fixed dac

vall_e/config.py

@@ -318,7 +318,6 @@ class Model:
 	name: str = "ar+nar" # vanity name for the model
 	version: int = 5 # 1 = old with MultiEmbedding, 2 = new with AudioEmbedding, 3+ = additional embeddings
 	size: str | dict = "full" # preset string or explicitly defined dimensionality
-	resp_levels: int = 8 # RVQ-bin levels this model supports
 	tasks: int = 8 # ["tts", "ns", "sr", "tse", "cse", "nse"] and leaves two more for anything else I want (like "svc") (unused)
 	langs: int = 1 # defined languages (semi-unused)
 	tones: int = 1 # defined tones (unsued)
@@ -382,6 +381,16 @@ class Model:
 	def tokens(self):
 		return self.audio_tokens
 
+	@property
+	def resp_levels(self):
+		if isinstance(self.size, dict) and "resp_levels" in self.size:
+			return self.size['resp_levels']
+		
+		if cfg.audio_backend == "dac":
+			return 9
+
+		return 8
+
 	@property
 	def audio_tokens(self):
 		if isinstance(self.size, dict) and "audio_tokens" in self.size:
@@ -1043,6 +1052,10 @@ class Config(BaseConfig):
 			if not isinstance( model, dict ):
 				continue
 
+			# was made an inherent property tied to audio_backend
+			if "resp_levels" in model:
+				del model["resp_levels"]
+
 			# to-do: prune unused keys in here too automatically
 			if "experimental" not in model or not model["experimental"]:
 				model["experimental"] = {}

vall_e/emb/codecs/dac.py

@@ -2,7 +2,7 @@ import torch
 
 from dac import DACFile
 from audiotools import AudioSignal
-from dac.utils import load_model as __load_dac_model
+from dac.utils import load_model as load_dac_model
 
 from typing import Union
 from pathlib import Path

vall_e/emb/qnt.py

@@ -117,7 +117,7 @@ def _load_dac_model(device="cuda", dtype=None):
 	else:
 		raise Exception(f'unsupported sample rate: {cfg.sample_rate}')
 
-	model = __load_dac_model(**kwargs)
+	model = load_dac_model(**kwargs)
 	model = model.to(device)
 	model = model.eval()
 

vall_e/models/ar_nar_v2.py

@@ -828,7 +828,7 @@ def example_usage():
 		available_tasks = ["tts-nar"]
 
 	model = AR_NAR_V2(**kwargs).to(cfg.device)
-	steps = 500 // batch_size
+	steps = 250 # // batch_size
 
 	optimizer = cfg.hyperparameters.optimizer.lower() if cfg.yaml_path is not None else "prodigy"
 	scheduler = cfg.hyperparameters.scheduler.lower() if cfg.yaml_path is not None else ""