




'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


lowercase_     		= logging.get_logger(__name__)


lowercase_     		= {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all MVP models at https://huggingface.co/models?filter=mvp
lowercase_     		= {
    '''vocab_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json''',
    },
    '''added_tokens.json''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json''',
    },
    '''merges_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json''',
    },
}

lowercase_     		= {
    '''RUCAIBox/mvp''': 1024,
}
class   SCREAMING_SNAKE_CASE			(						__a):







		"""simple docstring"""
		lowercase   :      List[str]       =							VOCAB_FILES_NAMES
		lowercase   :      Union[str, Any]       =							PRETRAINED_VOCAB_FILES_MAP
		lowercase   :      Dict       =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowercase   :      List[str]       =							['input_ids', 'attention_mask']
		lowercase   :      Union[str, Any]       =							MvpTokenizer






		def __init__(   self		,						__A=None		,						__A=None		,						__A=None		,						__A="replace"		,						__A="<s>"		,						__A="</s>"		,						__A="</s>"		,						__A="<s>"		,						__A="<unk>"		,						__A="<pad>"		,						__A="<mask>"		,						__A=False		,						__A=True		,						**__A		,						) ->     Optional[int]:
								super().__init__(
								    A__		,						A__		,						tokenizer_file=A__		,						errors=A__		,						bos_token=A__		,						eos_token=A__		,						sep_token=A__		,						cls_token=A__		,						unk_token=A__		,						pad_token=A__		,						mask_token=A__		,						add_prefix_space=A__		,						trim_offsets=A__		,						**A__		,						)

								_lowerCAmelCase										=json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()				)
								if pre_tok_state.get('add_prefix_space'		,						A__				) != add_prefix_space:
														_lowerCAmelCase										=getattr(A__		,						pre_tok_state.pop('type'				)				)
														_lowerCAmelCase										=add_prefix_space
														_lowerCAmelCase										=pre_tok_class(**A__				)

								_lowerCAmelCase										=add_prefix_space

								# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
								_lowerCAmelCase										='post_processor'
								_lowerCAmelCase										=getattr(self.backend_tokenizer		,						A__		,						A__				)
								if tokenizer_component_instance:
														_lowerCAmelCase										=json.loads(tokenizer_component_instance.__getstate__()				)

														# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
														if "sep" in state:
																				_lowerCAmelCase										=tuple(state['sep']				)
														if "cls" in state:
																				_lowerCAmelCase										=tuple(state['cls']				)

														_lowerCAmelCase										=False

														if state.get('add_prefix_space'		,						A__				) != add_prefix_space:
																				_lowerCAmelCase										=add_prefix_space
																				_lowerCAmelCase										=True

														if state.get('trim_offsets'		,						A__				) != trim_offsets:
																				_lowerCAmelCase										=trim_offsets
																				_lowerCAmelCase										=True

														if changes_to_apply:
																				_lowerCAmelCase										=getattr(A__		,						state.pop('type'				)				)
																				_lowerCAmelCase										=component_class(**A__				)
																				setattr(self.backend_tokenizer		,						A__		,						A__				)






		@property
		def 		UpperCamelCase__       (   self				) ->     str:
								if self._mask_token is None:
														if self.verbose:
																				logger.error('Using mask_token, but it is not set yet.'				)
														return None
								return str(self._mask_token				)






		@mask_token.setter
		def 		UpperCamelCase__       (   self		,						__A				) ->     Union[str, Any]:
								_lowerCAmelCase										=AddedToken(A__		,						lstrip=A__		,						rstrip=A__				) if isinstance(A__		,						A__				) else value
								_lowerCAmelCase										=value






		def 		UpperCamelCase__       (   self		,						*__A		,						**__A				) ->     BatchEncoding:
								_lowerCAmelCase										=kwargs.get('is_split_into_words'		,						A__				)

								if is_split_into_words and not self.add_prefix_space:
														raise ValueError(
														    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
														    'to use it with pretokenized inputs.'				)

								return super()._batch_encode_plus(*A__		,						**A__				)






		def 		UpperCamelCase__       (   self		,						*__A		,						**__A				) ->     BatchEncoding:
								_lowerCAmelCase										=kwargs.get('is_split_into_words'		,						A__				)

								if is_split_into_words and not self.add_prefix_space:
														raise ValueError(
														    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
														    'to use it with pretokenized inputs.'				)

								return super()._encode_plus(*A__		,						**A__				)






		def 		UpperCamelCase__       (   self		,						__A		,						__A = None				) ->     Tuple[str]:
								_lowerCAmelCase										=self._tokenizer.model.save(A__		,						name=A__				)
								return tuple(A__				)






		def 		UpperCamelCase__       (   self		,						__A		,						__A=None				) ->     List[str]:
								_lowerCAmelCase										=[self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
														return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






		def 		UpperCamelCase__       (   self		,						__A		,						__A = None				) ->     List[int]:
								_lowerCAmelCase										=[self.sep_token_id]
								_lowerCAmelCase										=[self.cls_token_id]

								if token_ids_a is None:
														return len(cls + token_ids_a + sep				) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep				) * [0]






'''simple docstring'''

from PIL import Image



def 							UpperCamelCase__			(			a__			,      a__      ):


						'''simple docstring'''






						def brightness(a__      ) -> float:
												return 1_2_8 + level + (c - 1_2_8)

						if not -255.0 <= level <= 255.0:
												raise ValueError('level must be between -255.0 (black) and 255.0 (white)'      )
						return img.point(a__      )


if __name__ == "__main__":
							# Load image
							with Image.open('''image_data/lena.jpg''') as img:
														# Change brightness to 100
														lowercase_     		= change_brightness(img, 100)
														brigt_img.save('''image_data/lena_brightness.png''', format='''png''')





