removing unused variables in test_models.py in TestNaive class resolv…

…ing F841

tests/test_models.py

@@ -296,14 +296,11 @@ def test_kernel_size(self, mdl, einstein_img):
     @pytest.mark.parametrize("mdl", ["naive.Gaussian", "naive.CenterSurround"])
     @pytest.mark.parametrize("cache_filt", [False, True])
     def test_cache_filt(self, cache_filt, mdl):
-        img = torch.ones(1, 1, 100, 100).to(DEVICE).requires_grad_()
         if mdl == "naive.Gaussian":
             model = po.simul.Gaussian((31, 31), 1.0, cache_filt=cache_filt).to(DEVICE)
         elif mdl == "naive.CenterSurround":
             model = po.simul.CenterSurround((31, 31), cache_filt=cache_filt).to(DEVICE)
 
-        y = model(img)  # forward pass should cache filt if True
-
         if cache_filt:
             assert model._filt is not None
         else:
@@ -319,7 +316,7 @@ def test_CenterSurround_channels(self, center_std, out_channels, on_center):
                     (31, 31), center_std=center_std, out_channels=out_channels
                 )
         else:
-            model = po.simul.CenterSurround(
+            model = po.simul.CenterSurround(  # noqa: F841
                 (31, 31), center_std=center_std, out_channels=out_channels
             )
 

tests/test_tools.py

@@ -240,7 +240,6 @@ def test_stats(self):
         assert (
             torch.abs(v - torch.var(x, dim=1, keepdim=True, unbiased=False)) < 1e-5
         ).all()
-        s = po.tools.skew(x, mean=m, var=v, dim=1)
         k = po.tools.kurtosis(x, mean=m, var=v, dim=1)
         assert torch.abs(k.mean() - 3) < 1e-1