Using softTreeLoss error

[Muzijiajian]

Hello, I am trying to use softTreeLoss by using following codes:
from nbdt.loss import SoftTreeSupLoss
train_loss_fn = nn.CrossEntropyLoss().cuda()
criterion = SoftTreeSupLoss(criterion=train_loss_fn, dataset='Imagenet1000', tree_supervision_weight=1.0,
hierarchy='induced-efficientnet_b7b')
...
for i, (input, targets) in enumerate(train_loader):
targets = targets.cuda(async=True)
input_var = torch.autograd.Variable(input).cuda()
targets_var = torch.autograd.Variable(targets).cuda()
scores = model(input_var)
loss = criterion(scores, targets_var)

Then it comes the following errors:
File "/gruntdata/semantic-hierarchy-master/neural-backed-decision-trees/nbdt/model.py", line 240, in forward
wnid_to_outputs = self.forward_nodes(outputs)
File "/gruntdata/semantic-hierarchy-master/neural-backed-decision-trees/nbdt/model.py", line 101, in forward_nodes
return self.get_all_node_outputs(outputs, self.nodes)
File "/gruntdata/semantic-hierarchy-master/neural-backed-decision-trees/nbdt/model.py", line 90, in get_all_node_outputs
node_logits = cls.get_node_logits(outputs, node)
File "/gruntdata/semantic-hierarchy-master/neural-backed-decision-trees/nbdt/model.py", line 79, in get_node_logits
for new_label in range(node.num_classes)
File "/gruntdata/semantic-hierarchy-master/neural-backed-decision-trees/nbdt/model.py", line 79, in
for new_label in range(node.num_classes)
AttributeError: 'Tensor' object has no attribute 'T'

[alvinwan]

@Muzijiajian Hm, are you on PyTorch 1.4? https://github.com/alvinwan/neural-backed-decision-trees/blob/master/requirements.txt#L2. Your code looks right, and tensors should definitely support .T for transpose.