* 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
* add validation of the bounds of Ops.INDEX
* do mask properly
* more validation
* correct
* fix gated
* add CAST support to vmin/vmax
* fix ptx and image
* ptx no diff
* upat.index also stays
---------
Co-authored-by: qazal <qazal.software@gmail.com>
* wow argmax is so good
* 1 less line
* clean up and better variable names
* is this torch thing right...?
* add more tests
* slap a TODO on it
* clean ups
* prettier looking code and fix ceil mode test
* add return types and some docs
* ok that was a bad example since indices == value, just no example
* failed test case for threefry
not sure if it's always like this, but increment before _threefry_random_bits is incorrect. the counts should start with random numbers generated so far.
use jax to generate 20 + 20 + 10 random numbers, the first 20 + 20 matches and the last 10 are different. just moving increment after _threefry_random_bits matches the number but jit test failes
* workaround
* why is this different?
* revert those
* and that
* 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
* prep refactor for adding buffer ops last [pr]
* freeze buffers
* add swizzle_reduceop
* shape for reduceop_view_right
* simpler elementwise_view_right
* add shapetracker to const
* only const
* from process replay
* enable loading >2 GiB buffer from disk on macOS
* handle None case raised by mypy
* add test
* revert fix to repro bug in CI
* tell CI to run a unit test for macOS
* reapply fix
