AI-Toolbox VS tensorflow

Makes sense. I was just wondering if someone had any comparisons to share. I will create a toy environment in Unreal and compare integrating RL C++ libraries (looking at AI-Toolbox and mlpack) vs using Python with socket communication.

I maintain a repository of many implementations of classical (tabular) RL algorithms [1] which you might enjoy playing with when starting out. I use it for both research and for student projects. The advantage of avoiding NNs when starting out is that it is much simpler to inspect the inner workings of an algorithm to see whether it's working or not.

I'm always happy to help if something is unclear or difficult so feel free to open issues there :)

[1]: https://github.com/Svalorzen/AI-Toolbox

# L2-normalize the encoding tensors image_encoding = tf.math.l2_normalize(image_encoding, axis=1) audio_encoding = tf.math.l2_normalize(audio_encoding, axis=1) # Find euclidean distance between image_encoding and audio_encoding # Essentially trying to detect if the face is saying the audio # Will return nan without the 1e-12 offset due to https://github.com/tensorflow/tensorflow/issues/12071 d = tf.norm((image_encoding - audio_encoding) + 1e-12, ord='euclidean', axis=1, keepdims=True) discriminator = keras.Model(inputs=[image_input, audio_input], outputs=[d], name="discriminator")

[3]: https://github.com/tensorflow/tensorflow/graphs/contributors

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

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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? :)