Running Keras model in eager execution causes most of the ops to be placed on the host instead of device. Obviously, it causes eager execution to be much slower. Is it some issue, or that’s how eager execution works?
TensorFlow Profiler output:
Code : keras-io/mnist_convnet.py at master · keras-team/keras-io · GitHub

Same code with run_eagerly=True in the model.compile().

system: 5.10.42-1-MANJARO
version: tensorflow 2.5 (Manjaro repository)