diff --git a/mohou/model/third_party/variational_lstm.py b/mohou/model/third_party/variational_lstm.py
index eb34e1f..3cfcfc0 100644
--- a/mohou/model/third_party/variational_lstm.py
+++ b/mohou/model/third_party/variational_lstm.py
@@ -131,7 +131,7 @@ def _setweights(self):
 
             mask = torch.autograd.Variable(torch.ones(raw_w.size(0), 1))
             if raw_w.is_cuda:
-                mask = mask.cuda()
+                mask = mask.cuda()  # type: ignore[assignment]
             mask = dropout(mask, p=self.dropout, training=True)  # type: ignore
             w = mask.expand_as(raw_w) * raw_w
             setattr(self.module, name_w, w)
diff --git a/mohou/types.py b/mohou/types.py
index 6ec942c..d591916 100644
--- a/mohou/types.py
+++ b/mohou/types.py
@@ -325,7 +325,7 @@ def extract_contour_by_laplacian(
         blur_kernel_size = (int(rgb.shape[0] * 0.02), int(rgb.shape[1] * 0.02))
 
     src_gray = cv2.cvtColor(rgb.numpy(), cv2.COLOR_BGR2GRAY)
-    dst = cv2.Laplacian(src_gray, cv2.CV_8U, ksize=laplace_kernel_size)
+    dst = cv2.Laplacian(src_gray, cv2.CV_8U, ksize=laplace_kernel_size)  # type: ignore[attr-defined]
     dst2 = cv2.blur(dst, (blur_kernel_size[0], blur_kernel_size[1]))
     return GrayImage(np.expand_dims(np.uint8(dst2), axis=2))