Sidecar supports both vocoders and uses the one in the HTTP request

models/tacotron2/vocodes_common.py

@@ -234,6 +234,7 @@ class TacotronWaveglowPipeline:
 
     def infer(self, args):
         assert('synthesizer_checkpoint_path' in args)
+        assert('vocoder_type' in args)
         assert('raw_text' in args)
         assert('output_audio_filename' in args)
         assert('output_spectrogram_filename' in args)
@@ -246,13 +247,15 @@ class TacotronWaveglowPipeline:
         with torch.no_grad():
             mel_outputs, mel_outputs_postnet, _, alignments = tacotron.inference(sequence)
 
-        print('Saving spectrogram as JSON...')
-        save_spectorgram_json_file(mel_outputs_postnet, args['output_spectrogram_filename'])
-
-        if False:
+        if args['vocoder_type'] == 'hifigan-superres':
+            self.vocode_hifigan_superres(args, mel_outputs_postnet)
+        elif args['vocoder_type'] == 'waveglow':
             self.vocode_waveglow(args, mel_outputs_postnet)
         else:
-            self.vocode_hifigan_superres(args, mel_outputs_postnet)
+            raise Exception('Wrong vocoder type: {}'.format(args['vocoder_type']))
+
+        print('Saving spectrogram as JSON...')
+        save_spectorgram_json_file(mel_outputs_postnet, args['output_spectrogram_filename'])
 
         print('Generating metadata file...')
         generate_metadata_file(args['output_audio_filename'], args['output_metadata_filename'])

models/tacotron2/vocodes_server.py

@@ -210,6 +210,7 @@ class ApiHandler():
 
         # Request parameters
         synthesizer_checkpoint_path = raw_data.get('synthesizer_checkpoint_path')
+        vocoder_type = raw_data.get('vocoder_type')
         waveglow_vocoder_checkpoint_path = raw_data.get('waveglow_vocoder_checkpoint_path')
         hifigan_vocoder_checkpoint_path = raw_data.get('hifigan_vocoder_checkpoint_path')
         hifigan_superres_vocoder_checkpoint_path = raw_data.get('hifigan_superres_vocoder_checkpoint_path')
@@ -223,6 +224,7 @@ class ApiHandler():
             raw_data.get('maybe_clear_synthesizer_checkpoint_path')
 
         print('synthesizer_checkpoint_path: {}'.format(synthesizer_checkpoint_path))
+        print('vocoder_type: {}'.format(vocoder_type))
         print('waveglow_vocoder_checkpoint_path: {}'.format(waveglow_vocoder_checkpoint_path))
         print('hifigan_vocoder_checkpoint_path: {}'.format(hifigan_vocoder_checkpoint_path))
         print('hifigan_superres_vocoder_checkpoint_path: {}'.format(hifigan_superres_vocoder_checkpoint_path))
@@ -245,6 +247,7 @@ class ApiHandler():
         inference_args = {
             'raw_text': inference_text,
             'synthesizer_checkpoint_path': synthesizer_checkpoint_path,
+            'vocoder_type': vocoder_type,
             'output_audio_filename': output_audio_filename,
             'output_spectrogram_filename': output_spectrogram_filename,
             'output_metadata_filename': output_metadata_filename,

src/database/enums/vocoder_type.rs

@@ -7,7 +7,11 @@ use crate::util::anyhow_result::AnyhowResult;
 #[serde(rename_all = "lowercase")]
 #[sqlx(rename_all = "lowercase")]
 pub enum VocoderType {
+  /// Current state of the art vocoder
+  #[serde(rename = "hifigan-superres")]
   HifiGanSuperResolution,
+
+  /// Older WaveGlow vocoder
   WaveGlow,
 }
 

src/tts_inference_job.rs

@@ -665,7 +665,7 @@ async fn process_job(
   inferencer.tts_inference_sidecar_client.request_inference(
     &job.raw_inference_text,
     &tts_synthesizer_fs_path,
-    VocoderType::WaveGlow,
+    VocoderType::HifiGanSuperResolution,
     &hifigan_vocoder_model_fs_path,
     &hifigan_superres_vocoder_model_fs_path,
     &waveglow_vocoder_model_fs_path,