Codacy complains

direct/engine.py

@@ -38,7 +38,6 @@
 from direct.utils.events import CommonMetricPrinter, EventStorage, JSONWriter, TensorboardWriter, get_event_storage
 from direct.utils.io import write_json
 
-
 logging.captureWarnings(True)
 
 

direct/functionals/ssim.py

@@ -9,6 +9,8 @@
 # All rights reserved.
 # Some changes are made to work together with DIRECT.
 
+# pylint: disable=too-many-locals
+
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -95,7 +97,6 @@ def forward(self, input_data: torch.Tensor, target_data: torch.Tensor, data_rang
         -------
         torch.Tensor
         """
-        # pylint: disable=too-many-locals
         data_range = data_range[:, None, None, None, None]
         C1 = (self.k1 * data_range) ** 2
         C2 = (self.k2 * data_range) ** 2

direct/nn/conv/conv.py

@@ -202,18 +202,6 @@ def __init__(
         adjust_scale=False,
         **kwargs,
     ):
-        super().__init__(
-            in_channels,
-            out_channels,
-            kernel_size,
-            stride,
-            padding,
-            output_padding,
-            groups,
-            bias,
-            dilation,
-            **kwargs,
-        )
         """Inits :class:`CWNConvTranspose2d`.
 
         Parameters
@@ -239,6 +227,18 @@ def __init__(
         adjust_scale : bool, optional
             If True, the scale factor is adjusted as a learnable parameter. Default: False.
         """
+        super().__init__(
+            in_channels,
+            out_channels,
+            kernel_size,
+            stride,
+            padding,
+            output_padding,
+            groups,
+            bias,
+            dilation,
+            **kwargs,
+        )
         self.weight_normalization = CWNorm()
         self.scale_ = torch.ones(in_channels, 1, 1, 1).fill_(n_scale)
         if adjust_scale: