


import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urllib.parse import urlparse
from zipfile import ZipFile, is_zipfile

import cva
import numpy as np
import requests
import wget
from filelock import FileLock
from PIL import Image
from tqdm.auto import tqdm
from yaml import Loader, dump, load


try:
		import torch

		lowerCamelCase		=						True
except ImportError:
		lowerCamelCase		=						False


try:
		from torch.hub import _get_torch_home

		lowerCamelCase		=						_get_torch_home()
except ImportError:
		lowerCamelCase		=						os.path.expanduser(
		    os.getenv('''TORCH_HOME''', os.path.join(os.getenv('''XDG_CACHE_HOME''', '''~/.cache'''), '''torch'''))
		)

lowerCamelCase		=						os.path.join(torch_cache_home, '''transformers''')

lowerCamelCase		=						'''https://cdn.huggingface.co'''
lowerCamelCase		=						'''https://s3.amazonaws.com/models.huggingface.co/bert'''
lowerCamelCase		=						'''/'''.join(str(Path(__file__).resolve()).split('''/''')[:-1])
lowerCamelCase		=						os.path.join(PATH, '''config.yaml''')
lowerCamelCase		=						os.path.join(PATH, '''attributes.txt''')
lowerCamelCase		=						os.path.join(PATH, '''objects.txt''')
lowerCamelCase		=						os.getenv('''PYTORCH_PRETRAINED_BERT_CACHE''', default_cache_path)
lowerCamelCase		=						os.getenv('''PYTORCH_TRANSFORMERS_CACHE''', PYTORCH_PRETRAINED_BERT_CACHE)
lowerCamelCase		=						os.getenv('''TRANSFORMERS_CACHE''', PYTORCH_TRANSFORMERS_CACHE)
lowerCamelCase		=						'''pytorch_model.bin'''
lowerCamelCase		=						'''config.yaml'''






def 	lowerCamelCase_       (			_a=OBJECTS      ,  _a=ATTRIBUTES			):




		"""simple docstring"""






		lowerCAmelCase__  :     int       	=   []
		with open(_a			) as f:
				for object in f.readlines():
						vg_classes.append(object.split(''','''			)[0].lower().strip()			)

		lowerCAmelCase__  :     Any       	=   []
		with open(_a			) as f:
				for object in f.readlines():
						vg_attrs.append(object.split(''','''			)[0].lower().strip()			)
		return vg_classes, vg_attrs






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		lowerCAmelCase__  :     Union[str, Any]       	=   OrderedDict()
		with open(_a      ,  '''rb'''			) as f:
				lowerCAmelCase__  :     Union[str, Any]       	=   pkl.load(_a			)['''model''']
		for k in copy.deepcopy(list(ckp.keys()			)			):
				lowerCAmelCase__  :     Optional[int]       	=   ckp.pop(_a			)
				if isinstance(_a      ,  np.ndarray			):
						lowerCAmelCase__  :     List[str]       	=   torch.tensor(_a			)
				else:
						assert isinstance(_a      ,  torch.tensor			), type(_a			)
				lowerCAmelCase__  :     Optional[int]       	=   v
		return r





class    _a				:
	_a    :    Optional[int]        =				{}




	def __init__(   self		:						Dict						,   _SCREAMING_SNAKE_CASE		:						dict						,   _SCREAMING_SNAKE_CASE		:						str = "root"						,   _SCREAMING_SNAKE_CASE		:						List[Any]=0						)->			Tuple:
			lowerCAmelCase__  :     Tuple       	=   name
			lowerCAmelCase__  :     int       	=   level
			lowerCAmelCase__  :     str       	=   {}
			for k, v in dictionary.items():
					if v is None:
							raise ValueError()
					lowerCAmelCase__  :     Any       	=   copy.deepcopy(_SCREAMING_SNAKE_CASE						)
					lowerCAmelCase__  :     Optional[int]       	=   copy.deepcopy(_SCREAMING_SNAKE_CASE						)
					if isinstance(_SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						):
							lowerCAmelCase__  :     Any       	=   Config(_SCREAMING_SNAKE_CASE						,   name=_SCREAMING_SNAKE_CASE						,   level=level + 1						)
					lowerCAmelCase__  :     Tuple       	=   v
					setattr(self						,   _SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						)

			lowerCAmelCase__  :     Union[str, Any]       	=   d




	def __repr__(   self		:						str						)->			str:
			return str(list((self._pointer.keys())						)						)




	def __setattr__(   self		:						Any						,   _SCREAMING_SNAKE_CASE		:						Union[str, Any]						,   _SCREAMING_SNAKE_CASE		:						List[str]						)->			Tuple:
			lowerCAmelCase__  :     Any       	=   val
			lowerCAmelCase__  :     List[Any]       	=   val
			lowerCAmelCase__  :     Tuple       	=   key.split('''.'''						)
			lowerCAmelCase__  :     Union[str, Any]       	=   len(_SCREAMING_SNAKE_CASE						) - 1
			lowerCAmelCase__  :     Any       	=   self._pointer
			if len(_SCREAMING_SNAKE_CASE						) > 1:
					for i, l in enumerate(_SCREAMING_SNAKE_CASE						):
							if hasattr(self						,   _SCREAMING_SNAKE_CASE						) and isinstance(getattr(self						,   _SCREAMING_SNAKE_CASE						)						,   _SCREAMING_SNAKE_CASE						):
									setattr(getattr(self						,   _SCREAMING_SNAKE_CASE						)						,   '''.'''.join(levels[i:]						)						,   _SCREAMING_SNAKE_CASE						)
							if l == last_level:
									lowerCAmelCase__  :     List[Any]       	=   val
							else:
									lowerCAmelCase__  :     Optional[Any]       	=   pointer[l]




	def 				UpperCAmelCase__(   self		:						Any						)->			int:
			return self._pointer




	def 				UpperCAmelCase__(   self		:						List[Any]						,   _SCREAMING_SNAKE_CASE		:						Any						,   _SCREAMING_SNAKE_CASE		:						Union[str, Any]						)->			str:
			with open(F'{file_name}'						,   '''w'''						) as stream:
					dump(_SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						)




	def 				UpperCAmelCase__(   self		:						List[Any]						,   _SCREAMING_SNAKE_CASE		:						int						,   _SCREAMING_SNAKE_CASE		:						str						)->			List[Any]:
			with open(F'{file_name}'						,   '''w'''						) as stream:
					json.dump(_SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						)




	@staticmethod
	def 				UpperCAmelCase__(   _SCREAMING_SNAKE_CASE		:						Optional[int]						)->			Tuple:
			with open(_SCREAMING_SNAKE_CASE						) as stream:
					lowerCAmelCase__  :     Tuple       	=   load(_SCREAMING_SNAKE_CASE						,   Loader=_SCREAMING_SNAKE_CASE						)
			return data




	def __str__(   self		:						Any						)->			Tuple:
			lowerCAmelCase__  :     Dict       	=   '''    '''
			if self._name != "root":
					lowerCAmelCase__  :     Union[str, Any]       	=   F'{t * (self._level-1)}{self._name}:\n'
			else:
					lowerCAmelCase__  :     str       	=   ''''''
			lowerCAmelCase__  :     Union[str, Any]       	=   self._level
			for i, (k, v) in enumerate(self._pointer.items()						):
					if isinstance(_SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						):
							r += F'{t * (self._level)}{v}\n'
							self._level += 1
					else:
							r += F'{t * (self._level)}{k}: {v} ({type(_SCREAMING_SNAKE_CASE						).__name__})\n'
					lowerCAmelCase__  :     Optional[Any]       	=   level
			return r[:-1]




	@classmethod
	def 				UpperCAmelCase__(   cls		:						Dict						,   _SCREAMING_SNAKE_CASE		:						str						,   **_SCREAMING_SNAKE_CASE		:						str						)->			Tuple:
			lowerCAmelCase__	,      lowerCAmelCase__  :     List[str]       	=   cls.get_config_dict(_SCREAMING_SNAKE_CASE						,   **_SCREAMING_SNAKE_CASE						)
			return cls(_SCREAMING_SNAKE_CASE						)




	@classmethod
	def 				UpperCAmelCase__(   cls		:						Optional[Any]						,   _SCREAMING_SNAKE_CASE		:						str						,   **_SCREAMING_SNAKE_CASE		:						Union[str, Any]						)->			List[str]:
			lowerCAmelCase__  :     int       	=   kwargs.pop('''cache_dir'''						,   _SCREAMING_SNAKE_CASE						)
			lowerCAmelCase__  :     Union[str, Any]       	=   kwargs.pop('''force_download'''						,   _SCREAMING_SNAKE_CASE						)
			lowerCAmelCase__  :     Optional[Any]       	=   kwargs.pop('''resume_download'''						,   _SCREAMING_SNAKE_CASE						)
			lowerCAmelCase__  :     Optional[Any]       	=   kwargs.pop('''proxies'''						,   _SCREAMING_SNAKE_CASE						)
			lowerCAmelCase__  :     Optional[Any]       	=   kwargs.pop('''local_files_only'''						,   _SCREAMING_SNAKE_CASE						)

			if os.path.isdir(_SCREAMING_SNAKE_CASE						):
					lowerCAmelCase__  :     Optional[int]       	=   os.path.join(_SCREAMING_SNAKE_CASE						,   _SCREAMING_SNAKE_CASE						)
			elif os.path.isfile(_SCREAMING_SNAKE_CASE						) or is_remote_url(_SCREAMING_SNAKE_CASE						):
					lowerCAmelCase__  :     Any       	=   pretrained_model_name_or_path
			else:
					lowerCAmelCase__  :     Union[str, Any]       	=   hf_bucket_url(_SCREAMING_SNAKE_CASE						,   filename=_SCREAMING_SNAKE_CASE						,   use_cdn=_SCREAMING_SNAKE_CASE						)

			try:
					# Load from URL or cache if already cached
					lowerCAmelCase__  :     Optional[int]       	=   cached_path(
					    _SCREAMING_SNAKE_CASE						,   cache_dir=_SCREAMING_SNAKE_CASE						,   force_download=_SCREAMING_SNAKE_CASE						,   proxies=_SCREAMING_SNAKE_CASE						,   resume_download=_SCREAMING_SNAKE_CASE						,   local_files_only=_SCREAMING_SNAKE_CASE						,   )
					# Load config dict
					if resolved_config_file is None:
							raise EnvironmentError

					lowerCAmelCase__  :     int       	=   Config.load_yaml(_SCREAMING_SNAKE_CASE						)

			except EnvironmentError:
					lowerCAmelCase__  :     str       	=   '''Can\'t load config for'''
					raise EnvironmentError(_SCREAMING_SNAKE_CASE						)

			if resolved_config_file == config_file:
					print('''loading configuration file from path'''						)
			else:
					print('''loading configuration file cache'''						)

			return Config.load_yaml(_SCREAMING_SNAKE_CASE						), kwargs






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		lowerCAmelCase__  :     List[str]       	=   torch.load('''dump.pt'''      ,  map_location=in_tensor.device			)
		lowerCAmelCase__  :     Union[str, Any]       	=   in_tensor.numpy()
		lowerCAmelCase__  :     Tuple       	=   out_tensor.numpy()[0]
		print(na.shape      ,  na[0, 0, :5]			)
		print(na.shape      ,  na[0, 0, :5]			)
		assert np.allclose(_a      ,  _a      ,  rtol=0.01      ,  atol=0.1			), (
		    f'{sum([1 for x in np.isclose(_a      ,  _a      ,  rtol=0.01      ,  atol=0.1			).flatten() if x is False]			)/len(na.flatten()			)*100:.4f} %'
		    " element-wise mismatch"
		)
		raise Exception('''tensors are all good'''			)

		# Hugging face functions below






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		lowerCAmelCase__  :     Any       	=   urlparse(_a			)
		return parsed.scheme in ("http", "https")






def 	lowerCamelCase_       (			_a      ,  _a      ,  _a=True			):




		"""simple docstring"""






		lowerCAmelCase__  :     Optional[Any]       	=   CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
		lowerCAmelCase__  :     Tuple       	=   '''/''' not in model_id
		if legacy_format:
				return f'{endpoint}/{model_id}-{filename}'
		else:
				return f'{endpoint}/{model_id}/{filename}'






def 	lowerCamelCase_       (			_a      ,  _a      ,  _a=None      ,  _a=0      ,  _a=None      ,  ):




		"""simple docstring"""






		lowerCAmelCase__  :     Optional[Any]       	=   '''python/{}'''.format(sys.version.split()[0]			)
		if _torch_available:
				ua += "; torch/{}".format(torch.__version__			)
		if isinstance(_a      ,  _a			):
				ua += "; " + "; ".join('''{}/{}'''.format(_a      ,  _a			) for k, v in user_agent.items()			)
		elif isinstance(_a      ,  _a			):
				ua += "; " + user_agent
		lowerCAmelCase__  :     Optional[Any]       	=   {'''user-agent''': ua}
		if resume_size > 0:
				lowerCAmelCase__  :     Optional[Any]       	=   '''bytes=%d-''' % (resume_size,)
		lowerCAmelCase__  :     Dict       	=   requests.get(_a      ,  stream=_a      ,  proxies=_a      ,  headers=_a			)
		if response.status_code == 416:  # Range not satisfiable
				return
		lowerCAmelCase__  :     Any       	=   response.headers.get('''Content-Length'''			)
		lowerCAmelCase__  :     List[Any]       	=   resume_size + int(_a			) if content_length is not None else None
		lowerCAmelCase__  :     List[Any]       	=   tqdm(
		    unit='''B'''      ,  unit_scale=_a      ,  total=_a      ,  initial=_a      ,  desc='''Downloading'''      ,  )
		for chunk in response.iter_content(chunk_size=1_024			):
				if chunk:  # filter out keep-alive new chunks
						progress.update(len(_a			)			)
						temp_file.write(_a			)
		progress.close()






def 	lowerCamelCase_       (			_a      ,  _a=None      ,  _a=False      ,  _a=None      ,  _a=10      ,  _a=False      ,  _a=None      ,  _a=False      ,  ):




		"""simple docstring"""






		if cache_dir is None:
				lowerCAmelCase__  :     Any       	=   TRANSFORMERS_CACHE
		if isinstance(_a      ,  _a			):
				lowerCAmelCase__  :     int       	=   str(_a			)

		os.makedirs(_a      ,  exist_ok=_a			)

		lowerCAmelCase__  :     Dict       	=   None
		if not local_files_only:
				try:
						lowerCAmelCase__  :     int       	=   requests.head(_a      ,  allow_redirects=_a      ,  proxies=_a      ,  timeout=_a			)
						if response.status_code == 200:
								lowerCAmelCase__  :     str       	=   response.headers.get('''ETag'''			)
				except (EnvironmentError, requests.exceptions.Timeout):
						# etag is already None
						pass

		lowerCAmelCase__  :     Optional[Any]       	=   url_to_filename(_a      ,  _a			)

		# get cache path to put the file
		lowerCAmelCase__  :     Union[str, Any]       	=   os.path.join(_a      ,  _a			)

		# etag is None = we don't have a connection, or url doesn't exist, or is otherwise inaccessible.
		# try to get the last downloaded one
		if etag is None:
				if os.path.exists(_a			):
						return cache_path
				else:
						lowerCAmelCase__  :     List[Any]       	=   [
						    file
						    for file in fnmatch.filter(os.listdir(_a			)      ,  filename + '''.*'''			)
						    if not file.endswith('''.json'''			) and not file.endswith('''.lock'''			)
						]
						if len(_a			) > 0:
								return os.path.join(_a      ,  matching_files[-1]			)
						else:
								# If files cannot be found and local_files_only=True,
								# the models might've been found if local_files_only=False
								# Notify the user about that
								if local_files_only:
										raise ValueError(
										    '''Cannot find the requested files in the cached path and outgoing traffic has been'''
										    ''' disabled. To enable model look-ups and downloads online, set \'local_files_only\''''
										    ''' to False.'''			)
								return None

    # From now on, etag is not None.
		if os.path.exists(_a			) and not force_download:
				return cache_path

		# Prevent parallel downloads of the same file with a lock.
		lowerCAmelCase__  :     Any       	=   cache_path + '''.lock'''
		with FileLock(_a			):
				# If the download just completed while the lock was activated.
				if os.path.exists(_a			) and not force_download:
						# Even if returning early like here, the lock will be released.
						return cache_path

				if resume_download:
						lowerCAmelCase__  :     str       	=   cache_path + '''.incomplete'''

						@contextmanager
						def _resumable_file_manager():
								with open(_a      ,  '''a+b'''			) as f:
										yield f

						lowerCAmelCase__  :     List[str]       	=   _resumable_file_manager
						if os.path.exists(_a			):
								lowerCAmelCase__  :     Optional[Any]       	=   os.stat(_a			).st_size
						else:
								lowerCAmelCase__  :     Tuple       	=   0
				else:
						lowerCAmelCase__  :     List[Any]       	=   partial(tempfile.NamedTemporaryFile      ,  dir=_a      ,  delete=_a			)
						lowerCAmelCase__  :     Dict       	=   0

				# Download to temporary file, then copy to cache dir once finished.
				# Otherwise you get corrupt cache entries if the download gets interrupted.
				with temp_file_manager() as temp_file:
						print(
						    '''%s not found in cache or force_download set to True, downloading to %s'''      ,  _a      ,  temp_file.name      ,  )

						http_get(
						    _a      ,  _a      ,  proxies=_a      ,  resume_size=_a      ,  user_agent=_a      ,  )

				os.replace(temp_file.name      ,  _a			)

				lowerCAmelCase__  :     Optional[Any]       	=   {'''url''': url, '''etag''': etag}
				lowerCAmelCase__  :     List[Any]       	=   cache_path + '''.json'''
				with open(_a      ,  '''w'''			) as meta_file:
						json.dump(_a      ,  _a			)

		return cache_path






def 	lowerCamelCase_       (			_a      ,  _a=None			):




		"""simple docstring"""






		lowerCAmelCase__  :     Optional[int]       	=   url.encode('''utf-8'''			)
		lowerCAmelCase__  :     Optional[int]       	=   shaaaa(_a			)
		lowerCAmelCase__  :     Dict       	=   url_hash.hexdigest()

		if etag:
				lowerCAmelCase__  :     str       	=   etag.encode('''utf-8'''			)
				lowerCAmelCase__  :     Optional[Any]       	=   shaaaa(_a			)
				filename += "." + etag_hash.hexdigest()

		if url.endswith('''.h5'''			):
				filename += ".h5"

		return filename






def 	lowerCamelCase_       (			_a      ,  _a=None      ,  _a=False      ,  _a=None      ,  _a=False      ,  _a=None      ,  _a=False      ,  _a=False      ,  _a=False      ,  ):




		"""simple docstring"""






		if cache_dir is None:
				lowerCAmelCase__  :     Optional[int]       	=   TRANSFORMERS_CACHE
		if isinstance(_a      ,  _a			):
				lowerCAmelCase__  :     List[Any]       	=   str(_a			)
		if isinstance(_a      ,  _a			):
				lowerCAmelCase__  :     Union[str, Any]       	=   str(_a			)

		if is_remote_url(_a			):
				# URL, so get it from the cache (downloading if necessary)
				lowerCAmelCase__  :     Union[str, Any]       	=   get_from_cache(
				    _a      ,  cache_dir=_a      ,  force_download=_a      ,  proxies=_a      ,  resume_download=_a      ,  user_agent=_a      ,  local_files_only=_a      ,  )
		elif os.path.exists(_a			):
				# File, and it exists.
				lowerCAmelCase__  :     str       	=   url_or_filename
		elif urlparse(_a			).scheme == "":
				# File, but it doesn't exist.
				raise EnvironmentError('''file {} not found'''.format(_a			)			)
		else:
				# Something unknown
				raise ValueError('''unable to parse {} as a URL or as a local path'''.format(_a			)			)

		if extract_compressed_file:
				if not is_zipfile(_a			) and not tarfile.is_tarfile(_a			):
						return output_path

				# Path where we extract compressed archives
				# We avoid '.' in dir name and add "-extracted" at the end: "./model.zip" => "./model-zip-extracted/"
				lowerCAmelCase__	,      lowerCAmelCase__  :     Tuple       	=   os.path.split(_a			)
				lowerCAmelCase__  :     Any       	=   output_file.replace('''.'''      ,  '''-'''			) + '''-extracted'''
				lowerCAmelCase__  :     List[str]       	=   os.path.join(_a      ,  _a			)

				if os.path.isdir(_a			) and os.listdir(_a			) and not force_extract:
						return output_path_extracted

				# Prevent parallel extractions
				lowerCAmelCase__  :     int       	=   output_path + '''.lock'''
				with FileLock(_a			):
						shutil.rmtree(_a      ,  ignore_errors=_a			)
						os.makedirs(_a			)
						if is_zipfile(_a			):
								with ZipFile(_a      ,  '''r'''			) as zip_file:
										zip_file.extractall(_a			)
										zip_file.close()
						elif tarfile.is_tarfile(_a			):
								lowerCAmelCase__  :     int       	=   tarfile.open(_a			)
								tar_file.extractall(_a			)
								tar_file.close()
						else:
								raise EnvironmentError('''Archive format of {} could not be identified'''.format(_a			)			)

				return output_path_extracted

		return output_path






def 	lowerCamelCase_       (			_a      ,  _a=","			):




		"""simple docstring"""






		assert isinstance(_a      ,  _a			)
		if os.path.isfile(_a			):
				with open(_a			) as f:
						lowerCAmelCase__  :     Dict       	=   eval(f.read()			)
		else:
				lowerCAmelCase__  :     int       	=   requests.get(_a			)
				try:
						lowerCAmelCase__  :     Optional[int]       	=   requests.json()
				except Exception:
						lowerCAmelCase__  :     Optional[Any]       	=   req.content.decode()
						assert data is not None, "could not connect"
						try:
								lowerCAmelCase__  :     Optional[Any]       	=   eval(_a			)
						except Exception:
								lowerCAmelCase__  :     List[str]       	=   data.split('''\n'''			)
				req.close()
		return data






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		lowerCAmelCase__  :     Any       	=   requests.get(_a			)
		lowerCAmelCase__  :     int       	=   np.array(Image.open(BytesIO(response.content			)			)			)
		return img






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		lowerCAmelCase__  :     int       	=   url.split('''/'''			)[-1]
		if fn not in os.listdir(os.getcwd()			):
				wget.download(_a			)
		with open(_a      ,  '''rb'''			) as stream:
				lowerCAmelCase__  :     str       	=   pkl.load(_a			)
		lowerCAmelCase__  :     Optional[int]       	=   weights.pop('''model'''			)
		lowerCAmelCase__  :     Optional[int]       	=   {}
		for k, v in model.items():
				lowerCAmelCase__  :     List[str]       	=   torch.from_numpy(_a			)
				if "running_var" in k:
						lowerCAmelCase__  :     Tuple       	=   torch.tensor([0]			)
						lowerCAmelCase__  :     Dict       	=   k.replace('''running_var'''      ,  '''num_batches_tracked'''			)
						lowerCAmelCase__  :     Optional[Any]       	=   zero
		return new






def 	lowerCamelCase_       (			):




		"""simple docstring"""






		print(f'{os.path.abspath(os.path.join(_a      ,  os.pardir			)			)}/demo.ipynb'			)






def 	lowerCamelCase_       (			_a      ,  _a="RGB"			):




		"""simple docstring"""






		assert isinstance(_a      ,  _a			)
		if os.path.isfile(_a			):
				lowerCAmelCase__  :     List[Any]       	=   cva.imread(_a			)
		else:
				lowerCAmelCase__  :     Dict       	=   get_image_from_url(_a			)
				assert img is not None, f'could not connect to: {im}'
		lowerCAmelCase__  :     Dict       	=   cva.cvtColor(_a      ,  cva.COLOR_BGR2RGB			)
		if input_format == "RGB":
				lowerCAmelCase__  :     List[str]       	=   img[:, :, ::-1]
		return img






def 	lowerCamelCase_       (			_a      ,  _a=1			):




		"""simple docstring"""






		return (images[i : i + batch] for i in range(0      ,  len(_a			)      ,  _a			))








from __future__ import annotations

from string import ascii_letters






def 	lowerCamelCase_       (			_a      ,  _a      ,  _a = None			):




		"""simple docstring"""






		lowerCAmelCase__  :     List[Any]       	=   alphabet or ascii_letters

		# The final result string
		lowerCAmelCase__  :     Optional[Any]       	=   ''''''

		for character in input_string:
				if character not in alpha:
						# Append without encryption if character is not in the alphabet
						result += character
				else:
						# Get the index of the new key and make sure it isn't too large
						lowerCAmelCase__  :     int       	=   (alpha.index(_a			) + key) % len(_a			)

						# Append the encoded character to the alphabet
						result += alpha[new_key]

		return result






def 	lowerCamelCase_       (			_a      ,  _a      ,  _a = None			):




		"""simple docstring"""






		key *= -1

		return encrypt(_a      ,  _a      ,  _a			)






def 	lowerCamelCase_       (			_a      ,  _a = None			):




		"""simple docstring"""






		lowerCAmelCase__  :     Optional[Any]       	=   alphabet or ascii_letters

		# To store data on all the combinations
		lowerCAmelCase__  :     Optional[int]       	=   {}

		# Cycle through each combination
		for key in range(1      ,  len(_a			) + 1			):
				# Decrypt the message and store the result in the data
				lowerCAmelCase__  :     Optional[int]       	=   decrypt(_a      ,  _a      ,  _a			)

		return brute_force_data


if __name__ == "__main__":
		while True:
				print(f'''\n{"-" * 10}\n Menu\n{"-" * 10}''')
				print(*['''1.Encrypt''', '''2.Decrypt''', '''3.BruteForce''', '''4.Quit'''], sep='''\n''')

				# get user input
				lowerCamelCase		=						input('''\nWhat would you like to do?: ''').strip() or '''4'''

				# run functions based on what the user chose
				if choice not in ("1", "2", "3", "4"):
						print('''Invalid choice, please enter a valid choice''')
				elif choice == "1":
						lowerCamelCase		=						input('''Please enter the string to be encrypted: ''')
						lowerCamelCase		=						int(input('''Please enter off-set: ''').strip())

						print(encrypt(input_string, key))
				elif choice == "2":
						lowerCamelCase		=						input('''Please enter the string to be decrypted: ''')
						lowerCamelCase		=						int(input('''Please enter off-set: ''').strip())

						print(decrypt(input_string, key))
				elif choice == "3":
						lowerCamelCase		=						input('''Please enter the string to be decrypted: ''')
						lowerCamelCase		=						brute_force(input_string)

						for key, value in brute_force_data.items():
								print(f'''Key: {key} | Message: {value}''')

				elif choice == "4":
						print('''Goodbye.''')
						break




