Add the period for VITS multi-period discriminator in model_args

TTS/server/server.py

@@ -114,7 +114,7 @@ synthesizer = Synthesizer(
 use_multi_speaker = hasattr(synthesizer.tts_model, "num_speakers") and (
     synthesizer.tts_model.num_speakers > 1 or synthesizer.tts_speakers_file is not None
 )
-print("Multispeaker?", use_multi_speaker, synthesizer.tts_model.num_speakers)
+
 speaker_manager = getattr(synthesizer.tts_model, "speaker_manager", None)
 # TODO: set this from SpeakerManager
 use_gst = synthesizer.tts_config.get("use_gst", False)

TTS/tts/layers/vits/discriminator.py

@@ -58,10 +58,8 @@ class VitsDiscriminator(nn.Module):
         use_spectral_norm (bool): if `True` swith to spectral norm instead of weight norm.
     """
 
-    def __init__(self, use_spectral_norm=False):
+    def __init__(self, periods=(2, 3, 5, 7, 11), use_spectral_norm=False):
         super().__init__()
-        periods = [2, 3, 5, 7, 11]
-
         self.nets = nn.ModuleList()
         self.nets.append(DiscriminatorS(use_spectral_norm=use_spectral_norm))
         self.nets.extend([DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods])

TTS/tts/models/vits.py

@@ -362,6 +362,9 @@ class VitsArgs(Coqpit):
         upsample_kernel_sizes_decoder (List[int]):
             Kernel sizes for each upsampling layer of the decoder network. Defaults to `[16, 16, 4, 4]`.
 
+        periods_multi_period_discriminator (List[int]):
+            Periods values for Vits Multi-Period Discriminator. Defaults to `[2, 3, 5, 7, 11]`.
+
         use_sdp (bool):
             Use Stochastic Duration Predictor. Defaults to True.
 
@@ -475,6 +478,7 @@ class VitsArgs(Coqpit):
     upsample_rates_decoder: List[int] = field(default_factory=lambda: [8, 8, 2, 2])
     upsample_initial_channel_decoder: int = 512
     upsample_kernel_sizes_decoder: List[int] = field(default_factory=lambda: [16, 16, 4, 4])
+    periods_multi_period_discriminator: List[int] = field(default_factory=lambda: [2, 3, 5, 7, 11])
     use_sdp: bool = True
     noise_scale: float = 1.0
     inference_noise_scale: float = 0.667
@@ -628,7 +632,7 @@ class Vits(BaseTTS):
         )
 
         if self.args.init_discriminator:
-            self.disc = VitsDiscriminator(use_spectral_norm=self.args.use_spectral_norm_disriminator)
+            self.disc = VitsDiscriminator(periods=self.args.periods_multi_period_discriminator, use_spectral_norm=self.args.use_spectral_norm_disriminator)
 
         if self.args.TTS_part_sample_rate:
             self.interpolate_factor = self.config.audio["sample_rate"] / self.args.TTS_part_sample_rate

tests/tts_tests/test_vits_multilingual_speaker_emb_train.py

@@ -73,10 +73,11 @@ config.use_language_weighted_sampler = True
 
 # test upsample
 config.model_args.TTS_part_sample_rate = 11025
-config.model_args.interpolate_z = True
+config.model_args.interpolate_z = False
 config.model_args.detach_z_vocoder = True
 
-config.model_args.upsample_rates_decoder = [8, 8, 2, 2]
+config.model_args.upsample_rates_decoder = [8, 8, 4, 2]
+config.model_args.periods_multi_period_discriminator = [2, 3, 5, 7, 11, 13, 17, 19, 23]
 
 config.save_json(config_path)