Intel TensorFlow 1.0.0

pts/intel-tensorflow-1.0.0 - 28 April 2023 - Initial commit of Intel optimized TensorFlow for CPU benchmarking.

downloads.xml

<?xml version="1.0"?>
<!--Phoronix Test Suite v10.8.4-->
<PhoronixTestSuite>
  <Downloads>
    <Package>
      <URL>https://github.com/IntelAI/models/archive/92bc6044e5047a2ca55920d9cfec3bcf9a8bf23d.zip</URL>
      <MD5>bf93e9b2843aa26d7d9cdff90972fe8d</MD5>
      <SHA256>97fe718a428255f9350d788973a29d3f7c27c572e3107be45128f4b9160261f3</SHA256>
      <FileName>models-92bc6044e5047a2ca55920d9cfec3bcf9a8bf23d.zip</FileName>
      <FileSize>15428101</FileSize>
    </Package>
    <Package>
      <URL>https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_val.tar</URL>
      <MD5>29b22e2961454d5413ddabcf34fc5622</MD5>
      <SHA256>c7e06a6c0baccf06d8dbeb6577d71efff84673a5dbdd50633ab44f8ea0456ae0</SHA256>
      <FileName>ILSVRC2012_img_val.tar</FileName>
      <FileSize>6744924160</FileSize>
    </Package>
    <Package>
      <URL>https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_train.tar</URL>
      <MD5>1d675b47d978889d74fa0da5fadfb00e</MD5>
      <SHA256>b08200a27a8e34218a0e58fde36b0fe8f73bc377f4acea2d91602057c3ca45bb</SHA256>
      <FileName>ILSVRC2012_img_train.tar</FileName>
      <FileSize>147897477120</FileSize>
    </Package>
    <Package>
      <URL>https://storage.googleapis.com/intel-optimized-tensorflow/models/v1_8/resnet50_fp32_pretrained_model.pb</URL>
      <MD5>a996cd05e84cbaf37016b0dd7479d714</MD5>
      <SHA256>cade1dd9868e545600c39eb97ba4789524b3b2f7a3d1a63fe6da2f81387c084d</SHA256>
      <FileName>resnet50_fp32_pretrained_model.pb</FileName>
      <FileSize>102559229</FileSize>
    </Package>
    <Package>
      <URL>https://storage.googleapis.com/intel-optimized-tensorflow/models/v1_8/resnet50_int8_pretrained_model.pb</URL>
      <MD5>87c686ac9d6207b4349be152600728a2</MD5>
      <SHA256>26b3a05e79845ad465552bc2f133fd4591fb52c656b8b7367d459a9028582a2c</SHA256>
      <FileName>resnet50_int8_pretrained_model.pb</FileName>
      <FileSize>31868512</FileSize>
    </Package>
    <Package>
      <URL>https://storage.googleapis.com/intel-optimized-tensorflow/models/v1_8/inceptionv4_int8_pretrained_model.pb</URL>
      <MD5>ff6ff7a881062f4f361dcf07fd72dc1c</MD5>
      <SHA256>e17b1bdc20e8010f8e2fe0e865d3d994ca8c1a57667a1cfa7518ee403e9ea218</SHA256>
      <FileName>inceptionv4_int8_pretrained_model.pb</FileName>
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      <SHA256>94620d8eaad875053b904700d12ab4c366a912522e7c446121c289216b485f67</SHA256>
      <FileName>inceptionv4_fp32_pretrained_model.pb</FileName>
      <FileSize>170760381</FileSize>
    </Package>
    <Package>
      <URL>https://storage.googleapis.com/intel-optimized-tensorflow/models/2_10_0/mobilenetv1_fp32_pretrained_model.pb</URL>
      <MD5>42e61d4fbe639e3a282a421c181a5d9e</MD5>
      <SHA256>853d9c7d71280e1589fd61b527bb8f5dda36f6108ea8c0bad9aafa6973c097ee</SHA256>
      <FileName>mobilenetv1_fp32_pretrained_model.pb</FileName>
      <FileSize>16913065</FileSize>
    </Package>
    <Package>
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      <SHA256>f5a53a7b81ec130c6c7330c41d9241609c2af0e97dff839623c53c5f59577503</SHA256>
      <FileName>mobilenetv1_int8_pretrained_model.pb</FileName>
      <FileSize>4399013</FileSize>
    </Package>
  </Downloads>
</PhoronixTestSuite>

install.sh

#!/bin/sh
# imagenet URLs @ https://gist.github.com/bonlime/4e0d236cf98cd5b15d977dfa03a63643
pip3 install --user intel-tensorflow==2.12
unzip -o models-92bc6044e5047a2ca55920d9cfec3bcf9a8bf23d.zip 

if [ ! -d "imageraw" ] 
then
	mkdir imageraw
	cd imageraw
	ln -s ../ILSVRC2012_img_val.tar ILSVRC2012_img_val.tar
	ln -s ../ILSVRC2012_img_train.tar ILSVRC2012_img_train.tar
	~/models-92bc6044e5047a2ca55920d9cfec3bcf9a8bf23d/datasets/imagenet/imagenet_to_tfrecords.sh ~/imageraw/
	cd ~
fi

echo "#!/bin/bash
cd ~/models-92bc6044e5047a2ca55920d9cfec3bcf9a8bf23d/
export PRETRAINED_MODEL=\$HOME/\$1
export DATASET_DIR=~/imageraw/tf_records/
if [[ \$PRETRAINED_MODEL == *\"int8\"* ]]; then
  export PRECISION=int8
else
  export PRECISION=fp32
fi
if [[ \$PRETRAINED_MODEL == *\"resnet\"* ]]; then
  export SCRIPT_CMD=resnet50/inference/cpu/batch_inference.sh
elif [[ \$PRETRAINED_MODEL == *\"inceptionv4\"* ]]; then
  export SCRIPT_CMD=inceptionv4/inference/cpu/batch_inference.sh
elif [[ \$PRETRAINED_MODEL == *\"mobilenetv1\"* ]]; then
  export SCRIPT_CMD=mobilenet_v1/inference/cpu/inference_throughput_multi_instance.sh
else
  echo \"ERROR: No matching type\" > \$LOG_FILE
  echo 2 > ~/test-exit-status
  exit 2
fi
export OUTPUT_DIR=/tmp
export BATCH_SIZE=\$2

if [ \"\${BATCH_SIZE}\" -eq 1 ] && [[ \$PRETRAINED_MODEL == *\"mobilenetv1\"* ]]; then
  export SCRIPT_CMD=mobilenet_v1/inference/cpu/inference_realtime_multi_instance.sh
fi
./quickstart/image_recognition/tensorflow/\$SCRIPT_CMD > \$LOG_FILE 2>&1
echo \$? > ~/test-exit-status" > intel-tensorflow
chmod +x intel-tensorflow

results-definition.xml

<?xml version="1.0"?>
<!--Phoronix Test Suite v10.8.4-->
<PhoronixTestSuite>
  <ResultsParser>
    <OutputTemplate>Throughput: #_RESULT_# images/sec</OutputTemplate>
    <LineHint>Throughput:</LineHint>
    <ResultScale>images/sec</ResultScale>
    <ResultProportion>HIB</ResultProportion>
  </ResultsParser>
  <ResultsParser>
    <OutputTemplate>Summary total images/sec:
#_RESULT_#</OutputTemplate>
    <LineBeforeHint>Summary total images/sec</LineBeforeHint>
    <ResultScale>images/sec</ResultScale>
    <ResultProportion>HIB</ResultProportion>
  </ResultsParser>
  <ResultsParser>
    <OutputTemplate>steps = 50, #_RESULT_# images/sec</OutputTemplate>
    <MatchToTestArguments>inception</MatchToTestArguments>
    <ResultScale>images/sec</ResultScale>
    <ResultProportion>HIB</ResultProportion>
  </ResultsParser>
  <ResultsParser>
    <OutputTemplate>Latency: #_RESULT_# sec</OutputTemplate>
    <LineHint>Latency:</LineHint>
    <ResultScale>ms</ResultScale>
    <ResultProportion>LIB</ResultProportion>
  </ResultsParser>
</PhoronixTestSuite>

test-definition.xml

<?xml version="1.0"?>
<!--Phoronix Test Suite v10.8.4-->
<PhoronixTestSuite>
  <TestInformation>
    <Title>Intel TensorFlow</Title>
    <AppVersion>2.12</AppVersion>
    <Description>Intel optimized version of TensorFlow with benchmarks of Intel AI models and configurable batch sizes.</Description>
    <ResultScale>images/sec</ResultScale>
    <Proportion>HIB</Proportion>
    <TimesToRun>3</TimesToRun>
  </TestInformation>
  <TestProfile>
    <Version>1.0.0</Version>
    <SupportedPlatforms>Linux</SupportedPlatforms>
    <SoftwareType>Utility</SoftwareType>
    <TestType>System</TestType>
    <License>Free</License>
    <Status>Verified</Status>
    <ExternalDependencies>python, build-utilities</ExternalDependencies>
    <EnvironmentSize>1800</EnvironmentSize>
    <ProjectURL>https://pypi.org/project/intel-tensorflow/</ProjectURL>
    <RepositoryURL>https://github.com/IntelAI/models</RepositoryURL>
    <Maintainer>Michael Larabel</Maintainer>
    <RemoveInstallDirectoryOnReinstall>FALSE</RemoveInstallDirectoryOnReinstall>
    <SystemDependencies>numactl</SystemDependencies>
  </TestProfile>
  <TestSettings>
    <Option>
      <DisplayName>Model</DisplayName>
      <Identifier>model</Identifier>
      <Menu>
        <Entry>
          <Name>resnet50_fp32_pretrained_model</Name>
          <Value>resnet50_fp32_pretrained_model.pb</Value>
        </Entry>
        <Entry>
          <Name>resnet50_int8_pretrained_model</Name>
          <Value>resnet50_int8_pretrained_model.pb</Value>
        </Entry>
        <Entry>
          <Name>inceptionv4_fp32_pretrained_model</Name>
          <Value>inceptionv4_fp32_pretrained_model.pb</Value>
        </Entry>
        <Entry>
          <Name>inceptionv4_int8_pretrained_model</Name>
          <Value>inceptionv4_int8_pretrained_model.pb</Value>
        </Entry>
        <Entry>
          <Name>mobilenetv1_fp32_pretrained_model</Name>
          <Value>mobilenetv1_fp32_pretrained_model.pb</Value>
        </Entry>
        <Entry>
          <Name>mobilenetv1_int8_pretrained_model</Name>
          <Value>mobilenetv1_int8_pretrained_model.pb</Value>
        </Entry>
      </Menu>
    </Option>
    <Option>
      <DisplayName>Batch Size</DisplayName>
      <Identifier>batch-size</Identifier>
      <Menu>
        <Entry>
          <Name>1</Name>
          <Value>1</Value>
        </Entry>
        <Entry>
          <Name>16</Name>
          <Value>16</Value>
        </Entry>
        <Entry>
          <Name>32</Name>
          <Value>32</Value>
        </Entry>
        <Entry>
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          <Value>64</Value>
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        <Entry>
          <Name>96</Name>
          <Value>96</Value>
        </Entry>
        <Entry>
          <Name>256</Name>
          <Value>256</Value>
        </Entry>
        <Entry>
          <Name>512</Name>
          <Value>512</Value>
        </Entry>
        <Entry>
          <Name>960</Name>
          <Value>960</Value>
        </Entry>
      </Menu>
    </Option>
  </TestSettings>
</PhoronixTestSuite>