do not check sample rate as loading stats file for normalization to enable interpolation for different sample rate vocoder

.gitignore

@@ -129,3 +129,4 @@ TODO.txt
 .vscode/*
 data/*
 notebooks/data/*
+TTS/tts/layers/glow_tts/monotonic_align/core.c

TTS/tts/models/glow_tts.py

@@ -69,19 +69,18 @@ class GlowTts(nn.Module):
         self.length_scale=1.
 
         self.encoder = Encoder(num_chars,
-                                out_channels=out_channels,
-                                hidden_channels=hidden_channels,
-                                filter_channels=filter_channels,
-                                filter_channels_dp=filter_channels_dp,
-                                encoder_type=encoder_type,
-                                num_heads=num_heads,
-                                num_layers=num_layers_enc,
-                                kernel_size=kernel_size,
-                                dropout_p=dropout_p,
-                                mean_only=mean_only,
-                                use_prenet=use_encoder_prenet,
-                                c_in_channels=c_in_channels)
-
+                               out_channels=out_channels,
+                               hidden_channels=hidden_channels,
+                               filter_channels=filter_channels,
+                               filter_channels_dp=filter_channels_dp,
+                               encoder_type=encoder_type,
+                               num_heads=num_heads,
+                               num_layers=num_layers_enc,
+                               kernel_size=kernel_size,
+                               dropout_p=dropout_p,
+                               mean_only=mean_only,
+                               use_prenet=use_encoder_prenet,
+                               c_in_channels=c_in_channels)
 
         self.decoder = Decoder(out_channels,
                                hidden_channels_dec or hidden_channels,

TTS/utils/audio.py

@@ -174,8 +174,9 @@ class AudioProcessor(object):
         for key in stats_config.keys():
             if key in skip_parameters:
                 continue
-            assert stats_config[key] == self.__dict__[key],\
-                f" [!] Audio param {key} does not match the value used for computing mean-var stats. {stats_config[key]} vs {self.__dict__[key]}"
+            if key != 'sample_rate':
+                assert stats_config[key] == self.__dict__[key],\
+                    f" [!] Audio param {key} does not match the value used for computing mean-var stats. {stats_config[key]} vs {self.__dict__[key]}"
         return mel_mean, mel_std, linear_mean, linear_std, stats_config
 
     # pylint: disable=attribute-defined-outside-init
@@ -322,6 +323,7 @@ class AudioProcessor(object):
     def load_wav(self, filename, sr=None):
         if sr is None:
             x, sr = sf.read(filename)
+            assert self.sample_rate == sr, "%s vs %s"%(self.sample_rate, sr)
         else:
             x, sr = librosa.load(filename, sr=sr)
         if self.do_trim_silence:
@@ -329,7 +331,6 @@ class AudioProcessor(object):
                 x = self.trim_silence(x)
             except ValueError:
                 print(f' [!] File cannot be trimmed for silence - {filename}')
-        assert self.sample_rate == sr, "%s vs %s"%(self.sample_rate, sr)
         if self.do_sound_norm:
             x = self.sound_norm(x)
         return x

TTS/vocoder/models/fullband_melgan_generator.py

@@ -0,0 +1,31 @@
+import torch
+
+from TTS.vocoder.models.melgan_generator import MelganGenerator
+
+
+class FullbandMelganGenerator(MelganGenerator):
+    def __init__(self,
+                 in_channels=80,
+                 out_channels=1,
+                 proj_kernel=7,
+                 base_channels=512,
+                 upsample_factors=(2, 8, 2, 2),
+                 res_kernel=3,
+                 num_res_blocks=4):
+        super(FullbandMelganGenerator,
+              self).__init__(in_channels=in_channels,
+                             out_channels=out_channels,
+                             proj_kernel=proj_kernel,
+                             base_channels=base_channels,
+                             upsample_factors=upsample_factors,
+                             res_kernel=res_kernel,
+                             num_res_blocks=num_res_blocks)
+
+    @torch.no_grad()
+    def inference(self, cond_features):
+        cond_features = cond_features.to(self.layers[1].weight.device)
+        cond_features = torch.nn.functional.pad(
+            cond_features,
+            (self.inference_padding, self.inference_padding),
+            'replicate')
+        return self.layers(cond_features)

TTS/vocoder/utils/generic_utils.py

@@ -67,6 +67,15 @@ def setup_generator(c):
             upsample_factors=c.generator_model_params['upsample_factors'],
             res_kernel=3,
             num_res_blocks=c.generator_model_params['num_res_blocks'])
+    if c.generator_model in 'fullband_melgan_generator':
+        model = MyModel(
+            in_channels=c.audio['num_mels'],
+            out_channels=1,
+            proj_kernel=7,
+            base_channels=512,
+            upsample_factors=c.generator_model_params['upsample_factors'],
+            res_kernel=3,
+            num_res_blocks=c.generator_model_params['num_res_blocks'])
     if c.generator_model in 'parallel_wavegan_generator':
         model = MyModel(
             in_channels=1,