diff --git a/src/finn/transformation/fpgadataflow/convert_to_hw_layers.py b/src/finn/transformation/fpgadataflow/convert_to_hw_layers.py
index 9017b171dd..edea1a9d19 100644
--- a/src/finn/transformation/fpgadataflow/convert_to_hw_layers.py
+++ b/src/finn/transformation/fpgadataflow/convert_to_hw_layers.py
@@ -294,26 +294,30 @@ def apply(self, model):
                         scales = model.get_initializer(n.input[1])
                     elif len(n.input) == 3:
                         # Resize version 11 and up (no size input)
-                        scales = model.get_initializer(n.input[2]) 
+                        scales = model.get_initializer(n.input[2])
                     elif len(n.input) == 4:
                         # Resize version 11 and up
-                        scales_exists = (model.get_initializer(n.input[2]) is not None) and (len(model.get_initializer(n.input[2])) != 0)
-                        sizes_exists = (model.get_initializer(n.input[3]) is not None) and (len(model.get_initializer(n.input[3])) != 0)
-                        assert (scales_exists ^ sizes_exists), (
-                            "%s: Either scales or the target output size must " 
+                        scales_exists = (model.get_initializer(n.input[2]) is not None) and (
+                            len(model.get_initializer(n.input[2])) != 0
+                        )
+                        sizes_exists = (model.get_initializer(n.input[3]) is not None) and (
+                            len(model.get_initializer(n.input[3])) != 0
+                        )
+                        assert scales_exists ^ sizes_exists, (
+                            "%s: Either scales or the target output size must "
                             "be specified. Specifying both is prohibited." % n.name
-                            )  
-                        assert (model.get_initializer(n.input[1]) is None), (
-                            "%s: Defining the ROI is not supported" % n.name    
-                            )
-                        if (scales_exists): 
+                        )
+                        assert model.get_initializer(n.input[1]) is None, (
+                            "%s: Defining the ROI is not supported" % n.name
+                        )
+                        if scales_exists:
                             # Scales input
                             scales = model.get_initializer(n.input[2])
                         else:
                             # Convert sizes to scales
                             sizes = model.get_initializer(n.input[3])
-                            data_input_size =  model.get_tensor_shape(n.input[0])
-                            scales = sizes/data_input_size
+                            data_input_size = model.get_tensor_shape(n.input[0])
+                            scales = sizes / data_input_size
                 in_shape = model.get_tensor_shape(n.input[0])
 
                 dt = model.get_tensor_datatype(n.input[0])
diff --git a/src/finn/transformation/streamline/reorder.py b/src/finn/transformation/streamline/reorder.py
index 797c554297..9d7dc0b7ce 100644
--- a/src/finn/transformation/streamline/reorder.py
+++ b/src/finn/transformation/streamline/reorder.py
@@ -763,21 +763,25 @@ def apply(self, model):
                 else:
                     if len(n.input) == 2:
                         # Resize version 10
-                        transformation_ind = 1 
+                        transformation_ind = 1
                         d_type = "float32"
                     elif len(n.input) == 3:
                         # Resize version 11 and up (no size input)
-                        transformation_ind = 2 
+                        transformation_ind = 2
                         d_type = "float32"
                     elif len(n.input) == 4:
                         # Resize version 11 and up
-                        scales_exists = (model.get_initializer(n.input[2]) is not None) and (len(model.get_initializer(n.input[2])) != 0)
-                        sizes_exists = (model.get_initializer(n.input[3]) is not None) and (len(model.get_initializer(n.input[3])) != 0)
-                        assert (scales_exists ^ sizes_exists), (
-                            "%s: Either scales or the target output size must " 
+                        scales_exists = (model.get_initializer(n.input[2]) is not None) and (
+                            len(model.get_initializer(n.input[2])) != 0
+                        )
+                        sizes_exists = (model.get_initializer(n.input[3]) is not None) and (
+                            len(model.get_initializer(n.input[3])) != 0
+                        )
+                        assert scales_exists ^ sizes_exists, (
+                            "%s: Either scales or the target output size must "
                             "be specified. Specifying both is prohibited." % n.name
-                            )  
-                        if (scales_exists): 
+                        )
+                        if scales_exists:
                             # Scales input
                             transformation_ind = 2
                             d_type = "float32"
diff --git a/tests/transformation/streamline/test_scale_resize_nhwc.py b/tests/transformation/streamline/test_scale_resize_nhwc.py
index 47a34e4601..dfa2e7433a 100644
--- a/tests/transformation/streamline/test_scale_resize_nhwc.py
+++ b/tests/transformation/streamline/test_scale_resize_nhwc.py
@@ -179,6 +179,7 @@ def create_transpose_resize_transpose(ifm_dim, ifm_ch, scales, mode, idt):
 
     return model
 
+
 def create_resize_transpose_sizes(ifm_dim, ifm_ch, sizes, mode, idt):
     ofm_dim_h = sizes[2]
     ofm_dim_w = sizes[3]
@@ -189,7 +190,7 @@ def create_resize_transpose_sizes(ifm_dim, ifm_ch, sizes, mode, idt):
 
     # Not actually used, only needed for compliance with the Resize node interface
     roi = oh.make_tensor_value_info("roi", TensorProto.FLOAT, [4])
-    
+
     param = oh.make_tensor_value_info("sizes", TensorProto.INT64, [4])
 
     outp_up = oh.make_tensor_value_info(
@@ -232,6 +233,7 @@ def create_resize_transpose_sizes(ifm_dim, ifm_ch, sizes, mode, idt):
 
     return model
 
+
 def check_transform(model):
     graph = model.graph
     node_ind = 0
@@ -251,7 +253,9 @@ def check_transform(model):
 # scales
 @pytest.mark.parametrize("scales", [[1, 1, i, j] for i in range(2, 5) for j in range(2, 5)])
 # sizes
-@pytest.mark.parametrize("sizes", [[1, 3, 2**i, 2**j] for i in range(6, 7) for j in range(6, 7)])
+@pytest.mark.parametrize(
+    "sizes", [[1, 3, 2**i, 2**j] for i in range(6, 7) for j in range(6, 7)]
+)
 # mode
 @pytest.mark.parametrize("mode", ["nearest"])
 # input datatype