pytorch-template
This repository is my PyTorch project template (for Kaggle and research). Currently, this repository supports:
- some loss functions for semantic segmentation (src/losses.py)
- mean IoU cuda implementation (src/metrics.py)
- basic UNet implementation (src/models.py)
- learning rate scheduler (src/lr_scheduler.py)
- useful debugging module (src/debug.py)
Enviroments
This repository supports PyTorch >= 1.0. You can setup the enviroment using docker/Dockerfile (Ubuntu 16.04, cuda 9.2).
Run Experiments
Set working directory to "experiments" and run below commands,
# run training and evaluation (with saving checkpoints)
python exp0.py job --devices 0,1
# Run grid-search for better hyperparameter set.
# Parameter space can be set in "exp0.py".
# In below setting, each trial is conducted on a single gpu device
# and thus whole tuning processes are launched on multiple gpu devices in parallel.
python exp0.py tuning --devices 0,1 --n-gpu 1 --mode 'grid'