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metrics: Add Tensorflow ResNet50 int8 benchmark
This PR adds the Tensorflow ResNet50 int8 script for kata metrics. Fixes #7652 Signed-off-by: Gabriela Cervantes <gabriela.cervantes.tellez@intel.com>
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tests/metrics/machine_learning/tensorflow_resnet50_int8.sh
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155
tests/metrics/machine_learning/tensorflow_resnet50_int8.sh
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#!/bin/bash
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#
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# Copyright (c) 2023 Intel Corporation
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#
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# SPDX-License-Identifier: Apache-2.0
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set -o pipefial
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# General env
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SCRIPT_PATH=$(dirname "$(readlink -f "$0")")
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source "${SCRIPT_PATH}/../lib/common.bash"
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IMAGE="docker.io/library/resnet50int8:latest"
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DOCKERFILE="${SCRIPT_PATH}/resnet50_int8/Dockerfile"
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tensorflow_file=$(mktemp tensorflowresults.XXXXXXXXXX)
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NUM_CONTAINERS="$1"
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TIMEOUT="$2"
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TEST_NAME="tensorflow-resnet50int8"
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PAYLOAD_ARGS="tail -f /dev/null"
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TESTDIR="${TESTDIR:-/testdir}"
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# Options to control the start of the workload using a trigger-file
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dst_dir="/host"
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src_dir=$(mktemp --tmpdir -d tensorflowresnet50int8.XXXXXXXXXX)
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MOUNT_OPTIONS="type=bind,src=$src_dir,dst=$dst_dir,options=rbind:ro"
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start_script="resnet50_start.sh"
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# CMD points to the script that starts the workload
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# export DNNL_MAX_CPU_ISA=AVX512_CORE_AMX
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CMD="export KMP_AFFINITY=granularity=fine,verbose,compact && export OMP_NUM_THREADS=16 && $dst_dir/$start_script"
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guest_trigger_file="$dst_dir/$trigger_file"
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host_trigger_file="$src_dir/$trigger_file"
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INITIAL_NUM_PIDS=1
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CMD_FILE="cat results | grep 'Throughput' | wc -l"
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CMD_RESULTS="cat results | grep 'Throughput' | cut -d':' -f2 | cut -d' ' -f2 | tr '\n' ','"
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function remove_tmp_file() {
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rm -rf "${tensorflow_file}"
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}
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trap remove_tmp_file EXIT
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function help() {
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cat << EOF
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Usage: $0 <count> <timeout>
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Description:
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This script launches n number of containers
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to run the ResNet50 int8 using a Tensorflow
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container.
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Options:
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<count> : Number of containers to run.
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<timeout> : Timeout to launch the containers.
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EOF
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}
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function create_start_script() {
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local script="${src_dir}/${start_script}"
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rm -rf "${script}"
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cat <<EOF >>"${script}"
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#!/bin/bash
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python3.8 models/benchmarks/launch_benchmark.py --benchmark-only --framework tensorflow --model-name resnet50 --precision int8 --mode inference --in-graph /resnet50_int8_pretrained_model.pb --batch-size 116 --num-intra-threads 16 >> results
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EOF
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chmod +x "${script}"
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}
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function resnet50_int8_test() {
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info "Running ResNet50 Int8 Tensorflow test"
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local pids=()
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local j=0
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for i in "${containers[@]}"; do
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$(sudo -E "${CTR_EXE}" t exec --exec-id "$(random_name)" "${i}" sh -c "${CMD}")&
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pids["${j}"]=$!
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((j++))
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done
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# wait for all pids
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for pid in ${pids[*]}; do
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wait "${pid}"
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done
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touch "${host_trigger_file}"
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info "All containers are running the workload..."
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collect_results "${CMD_FILE}"
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for i in "${containers[@]}"; do
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sudo -E "${CTR_EXE}" t exec --exec-id "$(random_name)" "${i}" sh -c "${CMD_RESULTS}" >> "${tensorflow_file}"
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done
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local resnet50_int8_results=$(cat "${tensorflow_file}" | sed 's/.$//')
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local average_resnet50_int8=$(echo "${resnet50_int8_results}" | sed 's/.$//'| sed "s/,/+/g;s/.*/(&)\/2/g" | bc -l)
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local json="$(cat << EOF
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{
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"ResNet50Int8": {
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"Result": "${resnet50_int8_results}",
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"Average": "${average_resnet50_int8}",
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"Units": "images/s"
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}
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}
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EOF
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)"
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metrics_json_add_array_element "$json"
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metrics_json_end_array "Results"
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}
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function main() {
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# Verify enough arguments
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if [ $# != 2 ]; then
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echo >&2 "error: Not enough arguments [$@]"
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help
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exit 1
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fi
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local i=0
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local containers=()
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local not_started_count="${NUM_CONTAINERS}"
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# Check tools/commands dependencies
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cmds=("awk" "docker" "bc")
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check_cmds "${cmds[@]}"
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check_ctr_images "${IMAGE}" "${DOCKERFILE}"
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init_env
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create_start_script
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info "Creating ${NUM_CONTAINERS} containers"
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for ((i=1; i<= "${NUM_CONTAINERS}"; i++)); do
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containers+=($(random_name))
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sudo -E "${CTR_EXE}" run -d --runtime "${CTR_RUNTIME}" --mount="${MOUNT_OPTIONS}" "${IMAGE}" "${containers[-1]}" sh -c "${PAYLOAD_ARGS}"
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((not_started_count--))
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info "$not_started_count remaining containers"
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done
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metrics_json_init
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metrics_json_start_array
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# Check that the requested number of containers are running
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check_containers_are_up "${NUM_CONTAINERS}"
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# Check that the requested number of containers are running
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check_containers_are_running "${NUM_CONTAINERS}"
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# Get the initial number of pids in a single container before the workload starts
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INITIAL_NUM_PIDS=$(sudo -E "${CTR_EXE}" t metrics "${containers[-1]}" | grep pids.current | grep pids.current | xargs | cut -d ' ' -f 2)
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((INITIAL_NUM_PIDS++))
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resnet50_int8_test
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metrics_json_save
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sudo rm -rf "${src_dir}"
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clean_env_ctr
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}
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main "$@"
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