"avg_cost" why accumulated by batch_loss/total_batch, instead of batch_loss/batch_size ?

[Harryhaha]

in the file https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/2_BasicModels/logistic_regression.py
When compute the value of cost and avg_cost :

with tf.Session() as sess:
sess.run(init)
# Training cycle
for epoch in range(training_epochs):
avg_cost = 0.
total_batch = int(mnist.train.num_examples/batch_size)
# Loop over all batches
for i in range(total_batch):
batch_xs, batch_ys = mnist.train.next_batch(batch_size)
# Fit training using batch data
_, c = sess.run([optimizer, cost], feed_dict={x: batch_xs,
y: batch_ys})
# Compute average loss
avg_cost += c / total_batch

When accumulate "avg_cost", why added by c/total_batch, instead of c/batch_size ?
Since "avg_cost" is the average cost for each instance.

Thanks !!!