* feat: initial xor
* feat: initial threefly
* feat: remove custom random
* fix: really need to install precommit
* feat: lmao forgot that this is rotate not a shift
* clean: put that there
* feat: numpy xor
* feat: quick test for xor
* feat: llvm xor
* feat: slightly working xor in torch
* feat: rand works in jit
* clean: save a line
* feat: match jax
* feat: maybe test against jax
* feat: requires_grad
* fix: fix test_symbolic_ops
* feat: lower alpha
* feat: just pad
* fix: maybe fix training tests?
* fix: fix some llvm stuff
* feat: cursed realize on the way out
* feat: testing jax
* fix: why is the jax install process not simple
* fix: maybe passing test
* fix: symbolic workarounds
* clean: still need that precommit
* fix: aaaa
* fix: more test fixes
* fix: quick fix for wgsl
* feat: need to set requires_grad on the final tensor
* feat: one more tensor
* feat: don't take forever
* feat: seeing y ci is brok
* feat: can't allocate 64GiB lmao
* fix: fix this
* feat: hope this doesn't break smth before i go to bed
* feat: don't destroy ram
* feat: int
* feat: remove jax
* feat: properish workaround?
* feat: skip slow webgpu tests
* feat: no longer fails
* feat: use dtypes
* feat: real number
* fix: torch
* fix: don't test against reference for torch
* feat: to device
* feat: fix advanced indexing
* feat: correct casting
* feat: even rng_counter
* feat: match master
* feat: this was actually bad
* fix: maybe?
* feat: store
* feat: remove realizes
* feat: somehow this is important
* feat: somehow this is also important
* feat: save a line
* fix: don't need that anymore
* feat: restore this
* fix: linter
* feat: remove realizes
* fix: realized is in base now
* fix: add back cast
* fix: bump deadline
* fix: bump deadline
* fix: bump deadline
* fix: bump deadline
* fix: bump deadline
* fix: :(
* fix: :(
* fix: not being dumb
* feat: try changing less tests
* feat: shouldn't have to change that
* feat: contiguous bumps it by one
* fix: hmm
* fix: numpy memory moment
* fix: cl_khr_fp16
* fix: torch has different tensor count
* fix: missing contiguous
* hmm: hmm
* fix: some fixes
* fix: typing
* feat: dont do that
* feat: typing fixes
* feat: why is this realize required?
* feat: ngl kinda odd typing
* feat: oh
* feat: remove realizes
* feat: why is this realize required?
* fix: hacky patch for cudacpu
* fix: without this realize pytest crashes?????
* fix: shorter line
* fix: cudacpu fixes
* fix: cudacpu fixes
* feat: real buffer
* feat: don't search when searching lmao
* fix: can't use contiguous things
* fix: no more 100GB arrays
* fix: revert
* fix: skip 7 and 10
* feat: working ish beam
* feat: minimize changes
* feat: seed 0 stable diffusion example changed
* fix: different on ci
* fix: no beam
* feat: make threefry optional
* fix: check value
* fix: unused import
* feat: threefry default
* fix: 5d
* feat: allow non upcast div
* fix: 5d better
* fix: 5d better
* fix: save all dtype
* feat: proper error
* feat: lazyop key
* fix: check float
* feat: try removing this realize now
* feat: disable threefry for uops hip tensor cores
* feat: don't need that
* feat: only check upcast
* fix: disable threefry for some metal tests
* feat: disable for metal tensor uops as well
* feat: disable for most uops
* fix: disable threefry for new uops tests
* feat: multitensor
* fix: typing
* feat: threefry default off
* feat: skip threefry half rand
* feat: restore old
* fix: bad git
* clean: ruff
* feat: bfloat16 fix
* fix: :|
* feat: restore old
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* feat: initial xor
* feat: initial threefly
* feat: remove custom random
* fix: really need to install precommit
* feat: lmao forgot that this is rotate not a shift
* clean: put that there
* feat: numpy xor
* feat: quick test for xor
* feat: llvm xor
* feat: slightly working xor in torch
* feat: rand works in jit
* clean: save a line
* feat: match jax
* feat: maybe test against jax
* feat: requires_grad
* fix: fix test_symbolic_ops
* feat: lower alpha
* feat: just pad
* fix: maybe fix training tests?
* fix: fix some llvm stuff
* feat: cursed realize on the way out
* feat: testing jax
* fix: why is the jax install process not simple
* fix: maybe passing test
* fix: symbolic workarounds
* clean: still need that precommit
* fix: aaaa
* fix: more test fixes
* fix: quick fix for wgsl
* feat: need to set requires_grad on the final tensor
* feat: one more tensor
* feat: don't take forever
* feat: seeing y ci is brok
* feat: can't allocate 64GiB lmao
* fix: fix this
* feat: hope this doesn't break smth before i go to bed
* feat: don't destroy ram
* feat: int
* feat: remove jax
* feat: properish workaround?
* feat: skip slow webgpu tests
* feat: no longer fails
* feat: use dtypes
* feat: real number
* fix: torch
* fix: don't test against reference for torch
* feat: to device
* feat: fix advanced indexing
* feat: correct casting
* feat: even rng_counter
* feat: match master
* feat: this was actually bad
* fix: maybe?
* feat: store
* feat: remove realizes
* feat: somehow this is important
* feat: somehow this is also important
* feat: save a line
* fix: don't need that anymore
* feat: restore this
* fix: linter
* feat: remove realizes
* fix: realized is in base now
* fix: add back cast
* fix: bump deadline
* fix: bump deadline
* fix: bump deadline
* fix: bump deadline
* fix: bump deadline
* fix: :(
* fix: :(
* fix: not being dumb
* feat: try changing less tests
* feat: shouldn't have to change that
* feat: contiguous bumps it by one
* fix: hmm
* fix: numpy memory moment
* fix: cl_khr_fp16
* fix: torch has different tensor count
* fix: missing contiguous
* hmm: hmm
* fix: some fixes
* fix: typing
* feat: dont do that
* feat: typing fixes
* feat: why is this realize required?
* feat: ngl kinda odd typing
* feat: oh
* feat: remove realizes
* feat: why is this realize required?
* fix: hacky patch for cudacpu
* fix: without this realize pytest crashes?????
* fix: shorter line
* fix: cudacpu fixes
* fix: cudacpu fixes
* feat: real buffer
* feat: don't search when searching lmao
* fix: can't use contiguous things
* fix: no more 100GB arrays
* fix: revert
* fix: skip 7 and 10
* feat: working ish beam
* feat: minimize changes
* feat: seed 0 stable diffusion example changed
* fix: different on ci
* fix: no beam
* feat: make threefry optional
* fix: check value
* fix: unused import
* feat: threefry default
* fix: 5d
* feat: allow non upcast div
* fix: 5d better
* fix: 5d better
* fix: save all dtype
* feat: proper error
* feat: lazyop key
* fix: check float
* feat: try removing this realize now
* feat: disable threefry for uops hip tensor cores
* feat: don't need that
* feat: only check upcast
* fix: disable threefry for some metal tests
* feat: disable for metal tensor uops as well
* feat: disable for most uops
* fix: disable threefry for new uops tests
* feat: multitensor
* fix: typing
* feat: threefry default off
* feat: skip threefry half rand
* feat: restore old
* fix: bad git
* clean: ruff
* feat: bfloat16 fix
* fix: :|
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* where fold try 2
* assign fold
* test_where_fold works
* add gated store support to ops_python
---------
Co-authored-by: nimlgen <138685161+nimlgen@users.noreply.github.com>
* It works?
* Clamp correctly
* Refactor
* Make code better
* Undo some stuff
* First step to trying to make floats work
* Floats work in Python op but not metal because int div is different
Python integerdivision was implemented as // which rounds towards
negative infinity, but C integer division rounds towards 0 so there
is an off-by-1 division error
* arange does cumsum with ints and then multiplies by step
This is so loop optimization can remain int only
* Undo a lot of symbolic changes
* Final check
* Cleanup
* There can be multiple phis
* Fix multiple phi op removal
* const sets dtype correctly
* Fix bugs
* Fix a couple bugs and add loop vars to resolve
* missed one
* Don't trim too many ops
* Fix symbolic test
* Use ones instead of full
* Delete test
* Lint passes
* max node error
* Small updates to loop logic
* Remove unnecessary changes
* We are getting somewhere
* Simple case
* Fix
* rm, prn
* Better
* If NumNode doesn't work then continue
* clamp is needed for arange(256)
* Move everything into the optim fn
* Replace correctly
* Order optimizations better
* Delete
* mypy
* Test for simplification
* Rename
* Fix test
* update test description
* Undo more
* Cleanup
* No replaced_ops map
* Fix lint
* AssertionError
* back again
* Reinstate assertion
* Return true and make diff not as big
* Bigger range for test
* Change cumsum impl
* fix bug
* make big cumsum work
* lint
* Undo cumsum 2-stage removal
* No while helper
* optional min/max clamping
* floats work
* rm giant arange test
* fix python cast None
* Check phi parents
* one phi allowed per where
* Fix one phi per where
* Rework iteration
* Delete assertions
* convert to int
* Try mul -1 instead of neg for hip..?
* Remove one phi per where requirements
* one accum only
* Lint
* should simplify a loop at a time
* Don't get rid of loop explcitly
* Need to iterate backwards
* lint
* unary neg
* Make optim work for onnx and sum_pad_collapse
* Better message
* filter alu ops correctly
* Fix the limiter
* lint and simplify
* Add it back
* off by one error
* test wheres and phis
* test max ops and non-if stuff
* <=
* cast_scalar
* Oops
* Change test
* Pass loop uops instead of a modified map
* Cut param transfer between linearizer and uops
* Fix issues
* Fix lint
* fix efficientnet python 3.8 invalid syntax
* distinct vars in seen_vars
* accurate var names
---------
Co-authored-by: Patrick Tsai <patosai@users.noreply.github.com>
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
be more specific about invalid kernel opt, used that in test_linearizer_failures.
make BEAM kernel search work even with assertion disabled.
`BEAM=2 python3 -O examples/llama.py --temperature=0 --count=10 --prompt="Hello." --timing`
* search: add tensor core to beam search space
* kernel: refactor apply_tensor_core into apply_opt and hand_coded
* kernel: revert removal of apply_tensor_cores
also revert BEAM search parameter changes
* simplest one
* but i can trust this will be cached correctly
* wait that was wrong too
* cleanup
* test_reduce_upcast for single reduce case
* a late accumulator always outputs to gds
lint
* support same uidx in multiple shape positions
* rename var
* update comment
* add contiguous index check to global_store too
* update comment
* small change
* is this better?
* smh
* smaller change?
* get rid of more changes
* get rid of more changes
* is this even making anything better
* comment
* fix test
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* remove float cast
* cast scalars to the correct value in creation time
* cast scalar in the correct place
* wrong, use y_dtype
* make consts have a unique cache key
* add cast_scalar back
* test_load_cache_const_bufs
* add bool dtype
* test_const_dtype
* fix linters
Fully UNROLLing the first_reduce should not change the number of
local_dims.
Fully UNROLLing a GROUP dim should reduce the number of
group_for_reduces by one.
Also changed group_for_reduces to be a count as the axis number
isn't used anywhere (they are always the first reduce dims).
* ops_python: add HIP tensor core mock and refactor METAL
* Add tests to CI
* add DEBUG=2 to full tests
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* start uop emu
* tiny_add passes
* more ops
* emulate the whole warp
* test_gemm passes
* metal gemm test pass
* works on big gemm
* works on big gemm
* more tests pass
* touch ups
* fix mypy
* cleanups
* exp2 mypy
* arch is where it belongs
* actually emulate tensor cores
* fix test
* new style
* PoC faster wino compile by catting consts across data expand dim
* fix fusions
* faster + golf it
* noqa 501
* implicit broadcast
* Revert "implicit broadcast"
This reverts commit 5915a9083d045ec1e6be84dcb492333325d48666.
* shorter
* shorter
* oops
* 216 upcasts is probably fine
* wino kernel count test
* test winograd number of sts
* specify device for apply_matrix mat elements
* extra/gemm: add a simple_conv.py along with correctness check
The goal is to easily test tensor core triggering situations
* test: add tests for acc_dtype handling and fixed typing
* wmma: enable METAL half tensor cores and clean up cstyle
* revert simple_matmul rand changes and break line in tensor
* added metal fp16->fp32 tensor core
we previously only upcast uint and int, and half was using half for acc.
change to acc in float for precision. but cast the result back to half to match torch/jax output dtype
