I have a list of torch tensors, each is a tensor that holds predictions and i wish to average those. So, image 10982 predictions and we repeat that 3 times:

```
my_list = []
for i in range(3):
my_list.append(torch.arange(i,10982+i, dtype=torch.float32).reshape(10982,1))
```

is there a better way (a more pytorch or even numpy way) vs just doing list aggregate functions? It looks like the below is giving me what I want, it returns a tensor of size 10982,1 which is what I want. I just figured there is a more proper pytorch way of doing this.

`sum(my_list)/len(my_list)`