"""simple docstring"""







from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_clip import CLIPTokenizer


SCREAMING_SNAKE_CASE						=    logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE						=    {
    'vocab_file': {
        'openai/clip-vit-base-patch32': 'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json',
    },
    'merges_file': {
        'openai/clip-vit-base-patch32': 'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'openai/clip-vit-base-patch32': (
            'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json'
        ),
    },
}

SCREAMING_SNAKE_CASE						=    {
    'openai/clip-vit-base-patch32': 77,
}



class 			_lowerCamelCase      (_lowerCAmelCase  ):
				_snake_case  =	VOCAB_FILES_NAMES
				_snake_case  =	PRETRAINED_VOCAB_FILES_MAP
				_snake_case  =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_snake_case  =	["input_ids", "attention_mask"]
				_snake_case  =	CLIPTokenizer







				def __init__(			self     :							str      ,       lowerCamelCase_     :							List[str]=None      ,       lowerCamelCase_     :							Any=None      ,       lowerCamelCase_     :							Tuple=None      ,       lowerCamelCase_     :							List[str]="<|endoftext|>"      ,       lowerCamelCase_     :							int="<|startoftext|>"      ,       lowerCamelCase_     :							Union[str, Any]="<|endoftext|>"      ,       lowerCamelCase_     :							Optional[int]="<|endoftext|>"      ,       **lowerCamelCase_     :							str      ,       ):

					"""simple docstring"""






					super().__init__(
					    lowerCAmelCase__      ,       lowerCAmelCase__      ,       tokenizer_file=lowerCAmelCase__      ,       unk_token=lowerCAmelCase__      ,       bos_token=lowerCAmelCase__      ,       eos_token=lowerCAmelCase__      ,       pad_token=lowerCAmelCase__      ,       **lowerCAmelCase__      ,       )

					if not isinstance(self.backend_tokenizer.pre_tokenizer      ,       pre_tokenizers.Sequence    ):
						raise ValueError(
						    'The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been'
						    ' heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using'
						    ' to be compatible with this version.The easiest way to do so is'
						    ' `CLIPTokenizerFast.from_pretrained("path_to_local_folder_or_hub_repo, from_slow=True)`. If you want'
						    ' to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of'
						    ' transformers.'    )

					self._wrap_decode_method_backend_tokenizer()







				def 				__UpperCAmelCase       (			self     :							Dict    ):

					"""simple docstring"""






					_lowercase			:     Optional[int]      					=				self.backend_tokenizer.decode

					def new_decode_method(*lowerCamelCase_     :							List[str]      ,       **lowerCamelCase_     :							int    ):
						_lowercase			:     str      					=				orig_decode_method(*lowerCAmelCase__      ,       **lowerCAmelCase__    )
						_lowercase			:     List[str]      					=				text.replace(self.backend_tokenizer.model.end_of_word_suffix      ,       ' '    ).strip()
						return text

					_lowercase			:     Optional[Any]      					=				new_decode_method







				def 				__UpperCAmelCase       (			self     :							int      ,       lowerCamelCase_     :							List[int]      ,       lowerCamelCase_     :							Optional[List[int]] = None    ):

					"""simple docstring"""






					_lowercase			:     Optional[int]      					=				[self.bos_token_id]
					_lowercase			:     Any      					=				[self.eos_token_id]

					if token_ids_a is None:
						return bos_token + token_ids_a + eos_token
					return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token







				def 				__UpperCAmelCase       (			self     :							Dict      ,       lowerCamelCase_     :							List[int]      ,       lowerCamelCase_     :							Optional[List[int]] = None    ):

					"""simple docstring"""






					_lowercase			:     Dict      					=				[self.bos_token_id]
					_lowercase			:     Optional[int]      					=				[self.eos_token_id]

					if token_ids_a is None:
						return len(bos_token + token_ids_a + eos_token    ) * [0]
					return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token    ) * [0]







				def 				__UpperCAmelCase       (			self     :							List[str]      ,       lowerCamelCase_     :							str      ,       lowerCamelCase_     :							Optional[str] = None    ):

					"""simple docstring"""






					_lowercase			:     List[str]      					=				self._tokenizer.model.save(lowerCAmelCase__      ,       name=lowerCAmelCase__    )
					return tuple(lowerCAmelCase__    )










"""simple docstring"""




import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

UpperCamelCase_	 ={"""UserAgent""": UserAgent().random}
UpperCamelCase_	 ="""https://www.mywaifulist.moe/random"""





def 			a_							(				_lowercase			,		_lowercase  ):
						_UpperCamelCase     :   Optional[Any]      =       requests.get(_lowercase			,		headers=_lowercase  )
						with open(_lowercase			,		'''wb'''  ) as file:
												file.write(image.content  )





def 			a_							(				):
						_UpperCamelCase     :   Union[str, Any]      =       BeautifulSoup(requests.get(_lowercase			,		headers=_lowercase  ).text			,		'''html.parser'''  )
						_UpperCamelCase     :   List[str]      =       soup.find('''meta'''			,		attrs={'''property''': '''og:title'''}  ).attrs['''content''']
						_UpperCamelCase     :   Optional[int]      =       soup.find('''meta'''			,		attrs={'''property''': '''og:image'''}  ).attrs['''content''']
						_UpperCamelCase     :   Any      =       soup.find('''p'''			,		id='''description'''  ).get_text()
						_UpperCamelCase  ,				_UpperCamelCase     :   Optional[int]      =       os.path.splitext(os.path.basename(_lowercase  )  )
						_UpperCamelCase     :   Dict      =       title.strip().replace(''' '''			,		'''_'''  )
						_UpperCamelCase     :   str      =       F"""{image_title}{image_extension}"""
						save_image(_lowercase			,		_lowercase  )
						return (title, description, image_title)


if __name__ == "__main__":
						UpperCamelCase_ ,      UpperCamelCase_ ,      UpperCamelCase_	 =random_anime_character()
						print(F"{title}\n\n{desc}\n\nImage saved : {image_title}")



