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Unload the model using the "Remove all" button

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oobabooga 2023-03-26 23:47:29 -03:00
parent e07c9e3093
commit 95c97e1747
1 changed files with 8 additions and 19 deletions
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25
server.py
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@ -50,26 +50,20 @@ def get_available_softprompts():
def get_available_loras(): def get_available_loras():
return ['None'] + sorted([item.name for item in list(Path('loras/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower) return ['None'] + sorted([item.name for item in list(Path('loras/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
def unload_model():
shared.model = shared.tokenizer = None
clear_torch_cache()
def load_model_wrapper(selected_model): def load_model_wrapper(selected_model):
if selected_model != shared.model_name: if selected_model != shared.model_name:
shared.model_name = selected_model shared.model_name = selected_model
shared.model = shared.tokenizer = None
clear_torch_cache() unload_model()
if selected_model != '':
shared.model, shared.tokenizer = load_model(shared.model_name) shared.model, shared.tokenizer = load_model(shared.model_name)
return selected_model return selected_model
def reload_model():
unload_model()
shared.model, shared.tokenizer = load_model(shared.model_name)
def unload_model():
shared.model = shared.tokenizer = None
if not shared.args.cpu:
gc.collect()
torch.cuda.empty_cache()
print("Model weights unloaded.")
def load_lora_wrapper(selected_lora): def load_lora_wrapper(selected_lora):
add_lora_to_model(selected_lora) add_lora_to_model(selected_lora)
default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')] default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')]
@ -128,9 +122,6 @@ def create_model_and_preset_menus():
with gr.Row(): with gr.Row():
shared.gradio['preset_menu'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset') shared.gradio['preset_menu'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
ui.create_refresh_button(shared.gradio['preset_menu'], lambda : None, lambda : {'choices': get_available_presets()}, 'refresh-button') ui.create_refresh_button(shared.gradio['preset_menu'], lambda : None, lambda : {'choices': get_available_presets()}, 'refresh-button')
with gr.Row():
shared.gradio['unload_model'] = gr.Button(value='Unload model to free VRAM', elem_id="unload_model")
shared.gradio['reload_model'] = gr.Button(value='Reload the model into VRAM', elem_id="reload_model")
def create_settings_menus(default_preset): def create_settings_menus(default_preset):
generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', return_dict=True) generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', return_dict=True)
@ -185,8 +176,6 @@ def create_settings_menus(default_preset):
shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip']) shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip'])
shared.gradio['model_menu'].change(load_model_wrapper, [shared.gradio['model_menu']], [shared.gradio['model_menu']], show_progress=True) shared.gradio['model_menu'].change(load_model_wrapper, [shared.gradio['model_menu']], [shared.gradio['model_menu']], show_progress=True)
shared.gradio['unload_model'].click(fn=unload_model,inputs=[],outputs=[])
shared.gradio['reload_model'].click(fn=reload_model,inputs=[],outputs=[])
shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio[k] for k in ['preset_menu_mirror', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']]) shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio[k] for k in ['preset_menu_mirror', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
shared.gradio['preset_menu_mirror'].change(load_preset_values, [shared.gradio['preset_menu_mirror']], [shared.gradio[k] for k in ['preset_menu', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']]) shared.gradio['preset_menu_mirror'].change(load_preset_values, [shared.gradio['preset_menu_mirror']], [shared.gradio[k] for k in ['preset_menu', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
shared.gradio['lora_menu'].change(load_lora_wrapper, [shared.gradio['lora_menu']], [shared.gradio['lora_menu'], shared.gradio['textbox']], show_progress=True) shared.gradio['lora_menu'].change(load_lora_wrapper, [shared.gradio['lora_menu']], [shared.gradio['lora_menu'], shared.gradio['textbox']], show_progress=True)