https://github.com/pinto0309/sed4onnx
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.
https://github.com/pinto0309/sed4onnx
json model-converter models onnx python
Last synced: 4 months ago
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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.
- Host: GitHub
- URL: https://github.com/pinto0309/sed4onnx
- Owner: PINTO0309
- License: mit
- Created: 2022-05-15T07:26:25.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-12-30T15:58:56.000Z (almost 3 years ago)
- Last Synced: 2025-04-15T11:47:12.189Z (6 months ago)
- Topics: json, model-converter, models, onnx, python
- Language: Python
- Homepage:
- Size: 27.3 KB
- Stars: 6
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# sed4onnx
Simple ONNX constant encoder/decoder.
https://github.com/PINTO0309/simple-onnx-processing-tools
[](https://pepy.tech/project/sed4onnx)  [](https://pypi.org/project/sed4onnx/) [](https://github.com/PINTO0309/sed4onnx/actions?query=workflow%3ACodeQL)
## Key concept
- Since the constant values in the JSON files generated by **[onnx2json](https://github.com/PINTO0309/onnx2json)** are Base64-encoded values, ASCII <-> Base64 conversion is required when rewriting JSON constant values.
- After writing the converted Base64 strings to JSON using this tool, **[json2onnx](https://github.com/PINTO0309/json2onnx)** can be used to regenerate the constant-modified ONNX file.
## 1. Setup
### 1-1. HostPC
```bash
### option
$ echo export PATH="~/.local/bin:$PATH" >> ~/.bashrc \
&& source ~/.bashrc
### run
$ pip install -U sed4onnx
```
### 1-2. Docker
https://github.com/PINTO0309/simple-onnx-processing-tools#docker
## 2. CLI Usage
```
$ sed4onnx -h
usage:
sed4onnx [-h]
-cs CONSTANT_STRING
[-d {float16,float32,float64,uint8,int8,int16,int32,int64,string}]
[-m {encode,decode}]
optional arguments:
-h, --help
show this help message and exit.
-cs CONSTANT_STRING, --constant_string CONSTANT_STRING
Strings to be encoded and decoded for ONNX constants.
-d {float16,float32,float64,uint8,int8,int16,int32,int64,string}, \
--dtype {float16,float32,float64,uint8,int8,int16,int32,int64,string}
Data type.
-m {encode,decode}, --mode {encode,decode}
encode: Converts the string specified in constant_string to a Base64 format string
that can be embedded in ONNX constants.
decode: Converts a Base64 string specified in constant_string to ASCII like
Numpy string or pure string.
```
## 3. In-script Usage
```python
>>> from sed4onnx import encode
>>> from sed4onnx import decode
>>> help(encode)
Help on function encode in module sed4onnx.onnx_constant_encoder_decoder:
encode(constant_string: str) -> str
Parameters
----------
constant_string: str
ASCII string to be encoded.
dtype: str
'float16' or 'float32' or 'float64' or 'uint8'
or 'int8' or 'int16' or 'int32' or 'int64' or 'string'
Returns
-------
encoded_string: str
Base64-encoded ASCII string.
>>> help(decode)
Help on function decode in module sed4onnx.onnx_constant_encoder_decoder:
decode(constant_string: str, dtype: str) -> numpy.ndarray
Parameters
----------
constant_string: str
Base64 string to be decoded.
dtype: str
'float16' or 'float32' or 'float64' or 'uint8'
or 'int8' or 'int16' or 'int32' or 'int64' or 'string'
Returns
-------
decoded_ndarray: np.ndarray
Base64-decoded numpy.ndarray.
```
## 4. CLI Execution
```bash
$ sed4onnx \
--constant_string [-1,3,224,224] \
--dtype int64 \
--mode encode
$ sed4onnx \
--constant_string '//////////8DAAAAAAAAAOAAAAAAAAAA4AAAAAAAAAA=' \
--dtype int64 \
--mode decode
```
## 5. In-script Execution
```python
from sed4onnx import encode
from sed4onnx import decode
base64_string = encode(
constant_string='[-1,3,224,224]',
dtype='int64',
)
numpy_ndarray = decode(
constant_string='//////////8DAAAAAAAAAOAAAAAAAAAA4AAAAAAAAAA=',
dtype='int64',
)
```
## 6. Sample
```bash
$ sed4onnx \
--constant_string [-1,3,224,224] \
--dtype int64 \
--mode encode
//////////8DAAAAAAAAAOAAAAAAAAAA4AAAAAAAAAA=
$ sed4onnx \
--constant_string '//////////8DAAAAAAAAAOAAAAAAAAAA4AAAAAAAAAA=' \
--dtype int64 \
--mode decode
[-1,3,224,224]
```
## 7. Reference
1. https://github.com/onnx/onnx/blob/main/docs/Operators.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/PINTO0309/simple-onnx-processing-tools
5. https://github.com/PINTO0309/PINTO_model_zoo
## 8. Issues
https://github.com/PINTO0309/simple-onnx-processing-tools/issues