Optimized 3D implementation #51
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…nce with 3d; reworked lr_scheduler config definition; fixed launch args; fixed some printing issues; simplified apis of 3d layers
FrankLeeeee
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Dec 9, 2021
…nce with 3d; reworked lr_scheduler config definition; fixed launch args; fixed some printing issues; simplified apis of 3d layers (#51)
FrankLeeeee
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Dec 9, 2021
* 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 2e0b0b7. * improved consistency between trainer, engine and schedule (#23) Co-authored-by: 1SAA <[email protected]> * 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 2e0b0b7. * improved consistency between trainer, engine and schedule (#23) Co-authored-by: 1SAA <[email protected]> Co-authored-by: 1SAA <[email protected]> Co-authored-by: ver217 <[email protected]> * 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 <[email protected]> Co-authored-by: 1SAA <[email protected]> Co-authored-by: binmakeswell <[email protected]> * 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 2e0b0b7. * improved consistency between trainer, engine and schedule (#23) Co-authored-by: 1SAA <[email protected]> Co-authored-by: 1SAA <[email protected]> Co-authored-by: ver217 <[email protected]> * 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 <[email protected]> Co-authored-by: 1SAA <[email protected]> Co-authored-by: binmakeswell <[email protected]> * 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 <[email protected]> Co-authored-by: ver217 <[email protected]> Co-authored-by: puck_WCR <[email protected]> Co-authored-by: binmakeswell <[email protected]> Co-authored-by: アマデウス <[email protected]> Co-authored-by: BoxiangW <[email protected]>
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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