int4 linear op. Therefore, the final logit layer can be lowered to Vulkan.
Changes
VkInt4WeightOnlyQuantizerthat was causing it to ignore the logit layer of the transformerDifferential Revision: D72480177
cc @manuelcandales @cbilgin