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.test-dnn.yml
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script:
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(export 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST ResNet-50 (format=${FORMAT} pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./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} &&
(export 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST AlexNet (format=${FORMAT} pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./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} &&
(export 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST Overfeat (format=${FORMAT} pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./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} &&
(export 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST GoogleNet-v1 (format=${FORMAT} pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./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} &&
(export 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST GoogleNet-v3 (format=${FORMAT} pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./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} &&
(export 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST dcGAN (format=${FORMAT} pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./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} &&
(export 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
for PAD in 0 1; do
echo; echo "--- TEST VGGa (format=${FORMAT} pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./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 ${MAKEJ} &&
(export OMP_NUM_THREADS=$(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}" | cut -d_ -f1; else echo "0"; fi);
export 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} ${PAD};
done
done)
- if [ "knl" = "${PARTITIONS}" ] || [ "knltrb" = "${PARTITIONS}" ]; then exit 0; fi &&
make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(export OMP_NUM_THREADS=$(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}" | cut -d_ -f1; else echo "0"; fi);
export CHECK=1 ITERS=1000 MB=${OMP_NUM_THREADS};
for PAD in 0 1; do
echo; echo "--- TEST ResNet-50 (precision=16-bit pad=${PAD} mb=${MB} nt=${OMP_NUM_THREADS})";
./run_resnet50.sh ${MB} ${ITERS} -1 qi16f32 F 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 ${MB_NT} | cut -d_ -f1);
export OMP_NUM_THREADS=$(echo ${MB_NT} | cut -d_ -f2);
./layer_example_f32 1 299 299 ${MB} 3 32 3 3 0 0 2 U T 1 &&
./layer_example_f32 1 13 13 ${MB} 192 384 3 3 1 1 1 B L 1;
done)
- make -e ${MAKEJ} && cd samples/deeplearning/cnnlayer && make -e ${MAKEJ} &&
(export OMP_NUM_THREADS=$(if [ "" != "${MB_THREADS}" ]; then echo "${MB_THREADS}" | cut -d_ -f1; else echo "0"; fi);
export CHECK=1 CHECK_SCALE=1 ITERS=1 MB=${OMP_NUM_THREADS};
for KIND in F B U; do
echo; echo "--- TEST ResNet-50 (precision=bf16 kind=${KIND} mb=${MB} nt=${OMP_NUM_THREADS})";
./run_resnet50.sh ${MB} ${ITERS} -1 bf16 F L 1 &&
./run_resnet50.sh ${MB} ${ITERS} -1 bf16 B L 1 &&
./run_resnet50.sh ${MB} ${ITERS} -1 bf16 U L 1;
done)