




import importlib

import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Dict	,					__UpperCamelCase      :						Optional[int]=False				)  ->							Any:
    UpperCAmelCase_										=					OmegaConf.load(__UpperCamelCase				)
    if display:
        print(yaml.dump(OmegaConf.to_container(__UpperCamelCase				)				)				)
    return config




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Union[str, Any]	,					__UpperCamelCase      :						List[str]=None	,					__UpperCamelCase      :						Optional[int]=None				)  ->							Dict:
    if conf_path is None:
        UpperCAmelCase_										=					'''./model_checkpoints/vqgan_only.yaml'''
    UpperCAmelCase_										=					load_config(__UpperCamelCase	,					display=__UpperCamelCase				)
    UpperCAmelCase_										=					VQModel(**config.model.params				)
    if ckpt_path is None:
        UpperCAmelCase_										=					'''./model_checkpoints/vqgan_only.pt'''
    UpperCAmelCase_										=					torch.load(__UpperCamelCase	,					map_location=__UpperCamelCase				)
    if ".ckpt" in ckpt_path:
        UpperCAmelCase_										=					sd['''state_dict''']
    model.load_state_dict(__UpperCamelCase	,					strict=__UpperCamelCase				)
    model.to(__UpperCamelCase				)
    del sd
    return model




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[Any]	,					__UpperCamelCase      :						Union[str, Any]				)  ->							int:
    UpperCAmelCase_			,							UpperCAmelCase_			,							UpperCAmelCase_										=					model.encode(__UpperCamelCase				)
    print(f'VQGAN --- {model.__class__.__name__}: latent shape: {z.shape[2:]}'				)
    UpperCAmelCase_										=					model.decode(__UpperCamelCase				)
    return xrec




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[Any]	,					__UpperCamelCase      :						int=False				)  ->							Any:
    UpperCAmelCase_			,							UpperCAmelCase_										=					string.rsplit('''.'''	,					1				)
    if reload:
        UpperCAmelCase_										=					importlib.import_module(__UpperCamelCase				)
        importlib.reload(__UpperCamelCase				)
    return getattr(importlib.import_module(__UpperCamelCase	,					package=__UpperCamelCase				)	,					cls				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[Any]				)  ->							Tuple:
    if "target" not in config:
        raise KeyError('''Expected key `target` to instantiate.'''				)
    return get_obj_from_str(config['''target''']				)(**config.get('''params'''	,					{}				)				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Any	,					__UpperCamelCase      :						Tuple	,					__UpperCamelCase      :						Dict=True	,					__UpperCamelCase      :						Optional[Any]=True				)  ->							List[str]:
    UpperCAmelCase_										=					instantiate_from_config(__UpperCamelCase				)
    if sd is not None:
        model.load_state_dict(__UpperCamelCase				)
    if gpu:
        model.cuda()
    if eval_mode:
        model.eval()
    return {"model": model}




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						str	,					__UpperCamelCase      :						Tuple	,					__UpperCamelCase      :						Union[str, Any]	,					__UpperCamelCase      :						List[Any]				)  ->							Dict:
    # load the specified checkpoint
    if ckpt:
        UpperCAmelCase_										=					torch.load(__UpperCamelCase	,					map_location='''cpu'''				)
        UpperCAmelCase_										=					pl_sd['''global_step''']
        print(f'loaded model from global step {global_step}.'				)
    else:
        UpperCAmelCase_										=					{'''state_dict''': None}
        UpperCAmelCase_										=					None
    UpperCAmelCase_										=					load_model_from_config(config.model	,					pl_sd['''state_dict''']	,					gpu=__UpperCamelCase	,					eval_mode=__UpperCamelCase				)['''model''']
    return model, global_step











import baseaa




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						str				)  ->							bytes:
    return baseaa.baaencode(string.encode('''utf-8'''				)				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						bytes				)  ->							str:
    return baseaa.baadecode(__UpperCamelCase				).decode('''utf-8'''				)


if __name__ == "__main__":
 _lowerCamelCase      			=						'Hello World!'
 _lowerCamelCase      			=						baseaa_encode(test)
 print(encoded)

 _lowerCamelCase      			=						baseaa_decode(encoded)
 print(decoded)





