TF Graph Viewer

TF Graph Viewer provides a non-executable visualization of TensorFlow models to help engineers and researchers quickly grasp complex architectures. It accepts common TF artifacts and ONNX representations, rendering a topology that highlights operations, connections, and tensor relationships. The tool emphasizes readability, with options to focus on inputs, outputs, or specific subgraphs, and to filter by operation type or size. It does not run or modify the model; instead, it presents a faithful structural snapshot to support debugging, design validation, and knowledge transfer. By converting graphs into exportable visuals and metadata, teams can document architecture decisions, compare iterations, and share insights across cross-functional roles. The system is designed to be integrated into ML pipelines and documentation workflows, enabling automation-friendly consumption by dashboards and reporting engines. Core capabilities include input parsing, automatic layout, node labeling with type and shape when available, and export to SVG/PNG. Advanced features support large graphs through progressive rendering and targeted subgraph extraction, ensuring performance remains practical in real-world models. The tool complements runtime debuggers by showing structural issues (dimension mismatches, missing connections) without executing the graph, thus preserving model integrity while promoting rapid iteration. Users benefit from clearer communication of model structure and dependencies, particularly during peer reviews, onboarding, and knowledge transfer across teams.