Fix opt crash of local_gpu_lazy_ifelse.

theano/sandbox/cuda/opt.py

@@ -403,7 +403,12 @@ def local_gpu_lazy_ifelse(node):
         host_input = node.inputs[0]
         if (host_input.owner and
             isinstance(host_input.owner.op, theano.ifelse.IfElse) and
-            not host_input.owner.op.gpu):
+            not host_input.owner.op.gpu and
+            # If there is more then 1 outputs, we can't replace it
+            # here with a local optimizer as we replace the
+            # GpuFromHost node and the other output of the if won't be
+            # replaced.
+            host_input.owner.op.n_outs == 1):
             gpu_ifelse = theano.ifelse.IfElse(host_input.owner.op.n_outs,
                                                   gpu=True)
 

theano/tests/test_ifelse.py

@@ -159,6 +159,49 @@ class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
         assert numpy.all(outs_0[2] == 1.)
         assert numpy.all(outs_0[3] == 1.)
 
+    def test_multiple_out_crash(self):
+        # This test failed up to commit 2faeb62c38
+        p0 = self.shared(numpy.asarray(numpy.random.random([4, 8]),
+                                       dtype=self.dtype))
+        p1 = self.shared(numpy.asarray(numpy.random.random(8),
+                                       dtype=self.dtype))
+        p2 = self.shared(numpy.asarray(numpy.random.random([8, 3]),
+                                       dtype=self.dtype))
+        p3 = self.shared(numpy.asarray(numpy.random.random(3),
+                                       dtype=self.dtype))
+        p = [p0, p1, p2, p3]
+
+        # in my code these vars are the result of applying scan
+        ften0 = tensor.ftensor3('ft0')
+        fmat1 = tensor.fmatrix('fm1')
+        ften2 = tensor.ftensor3('ft2')
+        fmat3 = tensor.fmatrix('fm3')
+
+        # then I keep only the last iteration
+        fsub0 = ften0[-1]
+        fsub1 = fmat1[-1]
+        fsub2 = ften2[-1]
+        fsub3 = fmat3[-1]
+
+        fsub = [fsub0, fsub1, fsub2, fsub3]
+
+        acc = theano.tensor.constant(1, 'int8') >= 0
+
+        new_positions = theano.ifelse.ifelse(acc, fsub, p)
+
+        new_updates = [(p[0], new_positions[0])]
+
+        f = theano.function([ften0, fmat1, ften2, fmat3], [],
+                            updates=new_updates, mode=self.mode)
+        self.assertFunctionContains1(f, self.get_ifelse(4))
+
+        i1 = numpy.asarray(numpy.random.random([19, 4, 8]), dtype=self.dtype)
+        i2 = numpy.asarray(numpy.random.random([19, 8]), dtype=self.dtype)
+        i3 = numpy.asarray(numpy.random.random([19, 8, 3]), dtype=self.dtype)
+        i4 = numpy.asarray(numpy.random.random([19, 3]), dtype=self.dtype)
+
+        f(i1, i2, i3, i4)
+
     def test_dtype_mismatch(self):
         rng = numpy.random.RandomState(utt.fetch_seed())
         data = rng.rand(5).astype(self.dtype)