test empty std

test/test_std.py

@@ -6,10 +6,10 @@ from torch_scatter import scatter_std
 
 from .utils import grad_dtypes as dtypes, devices, tensor
 
-biass = [True, False]
+biases = [True, False]
 
 
-@pytest.mark.parametrize('dtype,device,bias', product(dtypes, devices, biass))
+@pytest.mark.parametrize('dtype,device,bias', product(dtypes, devices, biases))
 def test_std(dtype, device, bias):
     src = tensor([[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]], dtype, device)
     index = tensor([[0, 0, 0, 0, 0], [1, 1, 1, 1, 1]], torch.long, device)
@@ -18,3 +18,12 @@ def test_std(dtype, device, bias):
     std = src.std(dim=-1, unbiased=bias)[0].item()
     expected = tensor([[std, 0], [0, std]], dtype, device)
     assert torch.allclose(out, expected)
+
+
+@pytest.mark.parametrize('dtype,device', product(dtypes, devices))
+def test_empty_std(dtype, device):
+    src = tensor([], dtype, device)
+    index = tensor([], torch.long, device)
+
+    out = scatter_std(src, index, dim=-1)
+    assert out.tolist() == []