Twice the time is really nice. For me, is more like ten times.

  
    
    
    Eager execution: Most of the ops are placed on host instead of device General Discussion
  
  
    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 
[tf_profile_graph] 
Same code with run_eagerly=True in the model.compile(). 
[tf_profile_eager] 
system: 5.10.42-1-MANJARO
version: tensorflow 2.5 (Manjaro repository)