Commit Graph

626 Commits

Author SHA1 Message Date
chenyu cd801a15f3
scipy.signal.gaussian -> scipy.signal.windows.gaussian (#4205)
fixed unet3d model_eval, will add to CI after merging new dice loss
2024-04-17 19:15:37 -04:00
Elias Wahl 6eef8ee22a
Wikipedia download script for MLPerf BERT training (#4202)
* wikipedia download script

* add link

* checksum valueError

* ops
2024-04-17 16:34:57 -04:00
Francis Lam c91b7b1739
test: add fuzz_matmul and better debugging for simple_matmul (#4199)
also show unoptimized shape in verify_kernel
2024-04-16 23:40:31 -04:00
George Hotz 55ae73e951
Replicate llm.c in tinygrad (#4179)
* write llm.c and add a few new methods to tensor

* training works

* add jit

* tests for new functions

* test tolist

* simple fix for onnx test failures (#4186)

* write llm.c and add a few new methods to tensor

* training works

* add jit

* tests for new functions

* bump line count to 7500

* simplest fix

* safenumpy tolist for now

---------

Co-authored-by: George Hotz <geohot@gmail.com>
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>

---------

Co-authored-by: geohotstan <135171913+geohotstan@users.noreply.github.com>
2024-04-16 15:40:48 +04:00
George Hotz b7e281cf10
JitItem -> ExecItem (#4146)
* JitItem -> ExecItem

* execitem in realize

* cleaner

* JITRunner -> Runner
2024-04-11 08:24:57 -07:00
George Hotz e79a11b99c hotfix: revert llama change 2024-04-10 20:13:15 -07:00
George Hotz 2e6c39b0b2
Do less realizes (#4141)
* less realize

* corealize jit inputs

* prints

* print before we run
2024-04-10 19:50:50 -07:00
geohotstan fe88591890
update onnx to 1.16.0 (#4127)
* update

* pass tests and skip tests
2024-04-10 11:19:13 -04:00
Francis Lam 46850a0269
search: add a BEAM_COMPARE env to optionally not compare to hc/tc (#4107)
* search: add a BEAM_COMPARE env to optionally not compare to hc/tc

setting BEAM_COMPARE=0 will prevent additional memory allocation
needed to do the timing tests assuming the BEAM result is in
the diskcache.

* change to optionally use Buffer.allocate
2024-04-08 18:54:01 -04:00
chenyu f8dc82a8a7
use single tensor for llama kv chache (#4108)
similar to optimization in gpt2
2024-04-08 00:38:32 -04:00
chenyu 92c0675ccf
setitem initial support (#4093)
* wip setitem

it's an eager assign to output shapetracker view

* cleanups and tests

* more cleanups
2024-04-07 20:35:22 -04:00
geohotstan 183708b3fd
broadcast expand to match torch (#4085)
* initial version

* heh gimme grrrreen

* version 2

* clean ups

* some test confusion

* fix onnx

* rename to _broadcast_tensors

* improved errors and test

* fixed?

* some test fixup

* version 3 lol

* comments

* cleaner

* add failure test for expand to 0 test

* 1 more assertRaises test

* make err msg better

* also rewrite the expand onnx op? :s
2024-04-07 16:23:13 -04:00
George Hotz fffd9b05f5
mock mnist data for imagenet trainer (#4095)
* mock mnist data for imagenet

* move print and test

* needed to reshape
2024-04-06 08:08:40 -07:00
geohotstan dafa42e864
clean up (#4081)
Co-authored-by: chenyu <chenyu@fastmail.com>
2024-04-05 11:57:44 -04:00
nimlgen d6ba44bc1e
kfd free buffers (#4027)
* kfd free buffers

* unmap

* all test passes

* better pm4

* forgot these

* invalidate only range

* better cache

* forgot

* comments

* fixes
2024-04-01 15:50:58 -07:00
Francis Lam dcb58d3bed
extra/gemm/simple_matvec: add simple_matvec.py (#4021)
we can test with this or add it to CI for benchmarks
2024-03-31 16:38:52 -04:00
chenyu d3f27761b0
move const folding of ADD/SUB/MUL from tensor to lazy (#4020)
* move const folding of ADD/SUB/MUL from tensor to lazy

will do div and pow separately.

* fix onnx adding with None
2024-03-31 16:35:36 -04:00
George Hotz 2abb474d43
kfd driver wip (#3912)
* kfd driver wip

* cleanups

* kfd almost ready to ring doorbell

* ding dong?

* issues with signals

* something

* works

* ops kfd

* add amd_signal_t

* works...sometimes

* program runs

* _gpu_alloc cleanup

* cleanups

* work

* header + enable profiling (#3959)

* header + enable profiling

* just cleaner

* measure

* only local time domain

* remove old comments

* fix with master

* elf parsing (#3965)

* elf parsing

* fix kernels with private

* not used

* clean up

* clean up 2

* add flags

* kfd sdma (#3970)

* working sdma

* remove driver, shorter

* all commands we might need

* svm

* kfd remove hardcoded values (#4007)

* remove hardcoded values

* match above line

* 7k lines + revert hsa

* update that from origin

* fix sdma reg gen

* not the updated SDMA

* compiler_opts

* don't require kfd_ioctl

* get ioctls from python

* get ioctls from python

* remove build_sdma_command

* merge into 64-bit fields

* shorter

* fix property spelling and off by one

---------

Co-authored-by: nimlgen <138685161+nimlgen@users.noreply.github.com>
2024-03-30 15:08:12 -07:00
Francis Lam 04746022b1
extra/gemm/hip_matmul: fix to use new HSA devices and no headers (#3999)
* extra/gemm/hip_matmul: fix to use new HSA devices and no headers

* remove compile_hip import
2024-03-30 15:42:23 -04:00
chenyu c71627fee6
move GlobalCounter to helpers (#4002)
break circular import between ops and buffer
2024-03-30 00:30:30 -04:00
Akshit Talwar 0affbbf81c
update amx gemm (#3991) 2024-03-29 11:45:03 -04:00
George Hotz 9a6ac2a50a
create the buffer with the LazyBuffer (#3977)
* create the buffer with the LazyBuffer

* fixes

* hack underlying buffer when we change dtype

* we only care about allocated buffers

* asserts
2024-03-28 19:31:28 -07:00
chenyu b47f6cebb2
LinearizerOptions -> CompilerOptions (#3978) 2024-03-28 17:50:23 -04:00
David Hou 4b95350c41
fp16 resnet (without expand backwards sum in float, doesn't work) (#3816)
* fp16 resnet

* cast running mean and var back to default float

* extra cast

* check symbolic no overflow

* add linearizer failure

* loss scaler after grad contig

* oops

* i think this works

* don't loss scale fp32

* remove overflow test case

* remove symbolic bounds check

* loss scaler should be float

* temporarily disable padto cuz bug

shruggie

* make running stats in batchnorm float32?

* calculate lars stuff in fp32?

* oops

* remove most changes

* move loss scaler out of optimizer

* no more FP16 var

* oops

---------

Co-authored-by: chenyu <chenyu@fastmail.com>
2024-03-28 01:25:37 -04:00
Francis Lam 7c5729a3bd
wmma: refactor to remove wmma_func and create TC funcs as needed (#3945)
* wmma: refactor to remove wmma_func and create TC funcs as needed

* test_linearizer: disable bf16 CUDA during emulation testing

* cstyle: clean up creation of CUDA vec dtypes

* extra/gemm: add option to accumulate to bfloat16

* cleanups

* benchmark: add CUDA bfloat16 matmul

* more cleanups
2024-03-27 16:43:09 -04:00
George Hotz 68ca4d4276
split to schedule.py (#3949)
* split to schedule.py

* split
2024-03-26 21:02:46 -07:00
George Hotz 150ea2eb76
create engine folder and move code (#3948)
* retry

* older tf

* that
2024-03-26 20:38:03 -07:00
George Hotz 778d17fbd3
intel matmul (#3830)
* almost right

* intel xmx
2024-03-25 22:37:20 -07:00
wozeparrot 9a9cac58f9
add lars to nn (#3750)
* feat: add lars

* feat: don't remove this comment

* clean: smaller diff

* clean: shorter line

* feat: remove mlperf lars, switch resnet

* fix: fully remove mlperf lars

* clean: comment

* feat: contiguous

* feat: no weight decay on skip params

* feat: optimizergroup

* feat: classic momentum

* fix: pylint

* clean: move comment

* fix: correct algo

* feat: lrschedulergroup

* feat: skip list tests

* feat: :| forgot that params are a thing

* feat: remove skip_list params from main params

* feat: set moment

---------

Co-authored-by: chenyu <chenyu@fastmail.com>
2024-03-24 11:43:12 -04:00
George Hotz 46a3501cec
nv ioctl sniffer (#3892)
* nv ioctl sniffer

* unused import

* Update __init__.py

* that work

* that fix it
2024-03-23 00:29:30 -07:00
chenyu ee502c8055
fixup to_movement_ops and add back to CI (#3881) 2024-03-22 18:14:49 -04:00
Francis Lam 5587594a00
fuzz_linearizer: add --ast and --file params to read kernels (#3877)
also fix up ast_str_to_str to support the new tuple of LazyOps
2024-03-22 14:27:40 -04:00
Francis Lam a26090d404
search: change to use "spawn" and limit the number of tasks per child (#3862)
also clean up some examples to use __main__ and not initialize
resources outside of main
2024-03-21 21:23:36 -07:00
Francis Lam 6d5dec2fef
log optimized kernels and a script to compare with non-optimized ones (#3829)
* search: add BEAM_VERIFY option to validate search results

refactor fuzz_linearizer comparison to allow it to be used in for
BEAM_VERIFY in device.py

* search: fix to verify the beam_search result and not the fastest

* search: fix typing and clean up

* device: remove imports from test and add LOGKERN options

LOGKERN output can be used with test/external/verify_kernel.py
to validate correctness

* fix example in verify_kernel.py

* cleanup fixes

* fix to use f-strings
2024-03-20 19:22:08 -04:00
qazal 9452994201
add a better error message for resnet training (#3836)
* add a better error message

* assert

* use FileNotFoundError
2024-03-20 09:22:15 -07:00
chenyu 47b9cc2dfe
use float32 for rand buffer in test_beam_search and test in metal (#3831) 2024-03-19 23:22:58 -04:00
George Hotz 4c4d3cb3e3
restrict assignment to base (#3809)
* restrict assignment to base

* add some restrictions there

* more restrictions
2024-03-18 15:33:06 -07:00
chenyu 20681d5c4a
remove old dist multigpu (#3811) 2024-03-18 18:31:05 -04:00
wozeparrot a0ab755317
threefry again (#3785)
* 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>
2024-03-18 16:47:07 -04:00
chenyu 5ac1fa933f
apply the same fix_bf16 in llama and coder (#3789)
* apply the same fix_bf16 in llama and coder

did not realize the same logic was in llama too.
really fix #2775

* flag for native SUPPORT_BF16 cast
2024-03-17 21:25:24 -04:00
George Hotz 311cf2b7d3
Revert "threefry_2x32 (#2601)" (#3784)
This reverts commit db3de54bc4.
2024-03-17 10:27:20 -07:00
wozeparrot db3de54bc4
threefry_2x32 (#2601)
* 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>
2024-03-17 10:19:33 -07:00
George Hotz 53adcb34f5
remove hip backend (#3783)
* remove hip backend

* remove unused

* rhip

* more RHIP
2024-03-17 10:12:16 -07:00
qazal e3e89c244b
multioutput uoping infra (#3706)
* linearize multioutput

* add vars to copy
2024-03-15 21:56:59 -07:00
George Hotz 641f347232
simple LoadOps.ASSIGN (#3745)
* simple LoadOps.ASSIGN

* skip that test

* don't assign in onnx ops gemm

* track cache usage

* recreate the lazybuffer to avoid the cache

* fix contigs

* skip that test

* lol

* better letters
2024-03-14 20:44:34 -07:00
David Hou 199f7c4342
MLPerf Resnet (cleaned up) (#3573)
* this is a lot of stuff

TEST_TRAIN env for less data

don't diskcache get_train_files

debug message

no lr_scaler for fp32

comment, typo

type stuff

don't destructure proc

make batchnorm parameters float

make batchnorm parameters float

resnet18, checkpointing

hack up checkpointing to keep the names in there

oops

wandb_resume

lower lr

eval/ckpt use e+1

lars

report top_1_acc

some wandb stuff

split fw and bw steps to save memory

oops

save model when reach target

formatting

make sgd hparams consistent

just always write the cats tag...

pass X and Y into backward_step to trigger input replace

shuffle eval set to fix batchnorm eval

dataset is sorted by class, so the means and variances are all wrong

small cleanup

hack restore only one copy of each tensor

do bufs from lin after cache check (lru should handle it fine)

record epoch in wandb

more digits for topk in eval

more env vars

small cleanup

cleanup hack tricks

cleanup hack tricks

don't save ckpt for testeval

cleanup

diskcache train file glob

clean up a little

device_str

SCE into tensor

small

small

log_softmax out of resnet.py

oops

hack :(

comments

HeNormal, track gradient norm

oops

log SYNCBN to wandb

real truncnorm

less samples for truncated normal

custom init for Linear

log layer stats

small

Revert "small"

This reverts commit 988f4c1cf35ca4be6c31facafccdd1e177469f2f.

Revert "log layer stats"

This reverts commit 9d9822458524c514939adeee34b88356cd191cb0.

rename BNSYNC to SYNCBN to be consistent with cifar

optional TRACK_NORMS

fix label smoothing :/

lars skip list

only weight decay if not in skip list

comment

default 0 TRACK_NORMS

don't allocate beam scratch buffers if in cache

clean up data pipeline, unsplit train/test, put back a hack

remove print

run test_indexing on remu (#3404)

* emulated ops_hip infra

* add int4

* include test_indexing in remu

* Revert "Merge branch 'remu-dev-mac'"

This reverts commit 6870457e57dc5fa70169189fd33b24dbbee99c40, reversing
changes made to 3c4c8c9e16.

fix bad seeding

UnsyncBatchNorm2d but with synced trainable weights

label downsample batchnorm in Bottleneck

:/

:/

i mean... it runs... its hits the acc... its fast...

new unsyncbatchnorm for resnet

small fix

don't do assign buffer reuse for axis change

* remove changes

* remove changes

* move LARS out of tinygrad/

* rand_truncn rename

* whitespace

* stray whitespace

* no more gnorms

* delete some dataloading stuff

* remove comment

* clean up train script

* small comments

* move checkpointing stuff to mlperf helpers

* if WANDB

* small comments

* remove whitespace change

* new unsynced bn

* clean up prints / loop vars

* whitespace

* undo nn changes

* clean up loops

* rearrange getenvs

* cpu_count()

* PolynomialLR whitespace

* move he_normal out

* cap warmup in polylr

* rearrange wandb log

* realize both x and y in data_get

* use double quotes

* combine prints in ckpts resume

* take UBN from cifar

* running_var

* whitespace

* whitespace

* typo

* if instead of ternary for resnet downsample

* clean up dataloader cleanup a little?

* separate rng for shuffle

* clean up imports in model_train

* clean up imports

* don't realize copyin in data_get

* remove TESTEVAL (train dataloader didn't get freed every loop)

* adjust wandb_config entries a little

* clean up wandb config dict

* reduce lines

* whitespace

* shorter lines

* put shm unlink back, but it doesn't seem to do anything

* don't pass seed per task

* monkeypatch batchnorm

* the reseed was wrong

* add epoch number to desc

* don't unsyncedbatchnorm is syncbn=1

* put back downsample name

* eval every epoch

* Revert "the reseed was wrong"

This reverts commit 3440a07dff3f40e8a8d156ca3f1938558a59249f.

* cast lr in onecycle

* support fp16

* cut off kernel if expand after reduce

* test polynomial lr

* move polynomiallr to examples/mlperf

* working PolynomialDecayWithWarmup + tests.......

add lars_util.py, oops

* keep lars_util.py as intact as possible, simplify our interface

* no more half

* polylr and lars were merged

* undo search change

* override Linear init

* remove half stuff from model_train

* update scheduler init with new args

* don't divide by input mean

* mistake in resnet.py

* restore whitespace in resnet.py

* add test_data_parallel_resnet_train_step

* move initializers out of resnet.py

* unused imports

* log_softmax to model output in test to fix precision flakiness

* log_softmax to model output in test to fix precision flakiness

* oops, don't realize here

* is None

* realize initializations in order for determinism

* BENCHMARK flag for number of steps

* add resnet to bechmark.yml

* return instead of break

* missing return

* cpu_count, rearrange benchmark.yml

* unused variable

* disable tqdm if BENCHMARK

* getenv WARMUP_EPOCHS

* unlink disktensor shm file if exists

* terminate instead of join

* properly shut down queues

* use hip in benchmark for now

---------

Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
2024-03-14 00:53:41 -04:00
qazal aec4c4f01b
linearizer ast as a tuple of lazyops (#3689)
* multi store op linearizer

* currently we do only one output per kernel

* named opts
2024-03-11 15:39:04 -07:00
Francis Lam 3219a527d6
search: add a tool that beam searches one or more kernels (#3685) 2024-03-11 16:02:17 -04:00
Quentin Wach 89b8b5d549
Fix missing import. (#3666) 2024-03-09 14:55:23 -08:00
George Hotz ac02e7347d
ptx timing vs cuda timing (#3659) 2024-03-08 10:17:49 -08:00