test=develop

paddle/fluid/operators/reorg_op.cc

@@ -91,8 +91,8 @@ class ReorgOpMaker : public framework::OpProtoAndCheckerMaker {
 
         Examples:
 
-            1. Given a 3-D tensor Input(X) with a shape [2048, 26, 26], and the stride is 2, the reorg operator will transform Input(X)
-            into a 3-D tensor with shape [2048, 13, 13] and leaving Input(X)'s data unchanged.
+            1. Given a 4-D tensor Input(X) with a shape [128, 2048, 26, 26], and the stride is 2, the reorg operator will transform Input(X)
+            into a 4-D tensor with shape [128, 2048, 13, 13] and leaving Input(X)'s data unchanged.
 
     )DOC");
   }

python/paddle/fluid/layers/nn.py

@@ -7470,8 +7470,8 @@ def reorg(x, stride, name=None):
                 x=data, stride=2)
     """
 
-    if not (isinstance(stride, long)):
-        raise ValueError("stride must be a python long")
+    if not (isinstance(stride, int)):
+        raise ValueError("stride must be a python Int")
 
     helper = LayerHelper("reorg", **locals())
     if name is None:

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

@@ -256,7 +256,7 @@ class TestBook(unittest.TestCase):
                 shape=[32, 9, 6, 6],
                 append_batch_size=False,
                 dtype='float32')
-            self.assertIsNotNone(layers.reorg(data, long(3)))
+            self.assertIsNotNone(layers.reorg(data, 3))
         print(str(program))
 
     def test_sequence_unsqueeze(self):

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

@@ -22,16 +22,16 @@ from op_test import OpTest
 class TestReorgOp(OpTest):
     @staticmethod
     def helper(in_, width, height, channel, batch, stride, forward, out_):
-        channel_out = channel / (stride * stride)
+        channel_out = channel // (stride * stride)
         for b in range(batch):
             for k in range(channel):
                 for j in range(height):
                     for i in range(width):
                         in_index = i + width * (j + height * (k + channel * b))
                         channel2 = k % channel_out
-                        offset = k / channel_out
+                        offset = k // channel_out
                         width2 = i * stride + offset % stride
-                        height2 = j * stride + offset / stride
+                        height2 = j * stride + offset // stride
                         out_index = width2 + width * stride * (
                             height2 + height * stride *
                             (channel2 + channel_out * b))