Thanks a lot for replying … excuse me confirm just i got the point or not please …
i read the links and got to measure the time and memory consumption, i need to add those lines to my model

run_metadata = tf.RunMetadata()
with tf.Session() as sess:
_ = sess.run(train_op,
options=tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE),
run_metadata=run_metadata)

after the model finished , i should run tf.profiler.profile  ?
what if i finished the training stages and got the final file with h5 at epoch 20 … is there another way to measure time and memory instead start training again