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metrics: Update machine learning documentation
This PR updates the machine learning documentation related with Tensorflow and Pytorch benchmarks. Fixes #7359 Signed-off-by: Gabriela Cervantes <gabriela.cervantes.tellez@intel.com>
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Kata Containers provides a series of performance tests using the
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TensorFlow reference benchmarks (tf_cnn_benchmarks).
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The tf_cnn_benchmarks containers TensorFlow implementations of several
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popular convolutional models.
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popular convolutional models https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks.
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Currently the TensorFlow benchmark on Kata Containers includes test for
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the `AxelNet` and `ResNet50` models.
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## Running the test
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@ -15,9 +18,9 @@ $ ./tensorflow.sh 25 60
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```
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# Kata Containers Pytorch Metrics
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Kata Containers provides a series of performance tests using Pytorch
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benchmarks based on a suite of Python high performance computing
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benchmarks.
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Based on a suite of Python high performance computing benchmarks that
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uses various popular Python HPC libraries using Python
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https://github.com/dionhaefner/pyhpc-benchmarks.
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## Running the Pytorch test
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