Add class map in emotion config

TTS/bin/train_encoder.py

@@ -18,7 +18,7 @@ from TTS.encoder.utils.visual import plot_embeddings
 from TTS.tts.datasets import load_tts_samples
 from TTS.utils.audio import AudioProcessor
 from TTS.utils.generic_utils import count_parameters, remove_experiment_folder, set_init_dict
-from TTS.utils.io import load_fsspec
+from TTS.utils.io import load_fsspec, copy_model_files
 from TTS.utils.radam import RAdam
 from TTS.utils.training import check_update
 
@@ -56,8 +56,9 @@ def setup_loader(ap: AudioProcessor, is_val: bool = False, verbose: bool = False
             shuffle=False,
             num_workers=c.num_loader_workers,
             collate_fn=dataset.collate_fn,
-        )
-    return loader, dataset.get_num_classes()
+        )     
+
+    return loader, dataset.get_num_classes(), dataset.get_map_classid_to_classname()
 
 
 def train(model, optimizer, scheduler, criterion, data_loader, global_step):
@@ -160,7 +161,7 @@ def main(args):  # pylint: disable=redefined-outer-name
     # pylint: disable=redefined-outer-name
     meta_data_train, meta_data_eval = load_tts_samples(c.datasets, eval_split=False)
 
-    data_loader, num_classes = setup_loader(ap, is_val=False, verbose=True)
+    data_loader, num_classes, map_classid_to_classname = setup_loader(ap, is_val=False, verbose=True)
 
     if c.loss == "ge2e":
         criterion = GE2ELoss(loss_method="softmax")
@@ -168,6 +169,11 @@ def main(args):  # pylint: disable=redefined-outer-name
         criterion = AngleProtoLoss()
     elif c.loss == "softmaxproto":
         criterion = SoftmaxAngleProtoLoss(c.model_params["proj_dim"], num_classes)
+        if c.model == "emotion_encoder":
+            # update config with the class map
+            c.map_classid_to_classname = map_classid_to_classname
+            copy_model_files(c, OUT_PATH)
+            print(OUT_PATH)
     else:
         raise Exception("The %s  not is a loss supported" % c.loss)
 

TTS/encoder/dataset.py

@@ -102,6 +102,9 @@ class EncoderDataset(Dataset):
     def get_num_classes(self):
         return len(self.classes)
 
+    def get_map_classid_to_classname(self):
+        return dict((c_id, c_n) for c_n, c_id in self.classname_to_classid.items())
+
     def __sample_class(self, ignore_classes=None):
         class_name = random.sample(self.classes, 1)[0]
         # if list of classes_id is provide make sure that it's will be ignored

TTS/encoder/emotion_encoder_config.py

@@ -8,6 +8,7 @@ class EmotionEncoderConfig(SpeakerEncoderConfig):
     """Defines parameters for Speaker Encoder model."""
 
     model: str = "emotion_encoder"
+    map_classid_to_classname: dict = None
 
     def check_values(self):
         super().check_values()