def fre_losses(end_points, labels):
with tf.variable_scope('loss'):
loss = 0.0
for _, key in enumerate(end_points):
cost = fre_loss(key, labels)
loss += cost
tf.losses.add_loss(loss)
if loss is not None:
tf.logging.info('Add_loss Done!')
tf.summary.scalar('weights_loss', loss)
def fre_losses(end_points, labels):
loss = 0.0
if len(end_points) < 6:
raise ValueError('Master: lacking of a layers!')
with tf.variable_scope('loss'):
for i, key in enumerate(end_points):
cost = fre_loss(key, labels)
loss += cost
tf.losses.add_loss(loss)
if loss is not None:
tf.logging.info('Add_loss Done!')
tf.summary.scalar('weights_loss', loss)