tf.compat.v1.train.summary_iterator

Returns a iterator for reading Event protocol buffers from an event file.

You can use this function to read events written to an event file. It returns a Python iterator that yields Event protocol buffers.

Example: Print the contents of an events file.

for e in tf.compat.v1.train.summary_iterator(path to events file):
    print(e)

Example: Print selected summary values.

# 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.compat.v1.summary.scalar('loss', loss_tensor)`.
for e in tf.compat.v1.train.summary_iterator(path to events file):
    for v in e.summary.value:
        if v.tag == 'loss':
            print(v.simple_value)

Example: Continuously check for new summary values.

summaries = tf.compat.v1.train.summary_iterator(path to events file)
while True:
  for e in summaries:
      for v in e.summary.value:
          if v.tag == 'loss':
              print(v.simple_value)
  # Wait for a bit before checking the file for any new events
  time.sleep(wait time)

See the protocol buffer definitions of Event and Summary for more information about their attributes.

Args
path The path to an event file created by a SummaryWriter.
Returns
A iterator that yields Event protocol buffers

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/compat/v1/train/summary_iterator