code: def forward(self, *weights):
      gidxC, C_weights = _csrsum(self.gidxs, weights)
      (
          nrows,
          ncols,
          C_indptr,
          C_indices,
          C_eids,
      ) = gidxC.adjacency_matrix_tensors(0, False, "csr")
      # Note: the returned C_indptr, C_indices and C_eids tensors MUST be the same
      # as the underlying tensors of the created graph gidxC.
      self.backward_cache = gidxC
      nrows = nd.array([nrows], dtype="int64")
      ncols = nd.array([ncols], dtype="int64")
      return nrows, ncols, C_indptr, C_indices, C_eids, C_weights
  
imports: import mxnet
  import numpy
  from mxnet import nd
  from ..._sparse_ops import _bwd_segment_cmp, _csrmask, _csrmm, _csrsum, _gsddmm, _gspmm, _scatter_add, _segment_reduce
  from ...base import ALL, dgl_warning, is_all
  from ...heterograph_index import create_unitgraph_from_csr
  from .tensor import asnumpy, context, copy_to, to_backend_ctx, zerocopy_from_numpy
label_desc: Use image node_id 2 for calling the CSRSum obj's underlying member method code with example usage: obj.forward() and returns: nrows,  ncols,  C_indptr,  C_indices,  C_eids,  C_weights