Append PID to shared memory names in batch_load_retinanet to prevent
FileExistsError when pytest-xdist runs multiple test workers that each
call _setup_shared_mem with the same hardcoded name.
* preallocate all realized buffers
* contiguous
* work
* comment that out
* move to schedule
* better
* correct fix
* just buffer
* disk bufs
* fixes disk tensor stuff
* fix symbolic stuff
* fix multi
* 162 failures
* bugfixes
* don't check that anymore
* fix schedule tests
* mnist should be contiguious
* type and buffer
* fix tests
* shrink axis correction
* mypy fixes
* tests skips
* same 37 failures
* dedup
* no shrink in the graph
* 29 failures
* skips
* fix custom kernel
* fix training
* those optimizations aren't supported currently
* simpler
* more correct
* tests
* 14 failures
* works
* fix that test
* broken
* 11 failures
* only kernel counts left
* fixes
* all tests pass
* remove tensor_map
* op test
* 200 -> 230
* test fixes
* fixes
* revert test_tiny thing
* guard
* revert that
* test tiny passes
* no contigs there
* base realize back
* Revert "no contigs there"
This reverts commit c45bb9fcfd.
* revert that
* chop many assigns
* 12 failures
* fix tests
* tests
* apply after
* pre-commit
* remove old code
* delete that
* fix types
* remove extra contig
* fix dataloader
* torch fix
* disk fix
* update kernel fusion numbres
* runs on amd
* restore kernel count
* add that rule back
* that
* disable that
* wrong
* add the correct rule for that folding
* more tests
* guard c1.arg
* no newlines
* realize those
* split into a different file
* remove detach/contig back
* skip 2
* update that
* Revert "BUFFER_VIEW is a node in the kernel graph + delete ViewOp (#9298)"
This reverts commit 3210b656b6.
* Revert "substitute ast from kernel op [pr] (#9293)"
This reverts commit 5a9c788ae6.
python time 45ms -> 9ms, it was spending time to schedule the shard
also init bert data on CLANG since it's from numpy, so we don't create the tensor on default device then shard into GPUS
* testing dataloader
* matching dataloader implementation for unet3d
* remove comments
* clean up dataloader
* add cookie and cleanup
* use shm_path when creating SharedMemory
* add support for testing resnet and unet3d dataloaders
* update dataset test to return preprocesed data directory in prep for dataloader testing
* pass preprocessed dataset directory properly
* update loader function for dataloader
* add shuffling on indices
* update shm name
* more cleanup for unet3d dataloader
* remove changes to tests
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* this is a lot of stuff
TEST_TRAIN env for less data
don't diskcache get_train_files
debug message
no lr_scaler for fp32
comment, typo
type stuff
don't destructure proc
make batchnorm parameters float
make batchnorm parameters float
resnet18, checkpointing
hack up checkpointing to keep the names in there
oops
wandb_resume
lower lr
eval/ckpt use e+1
lars
report top_1_acc
some wandb stuff
split fw and bw steps to save memory
oops
save model when reach target
formatting
make sgd hparams consistent
just always write the cats tag...
pass X and Y into backward_step to trigger input replace
shuffle eval set to fix batchnorm eval
dataset is sorted by class, so the means and variances are all wrong
small cleanup
hack restore only one copy of each tensor
do bufs from lin after cache check (lru should handle it fine)
record epoch in wandb
more digits for topk in eval
more env vars
small cleanup
cleanup hack tricks
cleanup hack tricks
don't save ckpt for testeval
cleanup
diskcache train file glob
clean up a little
device_str
SCE into tensor
small
small
log_softmax out of resnet.py
oops
hack :(
comments
HeNormal, track gradient norm
oops
log SYNCBN to wandb
real truncnorm
less samples for truncated normal
custom init for Linear
log layer stats
small
Revert "small"
This reverts commit 988f4c1cf3.
Revert "log layer stats"
This reverts commit 9d98224585.
rename BNSYNC to SYNCBN to be consistent with cifar
optional TRACK_NORMS
fix label smoothing :/
lars skip list
only weight decay if not in skip list
comment
default 0 TRACK_NORMS
don't allocate beam scratch buffers if in cache
clean up data pipeline, unsplit train/test, put back a hack
remove print
run test_indexing on remu (#3404)
* emulated ops_hip infra
* add int4
* include test_indexing in remu
* Revert "Merge branch 'remu-dev-mac'"
This reverts commit 6870457e57, reversing
changes made to 3c4c8c9e16.
fix bad seeding
UnsyncBatchNorm2d but with synced trainable weights
label downsample batchnorm in Bottleneck
:/
:/
i mean... it runs... its hits the acc... its fast...
new unsyncbatchnorm for resnet
small fix
don't do assign buffer reuse for axis change
* remove changes
* remove changes
* move LARS out of tinygrad/
* rand_truncn rename
* whitespace
* stray whitespace
* no more gnorms
* delete some dataloading stuff
* remove comment
* clean up train script
* small comments
* move checkpointing stuff to mlperf helpers
* if WANDB
* small comments
* remove whitespace change
* new unsynced bn
* clean up prints / loop vars
* whitespace
* undo nn changes
* clean up loops
* rearrange getenvs
* cpu_count()
* PolynomialLR whitespace
* move he_normal out
* cap warmup in polylr
* rearrange wandb log
* realize both x and y in data_get
* use double quotes
* combine prints in ckpts resume
* take UBN from cifar
* running_var
* whitespace
* whitespace
* typo
* if instead of ternary for resnet downsample
* clean up dataloader cleanup a little?
* separate rng for shuffle
* clean up imports in model_train
* clean up imports
* don't realize copyin in data_get
* remove TESTEVAL (train dataloader didn't get freed every loop)
* adjust wandb_config entries a little
* clean up wandb config dict
* reduce lines
* whitespace
* shorter lines
* put shm unlink back, but it doesn't seem to do anything
* don't pass seed per task
* monkeypatch batchnorm
* the reseed was wrong
* add epoch number to desc
* don't unsyncedbatchnorm is syncbn=1
* put back downsample name
* eval every epoch
* Revert "the reseed was wrong"
This reverts commit 3440a07dff3f40e8a8d156ca3f1938558a59249f.
* cast lr in onecycle
* support fp16
* cut off kernel if expand after reduce
* test polynomial lr
* move polynomiallr to examples/mlperf
* working PolynomialDecayWithWarmup + tests.......
add lars_util.py, oops
* keep lars_util.py as intact as possible, simplify our interface
* no more half
* polylr and lars were merged
* undo search change
* override Linear init
* remove half stuff from model_train
* update scheduler init with new args
* don't divide by input mean
* mistake in resnet.py
* restore whitespace in resnet.py
* add test_data_parallel_resnet_train_step
* move initializers out of resnet.py
* unused imports
* log_softmax to model output in test to fix precision flakiness
* log_softmax to model output in test to fix precision flakiness
* oops, don't realize here
* is None
* realize initializations in order for determinism
* BENCHMARK flag for number of steps
* add resnet to bechmark.yml
* return instead of break
* missing return
* cpu_count, rearrange benchmark.yml
* unused variable
* disable tqdm if BENCHMARK
* getenv WARMUP_EPOCHS
* unlink disktensor shm file if exists
* terminate instead of join
* properly shut down queues
* use hip in benchmark for now
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
