fixing attention perf test attempt 1

tests/test_attention.py

@@ -214,7 +214,6 @@ class TestNeighborhoodAttentionS2(unittest.TestCase):
             self.assertTrue(torch.allclose(grad, grad_ref, atol=atol, rtol=rtol), f"Parameter gradient mismatch")
 
 
-    @unittest.skipUnless((torch.cuda.is_available() and _cuda_extension_available), "skipping performance test because CUDA is not available")
     @parameterized.expand(
         [
             # self attention
@@ -223,6 +222,7 @@ class TestNeighborhoodAttentionS2(unittest.TestCase):
         ],
         skip_on_empty=True,
     )
+    @unittest.skipUnless((torch.cuda.is_available() and _cuda_extension_available), "skipping performance test because CUDA is not available")
     def test_perf(self, batch_size, channels, heads, in_shape, out_shape, grid_in, grid_out, atol, rtol, verbose=True):
 
         # extract some parameters