semvec/pypi-packages huggingface dataset:
lowpy 0.4.3
High level GPU simulations of low level device characteristics in ML algorithms
Requires Python: >=3.6

# Welcome to LowPy (Pre-release)!
<p align="center"><img src="logo.png" height="100px"></p>

**LowPy** is a high level GPU simulator of low level device characteristics in machine algorithms. It seeks to streamline the investigation process when considering memristive and other novel devices for implementing a machine learning algorithm in hardware. By using the familiar [Keras](https://keras.io) syntax, it will be second nature to write GPU-optimized code to push your algorithm to its limits.

# Features
The aim is to focus first on the algorithms most published on in the field of neuromorphic computing, for both static and time series datasets.
### Datasets
- MNIST
### Algorithms
- Single Layer Perceptron (SLP)
- Multi-Layer Perceprton (MLP)
### Activation Functions
- Sigmoid
### Optimization Functions
- Stochastic Gradient Descent (SGD)
- SGD with Momentum
### Initialization Distributions
- Uniform 
- Normal
### Device Characteristics
- Write Variability


# Requirements
The following are required to use LowPy:
- GPU: NVIDIA
- OS: Linux (should work on Windows, not tested)
- Python 3.0 or newer
- PyCUDA
outcome-peewee-validates 2.1.2
Fork of Peewee-validates
Requires Python: >=3.8.6,<4.0.0

# peewee-validates-py
![Continuous Integration](https://github.com/outcome-co/peewee-validates-py/actions/workflows/ci.py.opensource.yaml/badge.svg) ![version-badge](https://img.shields.io/badge/version-2.1.2-brightgreen)

Validation library for peewee.

## Usage

```sh
poetry add outcome-peewee-validates
```

## Development

Remember to run `./bootstrap.sh` when you clone the repository.