soc4onnx
A very simple tool that forces a change in the opset of an ONNX graph. Simple Opset Changer for ONNX.
Decision gist · record as of 2026-08-14
Yes, if you need a simple one-off opset conversion and are working with a stable ONNX version. No, if you require ongoing maintenance, support for recent ONNX releases, or assurance that the tool will handle edge cases—the package is abandoned and will not receive updates. Consider it a utility for legacy workflows rather than a foundation for new projects.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires ONNX library to be installed separately; package is abandoned and may not work with recent ONNX versions.
- Low install friction with no runtime dependencies.
- However, the package is abandoned—last release was 2022-09-09 and no commits since then—so it will not receive bug fixes or updates for newer ONNX versions or Python releases.
License · maintenance · safety
MIT License (permissive) — MIT License permits commercial and private use with minimal restrictions, requiring only attribution and inclusion of the license notice.
last release 2022-09-09 (1435 days) · last repo commit 2022-09-09 · 7 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 82,678 downloads/mo, #14,144 on PyPI
Alternatives
Verify before relying
pip install soc4onnx
from soc4onnx import change
changed_graph = change(
input_onnx_file_path='model.onnx',
output_onnx_file_path='model_opset13.onnx',
opset=13
)- Whether the tool handles all ONNX opset transitions correctly or only specific ranges.
- Whether changing opset can cause model validation or runtime failures on certain architectures.
- Current compatibility with recent ONNX library versions given the package's abandonment.
What it is and what it does
soc4onnx is a lightweight utility for modifying the opset version declared in an ONNX model file. ONNX models specify an opset version that indicates which operators and semantics they conform to; this tool allows you to change that version number in the model metadata without restructuring the graph itself. It works both as a command-line tool (taking input and output file paths plus a target opset number) and as a Python library (accepting either file paths or in-memory ONNX ModelProto objects).
The package has no runtime dependencies beyond ONNX itself, making it lightweight to install. However, it has been abandoned since September 2022 with no subsequent maintenance, so it may not work correctly with recent ONNX versions or Python releases, and any issues discovered will not be fixed.
Use it for
- Convert an ONNX model to a different opset version to match a target inference runtime's supported opset.
- Batch-process multiple ONNX files to standardize their opset versions across a model collection.
- Adjust opset in a model loaded in memory before serializing it to disk in a Python workflow.
- Downgrade or upgrade a model's declared opset to test compatibility with different ONNX runtime versions.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need a simple one-off opset conversion and are working with a stable ONNX version.
No, if you require ongoing maintenance, support for recent ONNX releases, or assurance that the tool will handle edge cases—the package is abandoned and will not receive updates. Consider it a utility for legacy workflows rather than a foundation for new projects.
Install
soc4onnx on PyPI
Before you install
Low install friction with no runtime dependencies. However, the package is abandoned—last release was 2022-09-09 and no commits since then—so it will not receive bug fixes or updates for newer ONNX versions or Python releases.
Requires ONNX library to be installed separately; package is abandoned and may not work with recent ONNX versions.
License in practice
MIT License permits commercial and private use with minimal restrictions, requiring only attribution and inclusion of the license notice.
Quickstart
pip install soc4onnx
from soc4onnx import change
changed_graph = change(
input_onnx_file_path='model.onnx',
output_onnx_file_path='model_opset13.onnx',
opset=13
)Verify before relying
- Whether the tool handles all ONNX opset transitions correctly or only specific ranges.
- Whether changing opset can cause model validation or runtime failures on certain architectures.
- Current compatibility with recent ONNX library versions given the package's abandonment.
Package facts
| License | MIT License permissive |
| Python support | Supports the current Python release >=3.6 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Abandoned 1,435 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 82,678 / month, #14,144 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: soc4onnx-1.0.2-py3-none-any.whl
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