torch.Tensor.col_indices

Tensor.col_indices() → IntTensor

Returns the tensor containing the column indices of the self tensor when self is a sparse CSR tensor of layout sparse_csr. The col_indices tensor is strictly of shape (self.nnz()) and of type int32 or int64. When using MKL routines such as sparse matrix multiplication, it is necessary to use int32 indexing in order to avoid downcasting and potentially losing information.

Example:

>>> csr = torch.eye(5,5).to_sparse_csr()
>>> csr.col_indices()
tensor([0, 1, 2, 3, 4], dtype=torch.int32)