Commit Graph

96 Commits (e619a651fb27dc9db9ca0b97a10e00b3516243b0)

Author SHA1 Message Date
Jiarui Fang 23ba3fc450
[zero] refactory ShardedOptimV2 init method (#416) 2022-03-15 10:45:55 +08:00
Frank Lee e79ea44247
[fp16] refactored fp16 optimizer (#392) 2022-03-15 10:05:38 +08:00
Jiarui Fang 21dc54e019
[zero] memtracer to record cuda memory usage of model data and overall system (#395) 2022-03-14 22:05:30 +08:00
Jiarui Fang 370f567e7d
[zero] new interface for ShardedOptimv2 (#406) 2022-03-14 20:48:41 +08:00
ver217 63469c0f91 polish code 2022-03-14 15:48:55 +08:00
ver217 88804aee49 add bucket tensor shard strategy 2022-03-14 14:48:32 +08:00
HELSON 7c079d9c33
[hotfix] fixed bugs in ShardStrategy and PcieProfiler (#394) 2022-03-11 18:12:46 +08:00
Jiarui Fang 3af13a2c3e [zero] polish ShardedOptimV2 unittest (#385)
* place params on cpu after zero init context

* polish code

* bucketzed cpu gpu tensor transter

* find a bug in sharded optim unittest

* add offload unittest for ShardedOptimV2.

* polish code and make it more robust
2022-03-11 15:50:28 +08:00
Jiarui Fang 272ebfb57d [bug] shard param during initializing the ShardedModelV2 (#381) 2022-03-11 15:50:28 +08:00
Jiarui Fang b5f43acee3 [zero] find miss code (#378) 2022-03-11 15:50:28 +08:00
Jiarui Fang 6b6002962a [zero] zero init context collect numel of model (#375) 2022-03-11 15:50:28 +08:00
jiaruifang d9217e1960 Revert "[zero] bucketized tensor cpu gpu copy (#368)"
This reverts commit bef05489b6.
2022-03-11 15:50:28 +08:00
Jiarui Fang 00670c870e [zero] bucketized tensor cpu gpu copy (#368) 2022-03-11 15:50:28 +08:00
Jiarui Fang 44e4891f57 [zero] able to place params on cpu after zero init context (#365)
* place params on cpu after zero init context

* polish code
2022-03-11 15:50:28 +08:00
ver217 253e54d98a fix grad shape 2022-03-11 15:50:28 +08:00
Jiarui Fang ea2872073f [zero] global model data memory tracer (#360) 2022-03-11 15:50:28 +08:00
Jiarui Fang cb34cd384d [test] polish zero related unitest (#351) 2022-03-11 15:50:28 +08:00
ver217 d0ae0f2215 [zero] update sharded optim v2 (#334) 2022-03-11 15:50:28 +08:00
jiaruifang 5663616921 polish code 2022-03-11 15:50:28 +08:00
jiaruifang 7977422aeb add bert for unitest and sharded model is not able to pass the bert case 2022-03-11 15:50:28 +08:00
ver217 1388671699 [zero] Update sharded model v2 using sharded param v2 (#323) 2022-03-11 15:50:28 +08:00
Jiarui Fang 11bddb6e55 [zero] update zero context init with the updated test utils (#327) 2022-03-11 15:50:28 +08:00
Jiarui Fang de0468c7a8 [zero] zero init context (#321)
* add zero init context

* add more flags for zero init context
fix bug of repeated converting param to ShardedParamV2

* polish code
2022-03-11 15:50:28 +08:00
LuGY a3269de5c9 [zero] cpu adam kernel (#288)
* Added CPU Adam

* finished the cpu adam

* updated the license

* delete useless parameters, removed resnet

* modified the method off cpu adam unittest

* deleted some useless codes

* removed useless codes

Co-authored-by: ver217 <lhx0217@gmail.com>
Co-authored-by: Frank Lee <somerlee.9@gmail.com>
Co-authored-by: jiaruifang <fangjiarui123@gmail.com>
2022-03-11 15:50:28 +08:00
Jiarui Fang 90d3aef62c [zero] yet an improved sharded param (#311) 2022-03-11 15:50:28 +08:00
Jiarui Fang c9e7d9582d [zero] polish shard strategy (#310)
* init shard param from shape tuple

* add more unitest for shard param

* add set_payload method for ShardedParam

* [zero] add shareded tensor class

* polish code

* add shard stratgy

* move shard and gather logic to shard strategy from shard tensor.

* polish code
2022-03-11 15:50:28 +08:00
ver217 3092317b80 polish code 2022-03-11 15:50:28 +08:00
ver217 36f9a74ab2 fix sharded param hook and unit test 2022-03-11 15:50:28 +08:00
ver217 001ca624dd impl shard optim v2 and add unit test 2022-03-11 15:50:28 +08:00
Jiarui Fang 74f77e314b [zero] a shard strategy in granularity of tensor (#307) 2022-03-11 15:50:28 +08:00
Jiarui Fang 80364c7686 [zero] sharded tensor (#305)
* init shard param from shape tuple

* add more unitest for shard param

* add set_payload method for ShardedParam

* [zero] add shareded tensor class

* polish code
2022-03-11 15:50:28 +08:00
ver217 b105371ace rename shared adam to sharded optim v2 2022-03-11 15:50:28 +08:00
ver217 70814dc22f fix master params dtype 2022-03-11 15:50:28 +08:00
ver217 795210dd99 add fp32 master params in sharded adam 2022-03-11 15:50:28 +08:00
ver217 a109225bc2 add sharded adam 2022-03-11 15:50:28 +08:00
Jiarui Fang e17e92c54d Polish sharded parameter (#297)
* init shard param from shape tuple

* add more unitest for shard param

* add more unittests to shareded param
2022-03-11 15:50:28 +08:00
ver217 7aef75ca42 [zero] add sharded grad and refactor grad hooks for ShardedModel (#287) 2022-03-11 15:50:28 +08:00
Frank Lee 9afb5c8b2d fixed typo in ShardParam (#294) 2022-03-11 15:50:28 +08:00
Frank Lee e17e54e32a added buffer sync to naive amp model wrapper (#291) 2022-03-11 15:50:28 +08:00
Jiarui Fang 5a560a060a Feature/zero (#279)
* add zero1 (#209)

* add zero1

* add test zero1

* update zero stage 1 develop (#212)

* Implement naive zero3 (#240)

* naive zero3 works well

* add zero3 param manager

* add TODOs in comments

* add gather full param ctx

* fix sub module streams

* add offload

* fix bugs of hook and add unit tests

* fix bugs of hook and add unit tests (#252)

* add gather full param ctx

* fix sub module streams

* add offload

* fix bugs of hook and add unit tests

* polish code and add state dict hook

* fix bug

* update unit test

* refactor reconstructed zero code

* clip_grad support zero3 and add unit test

* add unit test for Zero3ParameterManager

* [WIP] initialize the shard param class

* [WIP] Yet another sharded model implementation (#274)

* [WIP] initialize the shard param class

* [WIP] Yes another implementation of shardModel. Using a better hook method.

* torch.concat -> torch.cat

* fix test_zero_level_1.py::test_zero_level_1 unitest

* remove deepspeed implementation and refactor for the reconstructed zero module

* polish zero dp unittests

Co-authored-by: ver217 <lhx0217@gmail.com>
Co-authored-by: Frank Lee <somerlee.9@gmail.com>
2022-03-11 15:50:28 +08:00
HELSON 0f8c7f9804
Fixed docstring in colossalai (#171) 2022-01-21 10:44:30 +08:00
ver217 9ef05ed1fc
try import deepspeed when using zero (#130) 2022-01-07 17:24:57 +08:00
Frank Lee 91c327cb44
fixed zero level 3 dtype bug (#76) 2021-12-20 17:00:53 +08:00
Frank Lee 35813ed3c4
update examples and sphnix docs for the new api (#63) 2021-12-13 22:07:01 +08:00
ver217 7d3711058f
fix zero3 fp16 and add zero3 model context (#62) 2021-12-10 17:48:50 +08:00
Frank Lee da01c234e1
Develop/experiments (#59)
* Add gradient accumulation, fix lr scheduler

* fix FP16 optimizer and adapted torch amp with tensor parallel (#18)

* fixed bugs in compatibility between torch amp and tensor parallel and performed some minor fixes

* fixed trainer

* Revert "fixed trainer"

This reverts commit 2e0b0b7699.

* improved consistency between trainer, engine and schedule (#23)

Co-authored-by: 1SAA <c2h214748@gmail.com>

* Split conv2d, class token, positional embedding in 2d, Fix random number in ddp
Fix convergence in cifar10, Imagenet1000

* Integrate 1d tensor parallel in Colossal-AI (#39)

* fixed 1D and 2D convergence (#38)

* optimized 2D operations

* fixed 1D ViT convergence problem

* Feature/ddp (#49)

* remove redundancy func in setup (#19) (#20)

* use env to control the language of doc (#24) (#25)

* Support TP-compatible Torch AMP and Update trainer API (#27)

* Add gradient accumulation, fix lr scheduler

* fix FP16 optimizer and adapted torch amp with tensor parallel (#18)

* fixed bugs in compatibility between torch amp and tensor parallel and performed some minor fixes

* fixed trainer

* Revert "fixed trainer"

This reverts commit 2e0b0b7699.

* improved consistency between trainer, engine and schedule (#23)

Co-authored-by: 1SAA <c2h214748@gmail.com>

Co-authored-by: 1SAA <c2h214748@gmail.com>
Co-authored-by: ver217 <lhx0217@gmail.com>

* add an example of ViT-B/16 and remove w_norm clipping in LAMB (#29)

* add explanation for ViT example (#35) (#36)

* support torch ddp

* fix loss accumulation

* add log for ddp

* change seed

* modify timing hook

Co-authored-by: Frank Lee <somerlee.9@gmail.com>
Co-authored-by: 1SAA <c2h214748@gmail.com>
Co-authored-by: binmakeswell <binmakeswell@gmail.com>

* Feature/pipeline (#40)

* remove redundancy func in setup (#19) (#20)

* use env to control the language of doc (#24) (#25)

* Support TP-compatible Torch AMP and Update trainer API (#27)

* Add gradient accumulation, fix lr scheduler

* fix FP16 optimizer and adapted torch amp with tensor parallel (#18)

* fixed bugs in compatibility between torch amp and tensor parallel and performed some minor fixes

* fixed trainer

* Revert "fixed trainer"

This reverts commit 2e0b0b7699.

* improved consistency between trainer, engine and schedule (#23)

Co-authored-by: 1SAA <c2h214748@gmail.com>

Co-authored-by: 1SAA <c2h214748@gmail.com>
Co-authored-by: ver217 <lhx0217@gmail.com>

* add an example of ViT-B/16 and remove w_norm clipping in LAMB (#29)

* add explanation for ViT example (#35) (#36)

* optimize communication of pipeline parallel

* fix grad clip for pipeline

Co-authored-by: Frank Lee <somerlee.9@gmail.com>
Co-authored-by: 1SAA <c2h214748@gmail.com>
Co-authored-by: binmakeswell <binmakeswell@gmail.com>

* optimized 3d layer to fix slow computation ; tested imagenet performance with 3d; reworked lr_scheduler config definition; fixed launch args; fixed some printing issues; simplified apis of 3d layers (#51)

* Update 2.5d layer code to get a similar accuracy on imagenet-1k dataset

* update api for better usability (#58)

update api for better usability

Co-authored-by: 1SAA <c2h214748@gmail.com>
Co-authored-by: ver217 <lhx0217@gmail.com>
Co-authored-by: puck_WCR <46049915+WANG-CR@users.noreply.github.com>
Co-authored-by: binmakeswell <binmakeswell@gmail.com>
Co-authored-by: アマデウス <kurisusnowdeng@users.noreply.github.com>
Co-authored-by: BoxiangW <45734921+BoxiangW@users.noreply.github.com>
2021-12-09 15:08:29 +08:00