67 lines
2.9 KiB
Python
67 lines
2.9 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (c) Alibaba, Inc. and its affiliates.
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from scepter.modules.utils.config import Config
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from scepter.modules.utils.registry import Registry, build_from_config
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def build_model(cfg, registry, logger=None, *args, **kwargs):
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""" After build model, load pretrained model if exists key `pretrain`.
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pretrain (str, dict): Describes how to load pretrained model.
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str, treat pretrain as model path;
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dict: should contains key `path`, and other parameters token by function load_pretrained();
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"""
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if not isinstance(cfg, Config):
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raise TypeError(f'Config must be type dict, got {type(cfg)}')
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if cfg.have('PRETRAINED_MODEL'):
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pretrain_cfg = cfg.PRETRAINED_MODEL
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if pretrain_cfg is not None and not isinstance(pretrain_cfg, (str, list)):
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raise TypeError('Pretrain parameter must be a string or list')
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else:
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pretrain_cfg = None
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model = build_from_config(cfg, registry, logger=logger, *args, **kwargs)
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if pretrain_cfg is not None:
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if hasattr(model, 'load_pretrained_model'):
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model.load_pretrained_model(pretrain_cfg)
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return model
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def build_diffusion(cfg, registry, logger=None, *args, **kwargs):
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""" After build model, load pretrained model if exists key `pretrain`.
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pretrain (str, dict): Describes how to load pretrained model.
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str, treat pretrain as model path;
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dict: should contains key `path`, and other parameters token by function load_pretrained();
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"""
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if not isinstance(cfg, Config):
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raise TypeError(f'Config must be type dict, got {type(cfg)}')
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return build_from_config(cfg, registry, logger=logger, *args, **kwargs)
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def build_scheduler(cfg, registry, logger=None, *args, **kwargs):
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if not isinstance(cfg, Config):
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raise TypeError(f'Config must be type dict, got {type(cfg)}')
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return build_from_config(cfg, registry, logger=logger, *args, **kwargs)
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def build_diffusion_sampler(cfg, registry, logger=None, *args, **kwargs):
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if not isinstance(cfg, Config):
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raise TypeError(f'Config must be type dict, got {type(cfg)}')
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return build_from_config(cfg, registry, logger=logger, *args, **kwargs)
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MODELS = Registry('MODELS', build_func=build_model)
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TOKENIZERS = Registry('TOKENIZER', build_func=build_model)
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EMBEDDERS = Registry('EMBEDDERS', build_func=build_model)
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BACKBONES = Registry('BACKBONES', build_func=build_model)
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NECKS = Registry('NECKS', build_func=build_model)
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HEADS = Registry('HEADS', build_func=build_model)
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BRICKS = Registry('BRICKS', build_func=build_model)
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STEMS = BRICKS
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LOSSES = Registry('LOSSES', build_func=build_model)
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TUNERS = Registry('TUNERS', build_func=build_model)
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# reigister cls for diffusion.
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DIFFUSIONS = Registry('DIFFUSIONS', build_func=build_diffusion)
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NOISE_SCHEDULERS = Registry('NOISE_SCHEDULERS', build_func=build_diffusion)
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DIFFUSION_SAMPLERS = Registry('DIFFUSION_SAMPLERS', build_func=build_diffusion_sampler)
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