rapidpro VS tensorflow

https://github.com/ansible-community/ara/pull/358 https://github.com/b12io/orchestra/pull/830 https://github.com/batiste/django-page-cms/pull/210 https://github.com/carpentries/amy/pull/2130 https://github.com/celery/django-celery/pull/612 https://github.com/django-cms/django-cms/pull/7241 https://github.com/django-oscar/django-oscar/pull/3867 https://github.com/esrg-knights/Squire/pull/253https://github.com/Frojd/django-react-templatetags/pull/64 https://github.com/groveco/django-sql-explorer/pull/474 https://github.com/jazzband/django-silk/pull/550 https://github.com/keras-team/keras/pull/16073 https://github.com/ministryofjustice/cla_backend/pull/773 https://github.com/nitely/Spirit/pull/306 https://github.com/python/pythondotorg/pull/1987 https://github.com/rapidpro/rapidpro/pull/1610 https://github.com/ray-project/ray/pull/22396 https://github.com/saltstack/salt/pull/61647 https://github.com/Swiss-Polar-Institute/project-application/pull/483 https://github.com/UEWBot/dipvis/pull/216

Can you see the problem? Line 572 has implicit string concatenation!

# 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

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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? :)