Commit Graph

826 Commits (6ccecc0c6984b2fe03d3b1718a79fa170d53a430)

Author SHA1 Message Date
Jiarui Fang 0fcfb1e00d
[test] make zero engine test really work (#447) 2022-03-17 17:24:25 +08:00
Frank Lee bb2790cf0b
optimize engine and trainer test (#448) 2022-03-17 15:44:17 +08:00
Frank Lee b72b8445c6
optimized context test time consumption (#446) 2022-03-17 14:40:52 +08:00
Jiarui Fang 496cbb0760
[hotfix] fix initialize bug with zero (#442) 2022-03-17 13:16:22 +08:00
Jiarui Fang 17b8274f8a
[unitest] polish zero config in unittest (#438) 2022-03-17 10:20:53 +08:00
Jiarui Fang 640a6cd304
[refactory] refactory the initialize method for new zero design (#431) 2022-03-16 19:29:37 +08:00
ver217 fce9432f08 sync before creating empty grad 2022-03-16 14:24:09 +08:00
Jiarui Fang f9c762df85
[test] merge zero optim tests (#428) 2022-03-16 12:22:45 +08:00
Jiarui Fang 5d7dc3525b
[hotfix] run cpu adam unittest in pytest (#424) 2022-03-16 10:39:55 +08:00
Jiarui Fang adebb3e041
[zero] cuda margin space for OS (#418) 2022-03-15 12:02:19 +08:00
Jiarui Fang 56bb412e72
[polish] use GLOBAL_MODEL_DATA_TRACER (#417) 2022-03-15 11:29:46 +08:00
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 a37bf1bc42
[hotfix] rm test_tensor_detector.py (#413) 2022-03-14 21:39:48 +08:00
Jiarui Fang 370f567e7d
[zero] new interface for ShardedOptimv2 (#406) 2022-03-14 20:48:41 +08:00
LuGY a9c27be42e
Added tensor detector (#393)
* Added tensor detector

* Added the - states

* Allowed change include_cpu when detect()
2022-03-14 18:01:46 +08:00
ver217 54fd37f0e0 polish unit test 2022-03-14 15:06:02 +08:00
Frank Lee 1e4bf85cdb fixed bug in activation checkpointing test (#387) 2022-03-11 15:50:28 +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
Frank Lee 526a318032 [unit test] Refactored test cases with component func (#339)
* refactored test with component func

* fixed bug
2022-03-11 15:50:28 +08:00
LuGY de46450461 Added activation offload (#331)
* Added activation offload

* Fixed the import bug, used the pytest
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
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 532ae79cb0 add test sharded optim with cpu adam (#347) 2022-03-11 15:50:28 +08:00
HELSON 425bb0df3f Added Profiler Context to manage all profilers (#340) 2022-03-11 15:50:28 +08:00
ver217 d0ae0f2215 [zero] update sharded optim v2 (#334) 2022-03-11 15:50:28 +08:00
ver217 2b8cddd40e skip bert in test engine 2022-03-11 15:50:28 +08:00
ver217 f5f0ad266e fix bert unit test 2022-03-11 15:50:28 +08:00
jiaruifang d271f2596b polish engine unitest 2022-03-11 15:50:28 +08:00
jiaruifang 354c0f9047 polish code 2022-03-11 15:50:28 +08:00
jiaruifang 4d94cd513e adapting bert unitest interface 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
jiaruifang 799d105bb4 using pytest parametrize 2022-03-11 15:50:28 +08:00
jiaruifang dec24561cf show pytest parameterize 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
Frank Lee 6268446b81 [test] refactored testing components (#324) 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
1SAA 73bff11288 Added profiler communication operations
Fixed bug for learning rate scheduler
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 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
Jie Zhu d344689274 [profiler] primary memory tracer 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 27155b8513 added unit test for sharded optimizer (#293)
* added unit test for sharded optimizer

* refactor for elegance
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 8d653af408 add a common util for hooks registered on parameter. (#292) 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
1SAA 82023779bb Added TPExpert for special situation 2022-03-11 15:50:28 +08:00
1SAA 219df6e685 Optimized MoE layer and fixed some bugs;
Decreased moe tests;

Added FFNExperts and ViTMoE model
2022-03-11 15:50:28 +08:00
zbian 3dba070580 fixed padding index issue for vocab parallel embedding layers; updated 3D linear to be compatible with examples in the tutorial 2022-03-11 15:50:28 +08:00
アマデウス 9ee197d0e9 moved env variables to global variables; (#215)
added branch context;
added vocab parallel layers;
moved split_batch from load_batch to tensor parallel embedding layers;
updated gpt model;
updated unit test cases;
fixed few collective communicator bugs
2022-02-15 11:31:13 +08:00
Jiarui Fang 569357fea0
add pytorch hooks (#179)
* add pytorch hooks
fix #175

* remove licenses in src code

* add gpu memory tracer

* replacing print with logger in ophooks.
2022-01-25 22:20:54 +08:00
Frank Lee e2089c5c15
adapted for sequence parallel (#163) 2022-01-20 13:44:51 +08:00
ver217 7bf1e98b97
pipeline last stage supports multi output (#151) 2022-01-17 15:57:47 +08:00
ver217 96780e6ee4
Optimize pipeline schedule (#94)
* add pipeline shared module wrapper and update load batch

* added model parallel process group for amp and clip grad (#86)

* added model parallel process group for amp and clip grad

* update amp and clip with model parallel process group

* remove pipeline_prev/next group (#88)

* micro batch offload

* optimize pipeline gpu memory usage

* pipeline can receive tensor shape (#93)

* optimize pipeline gpu memory usage

* fix grad accumulation step counter

* rename classes and functions

Co-authored-by: Frank Lee <somerlee.9@gmail.com>
2021-12-30 15:56:46 +08:00
アマデウス 01a80cd86d
Hotfix/Colossalai layers (#92)
* optimized 1d layer apis; reorganized nn.layer modules; fixed tests

* fixed 2.5d runtime issue

* reworked split batch, now called in trainer.schedule.load_batch

Co-authored-by: BoxiangW <45734921+BoxiangW@users.noreply.github.com>
2021-12-29 23:32:10 +08:00
アマデウス 0fedef4f3c
Layer integration (#83)
* integrated parallel layers for ease of building models

* integrated 2.5d layers

* cleaned codes and unit tests

* added log metric by step hook; updated imagenet benchmark; fixed some bugs

* reworked initialization; cleaned codes

Co-authored-by: BoxiangW <45734921+BoxiangW@users.noreply.github.com>
2021-12-27 15:04:32 +08:00
ver217 8f02a88db2
add interleaved pipeline, fix naive amp and update pipeline model initializer (#80) 2021-12-20 23:26:19 +08:00
Frank Lee 91c327cb44
fixed zero level 3 dtype bug (#76) 2021-12-20 17:00:53 +08:00
Frank Lee cd9c28e055
added CI for unit testing (#69) 2021-12-16 10:32:08 +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
Frank Lee 3defa32aee
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>
2021-11-18 19:45:06 +08:00
アマデウス 3245a69fc2
cleaned test scripts 2021-10-29 00:48:14 +08:00
zbian 404ecbdcc6 Migrated project 2021-10-28 18:21:23 +02:00