diff --git a/ppdet/engine/trainer.py b/ppdet/engine/trainer.py
index 55890a979ec294c865eae3c2f8ca1f1d5bc21317..f022793b61bc2bfc8efd0ae86e41291a19b0eb55 100644
--- a/ppdet/engine/trainer.py
+++ b/ppdet/engine/trainer.py
@@ -429,10 +429,8 @@ class Trainer(object):
         model = self.model
         if self.cfg.get('to_static', False):
             model = apply_to_static(self.cfg, model)
-        sync_bn = (
-            getattr(self.cfg, 'norm_type', None) == 'sync_bn' and
-            (self.cfg.use_gpu or self.cfg.use_npu or self.cfg.use_mlu) and
-            self._nranks > 1)
+        sync_bn = (getattr(self.cfg, 'norm_type', None) == 'sync_bn' and
+                   (self.cfg.use_gpu or self.cfg.use_mlu) and self._nranks > 1)
         if sync_bn:
             model = paddle.nn.SyncBatchNorm.convert_sync_batchnorm(model)
 
diff --git a/ppdet/modeling/heads/sparsercnn_head.py b/ppdet/modeling/heads/sparsercnn_head.py
index 801ff04fb772aec568dd94d9d4916d2b778e88fe..0534cf4ad704001b07fdd9c898e68dc6606a4f4b 100644
--- a/ppdet/modeling/heads/sparsercnn_head.py
+++ b/ppdet/modeling/heads/sparsercnn_head.py
@@ -317,12 +317,15 @@ class SparseRCNNHead(nn.Layer):
             pooler_scales = [1.0 / 4.0, 1.0 / 8.0, 1.0 / 16.0, 1.0 / 32.0]
             end_level = 3
 
+        aligned = True
+        if paddle.device.is_compiled_with_custom_device('npu'):
+            aligned = False
         box_pooler = RoIAlign(
             resolution=pooler_resolution,
             spatial_scale=pooler_scales,
             sampling_ratio=sampling_ratio,
             end_level=end_level,
-            aligned=True)
+            aligned=aligned)
         return box_pooler
 
     def forward(self, features, input_whwh):