Remove reader logic

python/paddle/v2/inference.py

@@ -21,19 +21,8 @@ class Inference(object):
         self.__gradient_machine__ = gm
         self.__data_types__ = topo.data_type()
 
-    def iter_infer(self, input=None, batch_size=None, reader=None,
-                   feeding=None):
+    def iter_infer(self, input, feeding=None):
         feeder = DataFeeder(self.__data_types__, feeding)
-        if reader is None:
-            assert input is not None and isinstance(input, collections.Iterable)
-            if not isinstance(input, collections.Iterable):
-                raise TypeError("When reader is None, input should be whole "
-                                "inference data and should be iterable")
-
-            if batch_size is None:
-                if not hasattr(input, '__len__'):
-                    raise ValueError("Should set batch size when input data "
-                                     "don't contain length.")
         batch_size = len(input)
 
         def __reader_impl__():
@@ -41,10 +30,7 @@ class Inference(object):
                 yield each_sample
 
         reader = minibatch.batch(__reader_impl__, batch_size=batch_size)
-        else:
-            if input is not None:
-                raise ValueError("User should set either input or reader, "
-                                 "should not set them both.")
+
         self.__gradient_machine__.start()
         for data_batch in reader():
             yield self.__gradient_machine__.forwardTest(feeder(data_batch))