Refactor logging initialization

TTS/trainer.py

@@ -38,7 +38,7 @@ from TTS.utils.generic_utils import (
     to_cuda,
 )
 from TTS.utils.io import copy_model_files, load_fsspec, save_best_model, save_checkpoint
-from TTS.utils.logging import ConsoleLogger, TensorboardLogger, WandbLogger
+from TTS.utils.logging import ConsoleLogger, TensorboardLogger, WandbLogger, init_logger
 from TTS.utils.trainer_utils import get_optimizer, get_scheduler, is_apex_available, setup_torch_training_env
 from TTS.vocoder.datasets.preprocess import load_wav_data, load_wav_feat_data
 from TTS.vocoder.models import setup_model as setup_vocoder_model
@@ -160,28 +160,14 @@ class Trainer:
         self.output_path = output_path
         self.args = args
         self.config = config
-
+        self.config.output_log_path = output_path
         # init loggers
         self.c_logger = ConsoleLogger() if c_logger is None else c_logger
         self.dashboard_logger = dashboard_logger
 
         if self.dashboard_logger is None:
-            if config.dashboard_logger == "tensorboard":
-                self.dashboard_logger = TensorboardLogger(output_path, model_name=config.model)
+            self.dashboard_logger = init_logger(config)
 
-            elif config.dashboard_logger == "wandb":
-                project_name = config.model
-                if config.project_name:
-                    project_name = config.project_name
-
-                self.dashboard_logger = WandbLogger(
-                    project=project_name,
-                    name=config.run_name,
-                    config=config,
-                    entity=config.wandb_entity,
-                )
-
-        self.dashboard_logger.add_text("model-config", f"<pre>{config.to_json()}</pre>", 0)
         if not self.config.log_model_step:
             self.config.log_model_step = self.config.save_step
 
@@ -1129,6 +1115,7 @@ def process_args(args, config=None):
     if not experiment_path:
         experiment_path = get_experiment_folder_path(config.output_path, config.run_name)
     audio_path = os.path.join(experiment_path, "test_audios")
+    config.output_log_path = experiment_path
     # setup rank 0 process in distributed training
     dashboard_logger = None
     if args.rank == 0:
@@ -1146,21 +1133,7 @@ def process_args(args, config=None):
         os.chmod(audio_path, 0o775)
         os.chmod(experiment_path, 0o775)
 
-        if config.dashboard_logger == "tensorboard":
-            dashboard_logger = TensorboardLogger(config.output_path, model_name=config.model)
-
-        elif config.dashboard_logger == "wandb":
-            project_name = config.model
-            if config.project_name:
-                project_name = config.project_name
-
-            dashboard_logger = WandbLogger(
-                project=project_name,
-                name=config.run_name,
-                config=config,
-                entity=config.wandb_entity,
-            )
-        dashboard_logger.add_text("model-config", f"<pre>{config.to_json()}</pre>", 0)
+    dashboard_logger = init_logger(config)
     c_logger = ConsoleLogger()
     return config, experiment_path, audio_path, c_logger, dashboard_logger
 

TTS/utils/logging/__init__.py

@@ -1,3 +1,24 @@
 from TTS.utils.logging.console_logger import ConsoleLogger
 from TTS.utils.logging.tensorboard_logger import TensorboardLogger
 from TTS.utils.logging.wandb_logger import WandbLogger
+
+
+def init_logger(config):
+    if config.dashboard_logger == "tensorboard":
+        dashboard_logger = TensorboardLogger(config.output_log_path, model_name=config.model)
+
+    elif config.dashboard_logger == "wandb":
+        project_name = config.model
+        if config.project_name:
+            project_name = config.project_name
+
+        dashboard_logger = WandbLogger(
+            project=project_name,
+            name=config.run_name,
+            config=config,
+            entity=config.wandb_entity,
+        )
+
+    dashboard_logger.add_text("model-config", f"<pre>{config.to_json()}</pre>", 0)
+
+    return dashboard_logger