diff --git a/vocoder/tf/models/melgan_generator.py b/vocoder/tf/models/melgan_generator.py
index 8a2a49be..6ec269c8 100644
--- a/vocoder/tf/models/melgan_generator.py
+++ b/vocoder/tf/models/melgan_generator.py
@@ -83,6 +83,7 @@ class MelganGenerator(tf.keras.models.Model):  # pylint: disable=too-many-ancest
         # self.model_layers = tf.keras.models.Sequential(self.initial_layer + self.upsample_layers + self.final_layers, name="layers")
         self.model_layers = self.initial_layer + self.upsample_layers + self.final_layers
 
+    @tf.function(experimental_relax_shapes=True)
     def call(self, c, training=False):
         """
         c : B x C x T
@@ -94,10 +95,15 @@ class MelganGenerator(tf.keras.models.Model):  # pylint: disable=too-many-ancest
     def inference(self, c):
         c = tf.transpose(c, perm=[0, 2, 1])
         c = tf.expand_dims(c, 2)
-        c = tf.pad(c, [[0, 0], [self.inference_padding, self.inference_padding], [0, 0], [0, 0]], "REFLECT")
+        # FIXME: TF had no replicate padding as in Torch
+        # c = tf.pad(c, [[0, 0], [self.inference_padding, self.inference_padding], [0, 0], [0, 0]], "REFLECT")
         o = c
         for layer in self.model_layers:
             o = layer(o)
         # o = self.model_layers(c)
         o = tf.transpose(o, perm=[0, 3, 2, 1])
-        return o[:, :, 0, :]
\ No newline at end of file
+        return o[:, :, 0, :]
+
+    def build_inference(self):
+        x = tf.random.uniform((1, self.in_channels, 4), dtype=tf.float32)
+        self(x, training=False)
\ No newline at end of file
diff --git a/vocoder/tf/models/multiband_melgan_generator.py b/vocoder/tf/models/multiband_melgan_generator.py
index d3e1c754..2031aee4 100644
--- a/vocoder/tf/models/multiband_melgan_generator.py
+++ b/vocoder/tf/models/multiband_melgan_generator.py
@@ -37,7 +37,8 @@ class MultibandMelganGenerator(MelganGenerator):  # pylint: disable=too-many-anc
     def inference(self, c):
         c = tf.transpose(c, perm=[0, 2, 1])
         c = tf.expand_dims(c, 2)
-        c = tf.pad(c, [[0, 0], [self.inference_padding, self.inference_padding], [0, 0], [0, 0]], "REFLECT")
+        # FIXME: TF had no replicate padding as in Torch
+        # c = tf.pad(c, [[0, 0], [self.inference_padding, self.inference_padding], [0, 0], [0, 0]], "REFLECT")
         o = c
         for layer in self.model_layers:
             o = layer(o)