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.test-dnn.yml
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script:
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST ResNet-50 (format=${FORMAT} pad=${PAD})";
./run_resnet50.sh ${MB} ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_resnet50.sh ${MB} ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_resnet50.sh ${MB} ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST AlexNet (format=${FORMAT} pad=${PAD})";
./run_alexnet.sh ${MB} ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_alexnet.sh ${MB} ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_alexnet.sh ${MB} ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST Overfeat (format=${FORMAT} pad=${PAD})";
./run_overfeat.sh ${MB} ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_overfeat.sh ${MB} ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_overfeat.sh ${MB} ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST GoogleNet-v1 (format=${FORMAT} pad=${PAD})";
./run_googlenetv1.sh ${MB} ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_googlenetv1.sh ${MB} ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_googlenetv1.sh ${MB} ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST GoogleNet-v3 (format=${FORMAT} pad=${PAD})";
./run_googlenetv3.sh ${MB} ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_googlenetv3.sh ${MB} ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_googlenetv3.sh ${MB} ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST dcGAN (format=${FORMAT} pad=${PAD})";
./run_dcgan.sh ${MB} ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_dcgan.sh ${MB} ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_dcgan.sh ${MB} ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST VGGa (format=${FORMAT} pad=${PAD})";
./run_vgga.sh ${MB} ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_vgga.sh ${MB} ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_vgga.sh ${MB} ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(OMP_NUM_THREADS=$(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}" | cut -d_ -f1; else echo "0"; fi);
CHECK=1 ITERS=1;
for FORMAT in $(if [ "" != "${FORMATS}" ]; then echo "${FORMATS}"; else echo "L"; fi); do
for PAD in 0 1; do
echo; echo "--- TEST DeepBench (format=${FORMAT} pad=${PAD})";
./run_deepbench.sh ${ITERS} -1 f32 F ${FORMAT} ${PAD} &&
./run_deepbench.sh ${ITERS} -1 f32 B ${FORMAT} ${PAD} &&
./run_deepbench.sh ${ITERS} -1 f32 U ${FORMAT} ${PAD};
done
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(OMP_NUM_THREADS=$(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}" | cut -d_ -f1; else echo "0"; fi);
CHECK=1 ITERS=1000 MB=${OMP_NUM_THREADS};
for PAD in 0 1; do
echo; echo "--- TEST ResNet-50 (precision=16-bit pad=${PAD})";
./run_resnet50.sh ${MB} ${ITERS} -1 qi16f32 F L ${PAD} &&
./run_resnet50.sh ${MB} ${ITERS} -1 qi16f32 B L ${PAD} &&
./run_resnet50.sh ${MB} ${ITERS} -1 qi16f32 U L ${PAD};
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(echo; echo "--- TEST Quicktest";
for MB_NT in $(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}"; else echo "32_0"; fi); do
MB=$(echo ${MB_NT} | cut -d_ -f1);
OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
./layer_example_f32 1 299 299 ${MB} 3 32 3 3 0 0 2 U T 1;
done)