fix_test_nms (#3050)

ppdet/modeling/tests/test_ops.py

@@ -570,16 +570,19 @@ class TestAnchorGenerator(LayerTest):
 
 class TestMulticlassNms(LayerTest):
     def test_multiclass_nms(self):
-        boxes_np = np.random.rand(81, 4).astype('float32')
-        scores_np = np.random.rand(81).astype('float32')
-        rois_num_np = np.array([40, 41]).astype('int32')
+        boxes_np = np.random.rand(10, 81, 4).astype('float32')
+        scores_np = np.random.rand(10, 81).astype('float32')
+        rois_num_np = np.array([2, 8]).astype('int32')
         with self.static_graph():
             boxes = paddle.static.data(
-                name='bboxes', shape=[81, 4], dtype='float32', lod_level=1)
+                name='bboxes',
+                shape=[None, 81, 4],
+                dtype='float32',
+                lod_level=1)
             scores = paddle.static.data(
-                name='scores', shape=[81], dtype='float32', lod_level=1)
+                name='scores', shape=[None, 81], dtype='float32', lod_level=1)
             rois_num = paddle.static.data(
-                name='rois_num', shape=[40, 41], dtype='int32')
+                name='rois_num', shape=[None], dtype='int32')
 
             output = ops.multiclass_nms(
                 bboxes=boxes,
@@ -599,7 +602,10 @@ class TestMulticlassNms(LayerTest):
                     'rois_num': rois_num_np
                 },
                 fetch_list=output,
-                with_lod=False)
+                with_lod=True)
+            out_np = np.array(out_np)
+            index_np = np.array(index_np)
+            nms_rois_num_np = np.array(nms_rois_num_np)
 
         with self.dynamic_graph():
             boxes_dy = base.to_variable(boxes_np)