deeponnxcustom: custom ONNX and deep learning
Onnx, onnxruntime, deep learning, pytorch…
python setup.py build_ext --inplace
Generate the setup in subfolder dist:
python setup.py sdist
Generate the documentation in folder dist/html:
python setup.py build_sphinx
Run the unit tests:
python setup.py unittests
To check style:
python -m flake8 deeponnxcustom tests examples
The function check or the command line python -m deeponnxcustom check checks the module is properly installed and returns processing time for a couple of functions or simply:
import deeponnxcustom deeponnxcustom.check()
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Release files for deeponnxcustom 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| deeponnxcustom-0.1.0.tar.gz | 14.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deeponnxcustom-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 28.3 kB
Release files / deeponnxcustom-0.1.0.tar.gz
| Download URL | deeponnxcustom-0.1.0.tar.gz |
|---|---|
| Size | 14.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5
|
Release files / deeponnxcustom-0.1.0-py3-none-any.whl
| Download URL | deeponnxcustom-0.1.0-py3-none-any.whl |
|---|---|
| Size | 14.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5
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