[ET-VK][Ops] affine quantization operators registration#12440
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Pull Request resolved: #12369 # Context In order to enable dynamic quantization, especially for the source transform method using `Int8DynActInt4WeightQuantizer` we need to have vulkan versions for `quantize_affine`, `dequantize_affine`, and `choose_qparams_affine`. Currently we do not have a shader that performs block-based quantization as expected from these shaders, so we delegate to the per_tensor variant just to get unblocked. At a later stage, this will likely be developed more on in order to ensure we don't get too much accuracy loss. A full implementation for the affine operators will be done at a later time, since they are required for usage. However, if you wan't to just use the default as per_tensor then you must remove the checks made in `op_registry` and in the vulkan implementation so that the per_tensor version can be used. Without it they will not be registered. # Changes This creates a schema reference in the TorchAO library for out variants of these respective operators. Then there is a VK_REGISTER_OP done on them to ensure that we can properly register them when lowering the ET model with vulkan. We also changed `Linear.cpp`, particularly to allow a passthrough for weight_data since during dynamic quantization it's possible that it'll be a tensor_data than tensor_ref. ghstack-source-id: 295972790 @exported-using-ghexport Differential Revision: [D78035354](https://our.internmc.facebook.com/intern/diff/D78035354/)
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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: #12369 by @ahmtox
^ 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/ahmtox/39/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/ahmtox/39/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/ahmtox/38/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/ahmtox/39/orig
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