API: Add kwargs to sparse.einsum

sparse/_common.py

@@ -1393,7 +1393,7 @@ def _einsum_single(lhs, rhs, operand):
     return to_output_format(COO(new_coords, new_data, shape=new_shape, has_duplicates=True))
 
 
-def einsum(*operands):
+def einsum(*operands, **kwargs):
     """
     Perform the equivalent of :obj:`numpy.einsum`.
 
@@ -1406,6 +1406,11 @@ def einsum(*operands):
         included as well as subscript labels of the precise output form.
     operands : sequence of SparseArray
         These are the arrays for the operation.
+    dtype : data-type, optional
+        If provided, forces the calculation to use the data type specified.
+        Default is ``None``.
+    **kwargs : dict, optional
+        Any additional arguments to pass to the function.
 
     Returns
     -------
@@ -1417,6 +1422,9 @@ def einsum(*operands):
 
     check_zero_fill_value(*operands)
 
+    if "dtype" in kwargs and kwargs["dtype"] is not None:
+        operands = [o.astype(kwargs["dtype"]) for o in operands]
+
     if len(operands) == 1:
         return _einsum_single(lhs, rhs, operands[0])
 

sparse/tests/test_einsum.py

@@ -190,3 +190,15 @@ def test_einsum_shape_check():
     y = sparse.random((2, 3, 4), density=0.5)
     with pytest.raises(ValueError):
         sparse.einsum("abc,acb", x, y)
+
+
+@pytest.mark.parametrize("dtype", [np.int64, np.complex128])
+def test_einsum_dtype(dtype):
+    x = sparse.random((3, 3), density=0.5) * 10.
+    x = x.astype(np.float64)
+
+    y = sparse.COO.from_numpy(np.ones((3,1), dtype=np.float64))
+
+    result = sparse.einsum("ij,i->j", x, y, dtype=dtype)
+
+    assert result.dtype == dtype