How to Reverse Order of Rows in a Tensor

Question

I'm trying to reverse the order of the rows in a tensor that I create. I have tried with tensorflow and pytorch. Only thing I have found is the torch.flip() method. This does not work as it reverses not only the order of the rows, but also all of the elements in each row. I want the elements to remain the same. Is there an array operation of this to index the integers? For instance:

 tensor_a = [1, 2, 3]
       [4, 5, 6]
       [7, 8, 9]

I want it to be returned as:
       [7, 8, 9]
       [4, 5, 6]
       [1, 2, 3]

 however, torch.flip(tensor_a) = 
       [9, 8, 7]
       [6, 5, 4]
       [3, 2, 1]

Anyone have any suggestions?

Answer 1

According to documentation torch.flip has argument dims, which control what axis to be flipped. In this case torch.flip(tensor_a, dims=(0,)) will return expected result. Also torch.flip(tensor_a) will reverse all tensor, and torch.flip(tensor_a, dims=(1,)) will reverse every row, like [1, 2, 3] --> [3, 2, 1].

Answer 2

TF supports strided slicing. That'll be the most native way to do what you need.

>>> a = np.asarray([[1,2,3], [4,5,6]])

>>> a
array([[1, 2, 3],
       [4, 5, 6]])

>>> a[::-1, :]
array([[4, 5, 6],
       [1, 2, 3]])

>>> a[::, ::-1]
array([[3, 2, 1],
       [6, 5, 4]])