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Vladimir Gavrilov 318db6eccc Implement ExperimentalDetectronROIFeatureExtractor operation as nGraph op (#3739 )

* Commit.

* Written the header file of the nGraph operation ExperimentalDetectronROIFeatureExtractor.

* Started to write cpp-file for the nGraph operation ExperimentalDetectronROIFeatureExtractor.

* Deleted in_ports_count attribute for the MO operation ExperimentalDetectronROIFeatureExtractor.

* Written validate_and_infer_type() method of ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor.

* Code style fixes.

* Small fixes.

* Code style fixes.

* Now operation ExperimentalDetectronROIFeatureExtractor is read as nGraph operation ExperimentalDetectronROIFeatureExtractor.

* Implemented op::v6::ExperimentalDetectronROIFeatureExtractor::clone_with_new_inputs().

* Added macro NGRAPH_OP_SCOPE to the cpp-file of the nGraph operation ExperimentalDetectronROIFeatureExtractor.

* Fixes in some tests.

* Code style fix.

* Fixed yet another test for ExperimentalDetectronROIFeatureExtractor.

* Added tests for reading ExperimentalDetectronROIFeatureExtractor as operation from opset6.

* Added more test for reading ExperimentalDetectronROIFeatureExtractor as operation from opset6.

* Started to write shape infer tests for the nGraph operation ExperimentalDetectronROIFeatureExtractor.

* Corrected ngraph/test/CMakeLists.txt.

* Small changes.

* Code style fix.

* Small fixes.

* Added ctor of ExperimentalDetectronROIFeatureExtractor with NodeVector as argument.

* Added setting the attribute in_ports_count when the MO operation ExperimentalDetectronROIFeatureExtractor is creating in the MO transformation ONNXMaskRCNNTransformation.

* Added shape infer for the second output of the nGraph operation ExperimentalDetectronROIFeatureExtractor.

* Written shape infer tests for nGraph operation ExperimentalDetectronROIFeatureExtractor (case when input shapes are partially dynamic).

* Small fixes.

* Code style fix.

* Deleted redundant &expected_channels.

* Code style fix.

* Small refactoring.

* Small fixes.

* Small changes.

* Small fixes.

* Deleted attribute distribute_rois_between_levels of ExperimentalDetectronROIFeatureExtractoe.

* Deleted attribute preserve_rois_order of ExperimentalDetectronROIFeatureExtractoe.

* Deleted attribute image_id of ExperimentalDetectronROIFeatureExtractoe.

* Now MO generates attribute 'aligned' of ExperimentalDetectronROIFeatureExtractor only with values 'true' or 'false'.

* Small fix.

* Fix in the conversion of the attribute 'aligned' of MO operation ExperimentalDetectronROIFeatureExtractor to string.

* Tabs were replaced by spaces in some XMLs.

* Tabs were replaced by spaces in ngraph_reshape_tests.cpp.

* Fixed copyrights.

* Applied small patch to IREngine from PR https://github.com/openvinotoolkit/openvino/pull/3814.

* Tabs were replaced by spaces in cnn_ngraph_impl_tests.cpp.

* op::v6::ExperimentalDetectronROIFeatureExtractor::validate_and_infer_types() was rewritten using operator & for channels.

* Added tests for input shapes of op::v6::ExperimentalDetectronROIFeatureExtractor in the case when inputs shapes consist of intervals.

* Fixes in test type_prop.detectron_roi_feature_extractor_intervals.

2021-01-20 16:20:54 +03:00

automation

[MO] Implement transformation to avoid RandomUniform in dropout (#3678 )

2020-12-25 16:59:15 +03:00

extensions

Implement ExperimentalDetectronROIFeatureExtractor operation as nGraph op (#3739 )

2021-01-20 16:20:54 +03:00

install_prerequisites

[install_prerequisites.sh] upgrade pip to install tensorflow (#3392 )

2020-11-27 18:15:11 +03:00

Implement ExperimentalDetectronROIFeatureExtractor operation as nGraph op (#3739 )

2021-01-20 16:20:54 +03:00

.coveragerc

Create .coveragerc

2020-05-06 23:38:42 +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

[MO] Add CMake install for Model Optimizer (28291) (#2831 )

2020-10-30 14:37:06 +03:00

mo_caffe.py

Publishing 2020.1 content

2020-02-11 22:48:49 +03:00

mo_kaldi.py

Publishing 2020.1 content

2020-02-11 22:48:49 +03:00

mo_mxnet.py

Publishing 2020.1 content

2020-02-11 22:48:49 +03:00

mo_onnx.py

Publishing 2020.1 content

2020-02-11 22:48:49 +03:00

mo_tf.py

Publishing 2020.1 content

2020-02-11 22:48:49 +03:00

mo.py

Publishing 2020.1 content

2020-02-11 22:48:49 +03:00

README.md

MO dev guide refactoring (#3266 ) (#3595 )

2021-01-14 16:28:53 +03:00

requirements_caffe.txt

Updated MO requirements for numpy (#3034 )

2020-11-10 09:12:09 +03:00

requirements_dev.txt

Updated MO requirements files (#1511 )

2020-07-29 13:23:52 +03:00

requirements_kaldi.txt

Updated MO requirements for numpy (#3034 )

2020-11-10 09:12:09 +03:00

requirements_mxnet.txt

Set fixed version of the urllib3 package in the requirements because of the security issue in urllib3==1.25.8 (#3740 )

2020-12-25 18:02:23 +03:00

requirements_onnx.txt

Updated MO requirements for numpy (#3034 )

2020-11-10 09:12:09 +03:00

requirements_tf2.txt

[MO] Implement support of TensorFlow 2 Keras Embedding operation in MO (#3766 )

2021-01-10 22:05:58 +03:00

requirements_tf.txt

[MO] Implement support of TensorFlow 2 Keras Embedding operation in MO (#3766 )

2021-01-10 22:05:58 +03:00

requirements.txt

[MO] Implement support of TensorFlow 2 Keras Embedding operation in MO (#3766 )

2021-01-10 22:05:58 +03:00

README.md

Prerequisites

Model Optimizer requires:

Python 3 or newer
[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

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
```
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.
[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

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