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o GraphDRP parsl csa workflow
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name: Docker Parsl GraphDRP CSA workflow
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on: [push]
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jobs:
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test:
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runs-on: ubuntu-latest
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container:
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image: rajeeja/graphdrp-image:latest
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steps:
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- uses: actions/checkout@v4
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- name: Install missing libraries
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run: |
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apt-get update && apt-get install -y libxrender1 libxext6
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- name: Install and check
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run: |
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which python
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python --version
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which conda
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conda env list
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eval "$(conda shell.bash hook)" # Ensure Conda is properly initialized
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conda activate graphdrp
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pip install -e .
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export PYTHONPATH=$PYTHONPATH:.
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python -c "from improvelib.applications.drug_response_prediction.config import DRPPreprocessConfig; print('Import successful')"
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BASE_DIR=$(pwd)
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ls -ltrh
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cd /app/GraphDRP
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ls -ltrh
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conda list -n graphdrp
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python -c "import sys; print(sys.path)"
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cd $BASE_DIR/workflows/csa/parsl/
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pip install cryptography==37.0.1
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pip install pyopenssl==22.0.0
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pip install cffi==1.14.5
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pip install parsl numpy pandas scikit-learn pyyaml
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mv /app/GraphDRP/csa_data .
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echo "Preprocess started"
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ls -ltrh
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python workflow_preprocess.py --config_file ./parsl_csa_githubactions.ini
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echo "Preprocess done"
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python workflow_csa.py --config_file ./parsl_csa_githubactions.ini
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echo "Parsl CSA done"
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[DEFAULT]
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input_dir = ./csa_data/raw_data
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y_col_name = auc
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use_singularity = False
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singularity_image = path_to_your_singularity_container.sif
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hyperparameters_file = ./hyperparameters_default.json
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model_name = graphdrp
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model_scripts_dir = /app/GraphDRP
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model_environment = graphdrp
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only_cross_study = False
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epochs = 2
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input_supp_data_dir = ''
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; # Exp 3
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output_dir = ./parsl_csa_exp3
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source_datasets = ["CCLE","gCSI"]
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target_datasets = ["CCLE","gCSI"]
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split = ["0","1"]
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[Preprocess]
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[Train]
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[Infer]

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