[Relay][Tensorflow] Allow an op as loop var. (apache#3056)

python/tvm/relay/frontend/tensorflow.py

@@ -30,6 +30,7 @@
 from .. import ir_pass
 from .. import expr as _expr
 from .. import op as _op
+from ..expr_functor import ExprMutator
 
 __all__ = ['from_tensorflow']
 
@@ -1414,6 +1415,27 @@ def _get_abs_layer_name(node):
 # 1.x.
 _control_flow_nodes = ['Merge', 'Switch', 'NextIteration', 'Exit', 'Enter', 'LoopCond']
 
+class RewriteSubgraph(ExprMutator):
+    """
+    A helper class to rewrite expr in while loop function to variable
+
+    Parameters
+    ----------
+    rewrite_map : Dict[expr, expr]
+        A dictionay contains a set of expr to var mapping.
+    """
+    def __init__(self, rewrite_map):
+        ExprMutator.__init__(self)
+        self.rewrite_map = rewrite_map
+
+    def visit(self, expr):
+        if expr in self.rewrite_map:
+            return self.rewrite_map[expr]
+        return super().visit(expr)
+
+def rewrite_subgraph(expr, rewrites):
+    return RewriteSubgraph(rewrites).visit(expr)
+
 def _in_while_loop(control_flow_node_map, op_name):
     """
     Check if a given control flow operator is part of a while loop execution
@@ -1594,14 +1616,17 @@ def _while_loop(self):
         loop_vars = []
         bind_map = {}
         for i, var in enumerate(self.loop_vars):
-            assert isinstance(var, _expr.Var), repr(var)
-            v = tvm.relay.var("loop_var" + str(i),
-                              type_annotation=var.type_annotation)
+            if not isinstance(var, _expr.Var):
+                var_type = ir_pass.infer_type(var).checked_type
+            else:
+                var_type = var.type_annotation
+
+            v = tvm.relay.var("loop_var" + str(i), type_annotation=var_type)
             loop_vars.append(v)
             bind_map[var] = v
 
-        self.cond = tvm.relay.bind(self.cond, bind_map)
-        self.body = [tvm.relay.bind(b, bind_map) for b in self.body]
+        self.cond = rewrite_subgraph(self.cond, bind_map)
+        self.body = [rewrite_subgraph(b, bind_map) for b in self.body]
 
         cond = tvm.relay.op.min(self.cond)
 

tests/python/frontend/tensorflow/test_control_flow.py

@@ -51,6 +51,23 @@ def b(i): return tf.add(i, 1)
         check_equal(graph, tf_out)
 
 
+def test_callnode_loop_vars():
+    graph = tf.Graph()
+    with graph.as_default():
+        i = tf.add(tf.constant(0), 1)
+
+        def c(i): return tf.less(i, 10)
+
+        def b(i): return tf.add(i, 1)
+
+        r = tf.while_loop(c, b, [i])
+
+        with tf.Session() as sess:
+            tf_out = sess.run(r)
+
+        check_equal(graph, tf_out)
+
+
 def test_loop_2_vars():
     graph = tf.Graph()
     with graph.as_default():
@@ -288,6 +305,7 @@ def condition(x):
     test_loop_3_vars()
     test_loop_conditions()
     test_loop_bodies()
+    test_callnode_loop_vars()
 
     # tf.cond
     test_vanilla_cond()