def __init__(self,
plans_file,
fold,
output_folder=None,
dataset_directory=None,
batch_dice=True,
stage=None,
unpack_data=True,
deterministic=True,
fp16=False):
super(nnUNetTrainerWCET0,
self).__init__(plans_file, fold, output_folder,
dataset_directory, batch_dice, stage, unpack_data,
deterministic, fp16)
self.weight = torch.cuda.FloatTensor(
[1.0, 42.8]) # pre-defined according to the task
self.loss = WeightedCrossEntropyLoss(self.weight)
def __init__(self, soft_dice_kwargs, wce_kwargs, gamma=0.3):
super(ExpLog_loss, self).__init__()
self.wce = WeightedCrossEntropyLoss(**wce_kwargs)
self.dc = SoftDiceLoss(apply_nonlin=softmax_helper, **soft_dice_kwargs)
self.gamma = gamma