{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/4"}],"enrichment":{"capability":"ONNX GraphSurgeon lets you programmatically create and modify ONNX neural network models by working with an intermediate representation of graphs, nodes, and tensors.","skillfed_tags":["model-optimization","onnx-tools","graph-manipulation"],"use_cases":["Remove unused layers or nodes from ONNX models before deployment to reduce size","Programmatically build custom ONNX models from scratch without writing raw protobuf","Debug and visualize neural network graphs by inspecting nodes, tensors, and their connections","Adapt models by inserting, removing, or rewiring layers for transfer learning workflows","Automate model transformations as part of a model compilation or optimization pipeline"],"what_it_does":"ONNX GraphSurgeon is a Python library for creating and modifying ONNX neural network models. It provides an intermediate representation (IR) layer that abstracts away ONNX's low-level details, letting you work with graphs, nodes, and tensors as Python objects. You can import ONNX models, manipulate their structure by adding, removing, or rewiring nodes and tensors, and export the result back to ONNX format.\n\nThe library is organized around three main components: importers (to load ONNX models into the IR), the IR itself (where all modifications happen), and exporters (to write modified graphs back to ONNX). It handles both in-memory models and models with externally stored data. Common operations include topological sorting, cleanup of unused nodes, and direct manipulation of tensor values and node attributes.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and solves a real problem for anyone working with ONNX models programmatically. The permissive Apache 2.0 license poses no restrictions. Install it if you need to create or modify ONNX graphs in code."},"id":"onnx-graphsurgeon","links":{"html":"https://skillfed.io/packages/onnx-graphsurgeon","md":"https://skillfed.io/packages/onnx-graphsurgeon.md","pypi":"https://pypi.org/project/onnx-graphsurgeon/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-08","license_spdx":null,"license_treatment":"permissive","name":"onnx-graphsurgeon","python_support":"unspecified","summary":"ONNX GraphSurgeon"},"popularity":{"monthly_downloads":751950,"position":5155,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.6.1"}