python k.transpose(-2, -1)

In Python, `k.transpose(-2, -1)` means to transpose the second last and last dimensions of tensor `k`. Specifically, if the shape of tensor `k` is `(batch_size, seq_length, hidden_size)`, then `k.transpose(-2, -1)` will return a tensor of shape `(batch_size, hidden_size, seq_length)`. The second last dimension `seq_length` becomes the last dimension of the returned tensor, while the last dimension `hidden_size` becomes the second last dimension of the returned tensor.

This operation is commonly used in deep learning models such as Transformers, where it is used to transpose the attention score matrix so that the rows and columns correspond to the query and key vectors, respectively, making it easier to perform matrix multiplication in subsequent steps.