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Mobile Neural Network 1.0.1
pts/mnn-1.0.1
- 17 September 2020 -
Add min/max reporting to result parser.
downloads.xml
<?xml version="1.0"?> <!--Phoronix Test Suite v10.0.0m2--> <PhoronixTestSuite> <Downloads> <Package> <URL>http://www.phoronix-test-suite.com/benchmark-files/MNN-20200917.tar.xz</URL> <MD5>3ff6ec706704f5f83c6e4766e40491f6</MD5> <SHA256>547724ab279f2b1a8f83e64d327be7cd17b9ddda17636c64d5a0cdfb9a7ee118</SHA256> <FileName>MNN-20200917.tar.xz</FileName> <FileSize>4831952</FileSize> </Package> </Downloads> </PhoronixTestSuite>
install.sh
#!/bin/sh tar -xf MNN-20200917.tar.xz rm -rf MNN-master mv MNN MNN-master cd MNN-master cd schema ./generate.sh cd .. mkdir build cd build cmake .. -DMNN_BUILD_BENCHMARK=true make -j $NUM_CPU_CORES echo $? > ~/install-exit-status cd ~/ cat>mnn<<EOT #!/bin/sh cd MNN-master/build ./benchmark.out ../benchmark/models/ 1000 100 0 \$NUM_CPU_CORES > \$LOG_FILE echo \$? > ~/test-exit-status EOT chmod +x mnn
results-definition.xml
<?xml version="1.0"?> <!--Phoronix Test Suite v10.0.0m2--> <PhoronixTestSuite> <ResultsParser> <OutputTemplate>[ - ] SqueezeNetV1.0.mnn max = #_MAX_RESULT_# min = #_MIN_RESULT_# avg = #_RESULT_#</OutputTemplate> <LineHint>SqueezeNetV1.0.mnn</LineHint> <StripFromResult>ms</StripFromResult> <ArgumentsDescription>Model: SqueezeNetV1.0</ArgumentsDescription> </ResultsParser> <ResultsParser> <OutputTemplate>[ - ] resnet-v2-50.mnn max = #_MAX_RESULT_# min = #_MIN_RESULT_# avg = #_RESULT_#</OutputTemplate> <LineHint>resnet-v2-50.mnn</LineHint> <StripFromResult>ms</StripFromResult> <ArgumentsDescription>Model: resnet-v2-50</ArgumentsDescription> </ResultsParser> <ResultsParser> <OutputTemplate>[ - ] MobileNetV2_224.mnn max = #_MAX_RESULT_# min = #_MIN_RESULT_# avg = #_RESULT_#</OutputTemplate> <LineHint>MobileNetV2_224.mnn</LineHint> <StripFromResult>ms</StripFromResult> <ArgumentsDescription>Model: MobileNetV2_224</ArgumentsDescription> </ResultsParser> <ResultsParser> <OutputTemplate>[ - ] mobilenet-v1-1.0.mnn max = #_MAX_RESULT_# min = #_MIN_RESULT_# avg = #_RESULT_#</OutputTemplate> <LineHint>mobilenet-v1-1.0.mnn</LineHint> <StripFromResult>ms</StripFromResult> <ArgumentsDescription>Model: mobilenet-v1-1.0</ArgumentsDescription> </ResultsParser> <ResultsParser> <OutputTemplate>[ - ] inception-v3.mnn max = #_MAX_RESULT_# min = #_MIN_RESULT_# avg = #_RESULT_#</OutputTemplate> <LineHint>inception-v3.mnn</LineHint> <StripFromResult>ms</StripFromResult> <ArgumentsDescription>Model: inception-v3</ArgumentsDescription> </ResultsParser> </PhoronixTestSuite>
test-definition.xml
<?xml version="1.0"?> <!--Phoronix Test Suite v10.0.0m2--> <PhoronixTestSuite> <TestInformation> <Title>Mobile Neural Network</Title> <AppVersion>2020-09-17</AppVersion> <Description>MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by ALibaba.</Description> <ResultScale>ms</ResultScale> <Proportion>LIB</Proportion> <TimesToRun>3</TimesToRun> </TestInformation> <TestProfile> <Version>1.0.1</Version> <SupportedPlatforms>Linux</SupportedPlatforms> <SoftwareType>Scientific</SoftwareType> <TestType>System</TestType> <License>Free</License> <Status>Verified</Status> <ExternalDependencies>cmake, build-utilities</ExternalDependencies> <EnvironmentSize>2700</EnvironmentSize> <ProjectURL>https://github.com/alibaba/MNN</ProjectURL> <Maintainer>Michael Larabel</Maintainer> </TestProfile> </PhoronixTestSuite>