[ET-VK] Conv2d quantize/dequantize ops for conv2d activations #14611
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14611
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Pull Request resolved: #14330 ## Context As title. Add shaders to quantize a floating point conv2d input tensor to packed int8 memory layout and dequantize a int8 conv2d output tensor back to floating point representation. Hooking it up to the export logic will be handled in a follow up diff. ghstack-source-id: 312106550 Differential Revision: [D82542335](https://our.internmc.facebook.com/intern/diff/D82542335/)
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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: #14330 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/330/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/330/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/331/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/330/orig
Differential Revision: D82542335
@diff-train-skip-merge