'''simple docstring'''

import importlib

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



def lowerCamelCase__    (							A_							,      A_=False							):
 UpperCAmelCase_												=       OmegaConf.load(__UpperCamelCase							)
 if display:
  print(yaml.dump(OmegaConf.to_container(__UpperCamelCase							)							)							)
 return config



def lowerCamelCase__    (							A_							,      A_=None							,      A_=None							):
 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 lowerCamelCase__    (							A_							,      A_							):
 UpperCAmelCase_							,							UpperCAmelCase_							,							UpperCAmelCase_												=       model.encode(__UpperCamelCase							)
 print(F"""VQGAN --- {model.__class__.__name__}: latent shape: {z.shape[2:]}"""							)
 UpperCAmelCase_												=       model.decode(__UpperCamelCase							)
 return xrec



def lowerCamelCase__    (							A_							,      A_=False							):
 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 lowerCamelCase__    (							A_							):
 if "target" not in config:
  raise KeyError("Expected key `target` to instantiate."							)
 return get_obj_from_str(config["target"]							)(**config.get("params"							,      {}							)							)



def lowerCamelCase__    (							A_							,      A_							,      A_=True							,      A_=True							):
 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 lowerCamelCase__    (							A_							,      A_							,      A_							,      A_							):
 # 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




'''simple docstring'''
def 					lowerCamelCase_ ( __UpperCamelCase					:       int		)					->	bool:







     """simple docstring"""
     return str(__UpperCamelCase		) == str(__UpperCamelCase		)[::-1]

def 					lowerCamelCase_ ( __UpperCamelCase					:       int		)					->	int:







     """simple docstring"""
     return int(__UpperCamelCase		) + int(str(__UpperCamelCase		)[::-1]		)

def 					lowerCamelCase_ ( __UpperCamelCase					:       int = 1_0_0_0_0		)					->	int:







     """simple docstring"""
     _A				=							[]
     for num in range(1							,    __UpperCamelCase		):
          _A				=							0
          _A				=							num
          while iterations < 5_0:
               _A				=							sum_reverse(__UpperCamelCase		)
               iterations += 1
               if is_palindrome(__UpperCamelCase		):
                    break
          else:
               lychrel_nums.append(__UpperCamelCase		)
     return len(__UpperCamelCase		)


if __name__ == "__main__":
    print(F'{solution() = }')





