diff --git a/mozc-nazoru/bin/nazoru-training b/mozc-nazoru/bin/nazoru-training
index a851631..a28288d 100755
--- a/mozc-nazoru/bin/nazoru-training
+++ b/mozc-nazoru/bin/nazoru-training
@@ -15,8 +15,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tensorflow.contrib import slim
-from tensorflow.contrib.slim.python.slim.learning import train_step
+import tf_slim as slim
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import graph_util
 from tensorflow.python.platform import gfile
@@ -31,7 +30,7 @@ import nazoru.core as nazoru
 import numpy as np
 import os
 import sys
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 import zipfile
 
 FLAGS = None
@@ -139,6 +138,7 @@ def main(_):
     nazoru.DepthSepConv(kernel=[3, 3], stride=1, depth=128),
   ]
 
+  tf.disable_eager_execution()
   with tf.Graph().as_default():
     tf.logging.set_verbosity(tf.logging.INFO)
 
@@ -176,7 +176,7 @@ def main(_):
     train_op = slim.learning.create_train_op(train_total_loss, optimizer)
 
     def train_step_fn(sess, *args, **kwargs):
-      total_loss, should_stop = train_step(sess, *args, **kwargs)
+      total_loss, should_stop = slim.learning.train_step(sess, *args, **kwargs)
       if train_step_fn.step % FLAGS.n_steps_to_log == 0:
         val_acc = sess.run(val_accuracy)
         tf_logging.info('step: %d, validation accuracy: %.3f' % (
@@ -236,19 +236,19 @@ if __name__ == '__main__':
   parser.add_argument(
       '--output_graph',
       type=str,
-      default='nazoru.pb',
+      default='nazoru_custom.pb',
       help='Where to save the trained graph.'
   )
   parser.add_argument(
       '--optimized_output_graph',
       type=str,
-      default='optimized_nazoru.pb',
+      default='optimized_nazoru_custom.pb',
       help='Where to save the trained graph optimized for inference.'
   )
   parser.add_argument(
       '--saved_model_dir',
       type=str,
-      default='nazoru_saved_model',
+      default='nazoru_saved_model_custom',
       help='Where to save the exported graph.'
   )
   parser.add_argument(
diff --git a/mozc-nazoru/setup.py b/mozc-nazoru/setup.py
index 827e54e..acedbb0 100755
--- a/mozc-nazoru/setup.py
+++ b/mozc-nazoru/setup.py
@@ -59,12 +59,10 @@ setup(
     # data_files=[('/etc/systemd/system', ['data/nazoru.service'])],
 
     install_requires=[
-        'np_utils',
-        'cairocffi<=1.0.0',
-        'h5py',
+        'cairocffi',
         'pillow',
-        'tensorflow~=1.15.4',
-        'markdown<=3.0.1',
+        'tensorflow~=2.5.1',
+        'tf_slim~=1.1.0',
         'enum34;python_version<"3.4"',
         'pyserial',
         'evdev;platform_system=="Linux"',
diff --git a/mozc-nazoru/src/nazoru/nazorunet.py b/mozc-nazoru/src/nazoru/nazorunet.py
index 2fabab3..c3c5073 100644
--- a/mozc-nazoru/src/nazoru/nazorunet.py
+++ b/mozc-nazoru/src/nazoru/nazorunet.py
@@ -20,8 +20,8 @@ predict input characters from visualized trace.
 """
 
 from collections import namedtuple
-from tensorflow.contrib import slim
-import tensorflow as tf
+import tf_slim as slim
+import tensorflow.compat.v1 as tf
 
 Conv = namedtuple('Conv', ['kernel', 'stride', 'depth'])
 DepthSepConv = namedtuple('DepthSepConv', ['kernel', 'stride', 'depth'])
@@ -161,7 +161,7 @@ def nazorunet(inputs,
               is_training=True,
               min_depth=8,
               depth_multiplier=1.0,
-              prediction_fn=tf.contrib.layers.softmax,
+              prediction_fn=slim.layers.softmax,
               spatial_squeeze=True,
               reuse=None,
               scope='NazoruNet',
diff --git a/mozc-nazoru/src/nazoru/predictor.py b/mozc-nazoru/src/nazoru/predictor.py
index 94a6ed7..20c907e 100644
--- a/mozc-nazoru/src/nazoru/predictor.py
+++ b/mozc-nazoru/src/nazoru/predictor.py
@@ -23,7 +23,7 @@ import numpy as np
 
 def _load_graph(model_file):
   graph = tf.Graph()
-  graph_def = tf.GraphDef()
+  graph_def = tf.compat.v1.GraphDef()
   with open(model_file, "rb") as f:
     graph_def.ParseFromString(f.read())
   with graph.as_default():
@@ -44,7 +44,7 @@ class NazoruPredictor():
       inputs = lib.keydowns2image(data, True, True, 16, 2)
       inputs = np.expand_dims(inputs, axis=0)
     with utils.Measure('sess.run'):
-      with tf.Session(graph=self._graph) as sess:
+      with tf.compat.v1.Session(graph=self._graph) as sess:
         result = sess.run(self._output_operation.outputs[0],
                           {self._input_operation.outputs[0]: inputs})[0]
     return result