After reading the documentation for Tensor.view,

https://pytorch.org/docs/stable/tensors.html#torch.Tensor.view

it seems like it could be used to swap two dimension in a tensor, but this is not the case:

```
a=torch.randn((1,2,3,4))
# Swap 2nd and 3rd dimensions using split and stack
b = torch.stack(a.split(1, 1), 3).squeeze(1) # has shape (1, 3, 2, 4)
# Swap 2nd and 3rd dimensions using tensor.view
c = a.view((1, 3, 2, 4)) # has shape (1, 3, 2, 4)
(b == c).all() # False
```

Am I misunderstanding the documentation? What exactly does tensor.view() do in the example above?