Metadata-Version: 2.1
Name: neuralnet-visualize
Version: 0.2.3
Summary: Generate a neural network architecture Image
Home-page: https://github.com/AnuragAnalog/nn_visualize
Author: Anurag Peddi
Author-email: anurag.peddi1998@gmail.com
License: Apache License 2.0
Download-URL: https://pypi.org/project/neuralnet-visualize/
Keywords: Deep,Visualizer,Neural,Network,Visualize,Graphviz,Python
Platform: UNKNOWN
Classifier: Natural Language :: English
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=2.7
Description-Content-Type: text/markdown
Requires-Dist: graphviz (>=0.14)

# Neural Network Visualizer

## General Description

A module which creates a neural network image with the given architecture. It's a handy tool to see how your network is built as compared to a model summary.

## Installation

### Before installation

Before installing the module, run the below command at your prompt to install the graphviz
```shell
$ sudo apt install graphviz
```

### Normal installation
```shell
$ sudo pip3 install neuralnet-visualize
```

### Development installation
```shell
$ git clone https://github.com/AnuragAnalog/nn_visualize.git
$ cd nn_visualize
```

### After installation

After installing the module, if you want to upgrade the module, run the below command.
```shell
sudo pip3 install neuralnet-visualize --upgrade
```

## Future Works

- [x] Add Convolutional layers, Maxpooling, Flatten layers
- [ ] Add Sequence model layers
- [ ] Directly from the pickle files
- [ ] Specific colors for activation functions
- [ ] Directly convert from pytorch models


# Neural Network Visualizer Version History

### 0.2.3

* Added from_pytorch method
* Fixed a bug of multiple titles in an image
* Changed the logic of from_tensorflow method
* Fixed a bug, unique layer names for non trainable layers

### 0.2.2

* Added more docstring
* Can now be downloaded in py2

### 0.2.1

* Added title to the image
* Optimized some code

## 0.2.0

* Made it independent of tensorflow
* Fixed some bugs

### 0.1.4

* Fixed some bugs
* Added more layers maxpooling, avgpooling, flatten
* changed the shape of conv2d layer

### 0.1.3

* Added class docstrings with examples
* Added some more parameters for conv layer
* Disabled custom addition of layers after from_tensorflow call

### 0.1.2

* Added Conv layer, with kernel size parameter
* Refactored add_layer function
* Added Conv layer to from_tensorflow

### 0.1.1

* Added some possible exceptions
* Restructred basic functions in while initial import

## 0.1.0

* Added documentation

### 0.0.4

* Refactored summarize function
* Added a code part which colors output layer to red
* Added from_tensorflow method

### 0.0.3

* Added more display orientations
* Refactored the build network and add layer code
* Added some more file extensions to which image can be saved
* Added summarize function

### 0.0.2

* Added colors to type of layers
* Added Dense layers

### 0.0.1

Intial Version

* Starting code

