test-configuration-win.yml

#===============================================================================
# Copyright 2024 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#===============================================================================
steps:
  - task: UsePythonVersion@0
    displayName: "Use Python $(PYTHON_VERSION)"
    inputs:
      versionSpec: "$(PYTHON_VERSION)"
  - powershell: Write-Host "##vso[task.prependpath]$env:CONDA\Scripts"
    displayName: Add conda to Windows PATH
  - script: |
      conda create -y -n bench-env -c conda-forge -c nodefaults python=$(PYTHON_VERSION)
    displayName: Environment initialization
  - script: |
      call activate bench-env
      pip install -r envs/requirements-sklearn.txt
      pip list
    displayName: Install requirements via pip
    condition: eq(variables['PKG_MANAGER'], 'pip')
  - script: |
      call activate bench-env
      conda env update -f envs/conda-env-sklearn.yml -n bench-env
      conda list
    displayName: Install requirements via conda
    condition: eq(variables['PKG_MANAGER'], 'conda')
  - script: |
      call activate bench-env
      python -m sklbench --report -l DEBUG --report -p algorithm:library=sklearn,sklearnex algorithm:estimator=PCA,KMeans,ElasticNet,KNeighborsClassifier data:dataset=skin_segmentation data:split_kwargs:train_size=5000 data:split_kwargs:test_size=5000
    displayName: CLI arguments example run
  - script: |
      call activate bench-env
      python -m sklbench --report -l DEBUG --report -c configs/sklearn_example.json
    displayName: Sklearn example run
  - script: |
      call activate bench-env
      python -m sklbench --report -l DEBUG --report -c configs/xgboost_example.json
    displayName: XGBoost example run
  - script: |
      call activate bench-env
      python -m sklbench -l INFO -c configs/testing/azure-pipelines-ci.json --prefetch-datasets --report --diff-cols library --compatibility-mode
    displayName: CI config run