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train_strong_test_generator.sh
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train_strong_test_generator.sh
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#!/bin/bash
env_name=
algo_name=
seed=0
filter=30
num_epochs=500
learning_rate=3e-4
batch_size=64
early_stopping_patience=50
num_layers=2
test_split=0.2
mutant_name=
testing_configurations="false"
undersample=0.0
percentage_failure_discard=0.9
mutant_configuration=
while [ $# -gt 0 ] ; do
case $1 in
-a | --algo-name) algo_name="$2" ;;
-e | --env-name) env_name="$2" ;;
-s | --seed) seed="$2" ;;
-f | --filter) filter="$2" ;;
-n | --num-epochs) num_epochs="$2" ;;
-l | --learning-rate) learning_rate="$2" ;;
-b | --batch-size) batch_size="$2" ;;
-p | --early-stopping-patience) early_stopping_patience="$2" ;;
-y | --num-layers) num_layers="$2" ;;
-m | --mutant-name) mutant_name="$2" ;;
-t | --testing-configurations) testing_configurations="$2" ;;
-u | --undersample) undersample="$2" ;;
-c | --mutant-configuration) mutant_configuration="$2" ;;
-d | --percentage-failure-discard) percentage_failure_discard="$2" ;;
-k | --test-split) test_split="$2" ;;
esac
shift
done
if [ -z "$mutant_name" ]; then
if [[ "$testing_configurations" == "true" ]]; then
# we just remove the filter parameter
python -m test_generation.train --algo "$algo_name" --env-name "$env_name" \
--testing-policy-for-training-name mlp --test-split 0.2 \
--seed "$seed" \
--n-epochs "$num_epochs" \
--learning-rate "$learning_rate" \
--batch-size "$batch_size" \
--weight-loss \
--patience "$early_stopping_patience" \
--layers "$num_layers" \
--train-from-multiple-runs \
--undersample "$undersample" \
--test-split "$test_split" \
--percentage-failure-discard "$percentage_failure_discard"
else
python -m test_generation.train --algo "$algo_name" --env-name "$env_name" \
--testing-policy-for-training-name mlp --test-split 0.2 \
--seed "$seed" --training-progress-filter "$filter" \
--n-epochs "$num_epochs" \
--learning-rate "$learning_rate" \
--batch-size "$batch_size" \
--weight-loss \
--patience "$early_stopping_patience" \
--layers "$num_layers" \
--train-from-multiple-runs \
--test-split "$test_split" \
--undersample "$undersample"
fi
else
if [[ "$testing_configurations" == "true" ]]; then
# we just remove the filter parameter
if [ -n "$mutant_configuration" ]; then
python -m test_generation.train --algo "$algo_name" --env-name "$env_name" \
--testing-policy-for-training-name mlp --test-split 0.2 \
--seed "$seed" \
--n-epochs "$num_epochs" \
--learning-rate "$learning_rate" \
--batch-size "$batch_size" \
--weight-loss \
--patience "$early_stopping_patience" \
--layers "$num_layers" \
--train-from-multiple-runs \
--mutant-name "$mutant_name" \
--mutant-configuration "$mutant_configuration" \
--undersample "$undersample" \
--test-split "$test_split" \
--percentage-failure-discard "$percentage_failure_discard"
else
python -m test_generation.train --algo "$algo_name" --env-name "$env_name" \
--testing-policy-for-training-name mlp --test-split 0.2 \
--seed "$seed" \
--n-epochs "$num_epochs" \
--learning-rate "$learning_rate" \
--batch-size "$batch_size" \
--weight-loss \
--patience "$early_stopping_patience" \
--layers "$num_layers" \
--train-from-multiple-runs \
--mutant-name "$mutant_name" \
--undersample "$undersample" \
--test-split "$test_split" \
--percentage-failure-discard "$percentage_failure_discard"
fi
else
if [ -n "$mutant_configuration" ]; then
python -m test_generation.train --algo "$algo_name" --env-name "$env_name" \
--testing-policy-for-training-name mlp --test-split 0.2 \
--seed "$seed" --training-progress-filter "$filter" \
--n-epochs "$num_epochs" \
--learning-rate "$learning_rate" \
--batch-size "$batch_size" \
--weight-loss \
--patience "$early_stopping_patience" \
--layers "$num_layers" \
--train-from-multiple-runs \
--mutant-name "$mutant_name" \
--mutant-configuration "$mutant_configuration" \
--test-split "$test_split" \
--undersample "$undersample"
else
python -m test_generation.train --algo "$algo_name" --env-name "$env_name" \
--testing-policy-for-training-name mlp --test-split 0.2 \
--seed "$seed" --training-progress-filter "$filter" \
--n-epochs "$num_epochs" \
--learning-rate "$learning_rate" \
--batch-size "$batch_size" \
--weight-loss \
--patience "$early_stopping_patience" \
--layers "$num_layers" \
--train-from-multiple-runs \
--mutant-name "$mutant_name" \
--test-split "$test_split" \
--undersample "$undersample"
fi
fi
fi