* probably how cumprod should look like
* update _cumalu to work with MUL
* shorter
* cumprod testing
* clean
* more cleanup
* add cumprod to torch backend.
* make it look like cumsum
* mypy fix
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* 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
* 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
* train_shakespeare_char.py works
* move aten.where.self_out to tiny_backend_out
* fix memory leak
* corealize in the backward_hook
* Update backend.py
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* 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>
* fix leak, realize everything on torch optim step
* only realize a subset
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* add torch inplace tests
* first set of tests passing
* wrap all inplace funcs, add more tests
* fixes and wrap more functions
* fix all uint8 tests to avoid slow tests
* fix the one test
* another test, another fix
* and one more, works for ddp now
* something on contiguous, cleanup
---------
Co-authored-by: qazal <77887910+Qazalin@users.noreply.github.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
* fix some torch tests
* fixup
* small change
* fixup
* fix test
* use default function
* add todo
* bunch of small changes
* fix tests
* more tests
* fix
* fix
* test fix
* simplify
* yml changes
* torch backend remove meta decomps and add test
* torch backend bump timeout for tests
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* fixes from chargpt for torch backend
* shrink support
* add stride support
* comment cleanup
* a few more
* work
* import the stream hack
* llvm multi auto
* rig up torch's testing framework [pr]
* support more movement ops
* dec on expand
* fix tests
* work
* fix tests
* a few more
* decomps + opt hook
* installed pytest
* different way to write torch backend
* both backends
* more work
* simpler code
* more work
* test both
* imply unwrap/wrap
* FORWARD_ONLY=1 TINY_BACKEND=1 python3 test/test_ops.py TestOps.test_add works
* ready to start making test_ops work in torch backend
* backward pass, TINY_BACKEND=1 python3 test/test_ops.py TestOps.test_add works
* FORWARD_ONLY=1 TINY_BACKEND=1 python3 test/test_ops.py TestOps.test_simple_conv2d works
* matmul backward is broken with as_strided
