* why does max_unpool2d feel slower than out.gradient ...
* slightly cleaner
* what happened to ruff
* need to think about this some more
* slightly faster now?
* clean up, 1 more failing edge case
* ok good
* working TINY_BACKEND
* nit doc wording
* retry CI
* poc
* repeated values fail, sigh
* is this being timed out?
* fix up down names
* bitonic v2, does this run?
* bitonic v3, faster
* bitonic v3.1, faster
* bitonic v3.1.1, same speed unlucky
* support dim and indices
* bitonic v3.2, simpler code, TODO repeated indices
* bruv gimme green for once cmon
* cat (stack) implementation, slow but maybe one day when cat is fast meow
* revert to v3.2
* bitonic v4, who let the cats out edition
* clean up variable names
* figured out repeated indices :D
* ruff check --fix
* use sort for topk
* add Tensor.sort everywhere
* fix docs and add some types
* slightly better variable names
* am I doing torch inplace correctly?
* delegate sort to values_stable
* add a contig, faster first sort
* maybe don't test_inplace
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* terrible but somewhat working impl
* linux behaves differently than macos?
* slightly better impl
* small clean up; haven't figured this out yet
* better
* torch has different behavior on linux and macos for duplicated values
* add sum docs
* fix test
* add torch return_type test
* add an exception test
* wrap_fxn instead, and move op lower in order
* better repeated values test
* rerun ci
* add `Tensor.isclose()`
* support `equal_nan`
so as to match PyTorch's behavior
* update unit tests
* remove some tests temporarily
* re-enable one test
* re-enable other test
* try to fix failing tests during CI
* save one line of code
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* pytorch scatter -> scatter_reduce
* WIP scatter_reduce implementation
* _pre_scatter return type hint
* split out src, mask to satisfy linter
* Add src cast back in
* dict of lambdas instead of ifs
* sum and prod reduction ops with include_self
* add reduce arg error message
* add amax and amin reduction ops
* Fix include_self for higher dims
* Simplify
* Simplify amax and amin too
* Pull include_self logic out into _inv_mask function
* reduce arg cannot be None for scatter_reduce
* Fix self-mask issue
* Add mean reduce op
* Add tests
* any() not needed here
* remove comment
* End support for Tensor src with reduce arg in tinygrad scatter
* Process index, dim inside actual functions
* Add scatter_reduce to onnx
* Add excluded onnx ScatterElements reduction tests back in
* Save 2 lines on the mask helpers
* Update docs
* Add include_self=False tests
* cleanup
* Remove unneeded helper function
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
it's a python style mod. possibily can be cleaner with a floor div
relaxed the vmin for MOD slightly for cstyle negatives mod, it's more correct and might fix other bugs
* working I think
* where are my onnx scatter tests??
* forward_only for now
* try if nan hack fix NV
* looks like issue is different... CUDA WHY
* oops that was wrong. Try if this fixes CUDA
* simpler multiply
* actually finish this up tmrw morning :x
* fix tests?
* improve tests
* improve test and implementation
* fix ruff
* complete but lots of expected failure...
* reviewed tests
* add onnx tests
* is this a processing op?
* add return type to indicate that it's not in-place
* final cleanups
* use or and improve tests a little
* add masked_index_select
* call it masked_setitem instead
* try
* FIXED
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* implement inverse trig functions
* guess we should still test nans?
* magnitude as variable name :D
* reorder onnx_ops ops
* approximation -> x for consistency
* address feedback
* simpler acos
* improvement?
* actually just have asin depend on atan
* actually this is nicer
* remove a comment
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* initial implementation and test
* some other places that can use meshgrid
* revert the onnx_ops change
* add to docs
* revert interpolate too
* update
* improve edge case test
* might as well test grad
* add to test can improve docs
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* move isinf and isnan to new branch
* sneak a roll documentation fix in
* add to docs
* update test coverage for detect_positive and detect_negative
* add types to isinf args
* move hardsigmoid to new branch
* add to test
* add NOTE to mention differing values for alpha and beta that match torch
* shift from relu6
* correct shift implementation
* or we just use relu? no more 666
