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.
<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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