kevinthesun commented on a change in pull request #5699:
URL: https://github.com/apache/incubator-tvm/pull/5699#discussion_r435748804



##########
File path: python/tvm/relay/frontend/tensorflow.py
##########
@@ -3194,6 +3191,55 @@ def _convert_operator(self, op_name, inputs, attrs,
             raise NotImplementedError("Operator {} not 
implemented.".format(op_name))
         return sym
 
+    def _licm_construct(self, loop_name, node_name):
+        """Construct a node by considering whether it is
+        loop invariant with the given while loop. If yes, we
+        generate a loop Variable. Otherwise, return regular
+        converted relay expression.
+
+        Parameters
+        ----------
+        loop_name : str
+            TensorFlow while loop name to be checked.
+
+        node_name : str
+            TensorFlow node name.
+
+        Returns
+        -------
+        out : relay.Expr or relay.Var
+            Converted relay expression or loop var.
+        """
+        actual_expr = self._backtrack_construct(node_name)
+        tn = node_name.split(':').split("^")[-1]
+        node_name = tn[0]
+        cloop_name = find_parent_loop_name(node_name, 
self._while_loop_name_set)
+
+        if loop_name in self._while_loop_name_set and not 
cloop_name.startswith(loop_name):

Review comment:
       Indeed when user sets tf op name in the way that the graph def node name 
is in the format of ```loop_name/xxx```, we can incorrectly recognize it to be 
part of a while loop.  The problem here is tf op name is a part of node name in 
graph def and there is no ```name``` attribute in node attr. For now I haven't 
found a better way to do licm node construction. In practice, this case should 
be rare since while loop name is a complicated hierarchical combination of op 
and sub-graph names.




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