Open nikhilyerra opened 10 months ago
running the entire pipeline (testing) steps to setup environment: conda create -n codex_pipeline python=3.9 conda activate codex_pipeline git clone https://github.com/hubmapconsortium/cwltool.git cd cwltool pip install .
conda create -n codex_pipeline python=3.9
conda activate codex_pipeline
git clone https://github.com/hubmapconsortium/cwltool.git
cd cwltool
pip install .
steps to run the pipeline: cwltool --singularity --move-outputs --outdir /path/to/local/output/dir pipeline.cwl --data_dir (the path to the codex directory) --gpus '0,1'
cwltool --singularity --move-outputs --outdir /path/to/local/output/dir pipeline.cwl --data_dir (the path to the codex directory) --gpus '0,1'
NOTE: This pipeline used lot of RAM (~200GB). 10 CPU's. It also requires GPU's
running the entire pipeline (testing) steps to setup environment:
conda create -n codex_pipeline python=3.9conda activate codex_pipelinegit clone https://github.com/hubmapconsortium/cwltool.gitcd cwltoolpip install .steps to run the pipeline:
cwltool --singularity --move-outputs --outdir /path/to/local/output/dir pipeline.cwl --data_dir (the path to the codex directory) --gpus '0,1'NOTE: This pipeline used lot of RAM (~200GB). 10 CPU's. It also requires GPU's