* add dropout layer, add dropout test
* modify seed manager as context manager
* add a copy of col_nn.layer
* add dist_crossentropy loss; separate module test
* polish the code
* fix dist crossentropy loss
* init shardformer code structure
* add implement of sharder (inject and replace)
* add implement of replace layer to colossal layer
* separate different layer policy, add some notion
* implement 1d and 2d slicer, can tell col or row
* fix bug when slicing and inject model
* fix some bug; add inference test example
* add share weight and train example
* add train
* add docstring and readme
* add docstring for other files
* pre-commit
* add dropout layer, add dropout test
* modify seed manager as context manager
* add a copy of col_nn.layer
* add dist_crossentropy loss; separate module test
* polish the code
* fix dist crossentropy loss
* init shardformer code structure
* add implement of sharder (inject and replace)
* add implement of replace layer to colossal layer
* separate different layer policy, add some notion
* implement 1d and 2d slicer, can tell col or row
* fix bug when slicing and inject model
* fix some bug; add inference test example
* add share weight and train example
* add train
* add docstring and readme
* add docstring for other files
* pre-commit
* Fixed several spelling errors under colossalai
* Fix the spelling error in colossalai and docs directory
* Cautious Changed the spelling error under the example folder
* Update runtime_preparation_pass.py
revert autograft to autograd
* Update search_chunk.py
utile to until
* Update check_installation.py
change misteach to mismatch in line 91
* Update 1D_tensor_parallel.md
revert to perceptron
* Update 2D_tensor_parallel.md
revert to perceptron in line 73
* Update 2p5D_tensor_parallel.md
revert to perceptron in line 71
* Update 3D_tensor_parallel.md
revert to perceptron in line 80
* Update README.md
revert to resnet in line 42
* Update reorder_graph.py
revert to indice in line 7
* Update p2p.py
revert to megatron in line 94
* Update initialize.py
revert to torchrun in line 198
* Update routers.py
change to detailed in line 63
* Update routers.py
change to detailed in line 146
* Update README.md
revert random number in line 402
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
* 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>
Hongxin Liu