diff --git a/NN/Nerf2D.py b/NN/Nerf2D.py
index fd6be73..082e0d5 100644
--- a/NN/Nerf2D.py
+++ b/NN/Nerf2D.py
@@ -132,15 +132,12 @@ def test_step(self, images):
 
   def _createAlgorithmInterceptor(self, interceptor, image, pos):
     from NN.restorators.samplers.CWatcherWithExtras import CWatcherWithExtras
-    def interceptorFactory(algorithm):
-      res = interceptor(algorithm)
-      res = CWatcherWithExtras(
-        watcher=res,
-        converter=self._converter,
-        residuals=None # residuals applied in the renderer
-      )
-      return res
-    return interceptorFactory
+    res = CWatcherWithExtras(
+      watcher=interceptor,
+      converter=self._converter,
+      residuals=None # residuals applied in the renderer
+    )
+    return res.interceptor()
   #####################################################
   @tf.function
   def _inference(
@@ -156,15 +153,6 @@ def _inference(
       tf.assert_equal(tf.shape(initialValues)[:1], (B, ))
       initialValues = tf.reshape(initialValues, (B, N, C))
 
-    if 'algorithmInterceptor' in reverseArgs: # update algorithm interceptor if provided
-      newParams = {k: v for k, v in encoderParams.items() if k != 'algorithmInterceptor'}
-      newParams['algorithmInterceptor'] = self._createAlgorithmInterceptor(
-        interceptor=reverseArgs['algorithmInterceptor'],
-        image=src, pos=tf.tile(pos[None], [B, 1, 1])
-      )
-      encoderParams = newParams
-      pass
-
     encoded = self._encoder(src, training=False, params=encoderParams)
     def getChunk(ind, sz):
       posC = pos[ind:ind+sz]
@@ -233,14 +221,12 @@ def call(self,
     reverseArgs = {k: v for k, v in reverseArgs.items() if k != 'encoder'}
     # add interceptors if needed
     if 'algorithmInterceptor' in reverseArgs:
-      newParams = {k: v for k, v in encoderParams.items()}
+      newParams = {k: v for k, v in reverseArgs.items()}
       newParams['algorithmInterceptor'] = self._createAlgorithmInterceptor(
         interceptor=reverseArgs['algorithmInterceptor'],
         image=src, pos=tf.tile(pos[None], [B, 1, 1])
       )
-      encoderParams = newParams
-      # remove the interceptor from the reverseArgs
-      reverseArgs = {k: v for k, v in reverseArgs.items() if k != 'algorithmInterceptor'}
+      reverseArgs = newParams
       pass
     
     probes = self._inference(