Search code examples
tensorboardtensorflow2.0

Tensorboard displaying scalar without keras.fit nor estimator in TF2.0

I have read TF 2.0 tutorial: Using TensorBoard with other methods Then I wrote this simple code but seems not working:

import tensorflow as tf

train_loss = tf.keras.metrics.Mean('train_loss', dtype=tf.float32)
test_loss = tf.keras.metrics.Mean('test_loss', dtype=tf.float32)

train_summary_writer = tf.summary.create_file_writer('logs/tr')
test_summary_writer = tf.summary.create_file_writer('logs/ts')

for ep in range(1000):
    train_loss(1*ep) # here I just want to display 1*ep...
    test_loss(2*ep) 
    tf.summary.scalar('trloss', train_loss.result(), step=ep)
    tf.summary.scalar('tsloss', test_loss.result(), step=ep)

%tensorboard --logdir logs

I get (in browser):

No scalar data was found.
Probable causes:

You haven’t written any scalar data to your event files.
TensorBoard can’t find your event files.

Did I miss something?

Solution

  • Answer by myself:

    with train_summary_writer.as_default():
    tf.summary.scalar('trloss', train_loss.result(), step=ep)
with test_summary_writer.as_default():
    tf.summary.scalar('tsloss', test_loss.result(), step=ep)

    It works! But, I couldn't find any proper documentation for this.