From 56f6b7052a54b4a8442552ecf4105404684c7bd9 Mon Sep 17 00:00:00 2001 From: oobabooga <112222186+oobabooga@users.noreply.github.com> Date: Fri, 5 May 2023 23:14:56 -0300 Subject: [PATCH] Sort dropdowns numerically --- modules/training.py | 32 ++++++++--------- modules/utils.py | 61 ++++++++++++++++++++++++++++++++ server.py | 85 +++++++++++---------------------------------- 3 files changed, 95 insertions(+), 83 deletions(-) create mode 100644 modules/utils.py diff --git a/modules/training.py b/modules/training.py index 82e42f4d..278291cc 100644 --- a/modules/training.py +++ b/modules/training.py @@ -14,9 +14,9 @@ from datasets import Dataset, load_dataset from peft import (LoraConfig, get_peft_model, prepare_model_for_int8_training, set_peft_model_state_dict) -from modules import shared, ui +from modules import shared, ui, utils from modules.evaluate import calculate_perplexity, generate_markdown_table, save_past_evaluations -from server import get_available_loras, get_available_models + # This mapping is from a very recent commit, not yet released. # If not available, default to a backup map for some common model types. @@ -41,10 +41,6 @@ WANT_INTERRUPT = False PARAMETERS = ["lora_name", "always_override", "save_steps", "micro_batch_size", "batch_size", "epochs", "learning_rate", "lr_scheduler_type", "lora_rank", "lora_alpha", "lora_dropout", "cutoff_len", "dataset", "eval_dataset", "format", "eval_steps", "raw_text_file", "overlap_len", "newline_favor_len", "higher_rank_limit", "warmup_steps", "optimizer"] -def get_datasets(path: str, ext: str): - return ['None'] + sorted(set([k.stem for k in Path(path).glob(f'*.{ext}') if k.stem != 'put-trainer-datasets-here']), key=str.lower) - - def create_train_interface(): with gr.Tab('Train LoRA', elem_id='lora-train-tab'): gr.Markdown("Confused? [[Click here for a guide]](https://github.com/oobabooga/text-generation-webui/blob/main/docs/Training-LoRAs.md)") @@ -55,8 +51,8 @@ def create_train_interface(): save_steps = gr.Number(label='Save every n steps', value=0, info='If above 0, a checkpoint of the LoRA will be saved every time this many steps pass.') with gr.Row(): - copy_from = gr.Dropdown(label='Copy parameters from', value='None', choices=get_available_loras()) - ui.create_refresh_button(copy_from, lambda: None, lambda: {'choices': get_available_loras()}, 'refresh-button') + copy_from = gr.Dropdown(label='Copy parameters from', value='None', choices=utils.get_available_loras()) + ui.create_refresh_button(copy_from, lambda: None, lambda: {'choices': utils.get_available_loras()}, 'refresh-button') with gr.Row(): # TODO: Implement multi-device support. @@ -76,19 +72,19 @@ def create_train_interface(): with gr.Tab(label='Formatted Dataset'): with gr.Row(): - dataset = gr.Dropdown(choices=get_datasets('training/datasets', 'json'), value='None', label='Dataset', info='The dataset file to use for training.') - ui.create_refresh_button(dataset, lambda: None, lambda: {'choices': get_datasets('training/datasets', 'json')}, 'refresh-button') - eval_dataset = gr.Dropdown(choices=get_datasets('training/datasets', 'json'), value='None', label='Evaluation Dataset', info='The (optional) dataset file used to evaluate the model after training.') - ui.create_refresh_button(eval_dataset, lambda: None, lambda: {'choices': get_datasets('training/datasets', 'json')}, 'refresh-button') - format = gr.Dropdown(choices=get_datasets('training/formats', 'json'), value='None', label='Data Format', info='The format file used to decide how to format the dataset input.') - ui.create_refresh_button(format, lambda: None, lambda: {'choices': get_datasets('training/formats', 'json')}, 'refresh-button') + dataset = gr.Dropdown(choices=utils.get_datasets('training/datasets', 'json'), value='None', label='Dataset', info='The dataset file to use for training.') + ui.create_refresh_button(dataset, lambda: None, lambda: {'choices': utils.get_datasets('training/datasets', 'json')}, 'refresh-button') + eval_dataset = gr.Dropdown(choices=utils.get_datasets('training/datasets', 'json'), value='None', label='Evaluation Dataset', info='The (optional) dataset file used to evaluate the model after training.') + ui.create_refresh_button(eval_dataset, lambda: None, lambda: {'choices': utils.get_datasets('training/datasets', 'json')}, 'refresh-button') + format = gr.Dropdown(choices=utils.get_datasets('training/formats', 'json'), value='None', label='Data Format', info='The format file used to decide how to format the dataset input.') + ui.create_refresh_button(format, lambda: None, lambda: {'choices': utils.get_datasets('training/formats', 'json')}, 'refresh-button') eval_steps = gr.Number(label='Evaluate every n steps', value=100, info='If an evaluation dataset is given, test it every time this many steps pass.') with gr.Tab(label="Raw text file"): with gr.Row(): - raw_text_file = gr.Dropdown(choices=get_datasets('training/datasets', 'txt'), value='None', label='Text file', info='The raw text file to use for training.') - ui.create_refresh_button(raw_text_file, lambda: None, lambda: {'choices': get_datasets('training/datasets', 'txt')}, 'refresh-button') + raw_text_file = gr.Dropdown(choices=utils.get_datasets('training/datasets', 'txt'), value='None', label='Text file', info='The raw text file to use for training.') + ui.create_refresh_button(raw_text_file, lambda: None, lambda: {'choices': utils.get_datasets('training/datasets', 'txt')}, 'refresh-button') with gr.Row(): overlap_len = gr.Slider(label='Overlap Length', minimum=0, maximum=512, value=128, step=16, info='Overlap length - ie how many tokens from the prior chunk of text to include into the next chunk. (The chunks themselves will be of a size determined by Cutoff Length below). Setting overlap to exactly half the cutoff length may be ideal.') @@ -111,8 +107,8 @@ def create_train_interface(): with gr.Tab('Perplexity evaluation', elem_id='evaluate-tab'): with gr.Row(): with gr.Column(): - models = gr.Dropdown(get_available_models(), label='Models', multiselect=True) - evaluate_text_file = gr.Dropdown(choices=['wikitext', 'ptb', 'ptb_new'] + get_datasets('training/datasets', 'txt')[1:], value='wikitext', label='Input dataset', info='The raw text file on which the model will be evaluated. The first options are automatically downloaded: wikitext, ptb, and ptb_new. The next options are your local text files under training/datasets.') + models = gr.Dropdown(utils.get_available_models(), label='Models', multiselect=True) + evaluate_text_file = gr.Dropdown(choices=['wikitext', 'ptb', 'ptb_new'] + utils.get_datasets('training/datasets', 'txt')[1:], value='wikitext', label='Input dataset', info='The raw text file on which the model will be evaluated. The first options are automatically downloaded: wikitext, ptb, and ptb_new. The next options are your local text files under training/datasets.') with gr.Row(): stride_length = gr.Slider(label='Stride', minimum=1, maximum=2048, value=512, step=1, info='Used to make the evaluation faster at the cost of accuracy. 1 = slowest but most accurate. 512 is a common value.') max_length = gr.Slider(label='max_length', minimum=0, maximum=8096, value=0, step=1, info='The context for each evaluation. If set to 0, the maximum context length for the model will be used.') diff --git a/modules/utils.py b/modules/utils.py new file mode 100644 index 00000000..79969340 --- /dev/null +++ b/modules/utils.py @@ -0,0 +1,61 @@ +import os +import re +from pathlib import Path + +from modules import shared + + +def atoi(text): + return int(text) if text.isdigit() else text.lower() + + +def natural_keys(text): + return [atoi(c) for c in re.split(r'(\d+)', text)] + + +def get_available_models(): + if shared.args.flexgen: + return sorted([re.sub('-np$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if item.name.endswith('-np')], key=natural_keys) + else: + return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json', '.yaml'))], key=natural_keys) + + +def get_available_presets(): + return sorted(set((k.stem for k in Path('presets').glob('*.txt'))), key=natural_keys) + + +def get_available_prompts(): + prompts = [] + prompts += sorted(set((k.stem for k in Path('prompts').glob('[0-9]*.txt'))), key=natural_keys, reverse=True) + prompts += sorted(set((k.stem for k in Path('prompts').glob('*.txt'))), key=natural_keys) + prompts += ['None'] + return prompts + + +def get_available_characters(): + paths = (x for x in Path('characters').iterdir() if x.suffix in ('.json', '.yaml', '.yml')) + return ['None'] + sorted(set((k.stem for k in paths if k.stem != "instruction-following")), key=natural_keys) + + +def get_available_instruction_templates(): + path = "characters/instruction-following" + paths = [] + if os.path.exists(path): + paths = (x for x in Path(path).iterdir() if x.suffix in ('.json', '.yaml', '.yml')) + return ['None'] + sorted(set((k.stem for k in paths)), key=natural_keys) + + +def get_available_extensions(): + return sorted(set(map(lambda x: x.parts[1], Path('extensions').glob('*/script.py'))), key=natural_keys) + + +def get_available_softprompts(): + return ['None'] + sorted(set((k.stem for k in Path('softprompts').glob('*.zip'))), key=natural_keys) + + +def get_available_loras(): + return sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=natural_keys) + + +def get_datasets(path: str, ext: str): + return ['None'] + sorted(set([k.stem for k in Path(path).glob(f'*.{ext}') if k.stem != 'put-trainer-datasets-here']), key=natural_keys) diff --git a/server.py b/server.py index 603c82fc..c667f498 100644 --- a/server.py +++ b/server.py @@ -43,56 +43,11 @@ import torch import yaml from PIL import Image import modules.extensions as extensions_module -from modules import chat, shared, training, ui +from modules import chat, shared, training, ui, utils from modules.html_generator import chat_html_wrapper from modules.LoRA import add_lora_to_model from modules.models import load_model, load_soft_prompt, unload_model -from modules.text_generation import (encode, generate_reply, - stop_everything_event) - - -def get_available_models(): - if shared.args.flexgen: - return sorted([re.sub('-np$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if item.name.endswith('-np')], key=str.lower) - else: - return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json', '.yaml'))], key=str.lower) - - -def get_available_presets(): - return sorted(set((k.stem for k in Path('presets').glob('*.txt'))), key=str.lower) - - -def get_available_prompts(): - prompts = [] - prompts += sorted(set((k.stem for k in Path('prompts').glob('[0-9]*.txt'))), key=str.lower, reverse=True) - prompts += sorted(set((k.stem for k in Path('prompts').glob('*.txt'))), key=str.lower) - prompts += ['None'] - return prompts - - -def get_available_characters(): - paths = (x for x in Path('characters').iterdir() if x.suffix in ('.json', '.yaml', '.yml')) - return ['None'] + sorted(set((k.stem for k in paths if k.stem != "instruction-following")), key=str.lower) - - -def get_available_instruction_templates(): - path = "characters/instruction-following" - paths = [] - if os.path.exists(path): - paths = (x for x in Path(path).iterdir() if x.suffix in ('.json', '.yaml', '.yml')) - return ['None'] + sorted(set((k.stem for k in paths)), key=str.lower) - - -def get_available_extensions(): - return sorted(set(map(lambda x: x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower) - - -def get_available_softprompts(): - return ['None'] + sorted(set((k.stem for k in Path('softprompts').glob('*.zip'))), key=str.lower) - - -def get_available_loras(): - return sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower) +from modules.text_generation import encode, generate_reply, stop_everything_event def load_model_wrapper(selected_model): @@ -324,13 +279,13 @@ def create_model_menus(): with gr.Row(): with gr.Column(): with gr.Row(): - shared.gradio['model_menu'] = gr.Dropdown(choices=get_available_models(), value=shared.model_name, label='Model') - ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': get_available_models()}, 'refresh-button') + shared.gradio['model_menu'] = gr.Dropdown(choices=utils.get_available_models(), value=shared.model_name, label='Model') + ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': utils.get_available_models()}, 'refresh-button') with gr.Column(): with gr.Row(): - shared.gradio['lora_menu'] = gr.Dropdown(multiselect=True, choices=get_available_loras(), value=shared.lora_names, label='LoRA(s)') - ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': get_available_loras(), 'value': shared.lora_names}, 'refresh-button') + shared.gradio['lora_menu'] = gr.Dropdown(multiselect=True, choices=utils.get_available_loras(), value=shared.lora_names, label='LoRA(s)') + ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': utils.get_available_loras(), 'value': shared.lora_names}, 'refresh-button') with gr.Column(): with gr.Row(): @@ -411,8 +366,8 @@ def create_settings_menus(default_preset): with gr.Row(): with gr.Column(): with gr.Row(): - shared.gradio['preset_menu'] = gr.Dropdown(choices=get_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') + shared.gradio['preset_menu'] = gr.Dropdown(choices=utils.get_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': utils.get_available_presets()}, 'refresh-button') with gr.Column(): shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)') @@ -459,8 +414,8 @@ def create_settings_menus(default_preset): with gr.Accordion('Soft prompt', open=False): with gr.Row(): - shared.gradio['softprompts_menu'] = gr.Dropdown(choices=get_available_softprompts(), value='None', label='Soft prompt') - ui.create_refresh_button(shared.gradio['softprompts_menu'], lambda: None, lambda: {'choices': get_available_softprompts()}, 'refresh-button') + shared.gradio['softprompts_menu'] = gr.Dropdown(choices=utils.get_available_softprompts(), value='None', label='Soft prompt') + ui.create_refresh_button(shared.gradio['softprompts_menu'], lambda: None, lambda: {'choices': utils.get_available_softprompts()}, 'refresh-button') gr.Markdown('Upload a soft prompt (.zip format):') with gr.Row(): @@ -547,7 +502,7 @@ def create_interface(): shared.gradio['Clear history-cancel'] = gr.Button('Cancel', visible=False) shared.gradio['mode'] = gr.Radio(choices=['cai-chat', 'chat', 'instruct'], value=shared.settings['mode'], label='Mode') - shared.gradio['instruction_template'] = gr.Dropdown(choices=get_available_instruction_templates(), label='Instruction template', value='None', visible=shared.settings['mode'] == 'instruct', info='Change this according to the model/LoRA that you are using.') + shared.gradio['instruction_template'] = gr.Dropdown(choices=utils.get_available_instruction_templates(), label='Instruction template', value='None', visible=shared.settings['mode'] == 'instruct', info='Change this according to the model/LoRA that you are using.') with gr.Tab('Character', elem_id='chat-settings'): with gr.Row(): @@ -563,8 +518,8 @@ def create_interface(): shared.gradio['your_picture'] = gr.Image(label='Your picture', type='pil', value=Image.open(Path('cache/pfp_me.png')) if Path('cache/pfp_me.png').exists() else None) with gr.Row(): - shared.gradio['character_menu'] = gr.Dropdown(choices=get_available_characters(), label='Character', elem_id='character-menu') - ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': get_available_characters()}, 'refresh-button') + shared.gradio['character_menu'] = gr.Dropdown(choices=utils.get_available_characters(), label='Character', elem_id='character-menu') + ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': utils.get_available_characters()}, 'refresh-button') with gr.Row(): with gr.Tab('Chat history'): @@ -634,8 +589,8 @@ def create_interface(): gr.HTML('
') shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens']) with gr.Row(): - shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt') - ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button') + shared.gradio['prompt_menu'] = gr.Dropdown(choices=utils.get_available_prompts(), value='None', label='Prompt') + ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': utils.get_available_prompts()}, 'refresh-button') shared.gradio['save_prompt'] = gr.Button('Save prompt') shared.gradio['count_tokens'] = gr.Button('Count tokens') @@ -664,8 +619,8 @@ def create_interface(): with gr.Row(): with gr.Column(): with gr.Row(): - shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt') - ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button') + shared.gradio['prompt_menu'] = gr.Dropdown(choices=utils.get_available_prompts(), value='None', label='Prompt') + ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': utils.get_available_prompts()}, 'refresh-button') with gr.Column(): shared.gradio['status'] = gr.Markdown('') @@ -705,7 +660,7 @@ def create_interface(): gr.Markdown("*Experimental*") shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode") - shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=get_available_extensions(), value=shared.args.extensions, label="Available extensions") + shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=utils.get_available_extensions(), value=shared.args.extensions, label="Available extensions") shared.gradio['bool_menu'] = gr.CheckboxGroup(choices=bool_list, value=bool_active, label="Boolean command-line flags") shared.gradio['reset_interface'] = gr.Button("Apply and restart the interface") @@ -869,7 +824,7 @@ if __name__ == "__main__": shared.settings[item] = new_settings[item] # Default extensions - extensions_module.available_extensions = get_available_extensions() + extensions_module.available_extensions = utils.get_available_extensions() if shared.is_chat(): for extension in shared.settings['chat_default_extensions']: shared.args.extensions = shared.args.extensions or [] @@ -881,7 +836,7 @@ if __name__ == "__main__": if extension not in shared.args.extensions: shared.args.extensions.append(extension) - available_models = get_available_models() + available_models = utils.get_available_models() # Model defined through --model if shared.args.model is not None: