A utility package to scaffold PyTorch's DDP
Project description
DDPW
The Distributed Data Parallel wrapper (DDPW) is created as a utility package to encapsulate the scaffolding for PyTorch's Distributed Data Parallel.
This code is written in Python 3.8. The DDPW documentation contains details on how to use this package.
Overview
Installation
conda install -c tvsujal ddpw # with conda
pip install ddpw # with pip from PyPI
Usage
from ddpw import DDPWrapper, Platform
job = DDPWrapper(platform=Platform.GPU, nprocs=4, ...) # train on 4 GPUs
job.start(epoch=30) # start training
job.resume(ckpt=20, epochs=60) # resume training from 20th epoch
e = job.evaluate(ckpt=50) # evaluate the model saved at 50th epoch
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