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A set of simple tools for splitting, merging, OP deletion, size compression, rewriting attributes and constants, OP generation, change opset, change to the specified input order, addition of OP, RGB to BGR conversion, change batch size, batch rename of OP, and JSON convertion for ONNX models.

Project description

simple-onnx-processing-tools

A set of simple tools for splitting, merging, OP deletion, size compression, rewriting attributes and constants, OP generation, change opset, change to the specified input order, addition of OP, RGB to BGR conversion, change batch size, batch rename of OP, and JSON convertion for ONNX models.

Downloads GitHub PyPI

1. Tools

HostPC

# (1) Minimum configuration installation with no dependent packages installed
$ pip install -U simple-onnx-processing-tools \
&& pip install -U onnx \
&& python3 -m pip install -U onnx_graphsurgeon --index-url https://pypi.ngc.nvidia.com

or

# (2) When installing all dependent packages such as onnx-simplifier, onnxruntime, numpy, etc...
$ pip install -U simple-onnx-processing-tools[full] \
&& pip install -U onnx \
&& python3 -m pip install -U onnx_graphsurgeon --index-url https://pypi.ngc.nvidia.com

Docker

$ docker run --rm -it \
-v `pwd`:/workdir \
-w /workdir \
ghcr.io/pinto0309/simple-onnx-processing-tools:1.1.31
No. Tool Name Tags Summary
1 snc4onnx
snc
PyPIsnc Simple tool to combine(merge) onnx models. Simple Network Combine Tool for ONNX.
2 sne4onnx
image
PyPIsne A very simple tool for situations where optimization with onnx-simplifier would exceed the Protocol Buffers upper file size limit of 2GB, or simply to separate onnx files to any size you want. Simple Network Extraction for ONNX.
3 snd4onnx
snd
PyPIsnd Simple node deletion tool for onnx. Simple Node Deletion for ONNX.
4 scs4onnx
scs
PyPIscs A very simple tool that compresses the overall size of the ONNX model by aggregating duplicate constant values as much as possible. Simple Constant value Shrink for ONNX.
5 sog4onnx
sog
PyPIsog Simple ONNX operation generator. Simple Operation Generator for ONNX.
6 sam4onnx
sam
PyPIsam A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for ONNX.
7 soc4onnx
soc
PyPIsam A very simple tool that forces a change in the opset of an ONNX graph. Simple Opset Changer for ONNX.
8 scc4onnx
scc
PyPIsam Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel order of RGB and BGR. Simple Channel Converter for ONNX.
9 sna4onnx
sna
PyPIsog Simple node addition tool for onnx. Simple Node Addition for ONNX.
10 sbi4onnx
sbi
PyPIsbi4onnx A very simple script that only initializes the batch size of ONNX. Simple Batchsize Initialization for ONNX.
11 sor4onnx
sor
PyPIsor4onnx Simple OP Renamer for ONNX.
12 soa4onnx
soa
PyPIsoa4onnx Simple model Output OP Additional tools for ONNX.
13 sod4onnx
sod
PyPIsod4onnx Simple model Output OP Deletion tools for ONNX.
14 ssi4onnx
ssi
PyPIssi4onnx Simple Shape Inference tool for ONNX.
15 sit4onnx
sit
PyPIsit4onnx Tools for simple inference testing using TensorRT, CUDA and OpenVINO CPU/GPU and CPU providers. Simple Inference Test for ONNX.
16 onnx2json
onnx2json
PyPIonnx2json Exports the ONNX file to a JSON file.
17 json2onnx
json2onnx
PyPIsog Converts a JSON file to an ONNX file.
18 sed4onnx
sed
PyPIsog Simple ONNX constant encoder/decoder. Since the constant values in the JSON files generated by onnx2json are Base64-encoded values, ASCII <-> Base64 conversion is required when rewriting JSON constant values.
19 ssc4onnx
ssc
PyPIsog Checker with simple ONNX model structure. Simple Structure Checker for ONNX. Analyzes and displays the structure of huge size models that cannot be displayed by Netron.
20 sio4onnx
image
PyPIsio Simple tool to change the INPUT and OUTPUT shape of ONNX.
21 svs4onnx
image
PyPIsio A very simple tool to swap connections between output and input variables in an ONNX graph. Simple Variable Switch for ONNX.
22 onnx2tf
image
PyPIonnx2tf Self-Created Tools to convert ONNX files (NCHW) to TensorFlow format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf).
23 sng4onnx
image
PyPIsng4onnx A simple tool that automatically generates and assigns an OP name to each OP in an old format ONNX file.
24 sde4onnx
sde4onnx_icon
PyPIsde4onnx Simple doc_string eraser for ONNX.
25 spo4onnx
spo4onnx_icon
PyPIspo4onnx Simple tool for partial optimization of ONNX. Further optimize some models that cannot be optimized with onnx-optimizer and onnxsim by several tens of percent. In particular, models containing Einsum and OneHot.
26 components_of_onnx
components_of_onnx
[WIP]PyPIsog ONNX parts yard. The various operations described in Operator Schemas are converted in advance into OP stand-alone ONNX files.

2. Very useful tools

No. Tool Name Author Tags Summary
1 OnnxGraphQt
onnx_graph_qt
fateshelled OnnxGraphQt ONNX model visualizer. Model structure can be edited on the visualization tool.imageimage
2 onnx-modifier
image
ZhangGe6 onnx-modifier To edit an ONNX model, One common way is to visualize the model graph, and edit it using ONNX Python API.image
3 onnx-simplifier daquexian PyPIonnxsim ONNX Simplifier is presented to simplify the ONNX model. It infers the whole computation graph and then replaces the redundant operators with their constant outputs.
4 Sparsify
image
neuralmagic PyPIsparsify Easy-to-use UI for automatically sparsifying neural networks and creating sparsification recipes for better inference performance and a smaller footprint.image
5 DeepSparse Engine
image
neuralmagic PyPIdeepsparse Sparsity-aware neural network inference engine for GPU-class performance on CPUs.imageimage
6 Sparsebit megvii-research PyPISparsebit Sparsebit is a toolkit with pruning and quantization capabilities. It is designed to help researchers compress and accelerate neural network models by modifying only a few codes in existing pytorch project.
7 onnion Idein PyPIonnion onnion project. compile onnx to python. runtime depends only numpy.

2-1. OnnxGraphQt - [WIP] Startup Method Sample

git clone https://github.com/fateshelled/OnnxGraphQt
cd OnnxGraphQt
# build docker image
./docker/build.bash
# run
./docker/run.bash

3. Acknowledgments

  1. https://github.com/onnx/onnx/blob/main/docs/PythonAPIOverview.md
  2. https://docs.nvidia.com/deeplearning/tensorrt/onnx-graphsurgeon/docs/index.html
  3. https://github.com/NVIDIA/TensorRT/tree/main/tools/onnx-graphsurgeon
  4. https://github.com/onnx/onnx/blob/main/docs/Operators.md

4. References

  1. https://github.com/PINTO0309/PINTO_model_zoo

  2. https://github.com/PINTO0309/PINTO_model_zoo/tree/main/115_MoveNet/PINTO_Special/barracuda_gathernd_split

    https://user-images.githubusercontent.com/33194443/192281791-cf469dfd-f29a-4301-bd39-e96dd868dad9.mp4

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