https://github.com/kredde/pytorch-lightning-hydra-mlflow
PyTorch Lightning + Hydra + MLFlow - Deep learning template
https://github.com/kredde/pytorch-lightning-hydra-mlflow
config deep-learning hydra mlflow pytorch pytorch-lightning research template
Last synced: 3 months ago
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PyTorch Lightning + Hydra + MLFlow - Deep learning template
- Host: GitHub
- URL: https://github.com/kredde/pytorch-lightning-hydra-mlflow
- Owner: kredde
- License: mit
- Created: 2021-04-26T07:11:02.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-09-14T08:29:22.000Z (about 4 years ago)
- Last Synced: 2023-03-02T18:45:45.035Z (over 2 years ago)
- Topics: config, deep-learning, hydra, mlflow, pytorch, pytorch-lightning, research, template
- Language: Python
- Homepage:
- Size: 12.7 KB
- Stars: 20
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Pytorch Lightning Template using Hydra and MLFlow
## Quick start
1. Install dependencies `conda env create -f environment.yml -n envname`
2. Run an experiment using `python3 main.py +experiment=exp_name`
3. Check out the results of your runs using `mlflow ui`
4. Reload your experiment and execute evaluations by specifying the run id `exp_id: id` and running the evaluation pipeline `python3 evaluation.py +experiment=exp_name`
Train model with default configuration
```yaml
# default
python run.py
# train on CPU
python run.py trainer.gpus=0
# train on GPU
python run.py trainer.gpus=1
```
Train model with chosen experiment configuration from [configs/experiment/](configs/experiment/)
```yaml
python run.py +experiment=experiment_name
```
You can override any parameter from command line like this
```yaml
python run.py trainer.max_epochs=20 datamodule.batch_size=64
```
## Other Repositories
Inspirations
This template was inspired by:
[ashleve/lightning-hydra-template](https://github.com/ashleve/lightning-hydra-template),
[PyTorchLightning/deep-learninig-project-template](https://github.com/PyTorchLightning/deep-learning-project-template),
[drivendata/cookiecutter-data-science](https://github.com/drivendata/cookiecutter-data-science),
[tchaton/lightning-hydra-seed](https://github.com/tchaton/lightning-hydra-seed),
[Erlemar/pytorch_tempest](https://github.com/Erlemar/pytorch_tempest),
[lucmos/nn-template](https://github.com/lucmos/nn-template).