diff --git a/mmseg/models/decode_heads/decode_head.py b/mmseg/models/decode_heads/decode_head.py
index 4faf54559d..179d871fd1 100644
--- a/mmseg/models/decode_heads/decode_head.py
+++ b/mmseg/models/decode_heads/decode_head.py
@@ -350,9 +350,17 @@ def predict_by_feat(self, seg_logits: Tensor,
             Tensor: Outputs segmentation logits map.
         """
 
+        if isinstance(batch_img_metas[0]['img_shape'], torch.Size):
+            # slide inference
+            size = batch_img_metas[0]['img_shape']
+        elif 'pad_shape' in batch_img_metas[0]:
+            size = batch_img_metas[0]['pad_shape'][:2]
+        else:
+            size = batch_img_metas[0]['img_shape']
+
         seg_logits = resize(
             input=seg_logits,
-            size=batch_img_metas[0]['img_shape'],
+            size=size,
             mode='bilinear',
             align_corners=self.align_corners)
         return seg_logits
diff --git a/mmseg/models/decode_heads/san_head.py b/mmseg/models/decode_heads/san_head.py
index 03dedf2e49..d20da80192 100644
--- a/mmseg/models/decode_heads/san_head.py
+++ b/mmseg/models/decode_heads/san_head.py
@@ -586,8 +586,11 @@ def predict_by_feat(self, seg_logits: List[Tensor],
         """
         mask_pred = seg_logits[0]
         cls_score = seg_logits[1]
-        if 'pad_shape' in batch_img_metas[0]:
-            size = batch_img_metas[0]['pad_shape']
+        if isinstance(batch_img_metas[0]['img_shape'], torch.Size):
+            # slide inference
+            size = batch_img_metas[0]['img_shape']
+        elif 'pad_shape' in batch_img_metas[0]:
+            size = batch_img_metas[0]['pad_shape'][:2]
         else:
             size = batch_img_metas[0]['img_shape']
         # upsample mask
diff --git a/projects/hssn/decode_head/sep_aspp_contrast_head.py b/projects/hssn/decode_head/sep_aspp_contrast_head.py
index d1d087362c..331af30de4 100644
--- a/projects/hssn/decode_head/sep_aspp_contrast_head.py
+++ b/projects/hssn/decode_head/sep_aspp_contrast_head.py
@@ -127,10 +127,17 @@ def predict_by_feat(self, seg_logits: Tuple[Tensor],
         # elif seg_logit.size(1) == 144 # For Mapillary dataset, 124+16+4
         # unofficial repository not release mapillary until 2023/2/6
 
+        if isinstance(batch_img_metas[0]['img_shape'], torch.Size):
+            # slide inference
+            size = batch_img_metas[0]['img_shape']
+        elif 'pad_shape' in batch_img_metas[0]:
+            size = batch_img_metas[0]['pad_shape'][:2]
+        else:
+            size = batch_img_metas[0]['img_shape']
         seg_logit = seg_logit[:, :-hiera_num_classes]
         seg_logit = resize(
             input=seg_logit,
-            size=batch_img_metas[0]['img_shape'],
+            size=size,
             mode='bilinear',
             align_corners=self.align_corners)