diff --git a/core/leras/layers/Conv2D.py b/core/leras/layers/Conv2D.py
index ae37c50..fd121f0 100644
--- a/core/leras/layers/Conv2D.py
+++ b/core/leras/layers/Conv2D.py
@@ -23,28 +23,13 @@ class Conv2D(nn.LayerBase):
             if padding == "SAME":
                 padding = ( (kernel_size - 1) * dilations + 1 ) // 2
             elif padding == "VALID":
-                padding = 0
+                padding = None
             else:
                 raise ValueError ("Wrong padding type. Should be VALID SAME or INT or 4x INTs")
-
-        if isinstance(padding, int):
-            if padding != 0:
-                if nn.data_format == "NHWC":
-                    padding = [ [0,0], [padding,padding], [padding,padding], [0,0] ]
-                else:
-                    padding = [ [0,0], [0,0], [padding,padding], [padding,padding] ]
-            else:
-                padding = None
-
-        if nn.data_format == "NHWC":
-            strides = [1,strides,strides,1]
         else:
-            strides = [1,1,strides,strides]
-
-        if nn.data_format == "NHWC":
-            dilations = [1,dilations,dilations,1]
-        else:
-            dilations = [1,1,dilations,dilations]
+            padding = int(padding)
+            
+        
 
         self.in_ch = in_ch
         self.out_ch = out_ch
@@ -93,9 +78,26 @@ class Conv2D(nn.LayerBase):
         if self.use_wscale:
             weight = weight * self.wscale
 
-        if self.padding is not None:
-            x = tf.pad (x, self.padding, mode='CONSTANT')
+        padding = self.padding
+        if padding is not None:
+            if nn.data_format == "NHWC":
+                padding = [ [0,0], [padding,padding], [padding,padding], [0,0] ]
+            else:
+                padding = [ [0,0], [0,0], [padding,padding], [padding,padding] ]
+            x = tf.pad (x, padding, mode='CONSTANT')
+        
+        strides = self.strides
+        if nn.data_format == "NHWC":
+            strides = [1,strides,strides,1]
+        else:
+            strides = [1,1,strides,strides]
 
+        dilations = self.dilations
+        if nn.data_format == "NHWC":
+            dilations = [1,dilations,dilations,1]
+        else:
+            dilations = [1,1,dilations,dilations]
+            
         x = tf.nn.conv2d(x, weight, self.strides, 'VALID', dilations=self.dilations, data_format=nn.data_format)
         if self.use_bias:
             if nn.data_format == "NHWC":