* Fix max nan
* Adds nan check option to max function
* Calls to max can pass in "ignore_nan=True" argument
* Added max nan CI tests
* Fix max nan
* Adds nan check option to max function
* Calls to max can pass in "ignore_nan=True" argument
* Added max nan CI tests
* Turned off due to the need for granularity
* models matrix
* fix typo and install gpu deps
* install llvm deps if needed
* fix
* testops with cuda
* remove pip cache since not work
* cuda env
* install cuda deps
* maybe it will work now
* i can't read
* all tests in matrix
* trim down more
* opencl stuff in matrix
* opencl pip cache
* test split
* change cuda test exclusion
* test
* fix cuda maybe
* add models
* add more n=auto
* third thing
* fix bug
* cache pip more
* change name
* update tests
* try again cause why not
* balance
* try again...
* try apt cache for cuda
* try on gpu:
* try cuda again
* update packages step
* replace libz-dev with zlib1g-dev
* only cache cuda
* why error
* fix gpuocelot bug
* apt cache err
* apt cache to slow?
* opt and image in single runner
* add a couple n=autos
* remove test matrix
* try cuda apt cache again
* libz-dev -> zlib1g-dev
* remove -s since not supported by xdist
* the cache takes too long and doesn't work
* combine webgpu and metal tests
* combine imagenet to c and cpu tests
* torch tests with linters
* torch back by itself
* small windows clang test with torch tests
* fix a goofy windows bug
* im dumb
* bro
* clang with linters
* fix pylint error
* linter not work on windows
* try with clang again
* clang and imagenet?
* install deps
* fix
* fix quote
* clang by itself (windows too slow)
* env vars for imagenet
* cache pip for metal and webgpu tests
* try torch with metal and webgpu
* doesn't work, too long
* remove -v
* try -n=logical
* don't use logical
* revert accidental thing
* remove some prints unless CI
* fix print unless CI
* ignore speed tests for slow tests
* clang windows in matrix (ubuntu being tested in imagenet->c test)
* try manual pip cache
* fix windows pip cache path
* all manual pip cache
* fix pip cache dir for macos
* print_ci function in helpers
* CI as variable, no print_ci
* missed one
* cuda tests with docker image
* remove setup-python action for cuda
* python->python3?
* remove -s -v
* try fix pip cache
* maybe fix
* try to fix pip cache
* is this the path?
* maybe cache pip
* try again
* create wheels dir
* ?
* cuda pip deps in dockerfile
* disable pip cache for clang
* image from ghcr instead of docker hub
* why is clang like this
* fast deps
* try use different caches
* remove the fast thing
* try with lighter image
* remove setup python for cuda
* small docker and cuda fast deps
* ignore a few more tests
* cool docker thing (maybe)
* oops
* quotes
* fix docker command
* fix bug
* ignore train efficientnet test
* remove dockerfile (docker stuff takes too long)
* remove docker stuff and normal cuda
* oops
* ignore the tests for cuda
* does this work
* ignore test_train on slow backends
* add space
* llvm ignore same tests as cuda
* nvm
* ignore lr scheduler tests
* get some stats
* fix ignore bug
* remove extra '
* remove and
* ignore test for llvm
* change ignored tests and durationon all backends
* fix
* and -> or
* ignore some more cuda tests
* finally?
* does this fix it
* remove durations=0
* add some more tests to llvm
* make last pytest more readable
* fix
* don't train efficientnet on cpu
* try w/out pip cache
* pip cache seems to be generally better
* pytest file markers
* try apt fast for cuda
* use quick install for apt-fast
* apt-fast not worth
* apt-get to apt
* fix typo
* suppress warnings
* register markers
* disable debug on fuzz tests
* change marker names
* apt update and apt install in one command
* update marker names in test.yml
* webgpu pytest marker
* Add additional kernel when reducing multiple dimensions at once.
* Faster for smaller inputs
* Whitespace and naming
* Cleaner, guard for Metal only, and max 1 split rather than N
* Draft of different approach
* One additional kernel call for this test (as expected)
* Fuzz test symbolic and shapetracker
This reverts commit d5773ddebff54c1ff608838076f0b4ff126b8aa8.
* mess again
* no tail
* test shapetracker too
* Revert mess and enable all tests
* removed leftover
* new version
* fix abstractions
* try remove test
* Revert "try remove test"
This reverts commit 2fc18a9f8e.
* assert_allclose
* minimize the test
* minimize the test
* minimize the test
* minimize the test
* Revert "minimize the test"
This reverts commit e0c0929596.
* Revert "minimize the test"
This reverts commit 88240551b1.
* Revert "minimize the test"
This reverts commit 78328a7ce2.
* Revert "minimize the test"
This reverts commit 989523fded.
* skip test inside body
* oops
* oops
* Rename FusedOps to TernaryOps
* Support ternary broadcast
* Add where llop and mlop
* Make where op work in cstyle codegen
* Don't skip test_inf_where
* Add backward path to where op
* Use bool in cstyle codegen
* Add LLVM where op
* Add numpy where op
* Add torch where op
* Simplify where mlop
* Update documentation
* Forgot a rename
* Merged relevant changes from PR #1195 onto PR #1196
* Add test to cover changes to linearizer.ast_parse for WHERE op
Without this METAL will try to use ternary op on float4 and fail
* Make where op work in wgsl backend
* Allow ternary ops to be merged
* Make mypy happy
---------
Co-authored-by: Francis Lam <flam@alum.mit.edu>
* WIP: `tensor.squeeze` function
* Added `test_except` param to `helper_test_op` to avoid false positives
* Extracted new method `helper_test_exception` for testing exceptions
* Made `squeeze` not throw IndexError when ndim == 0 and dim <= 0 to match PyTorch
* initial commit
* 81 passing
* 105 passing tests
* 148 passing
* CI tests
* install dep on ci
* try opencl pkgs
* try using vulkan
* down to only 6 failing
* refactor
* cleaning up
* another test skipped due to buffer limit
* linter
* segfault
* indent fix
* another segfault found
* small touchups
* Fix max and maxpool tests
* Add constant folding
* Add javascript export script
* better asserts in codegen
* manual upcasting
* reverted token type change
* skip safetensor test due to unsupported type
* FIx efficientnet and all other model tests
* Remove np copy
* fixed indent and missing import
* manually destroy the buffer
* revert back to length
* linter errors
* removed extra val
* skip broken tests
* skipping more tests
* Make the page pretty
* Save model weights as safetensor
* Fix imagenet to c test
* Fix second imagenet to c bug
* Async and paralel kernel compilation
* workgroup support
* reversed local size
* fixed non local bug
* correct local groups
* ci experiment
* removed typo
* Fix define local by using shared memory
* Refactor
* try running on mac
* match metal tests
* add more workers
* scope down tests
* trying windows runner
* fixed windows env
* see how many it can do
* merged master
* refactor
* missed refactor
* increase test suite coverage
* missing import
* whitespace in test_efficientnet.py
* getting there
* fixed reset
* fixed bufs
* switched to cstyle
* cleanup
* min/max rename
* one more linter issue
* fixed demo
* linter
* testing ci chrome
* add unsafe webgpu arg
* add build step
* remove WEBGPU from cmd line
* use module
* try forcing directx
* trying forced metal backend
* temp disable conv2d for CI
* disable conv_trasnpose2d
---------
Co-authored-by: 0x4d - Martin Loretz <20306567+martinloretzzz@users.noreply.github.com>
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* Added test coverage for int32 in `test/test_dtype.py`
Tests for int32 include:
- testing that int32 can be converted into a numpy array
- testing that float and int64 can be cast into int32
- testing that int32 can be cast into float and int64
- testing addition, multiplication, and matrix multiplication with int32
- testing that addition, multiplication, and matrix multiplication with int32 and either float or int64 gets successfully cast into float and int64, respectively
Additional changes include testing that int8 casts into int32 and testing that float16 casts into int32
* Added type casting to the add, subtract, and divide binary operations
* Added automatic type casting when types differ to FusedOps.MULACC
I moved the match_types function back so that I could call it in einsum_mulacc where it would cast the types of the MULACC to be the same
* Added unit test for match_types and added type hints to the parameters
* Added tests for ops_cpu.match_types
* Changed ops_cpu.einsum logic to play nicely with PyTorch
Changed `tinygrad.runtime.ops_cpu.einsum_mulacc` logic to not perform type matching. Type matching was instead moved to the numpy_fxn_for_op dictionary in the ops_cpu file. Since ops_torch uses the same einsum_mulacc function, this should fix all the broken pytorch tests.
* empty commit to rerun ci
* reverting PR#1213 in attempt to fix broken test
* Removed all tests I added to see if they are causing CI issues
* Added back type matching tests
* removed type matching tests and added back int tests
* added back part of the type matching tests
* removed braking type matching tests
* empty commit for testing
* added test back but inside comment
* removed a test from the comment to see if it breaks CI
* removed another function
* more testing
* emptied test comment
* cleaned up comments
* Added optimize=True flag to einsum_mullac in cpu_ops.py
* Removed unnecessary imports from tests
* optimized match_types by removing unnecessary array copying
* Rename in files
* Move files
* Moved to extra/datasets as suggested
* Changes to files
* Fixed stupid mistake
---------
Co-authored-by: terafo <terafo@protonmail.com>
* Fixes + improved test coverage for helpers.py
- added exception handling in `proc`, if an exception was thrown, the thread would hang
- made `_early_exec_process` catch any Exception, before if an exception was thrown before the process was started, it would hand the thread
* Made `_early_exec_process` catch any Exception
Otherwise, if an exception was thrown before the process was started, it would hang the thread. For example a type error for an argument passed to `subprocess.check_output`
* Fixed `from tinygrad.helpers import Timing` import
oops, for some reason my IDE cleaned that import from extra/helpers.
* Fixed import in llama.py
Another one that I skipped by accident, mybad
* Extracted a class for tests of early exec
* Normalize line endings, windows uses /r/n
* Made `cross_process` not a daemon
