






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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_mbart import MBartTokenizer
else:
		UpperCamelCase			    =     None


UpperCamelCase			    =     logging.get_logger(__name__)


UpperCamelCase			    =     {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

UpperCamelCase			    =     {
    """vocab_file""": {
        """facebook/mbart-large-en-ro""": (
            """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"""
        ),
        """facebook/mbart-large-cc25""": (
            """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """facebook/mbart-large-en-ro""": """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json""",
        """facebook/mbart-large-cc25""": """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json""",
    },
}

UpperCamelCase			    =     {
    """facebook/mbart-large-en-ro""": 1_024,
    """facebook/mbart-large-cc25""": 1_024,
}

# fmt: off
UpperCamelCase			    =     ["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN"""]



class 				__UpperCAmelCase		(__snake_case   ):
			__snake_case    :				Dict									=							VOCAB_FILES_NAMES
			__snake_case    :				int									=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__snake_case    :				List[Any]									=							PRETRAINED_VOCAB_FILES_MAP
			__snake_case    :				str									=							["input_ids", "attention_mask"]
			__snake_case    :				int									=							MBartTokenizer

			__snake_case    :				int									=							[]
			__snake_case    :				Dict									=							[]







			def __init__(     self:  List[Any]				,     UpperCAmelCase_:  Union[str, Any]=None				,     UpperCAmelCase_:  Any=None				,     UpperCAmelCase_:  List[str]="<s>"				,     UpperCAmelCase_:  int="</s>"				,     UpperCAmelCase_:  int="</s>"				,     UpperCAmelCase_:  Any="<s>"				,     UpperCAmelCase_:  Any="<unk>"				,     UpperCAmelCase_:  Optional[Any]="<pad>"				,     UpperCAmelCase_:  int="<mask>"				,     UpperCAmelCase_:  Union[str, Any]=None				,     UpperCAmelCase_:  List[str]=None				,     UpperCAmelCase_:  Any=None				,     **UpperCAmelCase_:  Dict				,     ):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE     				=  AddedToken(a_				,     lstrip=a_				,     rstrip=a_					) if isinstance(a_				,     a_					) else mask_token

									super().__init__(
									    vocab_file=a_				,     tokenizer_file=a_				,     bos_token=a_				,     eos_token=a_				,     sep_token=a_				,     cls_token=a_				,     unk_token=a_				,     pad_token=a_				,     mask_token=a_				,     src_lang=a_				,     tgt_lang=a_				,     additional_special_tokens=a_				,     **a_				,     )

									_SCREAMING_SNAKE_CASE     				=  vocab_file
									_SCREAMING_SNAKE_CASE     				=  False if not self.vocab_file else True

									_SCREAMING_SNAKE_CASE     				=  FAIRSEQ_LANGUAGE_CODES.copy()

									if additional_special_tokens is not None:
															# Only add those special tokens if they are not already there.
															_additional_special_tokens.extend(
															    [t for t in additional_special_tokens if t not in _additional_special_tokens]					)

									self.add_special_tokens({"""additional_special_tokens""": _additional_special_tokens}					)
									_SCREAMING_SNAKE_CASE     				=  {
									    lang_code: self.convert_tokens_to_ids(a_					) for lang_code in FAIRSEQ_LANGUAGE_CODES
									}

									_SCREAMING_SNAKE_CASE     				=  src_lang if src_lang is not None else '''en_XX'''
									_SCREAMING_SNAKE_CASE     				=  self.convert_tokens_to_ids(self._src_lang					)
									_SCREAMING_SNAKE_CASE     				=  tgt_lang
									self.set_src_lang_special_tokens(self._src_lang					)







			@property
			def 							UpperCamelCase				(     self:  List[str]					):







									'''simple docstring'''




									return self._src_lang







			@src_lang.setter
			def 							UpperCamelCase				(     self:  Dict				,     UpperCAmelCase_:  List[Any]					):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE     				=  new_src_lang
									self.set_src_lang_special_tokens(self._src_lang					)







			def 							UpperCamelCase				(     self:  Optional[Any]				,     UpperCAmelCase_:  List[str]				,     UpperCAmelCase_:  Any = None					):







									'''simple docstring'''




									if token_ids_a is None:
															return self.prefix_tokens + token_ids_a + self.suffix_tokens
									# We don't expect to process pairs, but leave the pair logic for API consistency
									return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens







			def 							UpperCamelCase				(     self:  List[Any]				,     UpperCAmelCase_:  int				,     UpperCAmelCase_:  str = None					):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE     				=  [self.sep_token_id]
									_SCREAMING_SNAKE_CASE     				=  [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]







			def 							UpperCamelCase				(     self:  Dict				,     UpperCAmelCase_:  int				,     UpperCAmelCase_:  Optional[int]				,     UpperCAmelCase_:  Optional[Any]				,     UpperCAmelCase_:  Optional[Any]				,     **UpperCAmelCase_:  Optional[Any]					):







									'''simple docstring'''




									if src_lang is None or tgt_lang is None:
															raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""					)
									_SCREAMING_SNAKE_CASE     				=  src_lang
									_SCREAMING_SNAKE_CASE     				=  self(a_				,     add_special_tokens=a_				,     return_tensors=a_				,     **a_					)
									_SCREAMING_SNAKE_CASE     				=  self.convert_tokens_to_ids(a_					)
									_SCREAMING_SNAKE_CASE     				=  tgt_lang_id
									return inputs







			def 							UpperCamelCase				(     self:  Optional[Any]				,     UpperCAmelCase_:  Optional[int]				,     UpperCAmelCase_:  Optional[Any] = "en_XX"				,     UpperCAmelCase_:  str = None				,     UpperCAmelCase_:  Union[str, Any] = "ro_RO"				,     **UpperCAmelCase_:  Optional[int]				,     ):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE     				=  src_lang
									_SCREAMING_SNAKE_CASE     				=  tgt_lang
									return super().prepare_seqaseq_batch(a_				,     a_				,     **a_					)







			def 							UpperCamelCase				(     self:  Any					):







									'''simple docstring'''




									return self.set_src_lang_special_tokens(self.src_lang					)







			def 							UpperCamelCase				(     self:  Optional[Any]					):







									'''simple docstring'''




									return self.set_tgt_lang_special_tokens(self.tgt_lang					)







			def 							UpperCamelCase				(     self:  Union[str, Any]				,     UpperCAmelCase_:  List[str]					):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE     				=  self.convert_tokens_to_ids(a_					)
									_SCREAMING_SNAKE_CASE     				=  []
									_SCREAMING_SNAKE_CASE     				=  [self.eos_token_id, self.cur_lang_code]

									_SCREAMING_SNAKE_CASE     				=  self.convert_ids_to_tokens(self.prefix_tokens					)
									_SCREAMING_SNAKE_CASE     				=  self.convert_ids_to_tokens(self.suffix_tokens					)

									_SCREAMING_SNAKE_CASE     				=  processors.TemplateProcessing(
									    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str				,     pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str				,     special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str				,     self.prefix_tokens + self.suffix_tokens					)					)				,     )







			def 							UpperCamelCase				(     self:  Union[str, Any]				,     UpperCAmelCase_:  str					):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE     				=  self.convert_tokens_to_ids(a_					)
									_SCREAMING_SNAKE_CASE     				=  []
									_SCREAMING_SNAKE_CASE     				=  [self.eos_token_id, self.cur_lang_code]

									_SCREAMING_SNAKE_CASE     				=  self.convert_ids_to_tokens(self.prefix_tokens					)
									_SCREAMING_SNAKE_CASE     				=  self.convert_ids_to_tokens(self.suffix_tokens					)

									_SCREAMING_SNAKE_CASE     				=  processors.TemplateProcessing(
									    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str				,     pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str				,     special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str				,     self.prefix_tokens + self.suffix_tokens					)					)				,     )







			def 							UpperCamelCase				(     self:  List[str]				,     UpperCAmelCase_:  str				,     UpperCAmelCase_:  Dict = None					):







									'''simple docstring'''




									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(a_					):
															logger.error(F'Vocabulary path ({save_directory}) should be a directory.'					)
															return
									_SCREAMING_SNAKE_CASE     				=  os.path.join(
									    a_				,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]					)

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

									return (out_vocab_file,)









from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors

def 	__lowerCamelCase      (		snake_case__		)							->  int:






						"""simple docstring"""





						_SCREAMING_SNAKE_CASE     				=  prime_factors(snake_case__		)
						if is_square_free(snake_case__		):
												return -1 if len(snake_case__		) % 2 else 1
						return 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

