semvec/pypi-packages huggingface dataset:
linearinit 0.2.0
nn.linear with initialization created by nxdens

# linearinit

[![codecov](https://codecov.io/gh/nxdens/linearInit/branch/main/graph/badge.svg?token=linearInit_token_here)](https://codecov.io/gh/nxdens/linearInit)
[![CI](https://github.com/nxdens/linearInit/actions/workflows/main.yml/badge.svg)](https://github.com/nxdens/linearInit/actions/workflows/main.yml)

Creates an Fully connect network from nn.linear layers with a given activation. The layer is initialized based on the activation function chosen. 

## Install it from PyPI

```bash
pip install linearinit
```

## Usage

```py
from linearinit.base import FullyConnectedLayers
from linearinit.base import LinearWithInit

fcn = FullyConnectedLayers(layer_sizes=[1, 2, 3], activation=nn.LeakyReLU(), bias=True)
```
potatomagical 0.1
A simple magic package

# Magical

A simple magic package.

## Installation

Install via pip: `pip install potatomagical`

## Usage

```python
from potatomagical.magic import do_magic

print(do_magic("Potato"))  # "Potato is now potatomagical!"
```

## Packaging

First, make sure you have the necessary tools installed.

```
pip install twine wheel
```

Then, create a distribution package.


```
python setup.py sdist bdist_wheel
```


## Uploading to PyPI

First, check your package with twine.

```
twine check dist/*
```


If everything is okay, upload your package to PyPI.
```
twine upload dist/*
```

Remember, you'll need to create an account on [PyPI](https://pypi.org/) if you haven't already.

This is a very basic example. Depending on your project, you might need to add more information to `setup.py`, add a `MANIFEST.in` file, etc. Check the [Python Packaging User Guide](https://packaging.python.org/tutorials/packaging-projects/) for more details.