django-helpdesk VS tensorflow

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- Updating and documenting a legacy telecom diagnostics system which processes hundreds of gigabytes of Netscoute data every day

- Upgrading [django-helpdesk](https://github.com/django-helpdesk/django-helpdesk) to use class based views and performing a security audit on accessible endpoints

- Migrating a mid sized organizations server infrastructure from a diverse set of hosts: EC2, Heroku, VPSes to a unified kuberentes cluster, implementing a fully automated and rollback friendly CI/CD system.

- Maintaining, developing and administering a large Django application used for a bike to work event

- Design and implementation of the POSIX device subsystem for Docker 1.0

- Diagnosing a critical and hard to reproduce bug in Elm-lang's runtime.

- Author of [subuser.org](subuser.org]

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django-helpdesk

To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐

Explore here.

Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.

Right but that's not an inherent GPU determinism issue. It's a software issue.

https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.

Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.

Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.

and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:

Exactly what language do you think TensorFlow is written in? :)

You can use Tensorflow's deep learning API for this.

Since you've specifically mentioned ML, here's Tenserflow's GitHub. I'm sure a quick glance through that will change your mind.