Pytorch Extension Module.
Project description
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# (WIP) Pytorch Extension library
Pytorch Extenstion library provides advanced Neural Network Layers. You can easily use them like using original pytorch.
## Installation
```
$ git clone --recursive
$ cd torchex
$ pip install -e .
```
## Requirements
* Pytorch >= 0.4.0
## Documentation
After executing the following codes, you can read `PytorchExtenstion` documentation in docs/build/html/index.html.
```shell
$ pip install -r requirements.txt
$ cd docs
$ make html
```
## TODO
### Layers
- [x] support fundamental complex operations
- to_complex method
- to_real method
- complex_norm method
- [ ] add submodule for many examples.
- [ ] SeparableConv2D
- [ ] LocallyConnected1D
- [x] Highway
- [x] Inception
- [x] InceptionBN
- [x] Conv2dLocal
- [x] MLPConv2d
* [Network In Network](https://arxiv.org/abs/1312.4400v3)
- [ ] NaryTreeLSTM
- [ ] StatefulZoneoutLSTM
- [ ] StatefulPeepholeLSTM
- [ ] StatefulMGU
- [ ] BinaryHierarchicalSoftmax
- [ ] BlackOut
- [ ] CRF1d
- [ ] SimplifiedDropconnect
- [ ] Swish
- [ ] NegativeSampling
- [ ] ResidualCell
- [ ] Attention Cell
* [XiaoIce Band: A Melody and Arrangement Generation Framework for Pop Music](https://www.kdd.org/kdd2018/accepted-papers/view/xiaoice-banda-melody-and-arrangement-generation-framework-for-pop-music)
- [ ] MLP Cell
* same as above.
- [ ] DFT2d
* [Rotation Equivariance and Invariance in Convolutional Neural Networks](https://arxiv.org/pdf/1805.12301.pdf)
* https://github.com/bchidest/RiCNN/tree/master/ricnn
- [ ] My original DFT layer (made by Koji Ono)
- [ ] DFT1d
- [x] DFT2d
- [ ] DFT3d
- [ ] iDFT1d
- [ ] iDFT2d
- [ ] iDFT3d
- [ ] RFFT1d
- [ ] RFFT2d
- [ ] RFFT3d
- [ ] Conic Convolutional Layers
* same as above.
### Zoo
- [x] ImageTransferNet
### Optimizer
- [ ] chainer.optimizer_hooks.GradientLARS
### Atiributions
- [x] Integrated Gradients
## Examples
## Related Projects
* torchhp
* Hyper-Parameter Turning Library for Pytorch.
* torchrl
* Pytorch Reinforcement Learning Library.
* torchchem
* TorchChem aims to provide a high quality open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology.
* torchml
* Auto model optimization library for pytorch.
* torcdata
* Pytorch Datasets.
## Codes References
* Chainer
* One of the most wonderfull DeepLearning framework.
* https://github.com/chainer/chainer
* NLP
* allenNLP
* https://github.com/allenai/allennlp
* fairseq
* https://github.com/pytorch/fairseq
* text
* https://github.com/pytorch/text
* translate
* https://github.com/pytorch/translate
* Audio
* neural_sp
* https://github.com/hirofumi0810/neural_sp/
* deepspeech.pytorch
* https://github.com/SeanNaren/deepspeech.pytorch
* Awesome Speech Recognition Speech Synthesis Papers
* https://github.com/zzw922cn/awesome-speech-recognition-speech-synthesis-papers
* speech
* https://github.com/awni/speech
* pytorch-asr
* https://github.com/jinserk/pytorch-asr
[![Build Status](https://travis-ci.org/0h-n0/torchex.svg?branch=master)](https://travis-ci.org/0h-n0/torchex)
[![codecov](https://codecov.io/gh/0h-n0/torchex/branch/master/graph/badge.svg)](https://codecov.io/gh/0h-n0/torchex)
[![Maintainability](https://api.codeclimate.com/v1/badges/7cd6c99f10d22db13ee8/maintainability)](https://codeclimate.com/github/0h-n0/torchex/maintainability)
[![Test Coverage](https://api.codeclimate.com/v1/badges/7cd6c99f10d22db13ee8/test_coverage)](https://codeclimate.com/github/0h-n0/torchex/test_coverage)
[![BCH compliance](https://bettercodehub.com/edge/badge/0h-n0/torchex?branch=master)](https://bettercodehub.com/)
[![Downloads](https://img.shields.io/pypi/dm/torchex.svg)](https://pypi.org/project/torchex/)
# (WIP) Pytorch Extension library
Pytorch Extenstion library provides advanced Neural Network Layers. You can easily use them like using original pytorch.
## Installation
```
$ git clone --recursive
$ cd torchex
$ pip install -e .
```
## Requirements
* Pytorch >= 0.4.0
## Documentation
After executing the following codes, you can read `PytorchExtenstion` documentation in docs/build/html/index.html.
```shell
$ pip install -r requirements.txt
$ cd docs
$ make html
```
## TODO
### Layers
- [x] support fundamental complex operations
- to_complex method
- to_real method
- complex_norm method
- [ ] add submodule for many examples.
- [ ] SeparableConv2D
- [ ] LocallyConnected1D
- [x] Highway
- [x] Inception
- [x] InceptionBN
- [x] Conv2dLocal
- [x] MLPConv2d
* [Network In Network](https://arxiv.org/abs/1312.4400v3)
- [ ] NaryTreeLSTM
- [ ] StatefulZoneoutLSTM
- [ ] StatefulPeepholeLSTM
- [ ] StatefulMGU
- [ ] BinaryHierarchicalSoftmax
- [ ] BlackOut
- [ ] CRF1d
- [ ] SimplifiedDropconnect
- [ ] Swish
- [ ] NegativeSampling
- [ ] ResidualCell
- [ ] Attention Cell
* [XiaoIce Band: A Melody and Arrangement Generation Framework for Pop Music](https://www.kdd.org/kdd2018/accepted-papers/view/xiaoice-banda-melody-and-arrangement-generation-framework-for-pop-music)
- [ ] MLP Cell
* same as above.
- [ ] DFT2d
* [Rotation Equivariance and Invariance in Convolutional Neural Networks](https://arxiv.org/pdf/1805.12301.pdf)
* https://github.com/bchidest/RiCNN/tree/master/ricnn
- [ ] My original DFT layer (made by Koji Ono)
- [ ] DFT1d
- [x] DFT2d
- [ ] DFT3d
- [ ] iDFT1d
- [ ] iDFT2d
- [ ] iDFT3d
- [ ] RFFT1d
- [ ] RFFT2d
- [ ] RFFT3d
- [ ] Conic Convolutional Layers
* same as above.
### Zoo
- [x] ImageTransferNet
### Optimizer
- [ ] chainer.optimizer_hooks.GradientLARS
### Atiributions
- [x] Integrated Gradients
## Examples
## Related Projects
* torchhp
* Hyper-Parameter Turning Library for Pytorch.
* torchrl
* Pytorch Reinforcement Learning Library.
* torchchem
* TorchChem aims to provide a high quality open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology.
* torchml
* Auto model optimization library for pytorch.
* torcdata
* Pytorch Datasets.
## Codes References
* Chainer
* One of the most wonderfull DeepLearning framework.
* https://github.com/chainer/chainer
* NLP
* allenNLP
* https://github.com/allenai/allennlp
* fairseq
* https://github.com/pytorch/fairseq
* text
* https://github.com/pytorch/text
* translate
* https://github.com/pytorch/translate
* Audio
* neural_sp
* https://github.com/hirofumi0810/neural_sp/
* deepspeech.pytorch
* https://github.com/SeanNaren/deepspeech.pytorch
* Awesome Speech Recognition Speech Synthesis Papers
* https://github.com/zzw922cn/awesome-speech-recognition-speech-synthesis-papers
* speech
* https://github.com/awni/speech
* pytorch-asr
* https://github.com/jinserk/pytorch-asr
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