torchex 0.0.12

[](https://github.com/0h-n0/torchex)
[](https://github.com/0h-n0/torchex)
[](https://badge.fury.io/py/torchex)
[](https://circleci.com/gh/0h-n0/torchex)
[](https://travis-ci.org/0h-n0/torchex)
[](https://codecov.io/gh/0h-n0/torchex)
[](https://torchex.readthedocs.io/en/latest/?badge=latest)
[](https://codeclimate.com/github/0h-n0/torchex/maintainability)
[](https://codeclimate.com/github/0h-n0/torchex/test_coverage)
[](https://bettercodehub.com/)
[](https://pypi.org/project/torchex/)

# (WIP) `torchex library

`torchex` library provides advanced Neural Network Layers. You can easily use them like using original pytorch.

## Installation

```
$ pip install torchex
```

## Requirements

* Pytorch >= 1.0

## Documentation

* https://torchex.readthedocs.io/en/latest/index.html

## How to use

### Lazy Style Model Definition

```python
import torch
import torchex.nn as exnn

net = exnn.Linear(10)
# You don't need to give the size of input for this module.
# This network is equivalent to `nn.Linear(100, 10)`.

x = troch.randn(10, 100)

y = net(x)
```

### torchex.nn list

* `torchex.nn.Pass`
* `torchex.nn.Flatten`
* `torchex.nn.Linear`
* Lazy style
* `torchex.nn.Conv1d`
* Lazy style
* `torchex.nn.Conv2d`
* Lazy style
* `torchex.nn.Conv3d`
* Lazy style
* `torchex.nn.Conv2dLocal`