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openvino/model-optimizer
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Anastasia PopovaIlya ChuraevGleb Kazantaev
 cf48792134 Random Uniform MO implementation (#6694) 
* Added RandomUniform operation.

* Conflicts fix.

* Fix conflicts.

* Fix conflicts.

* Added ONNX extractor, fixed FP16 conversion, added double implementation.

* int32, int64 types.

* Added initial type attribute.

* Added extractors for MxNet and TF for RandomUniformInt.

* Fixed ChangeRandomUniformOutputType transformation.

* Corrected ONNX, MxNetextractors.

* Fixed extender.

* Code style corrected, updated BOM file.

* Small correction.

* Code reformat.

* Fixed type check.

* Small corrections, code style.

* Added RandomUniform tests to manifest file.

* Include fixed.

* Code style.

* Small corrections.

* Tests fixed.

* Manifest file updated.

* Removed initial type attribute.

* Small correction.

* Fixed problem with Const types change.

* Update ngraph/core/include/ngraph/op/random_uniform.hpp

Co-authored-by: Ilya Churaev <ilyachur@gmail.com>

* Update ngraph/core/src/op/random_uniform.cpp

Co-authored-by: Ilya Churaev <ilyachur@gmail.com>

* Update ngraph/core/src/op/random_uniform.cpp

Co-authored-by: Ilya Churaev <ilyachur@gmail.com>

* Applied comments to shell implementation.

* Applied comments to shell implementation.

* Moved shell and reference to separate PR.

* Moved shell and reference to separate PR.

* Corrected comments, code refactoring.

* Fixed seed attributes.

* Corrected mxnet extractor.

* Returned RandomUniform onnx extractor.

* Small fix.

* Used generator in tests, fixed input ports count in AttributedRandomUniform.

* Temporarily added DropoutWithRandomUniformReplacer and debug output.

* Temporarily added DropoutWithRandomUniformReplacer and debug output.

* Temporarily added DropoutWithRandomUniformReplacer and debug output.

* Temporarily added DropoutWithRandomUniformReplacer and debug output.

* Moved DropoutWithRandomUniformReplacer to ngraph, removed debug output.

* Fixed wrong change.

* Fixed wrong change.

* Added check that RandomUniform is in ShapeOf subgraph.

* Added layer tests, updated supported operations list.

* Small correction.

* Fix conflicts.

* Fix conflicts.

* Small fix.

* Used const for not changing values.

* Apply suggestions from code review

Co-authored-by: Gleb Kazantaev <gleb.nnstu@gmail.com>

* Added IR check in layer tests.

* Fixed error.

* Fixed test.

* Update inference-engine/src/transformations/include/transformations/common_optimizations/dropout_with_random_uniform_replacer.hpp

Co-authored-by: Gleb Kazantaev <gleb.nnstu@gmail.com>

* Removed ShapeOf and Mul from DropoutWithRandomUniformReplacer.

* Replaced register_new_node with make_shared.

* Added fp16 test.

* Extended for RandomUniform->Convert case.

* Used modf().

* Removed modf().

* Update inference-engine/src/transformations/src/transformations/common_optimizations/dropout_with_random_uniform_replacer.cpp

Co-authored-by: Gleb Kazantaev <gleb.nnstu@gmail.com>

* Added negative tests, added nullptr check for add_const_value.

Co-authored-by: Ilya Churaev <ilyachur@gmail.com>
Co-authored-by: Gleb Kazantaev <gleb.nnstu@gmail.com>
2021-09-14 21:26:57 +03:00
..
automation
Random Uniform MO implementation (#6694)
2021-09-14 21:26:57 +03:00
extensions
Random Uniform MO implementation (#6694)
2021-09-14 21:26:57 +03:00
install_prerequisites
Remove sudo from mo install_prerequisites.sh (#6378)
2021-07-08 17:10:00 +03:00
mo
Random Uniform MO implementation (#6694)
2021-09-14 21:26:57 +03:00
unit_tests
Random Uniform MO implementation (#6694)
2021-09-14 21:26:57 +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
Azure CI: run MO unit tests after OpenVINO build (#6772)
2021-07-23 17:42:49 +03:00
mo_caffe.py
Add Model Optimizer --transform option (#5504)
2021-05-12 18:42:56 +03:00
mo_kaldi.py
Add Model Optimizer --transform option (#5504)
2021-05-12 18:42:56 +03:00
mo_mxnet.py
Add Model Optimizer --transform option (#5504)
2021-05-12 18:42:56 +03:00
mo_onnx.py
Add Model Optimizer --transform option (#5504)
2021-05-12 18:42:56 +03:00
mo_paddle.py
Rename "pdpd" frontend to "paddle" (#6842)
2021-07-29 11:43:07 +03:00
mo_tf.py
Add Model Optimizer --transform option (#5504)
2021-05-12 18:42:56 +03:00
mo.py
Add Model Optimizer --transform option (#5504)
2021-05-12 18:42:56 +03:00
README.md
MO dev guide refactoring (#3266) (#3595)
2021-01-14 16:28:53 +03:00
requirements_caffe.txt
Add json validate (#6449)
2021-07-22 21:12:44 +03:00
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)
2021-09-14 18:05:18 +03:00
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/deployment_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
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