Dear Neel,



 Neel-Gupta:

Metal Device set to: AMD Radeo Pro 5500M


I am sorry that I forgot to mention that I am using MacBook Pro 16". And this machine is intel CPU & AMD gpu, not M1.
I built a CNN model to test the device with the cifar10 dataset.
Here is time-consuming for each epoch with AMD GPU,
112] Plugin optimizer for device_type GPU is enabled.
1667/1667 [==============================] - 49s 27ms/step - loss: 1.3462 - sparse_categorical_accuracy: 0.5124
Epoch 2/5
1667/1667 [==============================] - 47s 28ms/step - loss: 0.8867 - sparse_categorical_accuracy: 0.6872
Epoch 3/5
1667/1667 [==============================] - 50s 30ms/step - loss: 0.7183 - sparse_categorical_accuracy: 0.7503
Epoch 4/5
1667/1667 [==============================] - 56s 33ms/step - loss: 0.6007 - sparse_categorical_accuracy: 0.7901
Epoch 5/5
1667/1667 [==============================] - 53s 32ms/step - loss: 0.5020 - sparse_categorical_accuracy: 0.8227
Out[3]: <tensorflow.python.keras.callbacks.History at 0x169216af0>

And here is for CPU,
Epoch 1/5
1667/1667 [==============================] - 285s 170ms/step - loss: 1.3755 - sparse_categorical_accuracy: 0.5024
Epoch 2/5
1667/1667 [==============================] - 283s 170ms/step - loss: 0.9136 - sparse_categorical_accuracy: 0.6782
Epoch 3/5
  23/1667 [..............................] - ETA: 4:38 - loss: 0.7261 - sparse_categorical_accuracy: 0.7333
---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)

Sincerely,