Perceptrain is a Python package that provides a simple interface to execute distributed machine learning training. It supports customization, gradient-based, gradient-free optimizations and various experiment tracking methods.
**For more detailed information, check out the documentation.
**For any questions or comments, feel free to start a discussion. **
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Training models made simple with Trainer and Train Configurations.
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Support for gradient based and gradient free optimization.
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Accelerator supported distributed training made simple across multi node/multi gpu setups.
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Extensive callbacks, along with support for mlflow and tensorboard tracking.
perceptrain is available on PyPI and can be installed using pip as follows:
pip install perceptrainThe default, pre-installed backend for perceptrain is PyQTorch, a differentiable state vector simulator. It is possible to install additional following extras:
mlflow: For experiment tracking.
To install individual extras, use the following syntax (IMPORTANT Make sure to use quotes):
pip install "perceptrain[mlflow]"To install all available extras, simply do:
pip install "perceptrain[all]"Before making a contribution, please review our code of conduct.
- Submitting Issues: To submit bug reports or feature requests, please use our issue tracker.
- Developing in perceptrain: To learn more about how to develop within
perceptrain, please refer to contributing guidelines.
We recommend to use the hatch environment manager to install perceptrain from source:
python -m pip install hatch
# get into a shell with all the dependencies
python -m hatch shell
# run a command within the virtual environment with all the dependencies
python -m hatch run python my_script.pyWARNING
hatch will not combine nicely with other environment managers such as Conda. If you still want to use Conda,
install it from source using pip:
# within the Conda environment
python -m pip install -e .Users also report problems running Hatch on Windows, we suggest using WSL2.
If you use perceptrain for a publication, we kindly ask you to cite our work using the following BibTex entry:
@article{perceptrain2024pasqal,
title = {perceptrain},
author={Manu Lahariya},
year = {2025}
}Perceptrain is a free and open source software package, released under the Apache License, Version 2.0.