fix #542: add Exception for use numpy with lodtensor

python/paddle_serving_client/__init__.py

@@ -260,10 +260,16 @@ class Client(object):
                     if i == 0:
                         int_feed_names.append(key)
                         if isinstance(feed_i[key], np.ndarray):
+                            if key in self.lod_tensor_set:
+                                raise ValueError(
+                                    "LodTensor var can not be ndarray type.")
                             int_shape.append(list(feed_i[key].shape))
                         else:
                             int_shape.append(self.feed_shapes_[key])
                     if isinstance(feed_i[key], np.ndarray):
+                        if key in self.lod_tensor_set:
+                            raise ValueError(
+                                "LodTensor var can not be ndarray type.")
                         #int_slot.append(np.reshape(feed_i[key], (-1)).tolist())
                         int_slot.append(feed_i[key])
                         self.has_numpy_input = True
@@ -274,10 +280,16 @@ class Client(object):
                     if i == 0:
                         float_feed_names.append(key)
                         if isinstance(feed_i[key], np.ndarray):
+                            if key in self.lod_tensor_set:
+                                raise ValueError(
+                                    "LodTensor var can not be ndarray type.")
                             float_shape.append(list(feed_i[key].shape))
                         else:
                             float_shape.append(self.feed_shapes_[key])
                     if isinstance(feed_i[key], np.ndarray):
+                        if key in self.lod_tensor_set:
+                            raise ValueError(
+                                "LodTensor var can not be ndarray type.")
                         #float_slot.append(np.reshape(feed_i[key], (-1)).tolist())
                         float_slot.append(feed_i[key])
                         self.has_numpy_input = True