Fix 4bit groupwise dynamic linear quantization (#2251)

Summary:
Pull Request resolved: https://github.com/pytorch/executorch/pull/2251

This diff fixes following issues:
- removes scales packing/unpacking
- separate compute precision from scales storage precision, instead of
  maintaining activation/weight precision
- defaults to fp32 everywhere unless specified otherwise. This is because atm
  groupwise quant kernels in xnnpack are for fp32.
- Removes some dead code
- Remove k tile constraints: These were from GPU and are not needed here
- Replaces torch.ops.aten.linear with nn.functional.linear: This had to be done
  because otherwise delegation doesnt recognize the pattern. Yet another issue
  with pattern matching.
ghstack-source-id: 217579450
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bypassing check because oss failures are unrelated
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Reviewed By: cccclai

Differential Revision: D54427828

fbshipit-source-id: 634c34212e6ec80c41b21ae1dd1ad3211bf04862