def _build_localization_loss(loss_config):
"""Builds a localization loss based on the loss config.
Args:
loss_config: A losses_pb2.LocalizationLoss object.
Returns:
Loss based on the config.
Raises:
ValueError: On invalid loss_config.
"""
if not isinstance(loss_config, losses_pb2.LocalizationLoss):
raise ValueError('loss_config not of type losses_pb2.LocalizationLoss.')
loss_type = loss_config.WhichOneof('localization_loss')
if loss_type == 'weighted_l2':
return losses.WeightedL2LocalizationLoss()
if loss_type == 'weighted_smooth_l1':
return losses.WeightedSmoothL1LocalizationLoss(
loss_config.weighted_smooth_l1.delta)
if loss_type == 'weighted_iou':
return losses.WeightedIOULocalizationLoss()
raise ValueError('Empty loss config.')
def testReturnsCorrectLoss(self):
prediction_tensor = tf.constant([[[1.5, 0, 2.4, 1], [0, 0, 1, 1],
[0, 0, .5, .25]]])
target_tensor = tf.constant([[[1.5, 0, 2.4, 1], [0, 0, 1, 1],
[50, 50, 500.5, 100.25]]])
weights = [[1.0, .5, 2.0]]
loss_op = losses.WeightedIOULocalizationLoss()
loss = loss_op(prediction_tensor, target_tensor, weights=weights)
exp_loss = 2.0
with self.test_session() as sess:
loss_output = sess.run(loss)
self.assertAllClose(loss_output, exp_loss)