Fix python api of mean iou op. (#11797) (#11827)

* Fix mean iou op.

* Fix crop layer test.

* Fix unitest

* fix unitest.

python/paddle/fluid/layers/nn.py

@@ -5015,12 +5015,12 @@ def mean_iou(input, label, num_classes):
     out_correct = helper.create_tmp_variable(dtype='int32')
     helper.append_op(
         type="mean_iou",
-        inputs={"predictions": input,
-                "labels": label},
+        inputs={"Predictions": input,
+                "Labels": label},
         outputs={
-            "out_mean_iou": out_mean_iou,
-            "out_wrong": out_wrong,
-            "out_correct": out_correct
+            "OutMeanIou": out_mean_iou,
+            "OutWrong": out_wrong,
+            "OutCorrect": out_correct
         },
         attrs={"num_classes": num_classes})
     return out_mean_iou, out_wrong, out_correct

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

@@ -401,7 +401,7 @@ class TestBook(unittest.TestCase):
             self.assertIsNotNone(output)
         print(str(program))
 
-    def test_maxout(self):
+    def test_crop(self):
         program = Program()
         with program_guard(program):
             x = layers.data(name='x', shape=[3, 5], dtype="float32")
@@ -410,6 +410,15 @@ class TestBook(unittest.TestCase):
             self.assertIsNotNone(output)
         print(str(program))
 
+    def test_mean_iou(self):
+        program = Program()
+        with program_guard(program):
+            x = layers.data(name='x', shape=[16], dtype='float32')
+            y = layers.data(name='label', shape=[1], dtype='int64')
+            iou = layers.mean_iou(x, y, 2)
+            self.assertIsNotNone(iou)
+        print(str(program))
+
 
 if __name__ == '__main__':
     unittest.main()