skip test if nnpops is not installed

tests/test_cfconv.py

@@ -4,21 +4,32 @@
 
 import pytest
 from pytest import mark
-import torch as pt
-from torchmdnet.models.torchmd_gn import CFConv as RefCFConv
-from torchmdnet.models.utils import OptimizedDistance, GaussianSmearing, ShiftedSoftplus
 
-from NNPOps.CFConv import CFConv
-from NNPOps.CFConvNeighbors import CFConvNeighbors
+try:
+    import NNPOps
 
+    nnpops_available = True
+except ImportError:
+    nnpops_available = False
 
+
+@pytest.mark.skipif(not nnpops_available, reason="NNPOps not available")
 @mark.parametrize("device", ["cpu", "cuda"])
 @mark.parametrize(
     ["num_atoms", "num_filters", "num_rbfs"],
     [(3, 5, 7), (3, 7, 5), (5, 3, 7), (5, 7, 3), (7, 3, 5), (7, 5, 3)],
 )
 @mark.parametrize("cutoff_upper", [5.0, 10.0])
 def test_cfconv(device, num_atoms, num_filters, num_rbfs, cutoff_upper):
+    import torch as pt
+    from torchmdnet.models.torchmd_gn import CFConv as RefCFConv
+    from torchmdnet.models.utils import (
+        OptimizedDistance,
+        GaussianSmearing,
+        ShiftedSoftplus,
+    )
+    from NNPOps.CFConv import CFConv
+    from NNPOps.CFConvNeighbors import CFConvNeighbors
 
     if not pt.cuda.is_available() and device == "cuda":
         pytest.skip("No GPU")