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 format of ```loop_name/xxx```,
we can't know whether it belongs to a while loop or not. 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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