Omar Jamil

science * data

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I have been developing a machine learning model in Tensorflow 2.0, but because I need to have some custom functionality I am taking a more manual approach instead of full Keras API e.g. see https://www.tensorflow.org/tutorials/quickstart/advanced . One thing that was not clear to me was what algorithm does Keras use when you pass in the option metric=['acc'] to model.compile(). It turns out Keras does clever things and works out the appropriate metric based on your data. If you do not want…

Where I work, the compute clusters have been upgraded to RedHat Eneterprise Linux 7 (RHEL7). I therefore needed to rebuild Tensorflow. I have to build because the standard pip install binaries do not work on these systems as the glibc version is 2.17 on RHEL 7 while Tensorflow >= v1.14 need glibc 2.23. (See my RHEL6 post)

TensorFlow binaries do not work on RHEL6 because they require GLIBC 2.17. The system version is 2.12. Therefore you need to build Tensorflow. (Having another glibc on the system is just painful.) That still requires a few tricks.

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A scientist using Machine Learning to do Physics