config refactor #4 WIP

TTS/bin/compute_statistics.py

@@ -8,33 +8,41 @@
 import numpy as np
 from tqdm import tqdm
 
+from TTS.utils.config_manager import ConfigManager
 from TTS.tts.datasets.preprocess import load_meta_data
 from TTS.utils.audio import AudioProcessor
 from TTS.utils.io import load_config
 
 
 def main():
     """Run preprocessing process."""
-    parser = argparse.ArgumentParser(description="Compute mean and variance of spectrogtram features.")
-    parser.add_argument(
-        "--config_path", type=str, required=True, help="TTS config file path to define audio processin parameters."
-    )
-    parser.add_argument("--out_path", type=str, required=True, help="save path (directory and filename).")
+    CONFIG = ConfigManager()
+
+    parser = argparse.ArgumentParser(
+        description="Compute mean and variance of spectrogtram features.")
+    parser.add_argument("config_path", type=str,
+                        help="TTS config file path to define audio processin parameters.")
+    parser.add_argument("out_path", type=str,
+                        help="save path (directory and filename).")
+    parser.add_argument("--data_path", type=str, required=False,
+                        help="folder including the target set of wavs overriding dataset config.")
+    parser = CONFIG.init_argparse(parser)
     args = parser.parse_args()
+    CONFIG.parse_argparse(args)
 
     # load config
-    CONFIG = load_config(args.config_path)
-    CONFIG.audio["signal_norm"] = False  # do not apply earlier normalization
-    CONFIG.audio["stats_path"] = None  # discard pre-defined stats
+    CONFIG.load_config(args.config_path)
+    CONFIG.audio_config.signal_norm = False  # do not apply earlier normalization
+    CONFIG.audio_config.stats_path = None  # discard pre-defined stats
 
     # load audio processor
-    ap = AudioProcessor(**CONFIG.audio)
+    ap = AudioProcessor(**CONFIG.audio_config.to_dict())
 
     # load the meta data of target dataset
-    if "data_path" in CONFIG.keys():
-        dataset_items = glob.glob(os.path.join(CONFIG.data_path, "**", "*.wav"), recursive=True)
+    if args.data_path:
+        dataset_items = glob.glob(os.path.join(args.data_path, '**', '*.wav'), recursive=True)
     else:
-        dataset_items = load_meta_data(CONFIG.datasets)[0]  # take only train data
+        dataset_items = load_meta_data(CONFIG.dataset_config)[0]  # take only train data
     print(f" > There are {len(dataset_items)} files.")
 
     mel_sum = 0
@@ -73,14 +81,15 @@ def main():
     print(f" > Avg lienar spec scale: {linear_scale.mean()}")
 
     # set default config values for mean-var scaling
-    CONFIG.audio["stats_path"] = output_file_path
-    CONFIG.audio["signal_norm"] = True
+    CONFIG.audio_config.stats_path = output_file_path
+    CONFIG.audio_config.signal_norm = True
     # remove redundant values
-    del CONFIG.audio["max_norm"]
-    del CONFIG.audio["min_level_db"]
-    del CONFIG.audio["symmetric_norm"]
-    del CONFIG.audio["clip_norm"]
-    stats["audio_config"] = CONFIG.audio
+    del CONFIG.audio_config.max_norm
+    del CONFIG.audio_config.min_level_db
+    del CONFIG.audio_config.symmetric_norm
+    del CONFIG.audio_config.clip_norm
+    breakpoint()
+    stats['audio_config'] = CONFIG.audio_config.to_dict()
     np.save(output_file_path, stats, allow_pickle=True)
     print(f" > stats saved to {output_file_path}")
 

TTS/bin/train_tacotron.py

@@ -10,11 +10,9 @@
 import numpy as np
 import torch
 from torch.utils.data import DataLoader
-
 from TTS.tts.datasets.preprocess import load_meta_data
 from TTS.tts.datasets.TTSDataset import MyDataset
 from TTS.tts.layers.losses import TacotronLoss
-from TTS.tts.configs.tacotron_config import TacotronConfig
 from TTS.tts.utils.generic_utils import setup_model
 from TTS.tts.utils.io import save_best_model, save_checkpoint
 from TTS.tts.utils.measures import alignment_diagonal_score
@@ -24,8 +22,11 @@
 from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
 from TTS.utils.arguments import parse_arguments, process_args
 from TTS.utils.audio import AudioProcessor
-from TTS.utils.distribute import DistributedSampler, apply_gradient_allreduce, init_distributed, reduce_tensor
-from TTS.utils.generic_utils import KeepAverage, count_parameters, remove_experiment_folder, set_init_dict
+from TTS.utils.config_manager import ConfigManager
+from TTS.utils.distribute import (DistributedSampler, apply_gradient_allreduce,
+                                  init_distributed, reduce_tensor)
+from TTS.utils.generic_utils import (KeepAverage, count_parameters,
+                                     remove_experiment_folder, set_init_dict)
 from TTS.utils.radam import RAdam
 from TTS.utils.training import (
     NoamLR,
@@ -739,7 +740,10 @@ def main(args):  # pylint: disable=redefined-outer-name
 
 if __name__ == "__main__":
     args = parse_arguments(sys.argv)
-    c, OUT_PATH, AUDIO_PATH, c_logger, tb_logger = process_args(args, model_class="tts")
+    c = TacotronConfig()
+    args = c.init_argparse(args)
+    c, OUT_PATH, AUDIO_PATH, c_logger, tb_logger = process_args(
+        args, c, model_type='tacotron')
 
     try:
         main(args)