[ET-VK][ez] Allow logit linear layer to be lowered to Vulkan #9918
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## 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]
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9918
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## 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
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## 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]
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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
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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