diff --git a/mmseg/apis/inference.py b/mmseg/apis/inference.py
index 6fa7e3b34..7cebac986 100644
--- a/mmseg/apis/inference.py
+++ b/mmseg/apis/inference.py
@@ -89,7 +89,7 @@ def inference_segmentor(model, img):
         # scatter to specified GPU
         data = scatter(data, [device])[0]
     else:
-        data['img_metas'] = data['img_metas'][0].data
+        data['img_metas'] = [i.data[0] for i in data['img_metas']]
 
     # forward the model
     with torch.no_grad():
diff --git a/tests/test_inference.py b/tests/test_inference.py
new file mode 100644
index 000000000..046e03628
--- /dev/null
+++ b/tests/test_inference.py
@@ -0,0 +1,29 @@
+import os.path as osp
+
+import mmcv
+
+from mmseg.apis import inference_segmentor, init_segmentor
+
+
+def test_test_time_augmentation_on_cpu():
+    config_file = 'configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py'
+    config = mmcv.Config.fromfile(config_file)
+
+    # Remove pretrain model download for testing
+    config.model.pretrained = None
+    # Replace SyncBN with BN to inference on CPU
+    norm_cfg = dict(type='BN', requires_grad=True)
+    config.model.backbone.norm_cfg = norm_cfg
+    config.model.decode_head.norm_cfg = norm_cfg
+    config.model.auxiliary_head.norm_cfg = norm_cfg
+
+    # Enable test time augmentation
+    config.data.test.pipeline[1].flip = True
+
+    checkpoint_file = None
+    model = init_segmentor(config, checkpoint_file, device='cpu')
+
+    img = mmcv.imread(
+        osp.join(osp.dirname(__file__), 'data/color.jpg'), 'color')
+    result = inference_segmentor(model, img)
+    assert result[0].shape == (288, 512)