I'll add that like others, python 3.8.X is required.
Then run:
SYSTEM_VERSION_COMPAT=0 python -m pip install tensorflow-macos
(this will give you tensorflow-macos version 2.7 - don't get excited yet)
SYSTEM_VERSION_COMPAT=0 python -m pip install tensorflow-metal
(this will also succeed)
Install your other stuff as normal with conda (pandas, scikit-learn, jupyterlab, etc)
Then run your code. You can run:
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
Num GPUs Available: 1
So far so good right?!?! Looking Good!
Now run your model...
First line:
Metal device set to: AMD Radeon Pro 5600M
keeps looking better and better !!!
and then the kernel dies...
2022-01-13 17:02:36.447465: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2022-01-13 17:02:36.448221: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support. 2022-01-13 17:02:36.448581: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] 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: <undefined>)
Will tensorflow-macos ever work for Intel ?
hey hawkiyc, if you resolve the issue, please share with me how. cuz i am facing that issue rn.