Hi,
You can concatenate the two tensors and then do a random shuffle on the combined tensor.
Assuming that the torch tensor containing the positive examples is t1 and that of negative examples is t2, you can do something like this,
t1 = torch.cat((t1, t2), dim=0) # dim=0 assumes that your first axis is the batch axis. data = t1[torch.randperm(t1.size()[0])] # Shuffle the data
Hope this helps,
Cheers!