Looks like the version of Python matters.
My environment: MacBook Pro 14-inch, 2021, M1 Pro, 16 GB
Using this code example
I've created two different virtual environments:
Python 3.8.19
Python 3.11.9
Results
Python 3.8 (CPU)
Epoch 1/5
782/782 [==============================] - 403s 513ms/step - loss: 4.8157 - accuracy: 0.0648
Python 3.8 (GPU)
Epoch 1/5
2024-07-22 21:35:48.809586: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled.
782/782 [==============================] - 64s 77ms/step - loss: 4.9219 - accuracy: 0.0574
Python 3.11 (CPU)
Epoch 1/5
782/782 ━━━━━━━━━━━━━━━━━━━━ 435s 544ms/step - accuracy: 0.0480 - loss: 5.0793
Python 3.11 (GPU)
Epoch 1/5
2024-07-22 21:48:42.497240: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:117] Plugin optimizer for device_type GPU is enabled.
782/782 ━━━━━━━━━━━━━━━━━━━━ 412s 472ms/step - accuracy: 0.0487 - loss: 5.1804
I did not include the results for Python versions between 3.8 and 3.11, but the behavior is the same: slow. It looks like tensorflow-metal utilizes the Apple Silicon GPU well only in Python 3.8 🤷♂️
itwasme
Users receive reputation points by contributing quality content to the forums.
Posts include post and replies published on the forums.
Post authors can mark replies as Accepted to indicate successful solutions.
Apple Developer Forums admins can mark replies as Apple Recommended to indicate an approved solution
Last seen