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44 changes: 44 additions & 0 deletions
44
script/app-mlperf-inference-intel/build_retinanet_harness.sh
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| export PATH=${CM_CONDA_BIN_PATH}:$PATH | ||
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| cd ${CM_HARNESS_CODE_ROOT} | ||
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| export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"} | ||
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| export IPEX_PATH=${CM_IPEX_INSTALLED_PATH} | ||
| export TORCH_PATH=`python -c 'import torch;print(torch.utils.cmake_prefix_path)'` | ||
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| if [[ -z ${TORCH_PATH} ]]; then | ||
| echo "Torch not found" | ||
| exit 1 | ||
| fi | ||
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| export LOADGEN_DIR="${CM_MLPERF_INFERENCE_LOADGEN_INSTALL_PATH}/../" | ||
| export OPENCV_DIR=${CM_OPENCV_BUILD_PATH} | ||
| export RAPIDJSON_INCLUDE_DIR=${CM_RAPIDJSON_SRC_REPO_PATH}/include | ||
| export GFLAGS_DIR=${CM_GFLAGS_BUILD_PATH} | ||
| export USE_CUDA=0 | ||
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| BUILD_DIR=${PWD}/build | ||
| rm -rf "$BUILD_DIR" | ||
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| SRC_DIR=${PWD}/src | ||
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| export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${OPENCV_DIR}/lib:${ONEDNN_DIR}/build/src | ||
| export LIBRARY_PATH=${LIBRARY_PATH}:${CONDA_PREFIX}/lib | ||
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| cmd="cmake -DCMAKE_PREFIX_PATH=${TORCH_PATH} \ | ||
| -DLOADGEN_DIR=${LOADGEN_DIR} \ | ||
| -DOpenCV_DIR=${OPENCV_DIR} \ | ||
| -DRapidJSON_INCLUDE_DIR=${RAPIDJSON_INCLUDE_DIR} \ | ||
| -Dgflags_DIR=${GFLAGS_DIR} \ | ||
| -DINTEL_EXTENSION_FOR_PYTORCH_PATH=${IPEX_PATH} \ | ||
| -DCMAKE_BUILD_TYPE=Release \ | ||
| -B${BUILD_DIR} \ | ||
| -H${SRC_DIR}" | ||
| echo "$cmd" | ||
| eval "$cmd" | ||
| test "$?" -eq 0 || exit "$?" | ||
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| cmake --build ${BUILD_DIR} --config Release -j$(nproc) | ||
| test "$?" -eq 0 || exit "$?" |
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| export PATH=${CM_CONDA_BIN_PATH}:$PATH | ||
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| export CALIBRATION_ANNOTATIONS=${CM_DATASET_CALIBRATION_ANNOTATIONS_FILE_PATH} | ||
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| export CALIBRATION_DATA_DIR=${CM_CALIBRATION_DATASET_PATH} | ||
| export MODEL_CHECKPOINT=${CM_ML_MODEL_FILE_WITH_PATH} | ||
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| cd ${CM_HARNESS_CODE_ROOT} | ||
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| bash run_calibration.sh | ||
| test "$?" -eq 0 || exit "$?" |
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50 changes: 50 additions & 0 deletions
50
script/app-mlperf-inference-intel/run_retinanet_harness.sh
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| #!/bin/bash | ||
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| CPUS_PER_INSTANCE=8 | ||
| number_threads=`nproc --all` | ||
| export number_cores=`lscpu -b -p=Core,Socket | grep -v '^#' | sort -u | wc -l` | ||
| number_sockets=`grep physical.id /proc/cpuinfo | sort -u | wc -l` | ||
| cpu_per_socket=$((number_cores/number_sockets)) | ||
| number_instance=$((number_cores/CPUS_PER_INSTANCE)) | ||
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| WORKERS_PER_PROC=${WORKERS_PER_PROC:-4} | ||
| THREADS_PER_INSTANCE=$((( ${WORKERS_PER_PROC} * ${CM_HOST_CPU_THREADS_PER_CORE}) / ${CM_HOST_CPU_SOCKETS})) | ||
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| export LD_PRELOAD=${CONDA_PREFIX}/lib/libjemalloc.so | ||
| export LD_PRELOAD=${CONDA_PREFIX}/lib/libiomp5.so | ||
| export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000"; | ||
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| KMP_SETTING="KMP_AFFINITY=granularity=fine,compact,1,0" | ||
| export KMP_BLOCKTIME=1 | ||
| export $KMP_SETTING | ||
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| export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${CONDA_PREFIX}/lib | ||
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| executable="${CM_HARNESS_CODE_ROOT}/build/bin/mlperf_runner" | ||
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| number_threads=`nproc --all` | ||
| export number_cores=`lscpu -b -p=Core,Socket | grep -v '^#' | sort -u | wc -l` | ||
| num_numa=$(numactl --hardware|grep available|awk -F' ' '{ print $2 }') | ||
| num_instance=$(($number_cores / $THREADS_PER_INSTANCE)) | ||
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| scenario=${CM_MLPERF_LOADGEN_SCENARIO} | ||
| OUTDIR="${CM_MLPERF_OUTPUT_DIR}" | ||
| scenario="Offline" | ||
| #python ../../user_config.py | ||
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| #--warmup_iters 20 \ | ||
| CONFIG=" --scenario ${scenario} --mode ${LOADGEN_MODE} --model_name retinanet \ | ||
| --model_path ${MODEL_PATH} \ | ||
| --data_path ${DATA_DIR} \ | ||
| --mlperf_conf ${CM_MLPERF_CONF} --user_conf ${CM_MLPERF_USER_CONF} \ | ||
| --cpus_per_instance $CPUS_PER_INSTANCE \ | ||
| --num_instance $number_instance \ | ||
| --total_sample_count 24781 \ | ||
| --batch_size 1 | ||
| " | ||
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| cmd=" ${executable} ${CONFIG}" | ||
| echo "$cmd" | ||
| eval "$cmd" | ||
| test "$?" -eq 0 || exit "$?" |
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