import torch
import torch.nn as nn

class NsoltSynthesis2dNetwork(nn.Module):

    def __init__(self,
        number_of_channels=[],
        decimation_factor=[]):
        super(NsoltSynthesis2dNetwork, self).__init__()
        self.number_of_channels = number_of_channels
        self.decimation_factor = decimation_factor

    def forward(self,x):
        return x

@@ -30,16 +30,141 @@
  as nn%0D%0A
+from nsoltBlockIdct2dLayer import NsoltBlockIdct2dLayer%0D%0Afrom nsoltFinalRotation2dLayer import NsoltFinalRotation2dLayer %0D%0A%0D%0A
 %0D%0Aclass 
@@ -457,34 +457,472 @@
 or%0D%0A
-%0D%0A    def forward(self,x):
+        %0D%0A        # Instantiation of layers%0D%0A        self.layerV0 = NsoltFinalRotation2dLayer(%0D%0A            number_of_channels=number_of_channels,%0D%0A            decimation_factor=decimation_factor,%0D%0A            name='V0'%0D%0A        )%0D%0A        self.layerE0 = NsoltBlockIdct2dLayer(%0D%0A            decimation_factor=decimation_factor,%0D%0A            name='E0'%0D%0A        )%0D%0A%0D%0A    def forward(self,x):%0D%0A        u = self.layerV0.forward(x)%0D%0A        y = self.layerE0.forward(u) 
 %0D%0A  
@@ -934,11 +934,11 @@
  return 
-x
+y
 %0D%0A

Update nsoltSynthesis2dNetwork.py