misc

NN/Nerf2D.py

@@ -149,6 +149,18 @@ def _createAlgorithmInterceptor(self, interceptor, image, pos):
     )
     return res.interceptor()
   #####################################################
+  def _withBlur(self, reverseArgs, B):
+    R = None
+    if 'blurRadius' in reverseArgs:
+      R = reverseArgs['blurRadius']
+      if not tf.is_tensor(R):
+        R = tf.convert_to_tensor(R, dtype=tf.float32)
+      R = tf.reshape(R, [1, 1])
+      R = tf.tile(R, [B, 1])
+    else:
+      R = tf.zeros((B, 1), dtype=tf.float32) # let encoder to decide needed it or not
+    return R
+
   @tf.function
   def _inference(
     self, src, pos, 
@@ -163,16 +175,7 @@ def _inference(
       tf.assert_equal(tf.shape(initialValues)[:1], (B, ))
       initialValues = tf.reshape(initialValues, (B, N, C))
 
-    R = None
-    if 'blurRadius' in reverseArgs:
-      R = reverseArgs['blurRadius']
-      if not tf.is_tensor(R):
-        R = tf.convert_to_tensor(R, dtype=tf.float32)
-      R = tf.reshape(R, [1, 1])
-      R = tf.tile(R, [B, 1])
-    else:
-      R = tf.zeros((B, 1), dtype=tf.float32)
-      pass
+    R = self._withBlur(reverseArgs, B)
     encoded = self._encoder(src, training=False, params=encoderParams, R=R)
     def getChunk(ind, sz):
       posC = pos[ind:ind+sz]