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[Solved] TensorFlow – Importing data from a TensorBoard TFEvent file?

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error TensorFlow – Importing data from a TensorBoard TFEvent file? in python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How TensorFlow – Importing data from a TensorBoard TFEvent file Error Occurs?

Today I get the following error TensorFlow – Importing data from a TensorBoard TFEvent file? in python.

How To Solve TensorFlow – Importing data from a TensorBoard TFEvent file Error ?

  1. How To Solve TensorFlow – Importing data from a TensorBoard TFEvent file Error ?

    To Solve TensorFlow – Importing data from a TensorBoard TFEvent file Error To read a TFEvent you can get a Python iterator that yields Event protocol buffers.

  2. TensorFlow – Importing data from a TensorBoard TFEvent file?

    To Solve TensorFlow – Importing data from a TensorBoard TFEvent file Error To read a TFEvent you can get a Python iterator that yields Event protocol buffers.

Solution 1

As Fabrizio says, TensorBoard is a great tool for visualizing the contents of your summary logs. However, if you want to perform a custom analysis, you can use tf.train.summary_iterator() function to loop over all of the tf.Event and tf.Summary protocol buffers in the log:

for summary in tf.train.summary_iterator("/path/to/log/file"):
    # Perform custom processing in here.

UPDATE for tf2:

from tensorflow.python.summary.summary_iterator import summary_iterator

You need to import it, that module level is not currently imported by default. On 2.0.0-rc2

Solution 2

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)

Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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