* add Tensor.split (#2677)
* fix mypy errors
* add list support for Tensor.split
* fix ruff comments
* match tensor.split api
* simplify split and test_split
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Co-authored-by: George Hotz <[email protected]>
* remove type check for LazyOp.src now it's always LazyOp
also matched MULACC criteria between interpreted and compiled (that probably need to be refactored somewhere else)
* disable that test
* print DEBUG for TC=2 in CI
* enable TC=2
* no need to check src type
* LOAD has side effect
* don't push any local buffer
* update comment
* and BARRIER
* 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.
* test dtypes of return values of cumsum, argmax/min, multinomial
cumsum behaves like sum, and functions that return an index return in dtypes.default_int
* because webgpu is different
* 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
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Co-authored-by: George Hotz <[email protected]>
* ww/Fixed Tensor.randint() to accept shape tuples ()
* ww/Wrote a test to cover this typo
* ww/Updated Tensor random objects to optionally take (,) or *() to be more consistent
* ww/no lint no worries
* ww/Made peace with linter
* ww/Added new line can't reduce line size without reducing readablitity
* ww/reverted to using .mul
* space removal in formula and a single test to cover it
* space in torch einsum as well
* replacing spaces in a var formula to support truncating all the spaces
* better support for platform dependent flags
* osx test support
* removed unused import and made line length <150
* changed osx ci shm
* lstrip in case SharedMemory._name is passed
* don't match dtype with first input in where
`Tensor([1, 2, 3]).where(1.2, 2.3)` the first `[1, 2, 3]` can directly cast into bool without casting float (in broadcasted) first
* cast in one place
geohot