Just wanted to add I have tried most combinations of Tensorflow 2.16.1, 2.15, and 2.14, with Pythons 3.9, 3.10 and 3.11, and with conda or pip virtual environments, all with and without tensorflow-metal. The results are always the same, with all moderately complex models I've tried employing convolution and batch normalization total failures with gpu support, and with success under colab or cpu-only Mac configs. The tensorflow install page does suggest this, though they also link to install procedures for the defective tensorflow-metal package. macOS 10.12.6 (Sierra) or later (no GPU support) https://www.tensorflow.org/install

I have added a python file from the Coursera TensorFlow: Advanced Techniques Specialization, class Generative Deep Learning with TensorFlow , Course4, Week3, Assignment 1. This code runs correctly in colab or on local cpu cores, but fails drastically due to obvious untrapped numerical errors on a metal gpu. To reproduce, switch between environments with the two command lines: pip install tensorflow-metal pip uninstall tensorflow-metal Feel free to contact me if you require additional information, thanks! C4W3_Assignment.py