Update layers.py

layers.py

@@ -3,7 +3,6 @@ from librosa.filters import mel as librosa_mel_fn
 from audio_processing import dynamic_range_compression
 from audio_processing import dynamic_range_decompression
 from stft import STFT
-import torch.nn.functional as F
 
 
 class LinearNorm(torch.nn.Module):
@@ -36,16 +35,10 @@ class ConvNorm(torch.nn.Module):
             self.conv.weight, gain=torch.nn.init.calculate_gain(w_init_gain))
 
     def forward(self, signal):
-        if signal.dtype == torch.float16:
-            x = F.dropout(F.relu(self.conv(signal.to(torch.float32))), 0.5, self.training).to(torch.float16)
-        else:
-            x = F.dropout(F.relu(self.conv(signal)), 0.5, self.training)
-
-        conv_signal = x
+        conv_signal = self.conv(signal)
         return conv_signal
 
 
-
 class TacotronSTFT(torch.nn.Module):
     def __init__(self, filter_length=1024, hop_length=256, win_length=1024,
                  n_mel_channels=80, sampling_rate=22050, mel_fmin=0.0,
@@ -84,4 +77,4 @@ class TacotronSTFT(torch.nn.Module):
         magnitudes = magnitudes.data
         mel_output = torch.matmul(self.mel_basis, magnitudes)
         mel_output = self.spectral_normalize(mel_output)
-        return mel_output
+        return mel_output