semvec/pypi-packages huggingface dataset:
VladClc 0.0.2
A very basic calculator
License: MIT
Keywords: calculator

Basic package consisting of two modules, ""BasicMultiplication" and "BasicSum", which allow to add and multiply numbers


Change Log
===================

0.0.1 (19/06/2022)
---------------------------
First release

0.0.2 (19/06/2022)
---------------------------
-added help functions for both BasicSum, BasicMultiplication modules (.help())
deepair 0.2.0
PyTorch implementations of Deep reinforcement learning algorithms.
License: MIT
Requires Python: >=3.7.*
Keywords: reinforcement-learning-algorithms reinforcement-learning machine-learning deep rl

# Deepair is a Deep Reinforcement Learning library

[![PyPI version](https://badge.fury.io/py/deepair.svg)](https://badge.fury.io/py/deepair)
[![Documentation Status](https://readthedocs.org/projects/deepair/badge/?version=latest)](https://deepair.readthedocs.io/en/latest/?badge=latest)

Deepair implementations of reinforcement learning algorithms. It focus on DRL algorithms and implementing the latest advancements in DRL. Highly customizable support for training processes. Suitable for the research and application of the latest technologies in reinforcement learning.



# Features

# Documentation
Documentation is available: [https://deepair.readthedocs.io/](https://deepair.readthedocs.io/)

# Installation

```
pip install deepair
```

or
```
pip install git+https://github.com/sonnhfit/deepair.git
```

# Example

```python
import gym
from deepair.dqn import Rainbow

env = gym.make('LunarLander-v2')

rain = Rainbow(env=env, memory_size=10000, batch_size=32, target_update=256)

rain.train(timesteps=200000)

# test
state = env.reset()
done = False
score = 0

while not done:
    action = rain.select_action(state, deterministic=True)
    next_state, reward, done = env.step(action)

    state = next_state
    score += reward

print("score: ", score)
```

![rainbow lunalander env](docs/source/_static/img/rainbow_lunalander.gif)

# Implemented Algorithms

# Tutorial

# How To Contribute