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Hello - I have been struggling to find a solution online and I hope you can help me timely. I have installed the latest tesnorflow and tensorflow-metal, I even went to install the ternsorflow-nightly. My app generates the following as a result of my fit function on a CNN model with 8 layers. 2023-09-29 22:21:06.115768: I metal_plugin/src/device/metal_device.cc:1154] Metal device set to: Apple M1 Pro 2023-09-29 22:21:06.115846: I metal_plugin/src/device/metal_device.cc:296] systemMemory: 16.00 GB 2023-09-29 22:21:06.116048: I metal_plugin/src/device/metal_device.cc:313] maxCacheSize: 5.33 GB 2023-09-29 22:21:06.116264: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support. 2023-09-29 22:21:06.116483: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: ) Most importantly, the learning process is very slow and I'd like to take advantage of al the new features of the latest versions. What can I do?

I needed to use Legacy Optimizers for Adam. I get the following warnings from the sample code provided 2023-04-14 06:54:56.121557: W tensorflow/tsl/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz /Users/bridgelineIT/miniconda3/envs/ekbase/lib/python3.8/site-packages/keras/backend.py:5612: UserWarning: "sparse_categorical_crossentropy received from_logits=True, but the output argument was produced by a Softmax activation and thus does not represent logits. Was this intended? output, from_logits = _get_logits(