Generate a neural network architecture Image
Project description
Neural Network Visualizer
General Description
A module which creates a neural network with the given architecture(only Dense layers)
Installation
Before installation
Before installing the module, run the below command at your prompt to install the graphviz
$ sudo apt install graphviz
Normal installation
$ sudo pip3 install neuralnet-visualize
Development installation
$ 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.
sudo pip3 install neuralnet-visualize --upgrade
Future Works
- Add Convolutional layers, Maxpooling, Flatten layers, LSTM's
- Specific colors for activation functions
- Specific colors for types of layers
Neural Network Visualizer Version History
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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for neuralnet_visualize-0.1.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | fa20bfbebc4ba52a17367649176d6f3957965586ac63f27cccffaefeb68915ef |
|
MD5 | 3070d67e14a59fdba7e170fafb750267 |
|
BLAKE2b-256 | b2c0188fd7e128f52c795d19e9dcced746bd428031637c188cf5f2f4924de7af |
Close
Hashes for neuralnet_visualize-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2f9e9df197accaaa611c5798a1abe62b6d4c7e8e15b619594fdc4961f21cc06e |
|
MD5 | a56527427ab7f8af25c8205be0741053 |
|
BLAKE2b-256 | d45e0b2ff0b3834f0963481f3a69cd135126ccd8438d0ef28f3de4be1bff363e |