From 7443440abb8ed9e1dce423014c5c26001c3830e4 Mon Sep 17 00:00:00 2001
From: georgeyiasemis <georgeyiasemis@hotmail.com>
Date: Thu, 9 Nov 2023 18:34:20 +0100
Subject: [PATCH] Codacy complains

---
 direct/engine.py           |  1 -
 direct/functionals/ssim.py |  3 ++-
 direct/nn/conv/conv.py     | 24 ++++++++++++------------
 3 files changed, 14 insertions(+), 14 deletions(-)

diff --git a/direct/engine.py b/direct/engine.py
index 8deeb468..404bf129 100644
--- a/direct/engine.py
+++ b/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)
 
 
diff --git a/direct/functionals/ssim.py b/direct/functionals/ssim.py
index 913acb65..1de05128 100644
--- a/direct/functionals/ssim.py
+++ b/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
diff --git a/direct/nn/conv/conv.py b/direct/nn/conv/conv.py
index e3246770..51deae81 100644
--- a/direct/nn/conv/conv.py
+++ b/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: