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        "author": "Teodor Scorpan",
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        "description": "# Intuitive library to help with training neural networks in PyTorch\n\n[![Codacy Badge](https://api.codacy.com/project/badge/Grade/d418757720864208adf721433bd3d55d)](https://www.codacy.com/app/Catastropha/ignis)\n[![Codacy Badge](https://api.codacy.com/project/badge/coverage/d418757720864208adf721433bd3d55d)](https://www.codacy.com/app/Catastropha/ignis)\n[![Build Status](https://api.travis-ci.org/catastropha/ignis.svg?branch=master)](https://travis-ci.org/catastropha/ignis)\n[![Downloads](https://pepy.tech/badge/ignis)](https://pepy.tech/project/ignis)\n[![Version](https://img.shields.io/pypi/v/ignis.svg?style=flat)](https://pypi.org/project/ignis/#history)\n![License](https://img.shields.io/pypi/l/ignis.svg?style=flat)\n\n`ignis` is a high-level library that helps you write compact but full-featured training loops with metrics, early stops,\nand model checkpoints for deep learning library [PyTorch](https://pytorch.org/).\n\nWith `ignis` you can solve Supervised Learning and Deep Reinforcement Learning problems.\n\nYou can extend `ignis` according to your own needs. You can implement custom functionalities by extending simple\nabstract classes.\n\n## Deep Reinforcement Learning algorithms\n\n1.  Deep Q Network (DQN)\n2.  Deep Deterministic Policy Gradients (DDPG)\n\n## Installation\n\n1.  Install PyTorch. You can find it here: [PyTorch](https://pytorch.org/)\n2.  `pip install ignis`\n\n## Examples\n\nYou can find examples in `examples/` directory\n\nYou can also run examples: `python examples/iris.py`\n\nYou might want to `export PYTHONPATH=/path/to/this/directory`\n\n## Contribute\n\n1.  Implement new functionalities\n2.  Improve code design\n3.  Improve comments and readme\n4.  Tests\n\n",
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