fix: codestyle fixes from black and isort

Author: factnn

tests/test_binary_pointwise_ops.py

@@ -2550,20 +2550,6 @@ def test_accuracy_logaddexp(shape, dtype):
 
     with flag_gems.use_gems():
         res_out = torch.logaddexp(x, y)
-@pytest.mark.fmod
-@pytest.mark.parametrize("shape", POINTWISE_SHAPES)
-@pytest.mark.parametrize("dtype", FLOAT_DTYPES)
-def test_accuracy_fmod(shape, dtype):
-    inp1 = torch.randn(shape, dtype=dtype, device=flag_gems.device)
-    inp2 = torch.randn(shape, dtype=dtype, device=flag_gems.device)
-    # Avoid division by zero
-    inp2 = torch.where(inp2 == 0, torch.ones_like(inp2), inp2)
-    ref_inp1 = to_reference(inp1, True)
-    ref_inp2 = to_reference(inp2, True)
-
-    ref_out = torch.fmod(ref_inp1, ref_inp2)
-    with flag_gems.use_gems():
-        res_out = torch.fmod(inp1, inp2)
 
     gems_assert_close(res_out, ref_out, dtype)
 
@@ -2605,6 +2591,24 @@ def test_accuracy_copysign(shape, dtype):
     gems_assert_close(res_out, ref_out, dtype)
 
 
+@pytest.mark.fmod
+@pytest.mark.parametrize("shape", POINTWISE_SHAPES)
+@pytest.mark.parametrize("dtype", FLOAT_DTYPES)
+def test_accuracy_fmod(shape, dtype):
+    inp1 = torch.randn(shape, dtype=dtype, device=flag_gems.device)
+    inp2 = torch.randn(shape, dtype=dtype, device=flag_gems.device)
+    # Avoid division by zero
+    inp2 = torch.where(inp2 == 0, torch.ones_like(inp2), inp2)
+    ref_inp1 = to_reference(inp1, True)
+    ref_inp2 = to_reference(inp2, True)
+
+    ref_out = torch.fmod(ref_inp1, ref_inp2)
+    with flag_gems.use_gems():
+        res_out = torch.fmod(inp1, inp2)
+
+    gems_assert_close(res_out, ref_out, dtype)
+
+
 @pytest.mark.fmod
 @pytest.mark.parametrize("shape", POINTWISE_SHAPES)
 @pytest.mark.parametrize("scalar", SCALARS)