DeepGraph: A PyCharm Tool for Visualizing and Understanding Deep Learning Models

As more and more domain specific big data become available, there comes a strong need on the fast development and deployment of deep learning (DL) systems with high quality for domain specific applications, including many safetycritical scenarios. In traditional software engineering, software visualization plays an important role in improving developers' performance with various available tools. However, there are limited visualization supports existing for DL systems, especially in integrated development environments (IDEs) that allow a developer to visualize the source code of a deep neural network (DNN) and its corresponding graph architecture. In this paper, we propose DeepGraph, a visualization tool for visualizing and understanding deep neural networks. DeepGraph analyzes the training program to construct the graph representation of a DNN, and establishes and maintains the linkage (mapping) between the source code of the training program and its corresponding neural network architecture. We implemented DeepGraph as a PyCharm plugin and performed preliminary empirical study to demonstrate its usefulness for understanding deep neural networks.