use user constructor only for float32

theano/scan_module/scan_op.py

@@ -76,21 +76,40 @@ class Scan(PureOp):
             # Not that for mit_mot there are several output slices per
             # output sequence
             o = outputs[idx]
-            self.output_types.append(
-                typeConstructor(
-                    broadcastable=(False,) + o.type.broadcastable,
-                    dtype=o.type.dtype)
-                        )
+            # typeConstructor constructs only CudaNdarray when code is
+            # runnnig on gpu, but for outputs of a dtype different than
+            # float32 this results into an error
+            if o.type.dtype in ['float32']:
+                self.output_types.append(
+                    typeConstructor(
+                        broadcastable=(False,) + o.type.broadcastable,
+                        dtype=o.type.dtype))
+            else:
+                self.output_types.append(
+                    tensorConstructor(
+                        broadcastable=(False,) + o.type.broadcastable,
+                        dtype=o.type.dtype))
+
             idx += len(self.mit_mot_out_slices[jdx])
             jdx += 1
 
         # mit_sot / sit_sot / nit_sot
         end = idx + self.n_mit_sot + self.n_sit_sot + self.n_nit_sot
+
         for o in outputs[idx:end]:
-            self.output_types.append(
-                typeConstructor(
-                    broadcastable=(False,) + o.type.broadcastable,
-                    dtype=o.type.dtype))
+            # typeConstructor constructs only CudaNdarray when code is
+            # runnnig on gpu, but for outputs of a dtype different than
+            # float32 this results into an error
+            if o.type.dtype in ['float32']:
+                self.output_types.append(
+                    typeConstructor(
+                        broadcastable=(False,) + o.type.broadcastable,
+                        dtype=o.type.dtype))
+            else:
+                self.output_types.append(
+                    tensorConstructor(
+                        broadcastable=(False,) + o.type.broadcastable,
+                        dtype=o.type.dtype))
         # shared outputs + possibly the ending condition
         for o in outputs[end:]:
             self.output_types.append(o.type)