How to average summaries over multiple batches?

Question

Assuming I have a bunch of summaries defined like:

loss = ...
tf.scalar_summary(\"loss\", loss)
# ...
summaries = tf.m         


        

Answer 1

You can average store the current sum and recalculate the average after each batch, like:

loss_sum = tf.Variable(0.)
inc_op = tf.assign_add(loss_sum, loss)
clear_op = tf.assign(loss_sum, 0.)
average = loss_sum / batches
tf.scalar_summary("average_loss", average)

sess.run(clear_op)
for i in range(batches):
    sess.run([loss, inc_op])

sess.run(average)