A simple and easy to use tool to visualize Neural Networks.
Project description
Neural Network Visualizer (NNV)
Simple and easy to use tool to generate Neural Network Visualizations.
Installation
pip install nnv
Usage
from nnv import NNV
layersList = [
{"title":"input\n(relu)", "units": 3, "color": "darkBlue"},
{"title":"hidden 1\n(relu)", "units": 3},
{"title":"output\n(sigmoid)", "units": 1,"color": "darkBlue"},
]
NNV(layersList).render()
It is possible to customize the node size/colors, title font size, spacing between nodes and layers and maximum number of nodes to show,...
from nnv import NNV
layersList = [
{"title":"input\n(relu)", "units": 300, "color": "darkBlue"},
{"title":"hidden 1\n(relu)", "units": 150},
{"title":"hidden 2\n(relu)", "units": 75},
{"title":"Dropout\n(0.5)", "units": 75, "color": "lightGray"},
{"title":"hidden 4\n(relu)", "units": 18},
{"title":"hidden 5\n(relu)", "units": 9},
{"title":"hidden 6\n(relu)", "units": 4},
{"title":"output\n(sigmoid)", "units": 1,"color": "darkBlue"},
]
nnv.NNV(layersList, max_num_nodes_visible=10, spacing_layer=120, spacing_nodes=2, font_size=20).render(save_to_file="my_pdf_output_example.pdf", do_not_show=True)
Documentation
NNV documentation is still being created. For now, if you have any question, please look directly the library source code or open an Issue.
Future addittions
Some useful features that may be added in the future (help is welcome):
- add labels to each node
- import layers info directly from a keras model
Credits / Citation
You are not required, but if you use this library, you can cite it:
R. Cordeiro, "NNV: Neural Network Vizualizer", 2019. [Online]. Available: https://github.com/renatosc/nnv. [Accessed: DD- Month- 20YY].
or using:
@Misc{,
author = {Renato Cordeiro},
title = {NNV: Neural Network Vizualizer},
month = may,
year = {2019},
note = {Online; accessed <today>},
url = {https://github.com/renatosc/nnv},
}
Project details
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