diff --git a/TTS/utils/audio.py b/TTS/utils/audio.py
index f89d1ee5..618bc338 100644
--- a/TTS/utils/audio.py
+++ b/TTS/utils/audio.py
@@ -387,10 +387,9 @@ class AudioProcessor(object):
             x = self.sound_norm(x)
         return x
 
-    def save_wav(self, wav, path, sample_rate=None):
-        sample_rate = self.sample_rate if sample_rate is None else sample_rate
+    def save_wav(self, wav, path, sr=None):
         wav_norm = wav * (32767 / max(0.01, np.max(np.abs(wav))))
-        scipy.io.wavfile.write(path, sample_rate, wav_norm.astype(np.int16))
+        scipy.io.wavfile.write(path, sr if sr else self.sample_rate, wav_norm.astype(np.int16))
 
     @staticmethod
     def mulaw_encode(wav, qc):
diff --git a/TTS/vocoder/models/hifigan_generator.py b/TTS/vocoder/models/hifigan_generator.py
index 2b1f43f7..44b0edfa 100644
--- a/TTS/vocoder/models/hifigan_generator.py
+++ b/TTS/vocoder/models/hifigan_generator.py
@@ -1,8 +1,8 @@
 import torch
 import torch.nn.functional as F
 import torch.nn as nn
-from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from torch.nn import Conv1d, ConvTranspose1d
+from torch.nn.utils import weight_norm, remove_weight_norm
 
 LRELU_SLOPE = 0.1
 
@@ -115,6 +115,7 @@ class HifiganGenerator(torch.nn.Module):
                  resblock_kernel_sizes, upsample_kernel_sizes,
                  upsample_initial_channel, upsample_factors):
         super().__init__()
+        self.inference_padding = 5
         self.num_kernels = len(resblock_kernel_sizes)
         self.num_upsamples = len(upsample_factors)
         self.conv_pre = weight_norm(