NNC Dynamic Channels last fixes (#72032)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72032
This contains a few channels last changes from benchmarking:
- dont permute back to channels last on dynamic, cpu, perf is not good, and use cases for it are exotic atm
- remove the conditional one handling in permutting channels last symbolic tensor on cuda, it's not needed in the permutation case as tests show
- removing logic in torch/csrc/jit/tensorexpr/loopnest.cpp preventing inlining. the condition in checks is always valid given valid construction of ir
I can split up as needed.
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision: D33864652
Pulled By: eellison
fbshipit-source-id: f16674fb02dfff22670d8a2f856c5a317fd15717
(cherry picked from commit a9a069783956802e9e2f30c7a06e8e2ca8d210a1)