





import importlib

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

def   __snake_case    (       _lowerCAmelCase			:			List[Any]					,					_lowerCAmelCase			:			Any=False						)			->    Optional[Any]:
   A_       :					Optional[Any]        =      OmegaConf.load(_lowerCAmelCase						)
   if display:
      print(yaml.dump(OmegaConf.to_container(_lowerCAmelCase						)						)						)
   return config

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

def   __snake_case    (       _lowerCAmelCase			:			Dict					,					_lowerCAmelCase			:			str						)			->    str:
   A_   ,    A_   ,    A_       :					List[Any]        =      model.encode(_lowerCAmelCase						)
   print(f"VQGAN --- {model.__class__.__name__}: latent shape: {z.shape[2:]}"						)
   A_       :					Any        =      model.decode(_lowerCAmelCase						)
   return xrec

def   __snake_case    (       _lowerCAmelCase			:			Optional[Any]					,					_lowerCAmelCase			:			List[Any]=False						)			->    List[Any]:
   A_   ,    A_       :					Any        =      string.rsplit("."					,					1						)
   if reload:
      A_       :					Optional[int]        =      importlib.import_module(_lowerCAmelCase						)
      importlib.reload(_lowerCAmelCase						)
   return getattr(importlib.import_module(_lowerCAmelCase					,					package=_lowerCAmelCase						)					,					cls						)

def   __snake_case    (       _lowerCAmelCase			:			int						)			->    Tuple:
   if "target" not in config:
      raise KeyError("Expected key `target` to instantiate."						)
   return get_obj_from_str(config["target"]						)(**config.get("params"					,					{}						)						)

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





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







from timeit import timeit

_lowerCAmelCase				:   Tuple						       =						{
    '''MALAYALAM''': True,
    '''String''': False,
    '''rotor''': True,
    '''level''': True,
    '''A''': True,
    '''BB''': True,
    '''ABC''': False,
    '''amanaplanacanalpanama''': True,  # "a man a plan a canal panama"
}
# Ensure our test data is valid
assert all((key == key[::-1]) is value for key, value in test_data.items())

def   __snake_case    (       _lowerCAmelCase			:			str						)			->    bool:
   A_       :					List[str]        =      0
   A_       :					str        =      len(_lowerCAmelCase						) - 1
   while start_i < end_i:
      if s[start_i] == s[end_i]:
         start_i += 1
         end_i -= 1
      else:
         return False
   return True

def   __snake_case    (       _lowerCAmelCase			:			str						)			->    bool:
   A_       :					int        =      len(_lowerCAmelCase						) // 2
   A_       :					Union[str, Any]        =      len(_lowerCAmelCase						)

   # We need to traverse till half of the length of string
   # as we can get access of the i'th last element from
   # i'th index.
   # eg: [0,1,2,3,4,5] => 4th index can be accessed
   # with the help of 1st index (i==n-i-1)
   # where n is length of string
   return all(s[i] == s[n - i - 1] for i in range(_lowerCAmelCase						)						)

def   __snake_case    (       _lowerCAmelCase			:			str						)			->    bool:
   if len(_lowerCAmelCase						) <= 2:
      return True
   if s[0] == s[len(_lowerCAmelCase						) - 1]:
      return is_palindrome_recursive(s[1:-1]						)
   else:
      return False

def   __snake_case    (       _lowerCAmelCase			:			str						)			->    bool:
   return s == s[::-1]

def   __snake_case    (       _lowerCAmelCase			:			str						)			->    None:
   A_       :					int        =      f"all({name}(key) is value for key, value in test_data.items())"
   A_       :					List[str]        =      f"from __main__ import test_data, {name}"
   A_       :					str        =      500000
   A_       :					List[str]        =      timeit(stmt=_lowerCAmelCase					,					setup=_lowerCAmelCase					,					number=_lowerCAmelCase						)
   print(f"{name:<35} finished {number:,} runs in {result:.5f} seconds"						)


if __name__ == "__main__":
 for key, value in test_data.items():
  assert is_palindrome(key) is is_palindrome_recursive(key)
  assert is_palindrome(key) is is_palindrome_slice(key)
  print(F'''{key:21} {value}''')
 print('''a man a plan a canal panama''')

 # finished 500,000 runs in 0.46793 seconds
 benchmark_function('''is_palindrome_slice''')
 # finished 500,000 runs in 0.85234 seconds
 benchmark_function('''is_palindrome''')
 # finished 500,000 runs in 1.32028 seconds
 benchmark_function('''is_palindrome_recursive''')
 # finished 500,000 runs in 2.08679 seconds
 benchmark_function('''is_palindrome_traversal''')
