一个简单易用的神经网络可视化工具。
nnv的Python项目详细描述
神经网络可视化器(nnv)
简单易用的神经网络可视化生成工具。
安装
pip install nnv
用法
fromnnvimportNNVlayersList=[{"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()< >可以自定义节点大小/颜色、标题字体大小、节点和层之间的间距以及显示的最大节点数,…
fromnnvimportNNVlayersList=[{"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)
文档
nnv文档仍在创建中。现在,如果您有任何问题,请直接查看库源代码或打开一个问题。
未来附加值
将来可能会添加一些有用的功能(欢迎使用帮助):
- 向每个节点添加标签
- 直接从Keras模型导入图层信息
学分/引文
您不是必需的,但如果您使用此库,您可以引用它:
R. Cordeiro, "NNV: Neural Network Vizualizer", 2019. [Online]. Available: https://github.com/renatosc/nnv. [Accessed: DD- Month- 20YY].
或使用:
@Misc{,
author = {Renato Cordeiro},
title = {NNV: Neural Network Vizualizer},
month = may,
year = {2019},
note = {Online; accessed <today>},
url = {https://github.com/renatosc/nnv},
}