Set num output units based on audio processor and set imported audio processor based on config.json

train.py

@@ -325,17 +325,20 @@ def evaluate(model, criterion, criterion_st, data_loader, ap, current_step):
 def main(args):
     dataset = importlib.import_module('datasets.'+c.dataset)
     Dataset = getattr(dataset, 'MyDataset')
+    audio = importlib.import_module('utils.'+c.audio_processor)
+    AudioProcessor = getattr(audio, 'AudioProcessor')
 
-    ap = AudioProcessor(sample_rate = c.sample_rate,
-                        num_mels = c.num_mels, 
-                        min_level_db = c.min_level_db, 
-                        frame_shift_ms = c.frame_shift_ms,
-                        frame_length_ms = c.frame_length_ms,
-                        ref_level_db = c.ref_level_db,
-                        num_freq = c.num_freq,
-                        power = c.power,
-                        min_mel_freq = c.min_mel_freq,
-                        max_mel_freq = c.max_mel_freq)
+    ap = AudioProcessor(sample_rate=c.sample_rate,
+                        num_mels=c.num_mels, 
+                        min_level_db=c.min_level_db, 
+                        frame_shift_ms=c.frame_shift_ms,
+                        frame_length_ms=c.frame_length_ms,
+                        ref_level_db=c.ref_level_db,
+                        num_freq=c.num_freq,
+                        power=c.power,
+                        preemphasis=c.preemphasis,
+                        min_mel_freq=c.min_mel_freq,
+                        max_mel_freq=c.max_mel_freq)
 
     # Setup the dataset
     train_dataset = Dataset(c.data_path,
@@ -367,9 +370,10 @@ def main(args):
         val_loader = None
 
     model = Tacotron(c.embedding_size,
-                     c.num_freq,
+                     ap.num_freq,
                      c.num_mels,
                      c.r)
+    print(" | > Num output units : {}".format(ap.num_freq))
 
     optimizer = optim.Adam(model.parameters(), lr=c.lr)
     optimizer_st = optim.Adam(model.decoder.stopnet.parameters(), lr=c.lr)