i do not plan on publishing app.
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Yes but I'd like to know what it means :)
you might enjoy some of my code here using dataset (currently under intense development) : https://github.com/ker2x/recolorizeNN/blob/master/main.py
Caching, prefetching, lot of stuff here and there trying to get things faster.
Yes, this numpy version requirement can be a great source of troubles.
Tensorflow won't work with a higher version.
There was a post about it and apple answered that this was the version recommended by Tensorflow so they just followed the recommandation.
i have more now. I have some particularly bad result on some epoch, just like your. weird.
yes. tf.random is broken on 12.1
It's on a M1. don't use pip when dealing with Tensorflow as it's suppose to be installed using miniforge3
it's also worth adding that that simple/tiny model works faster on M1 cpu than gpu (even a discrete gpu). The google's TPU powerhouse is even more slower than anything on small model. The M1 CPU is surprisingly fast on small ML model.
you're welcome :)
models running faster on CPU than GPU is a very common occurence, it's not Mac specific. If there is a bug, identify it. saying that a cpu can be faster than gpu is not a bug, it's extremely common. It depend on the model, the cpu, the gpu, the input pipeline, etc ... I've also had the M1 CPU running faster than on a badass Nvidia Quadro or even a Nvidia P100. The M1 cpu is surprisingly good at this.
it works on 3.9 too (not sure if it worked on 3.9 when you posted this a month ago. But as of today, it works)
it doesn't works in a tf.function, it used to works, before 12.1, and a lot of exemple/guide/tutorial relying on random doesn't works anymore