[ET-VK] Add kInt8x4 dtype and GPUMemoryLayouts for packed quantized tensors
#14609
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…ed tensors Pull Request resolved: #14329 ## Motivation Lay the foundations for being able to execute statically quantized CNNs with ET-VK. Unlike with dynamic quantization, static quantization allows the output of quantized operators to stay in integer representation and be fed directly to the next quantized operator. ## Context Typically, int8 quantized tensors can be represented by simply having the tensor use the int8 data type. While this is possible in ET-VK, in practice quantized operators expect int8 quantized tensors to be packed so that 16 8-bit values are packed into each `ivec4`, such that quantized int8 tensors will load/store with a granularity of 16 elements. The reason for this is twofold: * Support for shader int8 / storage buffer int8 extension is not guaranteed, meaning some devices do not allow using int8 types in shaders * We have found that load/store from storage buffers/textures that use int8 data types sometimes results in worse memory load performance, due to vectorized load/store instructions not being used. Therefore, in ET-VK we need a way to mark that a quantized tensor should 1. Use int32 as the underlying data type for the storage buffer/texture 2. Account for the block-packing that may be used ## Changes First, introduce the `Int8x4` dtype that can be used for packed int8 tensors. This dtype is functionally the same as `Int`, but denotes that each int32 actually contains 4 packed 8-bit values. Second, introduce new memory layouts: `kPackedInt8_4W4C` and `kPackedInt8_4H4W`. The former will be used for convolution, whil the latter will be used for matrix multiplication. See the inline comments for more details about these memory layouts. Then, update `QuantizedConvolution.cpp` and `QuantizedLinear.cpp` to use the new data type and memory layouts for the packed int8 input tensor. ghstack-source-id: 312106548 Differential Revision: [D82542336](https://our.internmc.facebook.com/intern/diff/D82542336/)
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14609
Note: Links to docs will display an error until the docs builds have been completed. ❌ 3 New Failures, 20 PendingAs of commit 0c04519 with merge base c18abc8 ( NEW FAILURES - The following jobs have failed:
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This PR was created by the merge bot to help merge the original PR into the main branch.
ghstack PR number: #14329 by @SS-JIA
^ Please use this as the source of truth for the PR details, comments, and reviews
ghstack PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/329/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/329/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/main
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/329/orig
Differential Revision: D82542336
@diff-train-skip-merge