




"""simple docstring"""







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:
		a  =				None


a  =				logging.get_logger(__name__)


a  =				{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

a  =				{
    '''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''',
    },
}

a  =				{
    '''facebook/mbart-large-en-ro''': 1_0_2_4,
    '''facebook/mbart-large-cc25''': 1_0_2_4,
}

# fmt: off
a  =				['''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    SCREAMING_SNAKE_CASE__       (       a__       ):
						_a         =    VOCAB_FILES_NAMES
						_a         =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_a         =    PRETRAINED_VOCAB_FILES_MAP
						_a         =    ["""input_ids""", """attention_mask"""]
						_a         =    MBartTokenizer

						_a         =    []
						_a         =    []


						def __init__(				self					:      Optional[Any]    ,    lowerCAmelCase					:      str=None    ,    lowerCAmelCase					:      List[Any]=None    ,    lowerCAmelCase					:      Optional[Any]="<s>"    ,    lowerCAmelCase					:      List[Any]="</s>"    ,    lowerCAmelCase					:      int="</s>"    ,    lowerCAmelCase					:      Optional[Any]="<s>"    ,    lowerCAmelCase					:      Any="<unk>"    ,    lowerCAmelCase					:      Tuple="<pad>"    ,    lowerCAmelCase					:      List[str]="<mask>"    ,    lowerCAmelCase					:      List[str]=None    ,    lowerCAmelCase					:      Dict=None    ,    lowerCAmelCase					:      Optional[int]=None    ,    **lowerCAmelCase					:      List[Any]    ,    ):
										# Mask token behave like a normal word, i.e. include the space before it
										lowerCAmelCase						=					AddedToken(lowerCAmelCase__    ,    lstrip=lowerCAmelCase__    ,    rstrip=lowerCAmelCase__       ) if isinstance(lowerCAmelCase__    ,    lowerCAmelCase__       ) else mask_token

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

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

										lowerCAmelCase						=					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}       )
										lowerCAmelCase						=					{
										    lang_code: self.convert_tokens_to_ids(lowerCAmelCase__       ) for lang_code in FAIRSEQ_LANGUAGE_CODES
										}

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


						@property
						def 	__lowercase			(				self					:      List[Any]       ):
										return self._src_lang


						@src_lang.setter
						def 	__lowercase			(				self					:      List[Any]    ,    lowerCAmelCase					:      Any       ):
										lowerCAmelCase						=					new_src_lang
										self.set_src_lang_special_tokens(self._src_lang       )


						def 	__lowercase			(				self					:      Tuple    ,    lowerCAmelCase					:      str    ,    lowerCAmelCase					:      Optional[int] = None       ):
										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 	__lowercase			(				self					:      List[Any]    ,    lowerCAmelCase					:      int    ,    lowerCAmelCase					:      Optional[Any] = None       ):
										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]


						def 	__lowercase			(				self					:      Union[str, Any]    ,    lowerCAmelCase					:      Dict    ,    lowerCAmelCase					:      Optional[int]    ,    lowerCAmelCase					:      Tuple    ,    lowerCAmelCase					:      Optional[Any]    ,    **lowerCAmelCase					:      List[str]       ):
										if src_lang is None or tgt_lang is None:
														raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""       )
										lowerCAmelCase						=					src_lang
										lowerCAmelCase						=					self(lowerCAmelCase__    ,    add_special_tokens=lowerCAmelCase__    ,    return_tensors=lowerCAmelCase__    ,    **lowerCAmelCase__       )
										lowerCAmelCase						=					self.convert_tokens_to_ids(lowerCAmelCase__       )
										lowerCAmelCase						=					tgt_lang_id
										return inputs


						def 	__lowercase			(				self					:      Tuple    ,    lowerCAmelCase					:      int    ,    lowerCAmelCase					:      List[Any] = "en_XX"    ,    lowerCAmelCase					:      int = None    ,    lowerCAmelCase					:      Union[str, Any] = "ro_RO"    ,    **lowerCAmelCase					:      Optional[Any]    ,    ):
										lowerCAmelCase						=					src_lang
										lowerCAmelCase						=					tgt_lang
										return super().prepare_seqaseq_batch(lowerCAmelCase__    ,    lowerCAmelCase__    ,    **lowerCAmelCase__       )


						def 	__lowercase			(				self					:      Any       ):
										return self.set_src_lang_special_tokens(self.src_lang       )


						def 	__lowercase			(				self					:      Dict       ):
										return self.set_tgt_lang_special_tokens(self.tgt_lang       )


						def 	__lowercase			(				self					:      List[str]    ,    lowerCAmelCase					:      Optional[int]       ):
										lowerCAmelCase						=					self.convert_tokens_to_ids(lowerCAmelCase__       )
										lowerCAmelCase						=					[]
										lowerCAmelCase						=					[self.eos_token_id, self.cur_lang_code]

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

										lowerCAmelCase						=					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 	__lowercase			(				self					:      str    ,    lowerCAmelCase					:      Tuple       ):
										lowerCAmelCase						=					self.convert_tokens_to_ids(lowerCAmelCase__       )
										lowerCAmelCase						=					[]
										lowerCAmelCase						=					[self.eos_token_id, self.cur_lang_code]

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

										lowerCAmelCase						=					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 	__lowercase			(				self					:      Dict    ,    lowerCAmelCase					:      str    ,    lowerCAmelCase					:      List[Any] = None       ):
										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(lowerCAmelCase__       ):
														logger.error(f'''Vocabulary path ({save_directory}) should be a directory.'''       )
														return
										lowerCAmelCase						=					os.path.join(
										    lowerCAmelCase__    ,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )

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

										return (out_vocab_file,)












"""simple docstring"""




class 			__UpperCamelCase							:  # Public class to implement a graph






							def __init__(  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ ,   lowerCAmelCase__ )      ->					None:
								a :						int      =							row
								a :						Tuple      =							col
								a :						Optional[int]      =							graph






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ ,   lowerCAmelCase__ )      ->					bool:
								return (
								    0 <= i < self.ROW
								    and 0 <= j < self.COL
								    and not visited[i][j]
								    and self.graph[i][j]
								)






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ ,   lowerCAmelCase__ )      ->					None:
								# Checking all 8 elements surrounding nth element
								a :						Optional[Any]      =							[-1, -1, -1, 0, 0, 1, 1, 1]  # Coordinate order
								a :						str      =							[-1, 0, 1, -1, 1, -1, 0, 1]
								a :						str      =							True  # Make those cells visited
								for k in range(8 ):
									if self.is_safe(i + row_nbr[k] ,   j + col_nbr[k] ,   lowerCAmelCase__ ):
										self.diffs(i + row_nbr[k] ,   j + col_nbr[k] ,   lowerCAmelCase__ )






							def        __a  (  self )      ->					int:  # And finally, count all islands.
								a :						Union[str, Any]      =							[[False for j in range(self.COL )] for i in range(self.ROW )]
								a :						Dict      =							0
								for i in range(self.ROW ):
									for j in range(self.COL ):
										if visited[i][j] is False and self.graph[i][j] == 1:
											self.diffs(lowerCAmelCase__ ,   lowerCAmelCase__ ,   lowerCAmelCase__ )
											count += 1
								return count


