# dgl.sparse.div¶

`dgl.sparse.``div`(A: Union[dgl.sparse.sparse_matrix.SparseMatrix, dgl.sparse.diag_matrix.DiagMatrix], B: Union[dgl.sparse.diag_matrix.DiagMatrix, numbers.Number, torch.Tensor])Union[dgl.sparse.sparse_matrix.SparseMatrix, dgl.sparse.diag_matrix.DiagMatrix][source]

Elementwise division for `DiagMatrix` and `SparseMatrix`, equivalent to `A / B`.

The supported combinations are shown as follows.

 A \ B DiagMatrix SparseMatrix scalar DiagMatrix ✅ 🚫 ✅ SparseMatrix 🚫 🚫 ✅ scalar 🚫 🚫 🚫
Parameters
Returns

Diagonal matrix

Return type

DiagMatrix

Examples

```>>> A = dglsp.diag(torch.arange(1, 4))
>>> B = dglsp.diag(torch.arange(10, 13))
>>> dglsp.div(A, B)
DiagMatrix(val=tensor([0.1000, 0.1818, 0.2500]),
shape=(3, 3))
```
```>>> A = dglsp.diag(torch.arange(1, 4))
>>> dglsp.div(A, 2)
DiagMatrix(val=tensor([0.5000, 1.0000, 1.5000]),
shape=(3, 3))
```
```>>> indices = torch.tensor([[1, 0, 2], [0, 3, 2]])
>>> val = torch.tensor([1, 2, 3])
>>> A = dglsp.spmatrix(indices, val, shape=(3, 4))
>>> dglsp.div(A, 2)
SparseMatrix(indices=tensor([[1, 0, 2],
[0, 3, 2]]),
values=tensor([0.5000, 1.0000, 1.5000]),
shape=(3, 4), nnz=3)
```