def setUp(self):
super(SetupLossesTest, self).setUp()
is_train = True
gitapp = controller.GetInputTargetAndPredictedParameters(
self.dp, self.ap, 110, self.stride, self.stitch_patch_size,
self.bp, self.core_model, self.add_head, self.shuffle,
self.num_classes, util.softmax_cross_entropy, is_train)
(self.input_loss_lts,
self.target_loss_lts) = controller.setup_losses(gitapp)
def total_loss(
gitapp: controller.GetInputTargetAndPredictedParameters,
) -> Tuple[tf.Tensor, Dict[str, lt.LabeledTensor], Dict[str, lt.LabeledTensor]]:
"""Get the total weighted training loss."""
input_loss_lts, target_loss_lts = controller.setup_losses(gitapp)
def mean(lts: Dict[str, lt.LabeledTensor]) -> tf.Tensor:
sum_op = tf.add_n([t.tensor for t in lts.values()])
return sum_op / float(len(lts))
# Give the input loss the same weight as the target loss.
input_weight = 0.5
total_loss_op = input_weight * mean(input_loss_lts) + (
1 - input_weight) * mean(target_loss_lts)
tf.summary.scalar('total_loss', total_loss_op)
return total_loss_op, input_loss_lts, target_loss_lts