wrote the forward function for U-net

BrainMapperUNet.py

@@ -70,10 +70,37 @@ class BrainMapperUNet(nn.Module):
         self.classifier = modules.ClassifierBlock(parameters)
 
     def forward(self, X):
+        """Forward pass for U-net
+
+        Function computing the forward pass through the U-Net
+        The input to the function is the dMRI map
+
+        Args:
+            X (torch.tensor): Input dMRI map, shape = (N x C x H x W) 
+
+        Returns:
+            probability_map (torch.tensor): Output forward passed tensor through the U-net block
+
+        Raises:
+            None
+
         """
-        Description
-        """
-        return None
+
+        Y_encoder_1, Y_np1, pool_indices1 = self.encoderBlock1.forward(X)
+        Y_encoder_2, Y_np2, pool_indices2 = self.encoderBlock2.forward(Y_encoder_1)
+        Y_encoder_3, Y_np3, pool_indices3 = self.encoderBlock3.forward(Y_encoder_2)
+        Y_encoder_4, Y_np4, pool_indices4 = self.encoderBlock4.forward(Y_encoder_3)
+
+        Y_bottleNeck = self.bottleneck.forward(Y_encoder_4)
+
+        Y_decoder_1 = self.decoderBlock1.forward(Y_bottleNeck, Y_np4, pool_indices4)
+        Y_decoder_2 = self.decoderBlock2.forward(Y_decoder_1, Y_np3, pool_indices3)
+        Y_decoder_3 = self.decoderBlock3.forward(Y_decoder_2, Y_np2, pool_indices2)
+        Y_decoder_4 = self.decoderBlock4.forwrad(Y_decoder_3, Y_np1, pool_indices1)
+
+        probability_map = self.classifier.forward(Y_decoder_4)
+        
+        return probability_map
 
     def enable_test_dropout(self):
         """