reejs VS tensorflow

GitHub - rovelstars/reejs

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@renhiyama - Reejs wants you to "Make Sites Faster, without the need of building anything!"

If we don't spend much time thinking over this security, (and if you really think that much, consider selfhosting esm.sh or your own server for your needs...) let me show you how much storage I saved by converting a Nextjs project to My Framework Ree.js, and it used URL Imports to achieve such less storage!

When We first made our own implementation of URL Imports for Ree.js we learnt a simple hack from here that was based using experimental tags.

URL Imports (we welcome PRs and Issues over https://github.com/rovelstars/reejs)

# 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 ⭐

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? :)