array of size "(*batchsize, compressed_dim_size + 1)".  The
        last element of each batch is the number of non-zero elements
        or blocks. This tensor encodes the index in "values" and
        "plain_indices" depending on where the given compressed
        dimension (row or column) starts. Each successive number in
        the tensor subtracted by the number before it denotes the
        number of elements or blocks in a given compressed dimension.
  * **plain_indices** (*array_like*) -- Plain dimension (column or
    row) co-ordinates of each element or block in values.
    (B+1)-dimensional tensor with the same length as values.

  * **values** (*array_list*) -- Initial values for the tensor.
    Can be a list, tuple, NumPy "ndarray", scalar, and other
    types.  that represents a (1+K)-dimensional (for CSR and CSC
    layouts) or (1+2+K)-dimensional tensor (for BSR and BSC
    layouts) where "K" is the number of dense dimensions.
