Several tools can help visualize neural network architectures, making it easier for developers and researchers to understand and debug their models. Some popular tools include TensorBoard, Netron, and Keras-Visualizer.
TensorBoard, which is integrated with TensorFlow, provides a suite of visualizations to track training metrics, display model graphs, and monitor performance over time. Netron is a lightweight, web-based tool that can visualize pre-trained models and model architectures in a simple, interactive way. Keras-Visualizer is a tool specifically designed to visualize Keras models and their layers.
These tools are essential for debugging, understanding, and improving neural network architectures, especially when dealing with large and complex models.