2023-08-14 10:46:07 -04:00
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import copy
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from pathlib import Path
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import gradio as gr
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import torch
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import yaml
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from transformers import is_torch_xpu_available
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from modules import shared
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with open(Path(__file__).resolve().parent / '../css/NotoSans/stylesheet.css', 'r') as f:
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css = f.read()
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with open(Path(__file__).resolve().parent / '../css/main.css', 'r') as f:
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css += f.read()
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with open(Path(__file__).resolve().parent / '../js/main.js', 'r') as f:
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js = f.read()
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with open(Path(__file__).resolve().parent / '../js/save_files.js', 'r') as f:
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save_files_js = f.read()
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with open(Path(__file__).resolve().parent / '../js/switch_tabs.js', 'r') as f:
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switch_tabs_js = f.read()
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with open(Path(__file__).resolve().parent / '../js/show_controls.js', 'r') as f:
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show_controls_js = f.read()
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with open(Path(__file__).resolve().parent / '../js/update_big_picture.js', 'r') as f:
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update_big_picture_js = f.read()
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refresh_symbol = '🔄'
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delete_symbol = '🗑️'
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save_symbol = '💾'
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theme = gr.themes.Default(
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font=['Noto Sans', 'Helvetica', 'ui-sans-serif', 'system-ui', 'sans-serif'],
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font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'],
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).set(
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border_color_primary='#c5c5d2',
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button_large_padding='6px 12px',
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body_text_color_subdued='#484848',
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background_fill_secondary='#eaeaea'
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)
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if Path("notification.mp3").exists():
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audio_notification_js = "document.querySelector('#audio_notification audio')?.play();"
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else:
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audio_notification_js = ""
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def list_model_elements():
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elements = [
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'loader',
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'filter_by_loader',
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'cpu_memory',
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'auto_devices',
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'disk',
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'cpu',
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'bf16',
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'load_in_8bit',
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'trust_remote_code',
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'no_use_fast',
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'use_flash_attention_2',
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'load_in_4bit',
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'compute_dtype',
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'quant_type',
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'use_double_quant',
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'wbits',
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'groupsize',
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'model_type',
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'pre_layer',
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'triton',
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'desc_act',
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'no_inject_fused_attention',
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'no_inject_fused_mlp',
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'no_use_cuda_fp16',
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'disable_exllama',
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'disable_exllamav2',
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'cfg_cache',
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'no_flash_attn',
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'num_experts_per_token',
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'cache_8bit',
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'threads',
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'threads_batch',
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'n_batch',
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'no_mmap',
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'mlock',
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'no_mul_mat_q',
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'n_gpu_layers',
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'tensor_split',
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'n_ctx',
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'gpu_split',
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'max_seq_len',
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'compress_pos_emb',
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'alpha_value',
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'rope_freq_base',
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'numa',
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'logits_all',
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]
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if is_torch_xpu_available():
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for i in range(torch.xpu.device_count()):
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elements.append(f'gpu_memory_{i}')
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else:
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for i in range(torch.cuda.device_count()):
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elements.append(f'gpu_memory_{i}')
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return elements
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def list_interface_input_elements():
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elements = [
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'max_new_tokens',
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'auto_max_new_tokens',
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'max_tokens_second',
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'seed',
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'temperature',
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'temperature_last',
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'top_p',
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'min_p',
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'top_k',
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'typical_p',
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'epsilon_cutoff',
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'eta_cutoff',
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'repetition_penalty',
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'presence_penalty',
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'frequency_penalty',
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'repetition_penalty_range',
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'encoder_repetition_penalty',
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'no_repeat_ngram_size',
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'min_length',
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'do_sample',
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'penalty_alpha',
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'num_beams',
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'length_penalty',
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'early_stopping',
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'mirostat_mode',
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'mirostat_tau',
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'mirostat_eta',
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'grammar_string',
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'negative_prompt',
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'guidance_scale',
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'add_bos_token',
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'ban_eos_token',
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'custom_token_bans',
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'truncation_length',
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'custom_stopping_strings',
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'skip_special_tokens',
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'stream',
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'tfs',
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'top_a',
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]
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# Chat elements
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elements += [
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'textbox',
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'start_with',
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'character_menu',
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'history',
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'name1',
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'name2',
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'greeting',
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'context',
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'mode',
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'custom_system_message',
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'instruction_template_str',
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'chat_template_str',
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'chat_style',
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'chat-instruct_command',
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]
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# Notebook/default elements
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elements += [
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'textbox-notebook',
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'textbox-default',
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'output_textbox',
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'prompt_menu-default',
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'prompt_menu-notebook',
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]
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# Model elements
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elements += list_model_elements()
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return elements
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def gather_interface_values(*args):
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output = {}
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for i, element in enumerate(list_interface_input_elements()):
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output[element] = args[i]
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if not shared.args.multi_user:
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shared.persistent_interface_state = output
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return output
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def apply_interface_values(state, use_persistent=False):
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if use_persistent:
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state = shared.persistent_interface_state
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elements = list_interface_input_elements()
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if len(state) == 0:
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return [gr.update() for k in elements] # Dummy, do nothing
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else:
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return [state[k] if k in state else gr.update() for k in elements]
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def save_settings(state, preset, extensions, show_controls):
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output = copy.deepcopy(shared.settings)
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exclude = ['name2', 'greeting', 'context', 'turn_template']
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for k in state:
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if k in shared.settings and k not in exclude:
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output[k] = state[k]
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output['preset'] = preset
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output['prompt-default'] = state['prompt_menu-default']
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output['prompt-notebook'] = state['prompt_menu-notebook']
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output['character'] = state['character_menu']
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output['default_extensions'] = extensions
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output['seed'] = int(output['seed'])
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output['show_controls'] = show_controls
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return yaml.dump(output, sort_keys=False, width=float("inf"))
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def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_class, interactive=True):
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"""
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Copied from https://github.com/AUTOMATIC1111/stable-diffusion-webui
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"""
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def refresh():
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refresh_method()
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args = refreshed_args() if callable(refreshed_args) else refreshed_args
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for k, v in args.items():
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setattr(refresh_component, k, v)
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return gr.update(**(args or {}))
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refresh_button = gr.Button(refresh_symbol, elem_classes=elem_class, interactive=interactive)
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refresh_button.click(
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fn=refresh,
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inputs=[],
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outputs=[refresh_component]
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)
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return refresh_button
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