exper 0.1.3

This is a python package for running deep learning experiments. Users can rapidly run their experiments by importing this module.

# exper

exper is a very lightweight Python package designed for personal use to speed up the execution of PyTorch-based deep learning experiments. This framework is specifically crafted to support Distributed Data Parallel (DDP) training, mix precision training and provides a convenient mechanism for saving experiment logs.

## Features:

• PyTorch Integration: Built on top of PyTorch, exper allows seamless integration with the PyTorch deep learning ecosystem.

• DDP Training Support: exper supports Distributed Data Parallel training, enabling efficient and scalable model training across multiple GPUs.

• Experiment Logging: Easily log and save experiment details, parameters, and results for better reproducibility and analysis.

• Based on TorchDrug: exper is derived from the open-source library [TorchDrug](https://github.com/DeepGraphLearning/torchdrug/tree/master) developed by MILA, providing a foundation for reliable and robust deep learning experiments.

## Installation: `bash pip install exper==0.1.2 `

## License exper is released under [Apache-2.0 License](https://github.com/DeepGraphLearning/torchdrug/blob/master/LICENSE).

## Contributing Feel free to contribute your codes to make this package easy to use.