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ColossalAI/examples/language/gpt/experiments/pipeline_parallel
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Hongxin Liu b5f9e37c70
[legacy] clean up legacy code (#4743) 
* [legacy] remove outdated codes of pipeline (#4692)

* [legacy] remove cli of benchmark and update optim (#4690)

* [legacy] remove cli of benchmark and update optim

* [doc] fix cli doc test

* [legacy] fix engine clip grad norm

* [legacy] remove outdated colo tensor (#4694)

* [legacy] remove outdated colo tensor

* [test] fix test import

* [legacy] move outdated zero to legacy (#4696)

* [legacy] clean up utils (#4700)

* [legacy] clean up utils

* [example] update examples

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2023-09-18 16:31:06 +08:00
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model_zoo.py Move GPT PP Example 2023-01-06 14:48:58 +08:00
README.md [doc] Fix typo under colossalai and doc(#3618) 2023-04-26 11:38:43 +08:00
requirements.txt [example] fix requirements (#2488) 2023-01-17 13:07:25 +08:00
run.sh Move GPT PP Example 2023-01-06 14:48:58 +08:00
train_gpt_pp.py [legacy] clean up legacy code (#4743) 2023-09-18 16:31:06 +08:00

README.md

Pipeline Parallelism Demo with GPT2

Requirements

Before you can launch training, you need to install the following requirements.

Install PyTorch

#conda
conda install pytorch==1.12.0 torchvision==0.13.0 torchaudio==0.12.0 cudatoolkit=11.3 -c pytorch
#pip
pip install torch==1.12.0+cu113 torchvision==0.13.0+cu113 torchaudio==0.12.0 --extra-index-url https://download.pytorch.org/whl/cu113

Install Colossal-AI v0.2.0 From Official Website

pip install colossalai==0.2.0+torch1.12cu11.3 -f https://release.colossalai.org

Install transformers

pip install transformers

Dataset

For simplicity, the input data is randomly generated here.

Training

#Run the Pipeline Parallel on GPT with default setting and a dummy dataset.
#You can change the GPU number or microbatch number in the run.sh .
bash run.sh