* 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
* fold expands that precede a reduce if the reduction is on the same axis as the expansion
* add deterministic test for SIMPLIFY_SUM_RESHAPE_EXPAND_SUM optimization
* add a test case to make sure we don't fold reduce-expand-reduce on different axes
* fixed division by zero for fast operations
* made et closer to 0
* replace POW llop with SQRT
* updated mlops to swap SQRT and POW llops
* updated hlops to swap POW and SQRT
* added sqrt llop to cpu runtime
* added sqrt llop to cstyle codegen
* added POW llop to llvm ir codegen
* added SQRT llop to torch runtime
* moved pow from mlops to hlops
* found a better way to do reverse pow
* fixed indentation
* added SQRT llop to triton
* update docs to match new llops
* removed POW operator from assembly codegen
* added sqrt and rsqrt to pow hlop
* rewrote pow function in tensor.py
* Adjust tolerance
* Adjust for adamw
* Reduce for Adam too
* removed accidental leftover code
* removed all of accidental code
* added rsqrt test
* removed pow from mlops again
it was added back when resolving merge conflicts
---------
Co-authored-by: Jacky Lee <jla524@sfu.ca>
* fix syntax issues in imagenet_download.py
* use cloudpickle in cross_process to make it work in Python 3.9+
* add cross_process test
* prevent unpickling on every function call
* add cloudpickle to setup.py
* add support for args/kwargs
* new upcast works
* float4 try
* fix unaligned float4
* disallow unaligned access
* upcast dim
* maybe good now
* fix gpu half
* vstore_half4
* fix deep image bugs
* improve symbolic to fix issues
* fix symbolic
* cl test
* this maybe
* gcd of 1 is 1
* real fix for old python
* improve fuzzer
* realize hotspots
* no str check
* minor changes
* make this an assert
* faster and more readable
* nicer self.buffers
* tests for weak op + LAZYCACHE=0
* refactor: print formatting for llama timing, report median and individual runs
* feat: back to mean
* fix: whitespace
* fix: add mean to print
---------
Co-authored-by: Roelof van Dijk <roelof.van.dijk@vitestro.com>
* Dedup params in optimizer
* Passing the same tensor multiple times in the set of learnable params passed to optimizers can result in models completely failing to learn, but no errors are produced. This dedups tensors to avoid the problem.
* Fix types
* Use new variable to satisfy linter
* Use `helpers.dedup` instead of `set()` to dedup params
* Add test for duped params in optimizers
* MaskRCNN weights loading
* backbone maybe works
* backbone works, but resnet body atol 1e-3
* RPN Call, but veryy wrong output
* fixed topk
* RPN maybe works, not sure about nms
* Fix cursed modules
* add back editorconfig
* Full call, wrong output
* Full call works
* fix mask
* use NMS from retinanet
* Removing extra funcs
* refactor
* readable
* Add example to run model
* remove filter
* Fix split, batched inference is worse
* Fix image sizes
* Matching reference
* merge master
* add filter on top detections
* cuda backend fixed
* add model eval and spec
* convert images to rgb
* fix eval
* simplify examples code
* remove extra code
* meshgrid using tinygrad
* removing numpy
* roi align, floor, ceil
* remove numpy from level_mapper
* remove numpy from pooler
* Revert "Merge branch 'master' of github.com:kunwar31/tinygrad into mrcnn-inference"
This reverts commit 4b95a3cb49, reversing
changes made to 98f2b1fa2e.
* roi align gather
* fix master merge
* revert to old floor, ceil as ints present in domain
* use log2 op
* fix indexes
* weird bug with ints and gpu
* weird bug with ints and gpu
* refactors, add env var for gather
* floor with contiguous, where
* refactor topk, sort
* remove staticmethod
* refactor stride
* remove log2 mlop
* realize -> contiguous
* refactor forward
* remove num_classes, stride_in_1x1 from state
* refactor forward
* refactoring
* flake8
* removing numpy in anchor gen, use numpy for gather, nonzero, optimize topk
* keep using tinygrad for smaller gathers
* fix empty tensors
* comms
* move from tensor.py
* resnet test passing
* add coco dataset back
* fix spaces
* add test for log2
* no need to create Tensors
* no need to create Tensors
---------
Co-authored-by: Kunwar Raj Singh <kunwar31@pop-os.localdomain>
* test speed llama
* oops, put it back
* uses the real device codegen
* just do it on the mac
* pp
* is faster?
* Revert "is faster?"
This reverts commit 42db542010.
* disable docker again for less load on CI
