Jan IwaszkiewiczandSergey Lyalin
583939b828
* Remove inits, update main one * Fix stacklevel * Testing wrong solution * Testing test test * Fix test test test test * mo modules mo problems * Xfail test that check stdout/err? * not so correct solution to circular imports * Fix or not to fix * CMake magic, co-authors: my best team * Fix package imports * Fix tools inits * Fix ovc tf * Fix Q000 * Fix F401 * Fix linters * Add save_model * Remove LayoutMap * Move test_utils to 'internal modules' * First testing * Missing Type * Expand main namespace * Change some more tests * Add OVAny to namespace * Add Constant and Parameter to namespace * More tests changes * Fix inits * Add layout_helpers to main namespace * Revert CMake and linux.yml with ovc * Update main inits * Remove MO from tools inits * changes to init files * Fix tests --------- Co-authored-by: Sergey Lyalin <sergey.lyalin@intel.com>
Installation
Installing from PyPi
- Create a virtual environment and activate it, e.g.:
virtualenv -p /usr/bin/python3.7 .env3
source .env3/bin/activate
- Install openvino-dev package, it contains model conversion API:
pip install openvino-dev
This will download all requirements and will install MO in your current virtual environment. If you need only particular frameworks you can specify them manually as optional dependencies in square brackets. E.g. the command below will install dependencies to support ONNX* and TensorFlow2* models:
pip install openvino-dev[onnx,tensorflow2]
To enable support of MxNet* models run:
pip install openvino-dev[mxnet]
To enable support of all frameworks:
pip install openvino-dev[all]
By default, if no frameworks are specified, dependencies to support ONNX* and TensorFlow2* are installed.
Converting models
Setup development environment
If you want to contribute to model conversion API you will need to deploy developer environment. You can do that by following the steps below:
- Create virtual environment and activate it, e.g.:
virtualenv -p /usr/bin/python3.7 .env3
source .env3/bin/activate
- Clone the OpenVINO™ repository and change dir to model-optimizer
git clone https://github.com/openvinotoolkit/openvino
cd openvino/tools/mo/
- Install openvino-mo package for development:
pip install -e .
or run setup.py develop, result will be the same:
python setup.py develop
This will download all requirements and deploy model conversion API for development in your virtual environment: specifically will create *.egg-link into the current directory in your site-packages. As previously noted, you can also manually specify to support only selected frameworks :
pip install -e ".[onnx,tensorflow2]"
How to run unit-tests
- Run tests with:
python -m unittest discover -p "*_test.py" [-s PATH_TO_DIR]
How to capture unit-tests coverage
- Run tests with:
coverage run -m unittest discover -p "*_test.py" [-s PATH_TO_DIR]
- Build html report:
coverage html
How to run code linting
- Run the following command:
pylint openvino/tools/mo/ mo.py