Migrate the quantizer to use aten ops directly (#4195)

Summary:
Pull Request resolved: https://github.com/pytorch/executorch/pull/4195

This major change allows a lot more flexibility in the quantizer, and reduces the dependency on the decompositions/graph tracing tools.

The motivation is that some of those do not preserve or propagate `source_fn_stack` information, resulting in quantization misses. SDPA is an example, where the underlying `bmm` ops cannot be quantized with `source_fn_stack` information alone, or MHA, which can hide its SDPA component and sometimes even `linear` ops depending on the model (see ViT for an example).

Also note than in most cases, we match single nodes anyway, with a 1-1 mapping between the op (either nn.Module or nn.functional) and the aten op, so using the aten op directly is simply easier.

Summary of the changes:
- change the quantizer to match aten ops directly, through `node.target`
- propagate required changes to the `QuantFusion` pass
- update/remove existing patterns

Reviewed By: dulinriley

Differential Revision: D59552606

fbshipit-source-id: 0bc39679df9d4abfcca0f0091ec96fb94e5177b8