






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

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


if is_sentencepiece_available():
						from .tokenization_xlm_roberta import XLMRobertaTokenizer
else:
						_UpperCamelCase		:		List[Any]								=			None


_UpperCamelCase		:		Tuple								=			logging.get_logger(__name__)

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

_UpperCamelCase		:		Optional[Any]								=			{
    'vocab_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json'
        ),
    },
}

_UpperCamelCase		:		str								=			{
    'xlm-roberta-base': 512,
    'xlm-roberta-large': 512,
    'xlm-roberta-large-finetuned-conll02-dutch': 512,
    'xlm-roberta-large-finetuned-conll02-spanish': 512,
    'xlm-roberta-large-finetuned-conll03-english': 512,
    'xlm-roberta-large-finetuned-conll03-german': 512,
}


class 				snake_case__     (			UpperCamelCase):
					a_       =			VOCAB_FILES_NAMES
					a_       =			PRETRAINED_VOCAB_FILES_MAP
					a_       =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					a_       =			["input_ids", "attention_mask"]
					a_       =			XLMRobertaTokenizer




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

								super().__init__(
								    _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							,				**_A							,				)

								UpperCAmelCase_     :   str       =   vocab_file
								UpperCAmelCase_     :   Any       =   False if not self.vocab_file else True




					def 						A     (       self       :						List[Any]							,				_A       :						List[int]							,				_A       :						Optional[List[int]] = None     )  ->    List[int]:

								if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								UpperCAmelCase_     :   Any       =   [self.cls_token_id]
								UpperCAmelCase_     :   Optional[Any]       =   [self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep




					def 						A     (       self       :						List[Any]							,				_A       :						List[int]							,				_A       :						Optional[List[int]] = None     )  ->    List[int]:
								UpperCAmelCase_     :   str       =   [self.sep_token_id]
								UpperCAmelCase_     :   Dict       =   [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 						A     (       self       :						Optional[int]							,				_A       :						str							,				_A       :						Optional[str] = None     )  ->    Tuple[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(_A     ):
											logger.error(F"Vocabulary path ({save_directory}) should be a directory."     )
											return
								UpperCAmelCase_     :   List[Any]       =   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,)










'''simple docstring'''





def __UpperCAmelCase (			A			:	list[list[int]]						)  -> bool:
			# must be
			UpperCAmelCase_     :   int       =   [list(A						) for row in matrix]
			if matrix and isinstance(A	,   A						):
						if isinstance(matrix[0]	,   A						):
									UpperCAmelCase_     :   Optional[Any]       =   0
									for row in matrix:
												if prev_len == 0:
															UpperCAmelCase_     :   List[str]       =   len(A						)
															UpperCAmelCase_     :   Any       =   True
												else:
															UpperCAmelCase_     :   Tuple       =   prev_len == len(A						)
						else:
									UpperCAmelCase_     :   Any       =   True
			else:
						UpperCAmelCase_     :   Dict       =   False

			return result
def __UpperCAmelCase (			A			:	list[list[int]]						)  -> None:
			if check_matrix(A						) and len(A						) > 0:
						UpperCAmelCase_     :   Dict       =   [list(A						) for row in a]
						UpperCAmelCase_     :   List[Any]       =   len(A						)
						if isinstance(a[0]	,   A						):
									UpperCAmelCase_     :   Any       =   len(a[0]						)
						else:
									for dat in a:
												print(A						)
									return

						# horizotal printing increasing
						for i in range(0	,   A						):
									print(a[0][i]						)
						# vertical printing down
						for i in range(1	,   A						):
									print(a[i][mat_col - 1]						)
						# horizotal printing decreasing
						if mat_row > 1:
									for i in range(mat_col - 2	,   -1	,   -1						):
												print(a[mat_row - 1][i]						)
        # vertical printing up
						for i in range(mat_row - 2	,   0	,   -1						):
									print(a[i][0]						)
						UpperCAmelCase_     :   Union[str, Any]       =   [row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
						if len(A						) > 0:
									spiral_print_clockwise(A						)
						else:
									return
			else:
						print('''Not a valid matrix'''						)
						return
def __UpperCAmelCase (			A			:	list[list]						)  -> list[int]:
			if matrix:
						return list(matrix.pop(0						)						) + spiral_traversal(list(zip(*A						)						)[::-1]						)
			else:
						return []


# driver code
if __name__ == "__main__":
						import doctest

						doctest.testmod()

						_UpperCamelCase		:		List[Any]								=			[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
						spiral_print_clockwise(a)


