mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-12-27 06:39:33 +01:00
136 lines
4.4 KiB
Python
136 lines
4.4 KiB
Python
import re
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from pathlib import Path
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import yaml
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from modules import shared, ui
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def get_model_settings_from_yamls(model):
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settings = shared.model_config
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model_settings = {}
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for pat in settings:
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if re.match(pat.lower(), model.lower()):
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for k in settings[pat]:
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model_settings[k] = settings[pat][k]
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return model_settings
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def infer_loader(model_name):
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path_to_model = Path(f'{shared.args.model_dir}/{model_name}')
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model_settings = get_model_settings_from_yamls(model_name)
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if not path_to_model.exists():
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loader = None
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elif Path(f'{shared.args.model_dir}/{model_name}/quantize_config.json').exists() or ('wbits' in model_settings and type(model_settings['wbits']) is int and model_settings['wbits'] > 0):
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loader = 'AutoGPTQ'
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elif len(list(path_to_model.glob('*ggml*.bin'))) > 0:
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loader = 'llama.cpp'
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elif re.match('.*ggml.*\.bin', model_name.lower()):
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loader = 'llama.cpp'
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elif re.match('.*rwkv.*\.pth', model_name.lower()):
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loader = 'RWKV'
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else:
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loader = 'Transformers'
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return loader
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# UI: update the command-line arguments based on the interface values
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def update_model_parameters(state, initial=False):
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elements = ui.list_model_elements() # the names of the parameters
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gpu_memories = []
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for i, element in enumerate(elements):
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if element not in state:
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continue
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value = state[element]
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if element.startswith('gpu_memory'):
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gpu_memories.append(value)
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continue
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if initial and vars(shared.args)[element] != vars(shared.args_defaults)[element]:
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continue
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# Setting null defaults
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if element in ['wbits', 'groupsize', 'model_type'] and value == 'None':
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value = vars(shared.args_defaults)[element]
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elif element in ['cpu_memory'] and value == 0:
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value = vars(shared.args_defaults)[element]
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# Making some simple conversions
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if element in ['wbits', 'groupsize', 'pre_layer']:
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value = int(value)
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elif element == 'cpu_memory' and value is not None:
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value = f"{value}MiB"
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if element in ['pre_layer']:
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value = [value] if value > 0 else None
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setattr(shared.args, element, value)
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found_positive = False
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for i in gpu_memories:
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if i > 0:
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found_positive = True
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break
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if not (initial and vars(shared.args)['gpu_memory'] != vars(shared.args_defaults)['gpu_memory']):
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if found_positive:
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shared.args.gpu_memory = [f"{i}MiB" for i in gpu_memories]
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else:
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shared.args.gpu_memory = None
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# UI: update the state variable with the model settings
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def apply_model_settings_to_state(model, state):
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model_settings = get_model_settings_from_yamls(model)
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if 'loader' not in model_settings:
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loader = infer_loader(model)
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if 'wbits' in model_settings and type(model_settings['wbits']) is int and model_settings['wbits'] > 0:
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loader = 'AutoGPTQ'
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# If the user is using an alternative GPTQ loader, let them keep using it
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if not (loader == 'AutoGPTQ' and state['loader'] in ['GPTQ-for-LLaMa', 'ExLlama', 'ExLlama_HF']):
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state['loader'] = loader
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for k in model_settings:
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if k in state:
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if k in ['wbits', 'groupsize']:
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state[k] = str(model_settings[k])
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else:
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state[k] = model_settings[k]
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return state
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# Save the settings for this model to models/config-user.yaml
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def save_model_settings(model, state):
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if model == 'None':
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yield ("Not saving the settings because no model is loaded.")
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return
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with Path(f'{shared.args.model_dir}/config-user.yaml') as p:
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if p.exists():
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user_config = yaml.safe_load(open(p, 'r').read())
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else:
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user_config = {}
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model_regex = model + '$' # For exact matches
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for _dict in [user_config, shared.model_config]:
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if model_regex not in _dict:
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_dict[model_regex] = {}
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if model_regex not in user_config:
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user_config[model_regex] = {}
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for k in ui.list_model_elements():
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user_config[model_regex][k] = state[k]
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shared.model_config[model_regex][k] = state[k]
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with open(p, 'w') as f:
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f.write(yaml.dump(user_config, sort_keys=False))
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yield (f"Settings for {model} saved to {p}")
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