[SDPA] Add expanded autograd testing for fused kernels and disable head_dim128 sm86 mem-efficient (#94009)
# Summary
- Adds a large parameter sweep for testing the various configs a user can call sdpa with and compares the deviation of the fused kernels vs the eager math fallback to test for correctness.
- Sm86 + head_dim==128 is throwing an IMA for memory efficient attention. We add a filter for use_mem_efficient_attention(). This has since been fixed in the upstream Xformers version but will likely not make it for branch cut.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94009
Approved by: https://github.com/cpuhrsch
