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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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		| @@ -3,7 +3,10 @@ | ||||
| Kata Containers provides a series of performance tests using the | ||||
| TensorFlow reference benchmarks (tf_cnn_benchmarks). | ||||
| The tf_cnn_benchmarks containers TensorFlow implementations of several | ||||
| popular convolutional models. | ||||
| popular convolutional models https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks. | ||||
|  | ||||
| Currently the TensorFlow benchmark on Kata Containers includes test for | ||||
| the `AxelNet` and `ResNet50` models. | ||||
|  | ||||
| ## Running the test | ||||
|  | ||||
| @@ -15,9 +18,9 @@ $ ./tensorflow.sh 25 60 | ||||
| ``` | ||||
| # Kata Containers Pytorch Metrics | ||||
|  | ||||
| Kata Containers provides a series of performance tests using Pytorch | ||||
| benchmarks based on a suite of Python high performance computing | ||||
| benchmarks. | ||||
| Based on a suite of Python high performance computing benchmarks that | ||||
| uses various popular Python HPC libraries using Python | ||||
|  https://github.com/dionhaefner/pyhpc-benchmarks. | ||||
|  | ||||
| ## Running the Pytorch test | ||||
|  | ||||
|   | ||||
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