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[POT] Remove gitlab mention (#9079)

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* change in installation

* develop mode

* change in install guide

* style change

* change declare
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Milana Shhanukova 2021-12-22 17:45:37 +04:00 committed by GitHub
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tools/pot/README_dev.md
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@ -24,23 +24,22 @@ Post-Training Optimization Tool includes standalone command-line tool and Python
- OpenVINO
### Installation (Temporary)
1) Clone compression tool repo: `git clone git@gitlab-icv.inn.intel.com:algo/post-training-compression-tool.git`
1) Clone DLDT repo: `git clone https://github.com/openvinotoolkit/openvino`
2) Download submodules:
```
git submodule init
git submodule update
```
3) Clone DLDT repo: `git clone https://github.com/openvinotoolkit/openvino` (Not into the post-training-compression-tool)
4) Switch dldt to required branch: `feature/low_precision/develop_fp_v10`
5) Build inference engine (Instruction can be found in dldt repo)
6) Switch dldt to _mkaglins/poc_ branch (Inference engine is built from _feature/low_precision/develop_fp_v10_ branch to support `FakeQuantize` layers. ModelOptimizer is used from _mkaglins/poc_ branch. So stay on _mkaglins/poc_ branch as you've built IE and don't build it from there again)
7) Set _PYTHONPATH_ variable: `export PYTHONPATH=<path to DLDT bins>/bin/intel64/Release/lib/python_api/python3.6:<path to DLDT>/dldt/model-optimizer`
8) Install requirements for accuracy checker:
3) Setup Model Optimizer.
You can setup Model Optimizer that needs for POT purposed with the two ways:
1. Install Model Optimizer with pip using "python setup.py install" at the mo folder (`<openvino_path>/tools/mo/setup.py`)
2. Setup Model Optimizer for Python using PYTHONPATH environment variable. Add the the following `<openvino_path>/tools/mo` into PYTHONPATH.
4) Install requirements for accuracy checker:
- From POT root: `cd ./thirdparty/open_model_zoo/tools/accuracy_checker`
- Call setup script: `python3 setup.py install`
- Get back to root POT dir: `cd <PATH_TO_POT_DIR>`
9) Install requirements for the tool:
- Call setup script: `python3 setup.py install`
5) Install requirements for the tool:
- Call setup script: `python3 setup.py develop`
### Run
1) Prepare configuration file for the tool based on the examples in the `configs` folder
@ -48,7 +47,7 @@ Post-Training Optimization Tool includes standalone command-line tool and Python
3) Launch the tool running the following command:
`python3 main.py -c <path to config file> -e`
To test the tool you can use PyTorch Mobilenet_v2 model from `tests/data/models/mobilenetv2/mobilenetv2.onnx`
To test the tool you can use PyTorch Mobilenet_v2 model from `tests/data/models/mobilenetv2_example/mobilenetv2_example.onnx`
- If there're some errors with imports in ModelOptimizer first of all make the following steps:
- Checkout _mkaglins/poc_ branch in DLDT (It's important!)
- If there're some errors with imports in ModelOptimizer, first of all make the following steps:
- If you've installed ModelOptimizer with setting _PYTHONPATH_ variable, checkout the path. It should be as following `<openvino_path>/tools/mo.` The whole command can be found in step 3 Installation (Temporary) guide above.