{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/3"}],"enrichment":{"capability":"Generates visual diagrams of PyTorch neural network computation graphs and autograd traces, showing layer connections and tensor flow through the model.","skillfed_tags":["pytorch","visualization","debugging"],"use_cases":["Visualize a custom neural network architecture to verify layer connections and data flow during forward pass.","Debug autograd computation graphs to understand which operations are tracked for backpropagation.","Generate architecture diagrams for documentation or research papers showing model structure.","Inspect what intermediate tensors and gradients are saved during the forward pass for memory analysis."],"what_it_does":"torchviz is a small visualization utility for PyTorch that converts neural network computation graphs into diagrams. It takes a PyTorch tensor output and the model's parameters, then uses graphviz to render a visual representation of how data flows through the network's layers and operations during the forward pass. The package can optionally display what autograd saves for the backward pass (available for PyTorch 1.9 and later) by setting `show_attrs=True` and `show_saved=True`.\n\nThe package is designed for model inspection and debugging\u2014developers use it to understand network architecture visually, verify layer connections, and trace tensor transformations. It depends on torch for the computation graph structure and graphviz for rendering the diagram as an image or PDF. Installation requires both the Python package and the graphviz system library.","worth_installing":"Yes, if you need to visualize PyTorch computation graphs for debugging or documentation. The install is straightforward and the package has no known vulnerabilities. However, maintenance is dormant (620 days since last release), so verify compatibility with your PyTorch version before relying on it for production workflows. The graphviz system dependency is a minor friction point but standard for graph visualization."},"id":"torchviz","links":{"html":"https://skillfed.io/packages/torchviz","md":"https://skillfed.io/packages/torchviz.md","pypi":"https://pypi.org/project/torchviz/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-12-02","license_spdx":null,"license_treatment":"permissive","name":"torchviz","python_support":"unspecified","summary":"A small package to create visualizations of PyTorch execution graphs"},"popularity":{"monthly_downloads":2052967,"position":3338,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.0.3"}