I have a very large tensor of shape `(512,3,224,224)`

. I input it to model in batches of 32 and I then save the scores corresponding to the target label which is `2`

. in each iteration, after every slice, the shape of `scores`

changes. Which leads to the following error. What am I doing wrong and how to fix it.

`label = torch.ones(1)*2`

```
def sub_forward(self, x):
x = self.vgg16(x)
x = self.bn1(x)
x = self.linear1(x)
x = self.linear2(x)
return x
```

```
def get_scores(self, imgs, targets):
b, _, _, _ = imgs.shape
batch_size = 32
total_scores = []
for i in range(0, b, batch_size):
scores = self.sub_forward(imgs[i:i+batch_size,:,:,:])
scores = F.softmax(scores)
labels = targets[i:i+batch_size]
labels = labels.long()
scores = scores[:,labels]
print(i," scores: ", scores)
total_scores.append(scores)
print(i," total_socres: ", total_scores)
total_scores = torch.stack(total_scores)
return scores
```

```
0 scores: tensor([[0.0811],
[0.0918],
[0.0716],
[0.1680],
[0.1689],
[0.1319],
[0.1556],
[0.2966],
[0.0913],
[0.1238],
[0.1480],
[0.1215],
[0.2524],
[0.1283],
[0.1603],
[0.1282],
[0.2668],
[0.1146],
[0.2043],
[0.2475],
[0.0865],
[0.1869],
[0.0860],
[0.1979],
[0.1677],
[0.1983],
[0.2623],
[0.1975],
[0.1894],
[0.3299],
[0.1970],
[0.1094]], device='cuda:0')
0 total_socres: [tensor([[0.0811],
[0.0918],
[0.0716],
[0.1680],
[0.1689],
[0.1319],
[0.1556],
[0.2966],
[0.0913],
[0.1238],
[0.1480],
[0.1215],
[0.2524],
[0.1283],
[0.1603],
[0.1282],
[0.2668],
[0.1146],
[0.2043],
[0.2475],
[0.0865],
[0.1869],
[0.0860],
[0.1979],
[0.1677],
[0.1983],
[0.2623],
[0.1975],
[0.1894],
[0.3299],
[0.1970],
[0.1094]], device='cuda:0')]
32 scores: tensor([], device='cuda:0', size=(32, 0))
32 total_socres: [tensor([[0.0811],
[0.0918],
[0.0716],
[0.1680],
[0.1689],
[0.1319],
[0.1556],
[0.2966],
[0.0913],
[0.1238],
[0.1480],
[0.1215],
[0.2524],
[0.1283],
[0.1603],
[0.1282],
[0.2668],
[0.1146],
[0.2043],
[0.2475],
[0.0865],
[0.1869],
[0.0860],
[0.1979],
[0.1677],
[0.1983],
[0.2623],
[0.1975],
[0.1894],
[0.3299],
[0.1970],
[0.1094]], device='cuda:0'), tensor([], device='cuda:0', size=(32, 0))]
```

`

RuntimeError: stack expects each tensor to be equal size, but got [32, 1] at entry 0 and [32, 0] at entry 1

`