* subbuffer support
* diskbuffer offset
* cuda subbuffer works
* use subbuffer
* more subbuffer tests
* consecutive
* cast
* consec
* offset
* view is a better name
* offset is in nbytes
* fix view + memory planner
* delete unused DiskRunner
* reverse order
* no subbuffers on unrealized consts
* only enabled for disk
* don't reverse memory
* view supported devices
* pickle buffer view
* ring jit
* support extra view inputs in jit
* fix JIT=2 issue
* test copy jit
* p2p isn't an option anymore
* fix dep tracking issue
* fix mypy
* fix pickle
* from_nv is contents now
* search: fix edge cases on screening potential ops
won't change correctness, but will save a little python time by
properly deduplicating potential actions
* check for de-duplication instead of exact valid actions
* refactor long line
* fix mean underflow for half tensor
divide only the reduce factor. added unit test and non-nan assertion in resnet training. also added a failed test cast for symbolic shape var
* skip for python backend
* kernel: change PADTO check to allow up to 4x padding
also optionally remove PADTO from the search action space with
BEAM_PADTO=0.
* fix test_linearizer test_tensor_cores_padded tests
* update resnet runs to use SPLIT_REDUCEOP=1
* fix up search TC axis and amt checking
* fix up the dimensions of the TC tests
* add support for train/val datasets for kits19
* split dataset into train and val sets
* add tests for kits19 dataloader
* add MLPerf dataset tests to CI
* update unet3d model_eval script
* fix linting
* add nibabel
* fix how mock dataset gets created
* update ref implementation with permalink and no edits
* clean up test and update rand_flip implementation
* cleanups
* handle reshape with remainder in _reshape_mask
* remove trailing whitespce
* use helper_test_op to generate tensors from shapes
* test in shapetracket too
* remove whitespace
* revert property name in other class tests
* use at least float32 for optim.lr
when doing mixed precision training (float32 weight, default_float=half), still use float32 to store lr.
it would have been upcasted later in actual weight update, but would have lost precision.
this improved resnet convergence significantly
* undo type annotation
* no ret value and just force contiguous
* ok revert contiguous stuff
* actually do force it contiguous
* revert again lol
* add simple regression test
* add assert for MLB
* guess we're contiguous everything from now on
* lol ugly af empty return...
* don't change order cuz i don't get disk
* Preprocessing script
* short seq prob
* comments + env vars
* Add preprocessing reference. Add test
* lint fix + add eval test support
* whitespaces
* point to commit
* comment
* rename
* better comments
