Fix ifelse lifter when GraphToGPU don't encore the same type for corresponding inputs.

theano/gpuarray/opt.py

@@ -931,11 +931,20 @@ def local_gpua_lazy_ifelse(op, context_name, inputs, outputs):
         return
     c = inputs[0]
     inps = []
-    for v in inputs[1:]:
-        if isinstance(v.type, tensor.TensorType) and move_to_gpu(v):
-            inps.append(as_gpuarray_variable(v, context_name))
+    falses = []
+    # ifelse need corresponding true/false inputs variables to be of the same type.
+    # But we can't rely on inputs to respect that, as GraphToGPU don't enforce that.
+    # So we need to take care of this here.
+    for v1, v2 in zip(inputs[1:1+op.n_outs], inputs[1+op.n_outs:]):
+        if ((isinstance(v1.type, tensor.TensorType) and move_to_gpu(v1)) or
+                isinstance(v1.type, GpuArrayType) or
+                isinstance(v2.type, GpuArrayType)):
+            inps.append(as_gpuarray_variable(v1, context_name))
+            falses.append(as_gpuarray_variable(v2, context_name))
         else:
-            inps.append(v)
+            inps.append(v1)
+            falses.append(v2)
+    inps.extend(falses)
     return IfElse(op.n_outs, gpu=True)(c, *inps, return_list=True)
 
 

theano/gpuarray/tests/test_opt.py

@@ -267,6 +267,16 @@ class test_gpu_ifelse(test_ifelse.test_ifelse):
                             mode=mode_with_gpu)
         assert f(np.float32([1, 2, 3]), 0) == 6
 
+    def test_lifter_with_shared_var(self):
+        x = tensor.lscalar('x')
+        y = gpuarray_shared_constructor(np.asarray(1, dtype='float32'),
+                                        target=test_ctx_name)
+        z = tensor.constant(2.)
+
+        a = theano.ifelse.ifelse(x, y, z)
+        with theano.configparser.change_flags(on_opt_error='raise'):
+            f = theano.function([x], [a], mode=mode_with_gpu)
+
 
 def test_print_op():
     """ Test that print ops don't block gpu optimization"""