I\'ve run several training sessions with different graphs in TensorFlow. The summaries I set up show interesting results in the training and validation. Now, I\'d like to ta
To read a TFEvent you can get a Python iterator that yields Event protocol buffers.
# This example supposes that the events file contains summaries with a
# summary value tag 'loss'. These could have been added by calling
# `add_summary()`, passing the output of a scalar summary op created with
# with: `tf.scalar_summary(['loss'], loss_tensor)`.
for e in tf.train.summary_iterator(path_to_events_file):
for v in e.summary.value:
if v.tag == 'loss' or v.tag == 'accuracy':
print(v.simple_value)
more info: summary_iterator