Shuffling along a given axis in PyTorch
I have the a dataset that gets loaded in  with the following dimension [batch_size, seq_len, n_features] (e.g. torch.Size([16, 600, 130])).
I want to be able to shuffle this data along the sequence length axis=1 without altering the batch ordering or the feature vector ordering in PyTorch.
Further explanation: For exemplification let's say my batch size is 3, sequence length is 3 and number of features is 2.
example:
tensor([[[1,1],[2,2],[3,3]],[[4,4],[5,5],[6,6]],[[7,7],[8,8],[9,9]]])  I want to be able to randomly shuffle the following way:
tensor([[[3,3],[1,1],[2,2]],[[6,6],[5,5],[4,4]],[[8,8],[7,7],[9,9]]])
Are there any PyTorch functions that will do that automatically for me, or does anyone know what would be a good way to implement this?

You can use torch.randperm.
For tensor t, you can use:
t[:,torch.randperm(t.shape[1]),:]

For your example:
&gt;&gt;&gt; t = torch.tensor([[[1,1],[2,2],[3,3]],[[4,4],[5,5],[6,6]],[[7,7],[8,8],[9,9]]])
&gt;&gt;&gt; t
tensor([[[1, 1],
         [2, 2],
         [3, 3]],

        [[4, 4],
         [5, 5],
         [6, 6]],

        [[7, 7],
         [8, 8],
         [9, 9]]])
&gt;&gt;&gt; t[:,torch.randperm(t.shape[1]),:]
tensor([[[2, 2],
         [3, 3],
         [1, 1]],

        [[5, 5],
         [6, 6],
         [4, 4]],

        [[8, 8],
         [9, 9],
         [7, 7]]])

