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* Add CTCGreedyDecoder mo support * Update copiright * Update bom file * Add transformation * Fix code style * Fix according to review * Add CTCGreedyDecoder v6 to ConvertPrecision * Hot fix * Add replasment for ctc_greedy_decoder * Fix test * Fix * Update ie transform * Draft ctc lost replaser * Add ctcloss replaser * Update * Refactoring code * Update transformation * Update decoder * Remove comments * Convert seq mask from int to float * Fix unit test * Add dynamic tests * Refactoring code * Fix py code style * update style * Disable ctcgreedydecoder transform for mkldnn plugin * Add some comments * Add transfor code comments * Enable transform from differend plagins * Fix mo * fix tests * Fix comment * Fix convert precition * Update comment * Fix prcition * Refactoring according to reviw * Add ir reder extender * Rename transformation * Update bom file * Fix mo replacer * Fix tests * Move transform to decomp * Add check blank_index * Rafactoring ctcloss * Change dinemic rank check * Fix ctclos extractor * Remove comment * Fix code style * Refactoring pattern matcher for transformation CTCGreedyDecoder * Disavle transform for vpu * Refactoring according to review * Refactoring code * Disable transformation for cldnn * Remove unused code * Reverse transfomation * Fix code style * Hot fix transform * Fix unit tests * Update transform * Enable transform in common pipline * Fix names replasments for mo transformations * Hot fix * Fix
Prerequisites
Model Optimizer requires:
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Python 3 or newer
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[Optional] Please read about use cases that require Caffe* to be available on the machine in the documentation.
Installation instructions
- Go to the Model Optimizer folder:
cd PATH_TO_INSTALL_DIR/deployment_tools/model_optimizer
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Create virtual environment and activate it. This option is strongly recommended as it creates a Python sandbox and dependencies for the Model Optimizer do not influence global Python configuration, installed libraries etc. At the same time, special flag ensures that system-wide Python libraries are also available in this sandbox. Skip this step only if you do want to install all Model Optimizer dependencies globally:
- Create environment:
virtualenv -p /usr/bin/python3.6 .env3 --system-site-packages
- Activate it:
. .env3/bin/activate
- Create environment:
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Install dependencies. If you want to convert models only from particular framework, you should use one of available
requirements_*.txtfiles corresponding to the framework of choice. For example, for Caffe userequirements_caffe.txtand so on. When you decide to switch later to other frameworks, please install dependencies for them using the same mechanism:pip3 install -r requirements.txt
Or you can use the installation scripts from the "install_prerequisites" directory.
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[OPTIONAL] If you use Windows OS, most probably you get python version of
protobuflibrary. It is known to be rather slow, and you can use a boosted version of library by building the .egg file (Python package format) yourself, using instructions below (section 'How to boost Caffe model loading') for the target OS and Python, or install it with the pre-built .egg (it is built for Python 3.4, 3.5, 3.6, 3.7):python3 -m easy_install protobuf-3.6.1-py3.6-win-amd64.egg
It overrides the protobuf python package installed by the previous command.
Set environment variable to enable boost in protobuf performance:
set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=cpp
Setup development environment
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 mo/ extensions/ mo.py