* add a failing test for LR scheduler when using multigpu
* fix calculation order and unnecessary tensor created for float
* min_lr is no longer tensor
* updated most dtype hacks in onnx_ops
* temporarily revert dequantizelinear change
* I think this is right...
* MORE FIXES WOOOO NEW DTYPE IS AWESOME
* ok
* oops missed a print
* half -> float32 for CI
* is npdtype
* some more
* fix if ordering
* more clean ups
* final cleanups
* casting to half not allowed
* k nvm
* revert ArgMax change
* only GPU
* llvm begone
* teeny tiny change
* fix: attempt to add cast tests
* try this
* fix dequantizelinear
* revert some stuff
* tests pass pls
* less lines in onnx_tests
* oops missed string tensor tests
* clean up
* try: revert default behavior changes
* fix: disabled Cast and Castlike tests
* docs: small changes
* fix: fixed isNaN op and enabled associated tests
* fix: forgot about float16
* done
* update disabled test
* gah missed another float16
* disable rest of failing tests
* rm extra line
* try...
---------
Co-authored-by: chenyu <[email protected]>
* cleanup llama apply_rotary_emb and other helpers
used ellipsis and other higher level tensor function.
disabled the half @ half -> half tensor core as it fails uop dtype checks
* keep hip 8x8->8 wmma
the correct condition is that PADTO cannot be applied to reduce axis, not Reduce.MAX in ops.
even for Reduce.SUM it's possible that the reduce axis had a div before, and the padded 0 became inf then sum over it is incorrect.
* these asserts should pass
* fix that assert
* ALU dtypes
* acc dtype for group_for_reduce
* cast image ALUs to the base dtype
* remove all casts from linearizer
* fix argmax
* fix multinomial
* fix __getitem__
* Revert "fix __getitem__"
This reverts commit 62ad719bfa.
* fix MemBuffer outputs being wrong when there is an arange + ALU with a different dtype
eg. fancy slicing (int, float), bert embeddings (int, long)
this should be fixed in lazy instead of having to break the kernel
* cleanup argmax fix
* fix matmul in ints
cast in the end
* fix llama
* skip wrong hardcoded asts in the worlds dataset
* fix llama p2
* cleanup missing parts of the diff
---------
Co-authored-by: George Hotz <[email protected]>
* lazy rewrite, try 2
* min fix tests
* pass contig test
* put broken pads back
* move that to realize
* no contig child fixes array packing
* so wrong
* now that's correct
* base children
* fix bind issues
* disable to_image_idx
* fix tests
* that failure shouldn't break other tests
* more fixes
* fix torch
* skip failing tests in CI
* 1e-7
* half is broken
* 1e-6 margin of error
* bitcast renderers
* fast llama load
* make it one kernel
* regression testing p1: re-enable test_dtype for all backends
fix GPU
* regression testing p2: fuzz all possible cases against numpy
remove hancoded tests since the fuzzer covers them
* define ushort
* fix indent, probably need flake8 back for CI to catch
---------
Co-authored-by: George Hotz <[email protected]>
geohot