--- a
+++ b/tests/test_data/test_blending.py
@@ -0,0 +1,42 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import torch
+
+from mmaction.datasets import CutmixBlending, MixupBlending
+
+
+def test_mixup():
+    alpha = 0.2
+    num_classes = 10
+    label = torch.randint(0, num_classes, (4, ))
+    mixup = MixupBlending(num_classes, alpha)
+
+    # NCHW imgs
+    imgs = torch.randn(4, 4, 3, 32, 32)
+    mixed_imgs, mixed_label = mixup(imgs, label)
+    assert mixed_imgs.shape == torch.Size((4, 4, 3, 32, 32))
+    assert mixed_label.shape == torch.Size((4, num_classes))
+
+    # NCTHW imgs
+    imgs = torch.randn(4, 4, 2, 3, 32, 32)
+    mixed_imgs, mixed_label = mixup(imgs, label)
+    assert mixed_imgs.shape == torch.Size((4, 4, 2, 3, 32, 32))
+    assert mixed_label.shape == torch.Size((4, num_classes))
+
+
+def test_cutmix():
+    alpha = 0.2
+    num_classes = 10
+    label = torch.randint(0, num_classes, (4, ))
+    mixup = CutmixBlending(num_classes, alpha)
+
+    # NCHW imgs
+    imgs = torch.randn(4, 4, 3, 32, 32)
+    mixed_imgs, mixed_label = mixup(imgs, label)
+    assert mixed_imgs.shape == torch.Size((4, 4, 3, 32, 32))
+    assert mixed_label.shape == torch.Size((4, num_classes))
+
+    # NCTHW imgs
+    imgs = torch.randn(4, 4, 2, 3, 32, 32)
+    mixed_imgs, mixed_label = mixup(imgs, label)
+    assert mixed_imgs.shape == torch.Size((4, 4, 2, 3, 32, 32))
+    assert mixed_label.shape == torch.Size((4, num_classes))