* fix tensor realization bug in #8975
* that's a reshape now
* work
* works
* give those tests better names
* test when multiple mops result in the same ShapeTracker
* test_become_existing_buf_complex is enough
* that too
* add some docs about speed [pr]
* better torch gemm
* enable locals on llvm/clang
* disable locals for beam speed on LLVM/CLANG
* 0x20 alignment in llvm allows ymm use
* increase CI speed with more runners [pr]
* splits + cleanups [pr]
* more runners
* need that dep
* split that too
* can't be minimal
* move test readme
* bugfix + naming
* one more split
* bump to 22.04
CPython doesn't make any guarantees about order in which globals like
`msg` or `libobjc` are destroyed when the interpreter shuts down
https://github.com/tinygrad/tinygrad/pull/8949 triggered the
unlucky ordering which lead to a bunch of errors at exit
There is also a bunch of other places where similar problems exist
* refactor into subactions
* this work?
* add shell
* move install opencl
* valid?
* support mac os x
* refactor other osx
* fix linux/osx
* fixes
* cleanups
* used everywhere
* no quotes
* quotes on true
* bugfixes
* this run?
* hardcode
* that
* process replay action
* fix checkout
* restore to branch
* fix caching
* fix osx python cache
* does replace function exist
* Revert "does replace function exist"
This reverts commit 622177c5a0.
* Revert "fix osx python cache"
This reverts commit e70d55cd93.
* user on osx to fix untar issue
* that
* Switch to dawn, all tests passing locally
* Use dawn-python
* Skip failing test
* Skip midcast and fix timestamp on metal ci
* Autogen webgpu
* Try fetch dawn lib again
* /usr/lib
* Without lib prefix
* Test autogen diff
* Delete webgpu support, move everything to ops_webgpu
* mypy fix
* Simplify, refactor
* Line savings
* No ResultContainer
* Type annotation for result
* Some more simplifications
* Why was this explicit sync used at all?
* Refactor: delete functions that are only used once
* Create shader module inline
* Clear unit tests cache, maybe that solves it
* That wasn't it
* Try deleting cache to pass failing weight compare
* weights_only=False for pytorch 2.6
* Simplify ctype array creation
* Remove nanosecond precision timestamps
* Simplify error handling
* Refactor, add back type annotations
* Deleted custom submit function, refactor
* read_buffer simplify
* Fix use after free, refactor
* Simplify supported_features
* Runtime docs
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Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
