diff --git a/research/pate_2018/core.py b/research/pate_2018/core.py
index 4abc9d0..36317c0 100644
--- a/research/pate_2018/core.py
+++ b/research/pate_2018/core.py
@@ -152,7 +152,7 @@ def rdp_gaussian(logq, sigma, orders):
     if np.isscalar(orders):
       return 0.
     else:
-      return np.full_like(orders, 0., dtype=np.float)
+      return np.full_like(orders, 0., dtype=float)
 
   variance = sigma**2
 
diff --git a/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py b/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
index 6230ea1..6cea99c 100644
--- a/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
+++ b/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
@@ -43,7 +43,7 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
         np.reshape(
             per_example_gradients,
             [num_microbatches,
-             np.int(batch_size / num_microbatches), num_vars]),
+             int(batch_size / num_microbatches), num_vars]),
         axis=1)
     microbatch_gradients_norms = np.linalg.norm(microbatch_gradients, axis=1)