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October 1, 2022 13:31
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Bash script to execute Bert Base Uncased Model benchmark tests in GCP (multiple threads)
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#!/bin/bash | |
MACHINE_INFO_SCRIPT="onnxruntime/onnxruntime/python/tools/transformers/machine_info.py" | |
BENCHMARK_SCRIPT="onnxruntime/onnxruntime/python/tools/transformers/benchmark.py" | |
ITERATIONS=100 | |
BATCH_SIZE=1 | |
SEQUENCE_LENGTH=128 | |
MODEL_NAME="bert-base-uncased" | |
MODEL_PATH="bert-base-uncased/" | |
TIMESTAMP=$(date "+%Y.%m.%d-%H.%M.%S") | |
python "${MACHINE_INFO_SCRIPT}" | |
for NUM_THREADS in 2 4 8; do | |
export OMP_NUM_THREADS="${NUM_THREADS}" | |
echo "Update OMP_NUM_THREADS TO ${OMP_NUM_THREADS}" | |
# the following values are set in the base image by default | |
# KMP_AFFINITY=granularity=fine,verbose,compact,1,0 | |
# KMP_BLOCKTIME=0 | |
# KMP_INIT_AT_FORK=FALSE | |
# KMP_SETTINGS=1 | |
# Pytorch Model (fp32/int8) | |
python "${BENCHMARK_SCRIPT}" -e torch -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o | |
python "${BENCHMARK_SCRIPT}" -e torch -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o -p int8 | |
# Torchscript Model (fp32/int8) | |
python "${BENCHMARK_SCRIPT}" -e torchscript -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o | |
python "${BENCHMARK_SCRIPT}" -e torchscript -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o -p int8 | |
# Tensorflow Model (fp32/int8) | |
python "${BENCHMARK_SCRIPT}" -e tensorflow -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o | |
python "${BENCHMARK_SCRIPT}" -e tensorflow -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o -p int8 | |
awk '!x[$0]++' ./result.csv > "summary_result_openmp_thread_count_${NUM_THREADS}_${TIMESTAMP}.csv" | |
awk '!x[$0]++' ./fusion.csv > "summary_fusion_openmp_thread_count_${NUM_THREADS}_${TIMESTAMP}.csv" | |
awk '!x[$0]++' ./detail.csv > "summary_detail_openmp_thread_count_${NUM_THREADS}_${TIMESTAMP}.csv" | |
done | |
for NUM_THREADS in 2 4 8; do | |
# onnxruntime version >= 1.8 uses thread pool instead of OMP, so no need to export OMP_NUM_THREADS | |
# unsetting the following env variables is needed for two reasons | |
# 1. The variables are set by default in the base image | |
# 2. It slows down the onnx runtime speed | |
# https://github.com/microsoft/onnxruntime/issues/8385#issuecomment-883154985 | |
unset KMP_AFFINITY | |
unset KMP_BLOCKTIME | |
unset KMP_INIT_AT_FORK | |
unset KMP_SETTINGS | |
# Onnx Runtime Pytorch Model (fp32/int8) | |
python "${BENCHMARK_SCRIPT}" -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o | |
python "${BENCHMARK_SCRIPT}" -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" -o -p int8 | |
# Onnx Runtime TF Model (fp32/int8) | |
python "${BENCHMARK_SCRIPT}" -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" --model_source tf -o | |
python "${BENCHMARK_SCRIPT}" -m "${MODEL_NAME}" --model-path "${MODEL_PATH}" -v -i 1 --overwrite -b "${BATCH_SIZE}" -s "${SEQUENCE_LENGTH}" -t "${ITERATIONS}" -f fusion.csv -r result.csv -d detail.csv -c ./cache_models --onnx_dir ./onnx_models --num_threads "${NUM_THREADS}" --model_source tf -o -p int8 | |
awk '!x[$0]++' ./result.csv >> "summary_result_openmp_thread_count_${NUM_THREADS}_${TIMESTAMP}.csv" | |
awk '!x[$0]++' ./fusion.csv >> "summary_fusion_openmp_thread_count_${NUM_THREADS}_${TIMESTAMP}.csv" | |
awk '!x[$0]++' ./detail.csv >> "summary_detail_openmp_thread_count_${NUM_THREADS}_${TIMESTAMP}.csv" | |
done | |
# Upload results to GCS bucket | |
gsutil cp "summary*" gs://bert-inference-results |
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