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#!/bin/bash
# $1 is the name of the scripts seeder
# $2 are the tasks to run, seperated by comma
# $3 is the output folder
# $4 is the gpu ids that used for training, seperated by comma
# $5 is an optional argument that, if present, skips the check for finished tasks
IFS=',' read -ra arr <<< $2
output_folder=$3
mkdir -p $output_folder
CUDA_VISIBLE_DEVICES=$4
echo "CUDA_VISIBLE_DEVICES="$CUDA_VISIBLE_DEVICES
if [ -z "$5" ]; then
echo "Check if tasks have finished"
fi
for seed in {0..4}
do
for gene in ${arr[@]}
do
logdir=$(cat $1/$gene/$gene.seed.$seed.yaml | grep log_dir | sed 's/.*: //')
num_epochs=$(cat $1/$gene/$gene.seed.$seed.yaml | grep num_epochs | sed 's/.*: //')
data_type=$(cat $1/$gene/$gene.seed.$seed.yaml | grep data_type | sed 's/.*: //')
if [[ $data_type == "GLOF" ]]; then
echo "Begin "$gene
# check if task has finished, unless the skip argument is present
if [[ -z "$5" ]] && [[ -f $logdir/FOLD.3/model.epoch.$num_epochs.pt ]]; then
echo "Skip "$gene
else
echo "Run "$gene
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.yaml --mode train_4_fold
fi
echo "Begin large window of "$gene
logdir=$(cat $1/$gene/$gene.seed.$seed.large.window.yaml | grep log_dir | sed 's/.*: //')
num_epochs=$(cat $1/$gene/$gene.seed.$seed.large.window.yaml | grep num_epochs | sed 's/.*: //')
# check if task has finished, unless the skip argument is present
if [[ -z "$5" ]] && [[ -f $logdir/FOLD.3/model.epoch.$num_epochs.pt ]]; then
echo "Skip large window of "$gene
else
echo "Run large window of "$gene
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.large.window.yaml --mode train_4_fold
fi
else
# for DMS tasks, we can do continue train
echo "Begin "$gene
if [[ -z "$5" ]] && [[ -f $logdir/model.epoch.$num_epochs.pt ]]; then
echo "Skip "$gene
else
echo "Run "$gene
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.yaml --mode continue_train
fi
fi
done
done
# make inference
for seed in {0..4}
do
for gene in ${arr[@]}
do
echo "Begin "$gene
logdir=$(cat $1/$gene/$gene.seed.$seed.yaml | grep log_dir | sed 's/.*: //')
num_epochs=$(cat $1/$gene/$gene.seed.$seed.yaml | grep num_epochs | sed 's/.*: //')
data_type=$(cat $1/$gene/$gene.seed.$seed.yaml | grep data_type | sed 's/.*: //')
data_file_train=$(cat $1/$gene/$gene.seed.$seed.yaml | grep data_file_train: | sed 's/.*: //')
# if GLOF, do the same for large window
if [[ $data_type == "GLOF" ]]; then
# check if task has finished
if [[ -f $logdir/FOLD.0/model.epoch.$num_epochs.pt ]] && [[ -f $logdir/FOLD.1/model.epoch.$num_epochs.pt ]] && [[ -f $logdir/FOLD.2/model.epoch.$num_epochs.pt ]] && [[ -f $logdir/FOLD.3/model.epoch.$num_epochs.pt ]] && [[ ! -f $output_folder/$gene.training.seed.$seed.csv ]]; then
echo "Begin inference "$gene
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.yaml --mode interpret_4_fold --interpret-by both --out-dir $output_folder/$gene.testing.seed.$seed.csv
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.yaml --mode interpret_4_fold --interpret-by both --data-file-test $data_file_train --out-dir $output_folder/$gene.training.seed.$seed.csv
else
echo "Not finished "$gene
fi
echo "Begin large window of "$gene
logdir=$(cat $1/$gene/$gene.seed.$seed.large.window.yaml | grep log_dir | sed 's/.*: //')
num_epochs=$(cat $1/$gene/$gene.seed.$seed.large.window.yaml | grep num_epochs | sed 's/.*: //')
# check if task has finished
if [[ -f $logdir/FOLD.0/model.epoch.$num_epochs.pt ]] && [[ -f $logdir/FOLD.1/model.epoch.$num_epochs.pt ]] && [[ -f $logdir/FOLD.2/model.epoch.$num_epochs.pt ]] && [[ -f $logdir/FOLD.3/model.epoch.$num_epochs.pt ]] && [[ ! -f $output_folder/$gene.training.seed.$seed.large.window.csv ]]; then
echo "Begin inference large window of "$gene
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.large.window.yaml --mode interpret_4_fold --interpret-by both --out-dir $output_folder/$gene.testing.seed.$seed.large.window.csv
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.large.window.yaml --mode interpret_4_fold --interpret-by both --data-file-test $data_file_train --out-dir $output_folder/$gene.training.seed.$seed.large.window.csv
else
echo "Not finished large window of "$gene
fi
else
# if not GLOF we don't have to do large window
# check if task has finished
if [[ -f $logdir/model.epoch.$num_epochs.pt ]] && [[ ! -f $output_folder/$gene.testing.seed.$seed.csv ]]; then
echo "Begin inference "$gene
python -W ignore::UserWarning:torch_geometric.data.collate:147 train.py --conf $1/$gene/$gene.seed.$seed.yaml --mode interpret --interpret-by both --out-dir $output_folder/$gene.testing.seed.$seed.csv
else
echo "Not finished "$gene
fi
fi
done
done
# aggregate results
# get conda home
conda_home=$(conda info --base)
for gene in ${arr[@]}; do
$conda_home/envs/r4-base/bin/Rscript scripts/run.new.task.R $1/$gene/$gene $output_folder
done |