batch is the number of non-zeros. This tensor encodes the
        index in values and row_indices depending on where the given
        column starts. Each successive number in the tensor subtracted
        by the number before it denotes the number of elements in a
        given column.
  * **row_indices** (*array_like*) -- Row co-ordinates of each
    element 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 tensor where "K" is the
    number of dense dimensions.

  * **size** (list, tuple, "torch.Size", optional) -- Size of the
    sparse tensor: "(*batchsize, nrows, ncols, *densesize)". If
    not provided, the size will be inferred as the minimum size
    big enough to hold all non-zero elements.

Keyword Arguments: