diff --git a/dezero/datasets.py b/dezero/datasets.py
index c43ce83..86ec727 100644
--- a/dezero/datasets.py
+++ b/dezero/datasets.py
@@ -47,7 +47,7 @@ def get_spiral(train=True):
     num_data, num_class, input_dim = 100, 3, 2
     data_size = num_class * num_data
     x = np.zeros((data_size, input_dim), dtype=np.float32)
-    t = np.zeros(data_size, dtype=np.int)
+    t = np.zeros(data_size, dtype=int)
 
     for j in range(num_class):
         for i in range(num_data):
@@ -137,7 +137,7 @@ def prepare(self):
         filepath = get_file(url)
         if self.train:
             self.data = np.empty((50000, 3 * 32 * 32))
-            self.label = np.empty((50000), dtype=np.int)
+            self.label = np.empty((50000), dtype=int)
             for i in range(5):
                 self.data[i * 10000:(i + 1) * 10000] = self._load_data(
                     filepath, i + 1, 'train')
diff --git a/dezero/transforms.py b/dezero/transforms.py
index 8bcf1b0..df01b17 100644
--- a/dezero/transforms.py
+++ b/dezero/transforms.py
@@ -151,5 +151,5 @@ def __call__(self, array):
 
 
 class ToInt(AsType):
-    def __init__(self, dtype=np.int):
+    def __init__(self, dtype=int):
         self.dtype = dtype
diff --git a/examples/gan.py b/examples/gan.py
index 7784554..9d314ce 100755
--- a/examples/gan.py
+++ b/examples/gan.py
@@ -74,8 +74,8 @@ def init_weight(dis, gen, hidden_size):
 else:
     xp = np
 
-label_real = xp.ones(batch_size).astype(np.int)
-label_fake = xp.zeros(batch_size).astype(np.int)
+label_real = xp.ones(batch_size).astype(int)
+label_fake = xp.zeros(batch_size).astype(int)
 test_z = xp.random.randn(25, hidden_size).astype(np.float32)
 
 
@@ -130,4 +130,4 @@ def generate_image():
             epoch_detail = epoch + cnt / train_loader.max_iter
             print('epoch: {:.2f}, loss_g: {:.4f}, loss_d: {:.4f}'.format(
                 epoch_detail, float(avg_loss_g/cnt), float(avg_loss_d/cnt)))
-            generate_image()
\ No newline at end of file
+            generate_image()