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Update readme for sklearnex (#61)
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README.md

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@@ -40,7 +40,7 @@ Create a suitable conda environment for each framework to test. Each item in the
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* [**scikit-learn**](sklearn_bench#how-to-create-conda-environment-for-benchmarking)
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```bash
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conda create -n bench -c intel python=3.7 scikit-learn daal4py pandas
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conda create -n bench -c intel python=3.7 scikit-learn scikit-learn-intelex pandas
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```
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* [**daal4py**](daal4py_bench#how-to-create-conda-environment-for-benchmarking)
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runner options:
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* ``configs`` : configuration files paths
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* ``no-intel-optimized`` : use no intel optimized version. Now avalible for scikit-learn benchmarks. Default is intel-optimized version.
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* ``no-intel-optimized`` : using Scikit-learn without Intel(R) Extension for Scikit-learn*. Now avalible for scikit-learn benchmarks. Default starts with using Intel(R) Extension for Scikit-learn*.
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* ``output-file``: output file name for result benchmarks. Default is `result.json`
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* ``report``: create an Excel report based on benchmarks results. Need library `openpyxl`.
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* ``dummy-run`` : run configuration parser and datasets generation without benchmarks running.

azure-pipelines.yml

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@@ -6,7 +6,7 @@ jobs:
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- script: |
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conda update -y -q conda
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export FORCE_DAAL4PY_SKLEARN=yes
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conda create -q -y -n bench -c conda-forge python=3.7 pandas scikit-learn daal4py
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conda create -q -y -n bench -c conda-forge python=3.7 pandas scikit-learn scikit-learn-intelex
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displayName: Create Anaconda environment
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- script: |
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. /usr/share/miniconda/etc/profile.d/conda.sh
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- script: |
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. /usr/share/miniconda/etc/profile.d/conda.sh
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conda activate bench
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python runner.py --configs configs/testing/daal4py.json
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python runner.py --configs configs/testing/daal4py.json --no-intel-optimized
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displayName: Run bench
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- job: Linux_XGBoost_and_daal4py
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pool:
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- script: |
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. /usr/share/miniconda/etc/profile.d/conda.sh
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conda activate bench
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python runner.py --configs configs/testing/daal4py_xgboost.json
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python runner.py --configs configs/testing/daal4py_xgboost.json --no-intel-optimized
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displayName: Run bench
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- job: Pep8
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pool:

bench.py

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if not params.no_intel_optimized:
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try:
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from daal4py.sklearn import patch_sklearn
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from sklearnex import patch_sklearn
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patch_sklearn()
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except ImportError:
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print('Failed to import daal4py.sklearn.patch_sklearn.'
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print('Failed to import sklearnex.patch_sklearn.'
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'Use stock version scikit-learn', file=sys.stderr)
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params.device = 'None'
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else:

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