fix typo

python/paddle/fluid/tests/unittests/test_reduce_op.py

@@ -795,7 +795,9 @@ def test_dygraph(self):
         paddle.disable_static()
         for place in self.places:
             with fluid.dygraph.guard(place):
-                x = fluid.layers.assign(np.array([[1, 0], [1, 1]], dtype='int32'))
+                x = fluid.layers.assign(
+                    np.array(
+                        [[1, 0], [1, 1]], dtype='int32'))
                 x = fluid.layers.cast(x, 'bool')
 
                 out1 = paddle.all(x)
@@ -825,47 +827,49 @@ def setUp(self):
         self.places = [fluid.CPUPlace()]
         if core.is_compiled_with_cuda():
             self.places.append(fluid.CUDAPlace(0))
-    
+
     def check_static_result(self, place):
         paddle.disable_static()
         with fluid.program_guard(fluid.Program(), fluid.Program()):
             input = fluid.data(name="input", shape=[4, 4], dtype="float64")
             result = paddle.inverse(x=input)
             input_np = np.random.random([4, 4]).astype("float64")
             result_np = np.linalg.inv(input_np)
-            
+
             exe = fluid.Executor(place)
             fetches = exe.run(fluid.default_main_program(),
                               feed={"input": input_np},
                               fetch_list=[result])
             self.assertTrue(np.allclose(fetches[0], np.linalg.inv(input_np)))
-    
+
     def test_static(self):
         for place in self.places:
             self.check_static_result(place=place)
-    
+
     def test_dygraph(self):
         paddle.disable_static()
         for place in self.places:
             with fluid.dygraph.guard(place):
-                x = fluid.layers.assign(np.array([[1, 0], [1, 1]], dtype='int32'))
+                x = fluid.layers.assign(
+                    np.array(
+                        [[1, 0], [1, 1]], dtype='int32'))
                 x = fluid.layers.cast(x, 'bool')
-                
+
                 out1 = paddle.any(x)
                 res1 = fluid.layers.assign(np.array([1], dtype='int32'))
                 res1 = fluid.layers.cast(res1, 'bool')
                 self.assertTrue(out1, res1)
-                
+
                 out2 = paddle.any(x, axis=0)
                 res2 = fluid.layers.assign(np.array([1, 0], dtype='int32'))
                 res2 = fluid.layers.cast(res2, 'bool')
                 self.assertTrue(out2, res2)
-                
+
                 out3 = paddle.any(x, axis=-1)
                 res3 = fluid.layers.assign(np.array([1, 0], dtype='int32'))
                 res3 = fluid.layers.cast(res3, 'bool')
                 self.assertTrue(out3, res3)
-                
+
                 out4 = paddle.any(x, axis=1, keep_dim=True)
                 res4 = fluid.layers.assign(np.array([[1, 0]], dtype='int32'))
                 res4 = fluid.layers.cast(res4, 'bool')