blame mrq/ai-voice-cloning#122

src/utils.py

@@ -35,7 +35,7 @@ from datetime import timedelta
 from tortoise.api import TextToSpeech, MODELS, get_model_path, pad_or_truncate
 from tortoise.utils.audio import load_audio, load_voice, load_voices, get_voice_dir, get_voices
 from tortoise.utils.text import split_and_recombine_text
-from tortoise.utils.device import get_device_name, set_device_name, get_device_count, get_device_vram
+from tortoise.utils.device import get_device_name, set_device_name, get_device_count, get_device_vram, do_gc
 
 MODELS['dvae.pth'] = "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/3704aea61678e7e468a06d8eea121dba368a798e/.models/dvae.pth"
 
@@ -1547,13 +1547,6 @@ def get_dataset_list(dir="./training/"):
 def get_training_list(dir="./training/"):
 	return sorted([f'./training/{d}/train.yaml' for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d)) and "train.yaml" in os.listdir(os.path.join(dir, d)) ])
 
-def do_gc():
-	gc.collect()
-	try:
-		torch.cuda.empty_cache()
-	except Exception as e:
-		pass
-
 def pad(num, zeroes):
 	return str(num).zfill(zeroes+1)
 

src/webui.py

@@ -301,6 +301,7 @@ def setup_gradio():
 	result_voices = get_voice_list("./results/")
 	autoregressive_models = get_autoregressive_models()
 	dataset_list = get_dataset_list()
+	training_list = get_training_list()
 
 	global GENERATE_SETTINGS_ARGS
 	GENERATE_SETTINGS_ARGS = list(inspect.signature(generate_proxy).parameters.keys())[:-1]
@@ -492,8 +493,7 @@ def setup_gradio():
 			with gr.Tab("Run Training"):
 				with gr.Row():
 					with gr.Column():
-						training_list = get_training_list()
-						training_configs = gr.Dropdown(label="Training Configuration", choices=training_list, value=training_list[0])
+						training_configs = gr.Dropdown(label="Training Configuration", choices=training_list, value=training_list[0] if len(training_list) else "")
 						refresh_configs = gr.Button(value="Refresh Configurations")
 						training_output = gr.TextArea(label="Console Output", interactive=False, max_lines=8)
 						verbose_training = gr.Checkbox(label="Verbose Console Output", value=True)