Flip tensor in the up/down direction, returning a new tensor.
Flip the entries in each column in the up/down direction. Rows are preserved, but appear in a different order than before.
Note
torch.flipud makes a copy of input’s data. This is different from NumPy’s np.flipud, which returns a view in constant time. Since copying a tensor’s data is more work than viewing that data, torch.flipud is expected to be slower than np.flipud.
>>> x = torch.arange(4).view(2, 2)
>>> x
tensor([[0, 1],
[2, 3]])
>>> torch.flipud(x)
tensor([[2, 3],
[0, 1]])
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