tf.compat.v1.train.summary_iterator  |  TensorFlow v2.16.1 (original) (raw)

tf.compat.v1.train.summary_iterator

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

tf.compat.v1.train.summary_iterator(
    path
)

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(tf.make_ndarray(v.tensor))

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(tf.make_ndarray(v.tensor))
  # Wait for a bit before checking the file for any new events
  time.sleep(wait time)

See the protocol buffer definitions ofEventandSummaryfor more information about their attributes.

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Last updated 2024-04-26 UTC.