* add naive optimizer for 3DPlugin/refactor gpt2 shardformer test
* merge tests of PP/DP/TP combinations into one test file
* fix bug when sync grad for dp in HybridPlugin
* update supported precisions for 3DPlugin/fix bug when shifting tp_degree
* improve the passing of lazy_init
* modify lazy_init/use sync_shared_params
* [bf16] add bf16 support for fused adam (#3844)
* [bf16] fused adam kernel support bf16
* [test] update fused adam kernel test
* [test] update fused adam test
* [bf16] cpu adam and hybrid adam optimizers support bf16 (#3860)
* [bf16] implement mixed precision mixin and add bf16 support for low level zero (#3869)
* [bf16] add mixed precision mixin
* [bf16] low level zero optim support bf16
* [text] update low level zero test
* [text] fix low level zero grad acc test
* [bf16] add bf16 support for gemini (#3872)
* [bf16] gemini support bf16
* [test] update gemini bf16 test
* [doc] update gemini docstring
* [bf16] add bf16 support for plugins (#3877)
* [bf16] add bf16 support for legacy zero (#3879)
* [zero] init context support bf16
* [zero] legacy zero support bf16
* [test] add zero bf16 test
* [doc] add bf16 related docstring for legacy zero
* 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>
* 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>
Baizhou Zhang