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Simplified DL lib for simplified accelerated research

Project description

# tensorop
<img style="float: centre;" src="tensorop_logo.png">

[![PyPI version](https://badge.fury.io/py/tensorop.svg)](https://badge.fury.io/py/tensorop)

Tensorop is a Deep Learning library built over Pytorch to accelerate research in the simplest manner possible without compromising on flexibility. Each module/object returned can be used with Pytorch at any moment (total sync). It can also be extended with [fastai](https://github.com/fastai/fastai).

## Getting Started

### Prerequisites

Install `pytorch` and `torchvision` from [pytorch.org](pytorch.org)
- Pytorch 1.0
- Torchvision
- Fastai (Optional: Can be extended)
- Pandas
- Numpy

### Installing
Using with git (Recommended method)
```
$ git clone https://github.com/prajjwal1/tensorop
$ cd tensorop
```

Installation via Pypi
```
$ pip3 install tensorop
```
Pypi install is not being updated regularly until v0.1 comes out

### Example/Tutorials
Tutorials can be found [here](https://github.com/prajjwal1/tensorop/tree/master/nbs). They may not be updated,please refer to docs for updated API or file an issue.
- Image Classification
- [Example 1](https://github.com/prajjwal1/tensorop/blob/master/nbs/example1.ipynb)

## Docs
Docs can be found [here](https://github.com/prajjwal1/tensorop/tree/master/docs).

### Components (Structure)
- Model
- Dataset
- Loss
- Norm
- Torch Utils
- Trainer
- Transforms
- Ensembling
- Utils

These are frequently changing once `v0.1` is out

## Contributing
There is so much work which needs to be done as of now, PRs are always welcome.



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