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sod4onnx

Simple model output OP additional tools.

SkipPyPI Artificial IntelligenceReleased Sep 202282.6K downloads / moMIT LicensePure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — sod4onnx-1.0.0-py3-none-any.whl
v1.0.0 · released 2022-09-15 · Python >=3.6

No. While the tool is simple and has no install friction, it has been abandoned for nearly four years with no maintenance or updates. Compatibility with current ONNX versions is uncertain, and the lack of ongoing support makes it risky for production use. Consider alternatives that are actively maintained if you need reliable ONNX output deletion.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Installation is straightforward with no runtime dependencies, but the package has been abandoned since its single release on 2022-09-15 with no subsequent updates or maintenance.

License · maintenance · safety

MIT License (permissive) — MIT License permits free use, modification, and distribution with minimal restrictions, making it legally safe to adopt in most projects.

last release 2022-09-15 (1429 days) · last repo commit 2022-09-15 · 2 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 82,561 downloads/mo, #14,153 on PyPI

Verify before relying

pip install -U sod4onnx

from sod4onnx import outputs_delete
onnx_graph = outputs_delete(
    input_onnx_file_path="model.onnx",
    output_op_names=["cast1_output"],
    output_onnx_file_path="model_modified.onnx"
)
  • Whether the package works correctly with current ONNX versions or if API changes have broken compatibility.
  • Whether onnx_graphsurgeon (listed in the description's install instructions) is a required runtime dependency despite not appearing in the metadata.
Same gist for agents: .md · .json

What it is and what it does

sod4onnx is a lightweight utility for modifying ONNX model graphs by removing specified output operations. It provides both a command-line interface and a Python API (the `outputs_delete` function) to accept an ONNX model file or graph object, delete named outputs, and write the result back to disk or return it as a modified graph object.

The tool is designed for model optimization workflows where intermediate or unwanted outputs need to be pruned from a trained model before deployment. It has no runtime dependencies beyond Python itself, making installation friction minimal. However, the package has not been maintained since its initial release in September 2022, raising concerns about compatibility with newer ONNX specifications or Python versions.

Use it for

  • Remove intermediate output layers from ONNX models before deployment to reduce model size or inference overhead.
  • Prune unnecessary outputs from multi-output models to simplify downstream inference pipelines.
  • Prepare ONNX models for edge deployment by stripping outputs not needed on target hardware.
  • Automate ONNX graph cleanup in model conversion pipelines where intermediate outputs are generated but not used.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Skip

No.

While the tool is simple and has no install friction, it has been abandoned for nearly four years with no maintenance or updates. Compatibility with current ONNX versions is uncertain, and the lack of ongoing support makes it risky for production use. Consider alternatives that are actively maintained if you need reliable ONNX output deletion.

Install

sod4onnx on PyPI

Before you install

Installation is straightforward with no runtime dependencies, but the package has been abandoned since its single release on 2022-09-15 with no subsequent updates or maintenance.

License in practice

MIT License permits free use, modification, and distribution with minimal restrictions, making it legally safe to adopt in most projects.

Quickstart

pip install -U sod4onnx

from sod4onnx import outputs_delete
onnx_graph = outputs_delete(
    input_onnx_file_path="model.onnx",
    output_op_names=["cast1_output"],
    output_onnx_file_path="model_modified.onnx"
)

Verify before relying

  • Whether the package works correctly with current ONNX versions or if API changes have broken compatibility.
  • Whether onnx_graphsurgeon (listed in the description's install instructions) is a required runtime dependency despite not appearing in the metadata.

Package facts

LicenseMIT License permissive
Python supportSupports the current Python release >=3.6
Install frictionLow. Pure-Python wheel
Runtime dependenciesNone
MaintenanceAbandoned 1,429 days since the last release
Last repo commit
First released
Downloads82,561 / month, #14,153 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14

Evidence: sod4onnx-1.0.0-py3-none-any.whl

Tags

Capabilities
onnx model output deletionremove onnx output opsonnx graph surgeryonnx model modificationdelete onnx outputsonnx output pruningonnx model editing
Topics
onnx-toolsmodel-optimization

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See also soa4onnx · svs4onnx · sng4onnx · snd4onnx · sde4onnx · soc4onnx · sio4onnx · sor4onnx · simple-onnx-processing-tools · snc4onnx