* search: add BEAM_VERIFY option to validate search results
refactor fuzz_linearizer comparison to allow it to be used in for
BEAM_VERIFY in device.py
* search: fix to verify the beam_search result and not the fastest
* search: fix typing and clean up
* device: remove imports from test and add LOGKERN options
LOGKERN output can be used with test/external/verify_kernel.py
to validate correctness
* fix example in verify_kernel.py
* cleanup fixes
* fix to use f-strings
the goal is that big enough beam should be faster than hcopt/tc
also this failed on tc opt
NUM=2 FILTER_REDUCE=1 TEST_N=20 BEAM=4 DEBUG=2 python test/external/speed_beam_v_hcopt.py
* add FUZZ_NTH to fuzz_linearizer
also update tests in test_linearizer_failures to not just run on METAL
* update failures for HIP/HSA
* test_failure_21 LLVM PADTO
* working PolynomialDecayWithWarmup + tests.......
add lars_util.py, oops
* keep lars_util.py as intact as possible, simplify our interface
* whitespace
* clean up
* clean up
* asserts
* test polylr for full resnet training run
* add comment
* rename
* fix do_optim
* don't cast lr
* info
* calculate from train_files
* skip it
included non-reduce kernel and kernel with variables. green msg when everything passed
it's possible that creating rawbufs failed due to memory error, included that in failure cases
* lars optimizer + tests
* fix skip list!
* use id to compare in skip list
* go back to using set
* Tensor(bool) * Tensor(bool) is and
* don't lint external/mlperf_resnet
* whitespace
* add external_test_optim to opencl tests
* give mlperf task a name
* mlperf under onnx
* remove track_gnorm
* contiguous instead of realize
* assert momentum and weight decay positive
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* this mem fault still happening
* smaller
* that print doesn't work
* overflows test
* hip doesn't uses_ptr_arithmetic
* only with locals
* test overflow new name
* it's not ptr arith
* simpler
* simple repro
* old compiler
* simpler
* put that back
* test/external/fuzz_linearizer: add a FUZZ_MAX_SIZE option
this allows us to limit the size of the kernel and reduce running
times by avoiding ones that take a long time
* fix spacing and re-order to put parameters together
* remove cpu and torch backends
* don't copy to cpu
* use clang instead of cpu
* multitensor gathers on the first device
* clang is cpu + use default
* fixup
* bugfix
* set metal fast math default to 0 (disabled)
It's a correctness fix because we use inf and nan. Let's see how slow it is
* skip failed onnx tests
* tmp DISABLE_COMPILER_CACHE=1 in metal benchmark
* Revert "tmp DISABLE_COMPILER_CACHE=1 in metal benchmark"
This reverts commit 22267df380.
* env var METAL_FAST_MATH to disable fastmath for metal
use this to test impact of fast math. might need to disable compiler cache with DISABLE_COMPILER_CACHE
* failed onnx test with fast math
METAL_FAST_MATH=0 DISABLE_COMPILER_CACHE=1 NOOPT=1 python -m pytest -n=auto test/external/external_test_onnx_backend.py -k test_MaxPool3d_stride_padding_cpu
* Reapply "take merge views from corsix branch" (#3278)
This reverts commit d298916232.
* reintroduce merge views
* update second any
* isinstance -> not
* 25% less same but unequal
* add onnx test_reduce_log_sum_exp
* more reuse
* more
* stuff
* good CenterCropPad
* imports
* good ArrayFeatureExtractor
* pretty good Pad
* stuff
* stuff
* onnx.py
* Atan
* pass int8 test
* dtype related
* fastmath stuff
* Resize linear
* fix CI
* move back
