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openvino/model-optimizer
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Pavel Esir f661133242 [MO] fixed dealing with None in then/else branches of Select (#7465) 
* fixed dealing with None values in then/else branches of Select

* generalized solution when condition is non one elemental

* fix when both branches are None

* minor corrections

* rewritten Select unit-tests; fixed for condition with [True] mask

* removed mutable default arg from build_graph, added a few more test cases with masked condition, other minor corrections

* corrected output_shape calculation when broadcasting is off

* layer tests fixed: relaxed assert for condition shape to let pass TF Select

* corrected shape calculation when condition is not elementwise equal, calculated calculation for TF, corrected calculation of shape when values are not set

* fixed a typo for Select from TF Where
2021-10-15 18:51:52 +03:00
..
automation
[MO] IR Reader updates for support IR generated by PDPD FE (#7646)
2021-10-15 09:29:07 +03:00
extensions
[MO] fixed dealing with None in then/else branches of Select (#7465)
2021-10-15 18:51:52 +03:00
install_prerequisites
Remove sudo from mo install_prerequisites.sh (#6378)
2021-07-08 17:10:00 +03:00
mo
[MO] fixed dealing with None in then/else branches of Select (#7465)
2021-10-15 18:51:52 +03:00
unit_tests
[MO] fixed dealing with None in then/else branches of Select (#7465)
2021-10-15 18:51:52 +03:00
.coveragerc
Fix Gelu parameter name (#4895)
2021-03-22 19:35:32 +03:00
.pylintdict
moved pylint configuration files
2020-04-15 21:46:27 +03:00
.pylintrc
publish master branch snapshot, revision 0110d9c98fd7209589d06344f0d836f61d81f4b3
2020-04-27 21:21:29 +03:00
CMakeLists.txt
Add MO coveragerc to tests install pkg (#7707)
2021-10-01 13:34:07 +03:00
mo_caffe.py
Add Model Optimizer --transform option (#5504)
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mo_kaldi.py
Add Model Optimizer --transform option (#5504)
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mo_mxnet.py
Add Model Optimizer --transform option (#5504)
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mo_onnx.py
Add Model Optimizer --transform option (#5504)
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mo_paddle.py
Rename "pdpd" frontend to "paddle" (#6842)
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mo_tf.py
Add Model Optimizer --transform option (#5504)
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mo.py
Add Model Optimizer --transform option (#5504)
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README.md
New IRC package structure (#6255)
2021-09-15 16:49:11 +03:00
requirements_caffe.txt
Add json validate (#6449)
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requirements_dev.txt
Extend coverage versions in requirements_dev.txt (#7404)
2021-09-07 14:32:48 +03:00
requirements_kaldi.txt
Add json validate (#6449)
2021-07-22 21:12:44 +03:00
requirements_mxnet.txt
Add json validate (#6449)
2021-07-22 21:12:44 +03:00
requirements_onnx.txt
Add json validate (#6449)
2021-07-22 21:12:44 +03:00
requirements_tf2.txt
[requirements] Set TF to 2.5.0 (#6620)
2021-09-14 18:05:18 +03:00
requirements_tf.txt
Add json validate (#6449)
2021-07-22 21:12:44 +03:00
requirements.txt
[requirements] Set TF to 2.5.0 (#6620)
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setup.py
Add MO extras requires for supported DL frameworks (#5615)
2021-05-13 20:20:41 +03:00

README.md

Prerequisites

Model Optimizer requires:

  1. Python 3 or newer

  2. [Optional] Please read about use cases that require Caffe* to be available on the machine in the documentation.

Installation instructions

  1. Go to the Model Optimizer folder:
    cd PATH_TO_INSTALL_DIR/tools/model_optimizer

  1. 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

  2. Install dependencies. If you want to convert models only from particular framework, you should use one of available requirements_*.txt files corresponding to the framework of choice. For example, for Caffe use requirements_caffe.txt and 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.

  3. [OPTIONAL] If you use Windows OS, most probably you get python version of protobuf library. 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

  1. Run tests with:
    python -m unittest discover -p "*_test.py" [-s PATH_TO_DIR]

How to capture unit-tests coverage

  1. Run tests with:
    coverage run -m unittest discover -p "*_test.py" [-s PATH_TO_DIR]
  1. Build html report:
    coverage html

How to run code linting

  1. Run the following command:
    pylint mo/ extensions/ mo.py