_joker
March 26, 2020, 2:13am
#1
I am getting this error only during the testing phase, but I do not face any problem in the training and validation phase.

The code snippet looks like the one below,

The “lab” is a tensor value and prints out the range in such a way,

```
tensor([6, 7, 8])
tensor([ 9, 10, 11])
tensor([21, 22, 23])
```

(Note*: the length of this lab tensor can be of length ‘n’ based on the value of ElementsPerClass)

1 Like

Could you check, if `lab`

is an empty tensor at one point?
This would yield the same error message and since it’s calculated by `torch.arange`

this might happen, if `start`

and `end`

have equal values.

_joker
March 26, 2020, 6:31am
#3
I am testing for NumRows = 10 that is, ElementsPerClass = 1
This gives lab as single value tensors on every iteration like,

```
tensor([1])
tensor([4])
tensor([7])
```

as I want a single tile of masking for self.mem_dim = 10