




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_pegasus import PegasusTokenizer
else:
		__UpperCAmelCase     							=						None


__UpperCAmelCase     							=						logging.get_logger(__name__)


__UpperCAmelCase     							=						'▁'

__UpperCAmelCase     							=						{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__UpperCAmelCase     							=						{
    'vocab_file': {'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'},
    'tokenizer_file': {
        'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json'
    },
}

__UpperCAmelCase     							=						{
    'google/pegasus-xsum': 512,
}



class   lowerCamelCase				(_a      ):







		'''simple docstring'''



		_snake_case   :   Union[str, Any]							=  VOCAB_FILES_NAMES
		_snake_case   :   str							=  PRETRAINED_VOCAB_FILES_MAP
		_snake_case   :   str							=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_snake_case   :   Optional[int]							=  PegasusTokenizer
		_snake_case   :   Tuple							=  ['''input_ids''', '''attention_mask''']



		def __init__(							self    ,		_UpperCamelCase=None    ,		_UpperCamelCase=None    ,		_UpperCamelCase="<pad>"    ,		_UpperCamelCase="</s>"    ,		_UpperCamelCase="<unk>"    ,		_UpperCamelCase="<mask_2>"    ,		_UpperCamelCase="<mask_1>"    ,		_UpperCamelCase=None    ,		_UpperCamelCase=1_0_3    ,		**_UpperCamelCase    ,		)     ->							Dict:
							UpperCAmelCase_   :				Union[str, Any]						=						offset

							if additional_special_tokens is not None:
												if not isinstance(snake_case_    ,		snake_case_       ):
																	raise TypeError(
																	    f"additional_special_tokens should be of type {type(snake_case_       )}, but is"
																	    f" {type(snake_case_       )}"       )

												UpperCAmelCase_   :				Any						=						(
												    ([mask_token_sent] + additional_special_tokens)
												    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
												    else additional_special_tokens
												)
												# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
												additional_special_tokens_extended += [
												    f"<unk_{i}>" for i in range(len(snake_case_       )    ,		self.offset - 1       )
												]

												if len(set(snake_case_       )       ) != len(snake_case_       ):
																	raise ValueError(
																	    'Please make sure that the provided additional_special_tokens do not contain an incorrectly'
																	    f" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}."       )
												UpperCAmelCase_   :				int						=						additional_special_tokens_extended
							else:
												UpperCAmelCase_   :				List[Any]						=						[mask_token_sent] if mask_token_sent is not None else []
												additional_special_tokens += [f"<unk_{i}>" for i in range(2    ,		self.offset       )]

							super().__init__(
							    snake_case_    ,		tokenizer_file=snake_case_    ,		pad_token=snake_case_    ,		eos_token=snake_case_    ,		unk_token=snake_case_    ,		mask_token=snake_case_    ,		mask_token_sent=snake_case_    ,		offset=snake_case_    ,		additional_special_tokens=snake_case_    ,		**snake_case_    ,		)
							UpperCAmelCase_   :				Dict						=						vocab_file
							UpperCAmelCase_   :				Optional[int]						=						False if not self.vocab_file else True



		def  __UpperCAmelCase      (							self    ,		_UpperCamelCase       )     ->							List[str]:
							UpperCAmelCase_   :				Dict						=						set(self.all_special_ids       )  # call it once instead of inside list comp
							all_special_ids.remove(self.unk_token_id       )  # <unk> is only sometimes special

							if all_special_ids != set(range(len(self.additional_special_tokens       ) + 3       )       ):
												raise ValueError(
												    'There should be 3 special tokens: mask_token, pad_token, and eos_token +'
												    f" {len(self.additional_special_tokens       )} additional_special_tokens, but got {all_special_ids}"       )

							return [1 if x in all_special_ids else 0 for x in seq]



		def  __UpperCAmelCase      (							self    ,		_UpperCamelCase    ,		_UpperCamelCase = None    ,		_UpperCamelCase = False       )     ->							Dict:
							if already_has_special_tokens:
												return self._special_token_mask(snake_case_       )
							elif token_ids_a is None:
												return self._special_token_mask(snake_case_       ) + [1]
							else:
												return self._special_token_mask(token_ids_a + token_ids_a       ) + [1]



		def  __UpperCAmelCase      (							self    ,		_UpperCamelCase    ,		_UpperCamelCase=None       )     ->							Union[str, Any]:
							if token_ids_a is None:
												return token_ids_a + [self.eos_token_id]
							# We don't expect to process pairs, but leave the pair logic for API consistency
							return token_ids_a + token_ids_a + [self.eos_token_id]



		def  __UpperCAmelCase      (							self    ,		_UpperCamelCase    ,		_UpperCamelCase = None       )     ->							str:
							if not self.can_save_slow_tokenizer:
												raise ValueError(
												    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
												    'tokenizer.'       )

							if not os.path.isdir(snake_case_       ):
												logger.error(f"Vocabulary path ({save_directory}) should be a directory"       )
												return
							UpperCAmelCase_   :				Optional[int]						=						os.path.join(
							    snake_case_    ,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )

							if os.path.abspath(self.vocab_file       ) != os.path.abspath(snake_case_       ):
												copyfile(self.vocab_file    ,		snake_case_       )

							return (out_vocab_file,)














from collections import defaultdict
from math import ceil, sqrt




def 					lowercase__				(					__snake_case   :							int = 1_000_000					,	__snake_case   :							int = 10  ):


					'''simple docstring'''


					UpperCAmelCase_   :				defaultdict						=						defaultdict(__snake_case  )

					for outer_width in range(3					,	(t_limit // 4) + 2  ):
										if outer_width * outer_width > t_limit:
															UpperCAmelCase_   :				Union[str, Any]						=						max(
															    ceil(sqrt(outer_width * outer_width - t_limit  )  )					,	1  )
										else:
															UpperCAmelCase_   :				int						=						1

										hole_width_lower_bound += (outer_width - hole_width_lower_bound) % 2

										for hole_width in range(__snake_case					,	outer_width - 1					,	2  ):
															count[outer_width * outer_width - hole_width * hole_width] += 1

					return sum(1 for n in count.values() if 1 <= n <= 10  )


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






