distinguish feature names and indices in variable names #100
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name: Run Benchmarks | |
on: | |
push: | |
branches: | |
- main | |
paths: | |
- 'flexynesis/**' | |
- '.github/workflows/**' | |
- './spec-file.txt' | |
- './pyproject.toml' | |
- './manifest.scm' | |
- './guix.scm' | |
jobs: | |
run_package: | |
runs-on: ubuntu-latest | |
steps: | |
- name: Checkout repository | |
uses: actions/checkout@v2 | |
- name: Set up Python | |
uses: actions/setup-python@v2 | |
with: | |
python-version: '3.9' | |
- name: Set up Miniconda | |
uses: conda-incubator/setup-miniconda@v2 | |
with: | |
auto-update-conda: true | |
python-version: '3.9' | |
- name: Cache Conda environment | |
uses: actions/cache@v2 | |
with: | |
path: ~/miniconda/envs | |
key: ${{ runner.os }}-conda-${{ hashFiles('spec-file.txt') }} | |
restore-keys: | | |
${{ runner.os }}-conda- | |
- name: Create environment with dependencies | |
shell: bash -l {0} | |
run: | | |
conda create --name my_env --file spec-file.txt | |
conda activate my_env | |
- name: Install my package from source | |
shell: bash -l {0} | |
run: | | |
conda activate my_env | |
pip install -e . | |
# NOTE: Install pytorch geometric via pip | |
- name: Install pytorch-geometric | |
shell: bash -l {0} | |
run: | | |
conda activate my_env | |
pip install torch_geometric | |
- name: Download dataset1 | |
run: | | |
curl -L -o dataset1.tgz https://bimsbstatic.mdc-berlin.de/akalin/buyar/flexynesis-benchmark-datasets/dataset1.tgz | |
tar -xzvf dataset1.tgz | |
- name: Download stringdb data | |
run: | | |
wget https://stringdb-downloads.org/download/protein.links.v12.0/9606.protein.links.v12.0.txt.gz | |
gzip -cd 9606.protein.links.v12.0.txt.gz > dataset1/9606.protein.links.v12.0.txt | |
wget https://stringdb-downloads.org/download/protein.aliases.v12.0/9606.protein.aliases.v12.0.txt.gz | |
gzip -cd 9606.protein.aliases.v12.0.txt.gz > dataset1/9606.protein.aliases.v12.0.txt | |
- name: Download dataset2 | |
run: | | |
curl -L -o dataset2.tgz https://bimsbstatic.mdc-berlin.de/akalin/buyar/flexynesis-benchmark-datasets/dataset2.tgz | |
tar -xzvf dataset2.tgz | |
- name: Run DirectPred | |
shell: bash -l {0} | |
run: | | |
conda activate my_env | |
flexynesis --data_path dataset1 --model_class DirectPred --target_variables Erlotinib --batch_variables Crizotinib --fusion_type early --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,cnv --outdir . --prefix erlotinib_direct --early_stop_patience 3 --use_loss_weighting False --evaluate_baseline_performance False | |
- name: Run supervised_vae | |
shell: bash -l {0} | |
run: | | |
conda activate my_env | |
flexynesis --data_path dataset1 --model_class supervised_vae --target_variables Erlotinib,Crizotinib --fusion_type early --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,cnv --outdir . --prefix erlotinib_svae --early_stop_patience 3 --use_loss_weighting True --evaluate_baseline_performance False | |
- name: Run MultiTripletNetwork | |
shell: bash -l {0} | |
run: | | |
conda activate my_env | |
flexynesis --data_path dataset2 --model_class MultiTripletNetwork --target_variables y --fusion_type early --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,meth --outdir . --prefix msi_triplet --early_stop_patience 3 --evaluate_baseline_performance False | |
- name: Run DirectPredGCNN | |
shell: bash -l {0} | |
run: | | |
conda activate my_env | |
flexynesis --data_path dataset1 --model_class DirectPredGCNN --target_variables Erlotinib --batch_variables Crizotinib --fusion_type intermediate --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,cnv --outdir . --prefix erlotinib_direct --early_stop_patience 3 --use_loss_weighting False --evaluate_baseline_performance False |