






'''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:      Any  				=				None


A:      Optional[int]  				=				logging.get_logger(__name__)


A:      List[str]  				=				{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

A:      Dict  				=				{
    "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:      Tuple  				=				{
    "facebook/mbart-large-en-ro": 1_0_2_4,
    "facebook/mbart-large-cc25": 1_0_2_4,
}

# fmt: off
A:      Optional[Any]  				=				["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 							__magic_name__     (	UpperCAmelCase_				):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_					:      Any        =  VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE_					:      Optional[int]        =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE_					:      Any        =  PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE_					:      str        =  ['input_ids', 'attention_mask']
	SCREAMING_SNAKE_CASE_					:      str        =  MBartTokenizer

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

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

							lowercase_      :   List[Any]        =			vocab_file
							lowercase_      :   List[Any]        =			False if not self.vocab_file else True

							lowercase_      :   Optional[int]        =			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}       )
							lowercase_      :   Tuple        =			{
							    lang_code: self.convert_tokens_to_ids(_lowercase       ) for lang_code in FAIRSEQ_LANGUAGE_CODES
							}

							lowercase_      :   List[Any]        =			src_lang if src_lang is not None else 'en_XX'
							lowercase_      :   int        =			self.convert_tokens_to_ids(self._src_lang       )
							lowercase_      :   Any        =			tgt_lang
							self.set_src_lang_special_tokens(self._src_lang       )
	@property
	def        lowerCamelCase__		(							self       )						->  str:
							return self._src_lang
	@src_lang.setter
	def        lowerCamelCase__		(							self  ,      _lowercase       )						->  None:
							lowercase_      :   int        =			new_src_lang
							self.set_src_lang_special_tokens(self._src_lang       )
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = None       )						->  List[int]:
							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        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = None       )						->  List[int]:
							lowercase_      :   Union[str, Any]        =			[self.sep_token_id]
							lowercase_      :   int        =			[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        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase  ,      _lowercase  ,      _lowercase  ,      **_lowercase       )						->  Union[str, Any]:
							if src_lang is None or tgt_lang is None:
													raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'       )
							lowercase_      :   int        =			src_lang
							lowercase_      :   Any        =			self(_lowercase  ,      add_special_tokens=_lowercase  ,      return_tensors=_lowercase  ,      **_lowercase       )
							lowercase_      :   Optional[int]        =			self.convert_tokens_to_ids(_lowercase       )
							lowercase_      :   Optional[int]        =			tgt_lang_id
							return inputs
	def        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = "en_XX"  ,      _lowercase = None  ,      _lowercase = "ro_RO"  ,      **_lowercase  ,      )						->  BatchEncoding:
							lowercase_      :   Optional[int]        =			src_lang
							lowercase_      :   Union[str, Any]        =			tgt_lang
							return super().prepare_seqaseq_batch(_lowercase  ,      _lowercase  ,      **_lowercase       )
	def        lowerCamelCase__		(							self       )						->  Union[str, Any]:
							return self.set_src_lang_special_tokens(self.src_lang       )
	def        lowerCamelCase__		(							self       )						->  int:
							return self.set_tgt_lang_special_tokens(self.tgt_lang       )
	def        lowerCamelCase__		(							self  ,      _lowercase       )						->  None:
							lowercase_      :   str        =			self.convert_tokens_to_ids(_lowercase       )
							lowercase_      :   Any        =			[]
							lowercase_      :   Optional[int]        =			[self.eos_token_id, self.cur_lang_code]

							lowercase_      :   Optional[int]        =			self.convert_ids_to_tokens(self.prefix_tokens       )
							lowercase_      :   Optional[int]        =			self.convert_ids_to_tokens(self.suffix_tokens       )

							lowercase_      :   Any        =			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        lowerCamelCase__		(							self  ,      _lowercase       )						->  None:
							lowercase_      :   Union[str, Any]        =			self.convert_tokens_to_ids(_lowercase       )
							lowercase_      :   List[str]        =			[]
							lowercase_      :   Optional[int]        =			[self.eos_token_id, self.cur_lang_code]

							lowercase_      :   Any        =			self.convert_ids_to_tokens(self.prefix_tokens       )
							lowercase_      :   List[Any]        =			self.convert_ids_to_tokens(self.suffix_tokens       )

							lowercase_      :   Union[str, Any]        =			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        lowerCamelCase__		(							self  ,      _lowercase  ,      _lowercase = 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(_lowercase       ):
													logger.error(f"Vocabulary path ({save_directory}) should be a directory."       )
													return
							lowercase_      :   Tuple        =			os.path.join(
							    _lowercase  ,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )

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

							return (out_vocab_file,)








'''simple docstring'''

from __future__ import annotations






def 	_UpperCAmelCase    (  a		:	int = 4							)			->			list[list[int]]:





						"""simple docstring"""
						lowercase_      :   Tuple        =			abs(a							) or 4
						return [[1 + x + y * row_size for x in range(a							)] for y in range(a							)]






def 	_UpperCAmelCase    (  a		:	list[list[int]]							)			->			list[list[int]]:





						"""simple docstring"""
						return reverse_row(transpose(a							)							)
						# OR.. transpose(reverse_column(matrix))






def 	_UpperCAmelCase    (  a		:	list[list[int]]							)			->			list[list[int]]:





						"""simple docstring"""
						return reverse_row(reverse_column(a							)							)
						# OR.. reverse_column(reverse_row(matrix))






def 	_UpperCAmelCase    (  a		:	list[list[int]]							)			->			list[list[int]]:





						"""simple docstring"""
						return reverse_column(transpose(a							)							)
						# OR.. transpose(reverse_row(matrix))






def 	_UpperCAmelCase    (  a		:	list[list[int]]							)			->			list[list[int]]:





						"""simple docstring"""
						lowercase_      :   Any        =			[list(a							) for x in zip(*a							)]
						return matrix






def 	_UpperCAmelCase    (  a		:	list[list[int]]							)			->			list[list[int]]:





						"""simple docstring"""
						lowercase_      :   List[str]        =			matrix[::-1]
						return matrix






def 	_UpperCAmelCase    (  a		:	list[list[int]]							)			->			list[list[int]]:





						"""simple docstring"""
						lowercase_      :   str        =			[x[::-1] for x in matrix]
						return matrix






def 	_UpperCAmelCase    (  a		:	list[list[int]]							)			->			None:





						"""simple docstring"""
						for i in matrix:
												print(*a							)


if __name__ == "__main__":
						A:      Dict  				=				make_matrix()
						print("\norigin:\n")
						print_matrix(matrix)
						print("\nrotate 90 counterclockwise:\n")
						print_matrix(rotate_aa(matrix))

						A:      List[Any]  				=				make_matrix()
						print("\norigin:\n")
						print_matrix(matrix)
						print("\nrotate 180:\n")
						print_matrix(rotate_aaa(matrix))

						A:      List[str]  				=				make_matrix()
						print("\norigin:\n")
						print_matrix(matrix)
						print("\nrotate 270 counterclockwise:\n")
						print_matrix(rotate_aaa(matrix))
