[ROCm] ROCm compatible configs for triton kernels (#107584)
This PR brings in a few inductor changes required for ROCm
~**1 - Introduction of a toggle for enforced channel last convolution fallbacks**~
This addition is split off into its own PR after some cleanup by @pragupta https://github.com/pytorch/pytorch/pull/107812
**2 - Addition of ROCm specific block sizes**
We are now able to support the MAX_AUTOTUNE mode on ROCm, we are proposing conditions to allow us to finetune our own block tuning. Currently triton on ROCm does not benefit from pipelining so we are setting all configs to `num_stages=1` and we have removed some upstream tunings on ROCm to avoid running out of shared memory resources.
In the future we will provide more optimised tunings for ROCm but for now this should mitigate any issues
~**3 - Addition of device_type to triton's compile_meta**~
~Proposing this addition to `triton_heuristics.py`, Triton on ROCm requires device_type to be set to hip https://github.com/ROCmSoftwarePlatform/triton/pull/284 suggesting to bring this change in here so we can pass down the correct device type to triton.~
This change is split off and will arrive in the wheel update PR https://github.com/pytorch/pytorch/pull/107600 leaving this PR to focus on the ROCm specific block sizes.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/107584
Approved by: https://github.com/jithunnair-amd, https://github.com/jansel, https://github.com/eellison
