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EpyNN-1.2.9
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مشاهده بیشترتوضیحات
EpyNN: Educational python for Neural Networks.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | EpyNN-1.2.9 |
| نام | EpyNN |
| نسخه کتابخانه | 1.2.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Florian Malard and Stéphanie Olivier-Van Stichelen |
| ایمیل نویسنده | florian.malard@gmail.com |
| آدرس صفحه اصلی | https://github.com/synthaze/EpyNN |
| آدرس اینترنتی | https://pypi.org/project/EpyNN/ |
| مجوز | GPL-3.0 License |
# EpyNN
  
 
**EpyNN is written in pure Python/NumPy.**
If you use EpyNN in academia, please cite:
Malard F., Danner L., Rouzies E., Meyer J. G., Lescop E., Olivier-Van Stichelen S. [**EpyNN: Educational python for Neural Networks**](https://www.softxjournal.com/article/S2352-7110(22)00090-5/fulltext), *SoftwareX* 19 (2022).
## Documentation
Please visit https://epynn.net/ for extensive documentation.
### Purpose
EpyNN is intended for **teachers**, **students**, **scientists**, or more generally anyone with minimal skills in Python programming **who wish to understand** and build from basic implementations of Neural Network architectures.
Although EpyNN can be used for production, it is meant to be a library of **homogeneous architecture templates** and **practical examples** which is expected to save an important amount of time for people who wish to learn, teach or **develop from scratch**.
### Content
EpyNN features **scalable**, **minimalistic** and **homogeneous** implementations of major Neural Network architectures in **pure Python/Numpy** including:
* [Embedding layer (Input)](https://epynn.net/Embedding.html)
* [Fully connected layer (Dense)](https://epynn.net/Dense.html)
* [Recurrent Neural Network (RNN)](https://epynn.net/RNN.html)
* [Long Short-Term Memory (LSTM)](https://epynn.net/LSTM.html)
* [Gated Recurrent Unit (GRU)](https://epynn.net/GRU.html)
* [Convolution (CNN)](https://epynn.net/Convolution.html)
* [Pooling (CNN)](https://epynn.net/Pooling.html)
* [Dropout - Regularization](https://epynn.net/Dropout.html)
* [Flatten - Adapter](https://epynn.net/Flatten.html)
Model and function rules and definition:
* [Architecture Layers - Model](https://epynn.net/EpyNN_Model.html)
* [Neural Network - Model](https://epynn.net/Layer_Model.html)
* [Data - Model](https://epynn.net/Data_Model.html)
* [Activation - Functions](https://epynn.net/activation.html)
* [Loss - Functions](https://epynn.net/loss.html)
While not enhancing, extending or replacing EpyNN's documentation, series of live examples in Python and Jupyter notebook formats are offered online and within the archive, including:
* [Data preparation - Examples](https://epynn.net/data_examples.html)
* [Network training - Examples](https://epynn.net/run_examples.html)
### Reliability
EpyNN has been cross-validated against TensorFlow/Keras API and provides identical results for identical configurations in the limit of float64 precision.
Please see [Is EpyNN reliable?](https://epynn.net/index.html#is-epynn-reliable) for details and executable codes.
### Recommended install
* **Linux/MacOS**
```bash
# Use bash shell
bash
# Clone git repository
git clone https://github.com/synthaze/EpyNN
# Change directory to EpyNN
cd EpyNN
# Install EpyNN dependencies
pip3 install -r requirements.txt
# Export EpyNN path in $PYTHONPATH for current session
export PYTHONPATH=$PYTHONPATH:$PWD
# Alternatively, not recommended
# pip3 install EpyNN
# epynn
```
**Linux:** Permanent export of EpyNN directory path in ```$PYTHONPATH```.
```bash
# Append export instruction to the end of .bashrc file
echo "export PYTHONPATH=$PYTHONPATH:$PWD" >> ~/.bashrc
# Source .bashrc to refresh $PYTHONPATH
source ~/.bashrc
```
**MacOS:** Permanent export of EpyNN directory path in ```$PYTHONPATH```.
```bash
# Append export instruction to the end of .bash_profile file
echo "export PYTHONPATH=$PYTHONPATH:$PWD" >> ~/.bash_profile
# Source .bash_profile to refresh $PYTHONPATH
source ~/.bash_profile
```
* **Windows**
```bash
# Clone git repository
git clone https://github.com/synthaze/EpyNN
# Change directory to EpyNN
chdir EpyNN
# Install EpyNN dependencies
pip3 install -r requirements.txt
# Show full path of EpyNN directory
echo %cd%
# Alternatively, not recommended
# pip3 install EpyNN
# epynn
```
Copy the full path of EpyNN directory, then go to:
``Control Panel > System > Advanced > Environment variable``
If you already have ``PYTHONPATH`` in the ``User variables`` section, select it and click ``Edit``, otherwise click ``New`` to add it.
Paste the full path of EpyNN directory in the input field, keep in mind that paths in ``PYTHONPATH`` should be comma-separated.
ANSI coloring schemes do work on native Windows10 and later. For prior Windows versions, users should configure their environment to work with ANSI coloring schemes for optimal experience.
## Current release
### 1.2 Publication release
* Minor revisions for peer-review process.
See [CHANGELOG.md](CHANGELOG.md) for past releases.
## Project tree
**epynn**
* [convolution](epynn/convolution)
* [backward.py](epynn/convolution/backward.py)
* [forward.py](epynn/convolution/forward.py)
* [models.py](epynn/convolution/models.py)
* [parameters.py](epynn/convolution/parameters.py)
* [dense](epynn/dense)
* [backward.py](epynn/dense/backward.py)
* [forward.py](epynn/dense/forward.py)
* [models.py](epynn/dense/models.py)
* [parameters.py](epynn/dense/parameters.py)
* [dropout](epynn/dropout)
* [backward.py](epynn/dropout/backward.py)
* [forward.py](epynn/dropout/forward.py)
* [models.py](epynn/dropout/models.py)
* [parameters.py](epynn/dropout/parameters.py)
* [embedding](epynn/embedding)
* [backward.py](epynn/embedding/backward.py)
* [dataset.py](epynn/embedding/dataset.py)
* [forward.py](epynn/embedding/forward.py)
* [models.py](epynn/embedding/models.py)
* [parameters.py](epynn/embedding/parameters.py)
* [flatten](epynn/flatten)
* [backward.py](epynn/flatten/backward.py)
* [forward.py](epynn/flatten/forward.py)
* [models.py](epynn/flatten/models.py)
* [parameters.py](epynn/flatten/parameters.py)
* [gru](epynn/gru)
* [backward.py](epynn/gru/backward.py)
* [forward.py](epynn/gru/forward.py)
* [models.py](epynn/gru/models.py)
* [parameters.py](epynn/gru/parameters.py)
* [lstm](epynn/lstm)
* [backward.py](epynn/lstm/backward.py)
* [forward.py](epynn/lstm/forward.py)
* [models.py](epynn/lstm/models.py)
* [parameters.py](epynn/lstm/parameters.py)
* [pooling](epynn/pooling)
* [backward.py](epynn/pooling/backward.py)
* [forward.py](epynn/pooling/forward.py)
* [models.py](epynn/pooling/models.py)
* [parameters.py](epynn/pooling/parameters.py)
* [rnn](epynn/rnn)
* [backward.py](epynn/rnn/backward.py)
* [forward.py](epynn/rnn/forward.py)
* [models.py](epynn/rnn/models.py)
* [parameters.py](epynn/rnn/parameters.py)
* [template](epynn/template)
* [backward.py](epynn/template/backward.py)
* [forward.py](epynn/template/forward.py)
* [models.py](epynn/template/models.py)
* [parameters.py](epynn/template/parameters.py)
* [network](epynn/network)
* [backward.py](epynn/network/backward.py)
* [evaluate.py](epynn/network/evaluate.py)
* [forward.py](epynn/network/forward.py)
* [hyperparameters.py](epynn/network/hyperparameters.py)
* [initialize.py](epynn/network/initialize.py)
* [models.py](epynn/network/models.py)
* [report.py](epynn/network/report.py)
* [training.py](epynn/network/training.py)
* [commons](epynn/commons)
* [io.py](epynn/commons/io.py)
* [library.py](epynn/commons/library.py)
* [logs.py](epynn/commons/logs.py)
* [loss.py](epynn/commons/loss.py)
* [maths.py](epynn/commons/maths.py)
* [metrics.py](epynn/commons/metrics.py)
* [models.py](epynn/commons/models.py)
* [plot.py](epynn/commons/plot.py)
* [schedule.py](epynn/commons/schedule.py)
**epynnlive**
* [author_music](epynnlive/author_music)
* [captcha_mnist](epynnlive/captcha_mnist)
* [dummy_boolean](epynnlive/dummy_boolean)
* [dummy_image](epynnlive/dummy_image)
* [dummy_string](epynnlive/dummy_string)
* [dummy_time](epynnlive/dummy_time)
* [ptm_protein](epynnlive/ptm_protein)
نیازمندی
| مقدار | نام |
|---|---|
| ==8.3.1 | Pillow |
| ==2.10.0 | Pygments |
| ==0.10.0 | cycler |
| ==1.0.0 | jupyter |
| ==1.3.2 | kiwisolver |
| - | matplotlib |
| ==5.4.1 | nbconvert |
| ==1.21.2 | numpy |
| ==2.4.7 | pyparsing |
| ==2.8.2 | python-dateutil |
| ==1.6.3 | scipy |
| ==1.16.0 | six |
| ==0.8.9 | tabulate |
| ==1.1.0 | termcolor |
| ==1.6.4 | texttable |
| - | utilsovs-pkg |
| ==3.2 | wget |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl EpyNN-1.2.9:
pip install EpyNN-1.2.9.whl
نصب پکیج tar.gz EpyNN-1.2.9:
pip install EpyNN-1.2.9.tar.gz