






"""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_mbartaa import MBartaaTokenizer
else:
    _UpperCamelCase						:    Tuple		=						None


_UpperCamelCase						:    str		=						logging.get_logger(__name__)

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

_UpperCamelCase						:    str		=						{
    'vocab_file': {
        'facebook/mbart-large-50-one-to-many-mmt': (
            'https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'facebook/mbart-large-50-one-to-many-mmt': (
            'https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json'
        ),
    },
}

_UpperCamelCase						:    Optional[int]		=						{
    'facebook/mbart-large-50-one-to-many-mmt': 1_0_2_4,
}

# fmt: off
_UpperCamelCase						:    List[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', 'af_ZA', 'az_AZ', 'bn_IN', 'fa_IR', 'he_IL', 'hr_HR', 'id_ID', 'ka_GE', 'km_KH', 'mk_MK', 'ml_IN', 'mn_MN', 'mr_IN', 'pl_PL', 'ps_AF', 'pt_XX', 'sv_SE', 'sw_KE', 'ta_IN', 'te_IN', 'th_TH', 'tl_XX', 'uk_UA', 'ur_PK', 'xh_ZA', 'gl_ES', 'sl_SI']

class 			a	(  a_      ):
    UpperCAmelCase_					:	Any      	=VOCAB_FILES_NAMES
    UpperCAmelCase_					:	str      	=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase_					:	Union[str, Any]      	=PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase_					:	Optional[int]      	=["input_ids", "attention_mask"]
    UpperCAmelCase_					:	Optional[Any]      	=MBartaaTokenizer

    UpperCAmelCase_					:	List[int]      	=[]
    UpperCAmelCase_					:	List[int]      	=[]







    def __init__(     self				,						_lowerCamelCase=None				,						_lowerCamelCase=None				,						_lowerCamelCase=None				,						_lowerCamelCase=None				,						_lowerCamelCase="</s>"				,						_lowerCamelCase="</s>"				,						_lowerCamelCase="<s>"				,						_lowerCamelCase="<unk>"				,						_lowerCamelCase="<pad>"				,						_lowerCamelCase="<mask>"				,						**_lowerCamelCase				,						):
      # Mask token behave like a normal word, i.e. include the space before it
      lowercase				       =			AddedToken(_lowerCamelCase				,						lstrip=_lowerCamelCase				,						rstrip=_lowerCamelCase			) if isinstance(_lowerCamelCase				,						_lowerCamelCase			) else mask_token

      lowercase				       =			kwargs.get('additional_special_tokens'				,						[]			)
      kwargs["additional_special_tokens"] += [
          code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
      ]

      super().__init__(
          _lowerCamelCase				,						src_lang=_lowerCamelCase				,						tgt_lang=_lowerCamelCase				,						tokenizer_file=_lowerCamelCase				,						eos_token=_lowerCamelCase				,						sep_token=_lowerCamelCase				,						cls_token=_lowerCamelCase				,						unk_token=_lowerCamelCase				,						pad_token=_lowerCamelCase				,						mask_token=_lowerCamelCase				,						**_lowerCamelCase				,						)

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

      lowercase				       =			{
          lang_code: self.convert_tokens_to_ids(_lowerCamelCase			) for lang_code in FAIRSEQ_LANGUAGE_CODES
      }

      lowercase				       =			src_lang if src_lang is not None else 'en_XX'
      lowercase				       =			tgt_lang
      lowercase				       =			self.lang_code_to_id[self._src_lang]
      self.set_src_lang_special_tokens(self._src_lang			)







    @property
    def      UpperCamelCase_ (     self			):
      return self._src_lang







    @src_lang.setter
    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      lowercase				       =			new_src_lang
      self.set_src_lang_special_tokens(self._src_lang			)







    def      UpperCamelCase_ (     self				,						_lowerCamelCase				,						_lowerCamelCase = 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      UpperCamelCase_ (     self				,						_lowerCamelCase				,						_lowerCamelCase = "en_XX"				,						_lowerCamelCase = None				,						_lowerCamelCase = "ro_RO"				,						**_lowerCamelCase				,						):
      lowercase				       =			src_lang
      lowercase				       =			tgt_lang
      return super().prepare_seqaseq_batch(_lowerCamelCase				,						_lowerCamelCase				,						**_lowerCamelCase			)







    def      UpperCamelCase_ (     self			):
      return self.set_src_lang_special_tokens(self.src_lang			)







    def      UpperCamelCase_ (     self			):
      return self.set_tgt_lang_special_tokens(self.tgt_lang			)







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      lowercase				       =			self.convert_tokens_to_ids(_lowerCamelCase			)
      lowercase				       =			[self.cur_lang_code_id]
      lowercase				       =			[self.eos_token_id]

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

      lowercase				       =			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				,						_lowerCamelCase			):
      lowercase				       =			self.convert_tokens_to_ids(_lowerCamelCase			)
      lowercase				       =			[self.cur_lang_code_id]
      lowercase				       =			[self.eos_token_id]

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

      lowercase				       =			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				,						_lowerCamelCase				,						_lowerCamelCase				,						_lowerCamelCase				,						_lowerCamelCase				,						**_lowerCamelCase			):
      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				       =			src_lang
      lowercase				       =			self(_lowerCamelCase				,						add_special_tokens=_lowerCamelCase				,						return_tensors=_lowerCamelCase				,						**_lowerCamelCase			)
      lowercase				       =			self.convert_tokens_to_ids(_lowerCamelCase			)
      lowercase				       =			tgt_lang_id
      return inputs







    def      UpperCamelCase_ (     self				,						_lowerCamelCase				,						_lowerCamelCase = 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
      lowercase				       =			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,)







import numpy as np

def 			a		( _UpperCAmelCase				:   str					,  _UpperCAmelCase				:   Any="utf-8"					,  _UpperCAmelCase				:   List[Any]="surrogatepass"		):







		'''simple docstring'''





		__UpperCAmelCase       :	Union[str, Any]						=      bin(int.from_bytes(text.encode(_UpperCAmelCase					,  _UpperCAmelCase		)					,  '''big'''		)		)[2:]
		return bits.zfill(8 * ((len(_UpperCAmelCase		) + 7) // 8)		)

def 			a		( _UpperCAmelCase				:   Dict					,  _UpperCAmelCase				:   Any="utf-8"					,  _UpperCAmelCase				:   str="surrogatepass"		):







		'''simple docstring'''





		__UpperCAmelCase       :	List[str]						=      int(_UpperCAmelCase					,  2		)
		return n.to_bytes((n.bit_length() + 7) // 8					,  '''big'''		).decode(_UpperCAmelCase					,  _UpperCAmelCase		) or "\0"

def 			a		( _UpperCAmelCase				:   List[Any]					,  _UpperCAmelCase				:   List[str]		):







		'''simple docstring'''





		if size_par + len(_UpperCAmelCase		) <= 2**size_par - (len(_UpperCAmelCase		) - 1):
				raise ValueError('''size of parity don\'t match with size of data'''		)

		__UpperCAmelCase       :	str						=      []
		__UpperCAmelCase       :	Any						=      []
		__UpperCAmelCase       :	Any						=      [bin(_UpperCAmelCase		)[2:] for x in range(1					,  size_par + len(_UpperCAmelCase		) + 1		)]

		# sorted information data for the size of the output data
		__UpperCAmelCase       :	Optional[Any]						=      []
		# data position template + parity
		__UpperCAmelCase       :	Any						=      []
		# parity bit counter
		__UpperCAmelCase       :	Tuple						=      0
		# counter position of data bits
		__UpperCAmelCase       :	Optional[int]						=      0

		for x in range(1					,  size_par + len(_UpperCAmelCase		) + 1		):
				# Performs a template of bit positions - who should be given,
				# and who should be parity
				if qtd_bp < size_par:
						if (np.log(_UpperCAmelCase		) / np.log(2		)).is_integer():
								data_out_gab.append('''P'''		)
								__UpperCAmelCase       :	Union[str, Any]						=      qtd_bp + 1
						else:
								data_out_gab.append('''D'''		)
				else:
						data_out_gab.append('''D'''		)

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data[cont_data]		)
						cont_data += 1
				else:
						data_ord.append(_UpperCAmelCase		)

    # Calculates parity
		__UpperCAmelCase       :	Union[str, Any]						=      0  # parity bit counter
		for bp in range(1					,  size_par + 1		):
				# Bit counter one for a given parity
				__UpperCAmelCase       :	List[str]						=      0
				# counter to control the loop reading
				__UpperCAmelCase       :	str						=      0
				for x in data_ord:
						if x is not None:
								try:
										__UpperCAmelCase       :	Tuple						=      (bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										__UpperCAmelCase       :	List[str]						=      '''0'''
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(cont_bo % 2		)

				qtd_bp += 1

		# Mount the message
		__UpperCAmelCase       :	int						=      0  # parity bit counter
		for x in range(0					,  size_par + len(_UpperCAmelCase		)		):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp]		)		)
						cont_bp += 1
				else:
						data_out.append(data_ord[x]		)

		return data_out

def 			a		( _UpperCAmelCase				:   List[str]					,  _UpperCAmelCase				:   str		):







		'''simple docstring'''





		__UpperCAmelCase       :	str						=      []
		# Parity bit counter
		__UpperCAmelCase       :	List[str]						=      0
		# Counter p data bit reading
		__UpperCAmelCase       :	int						=      0
		# list of parity received
		__UpperCAmelCase       :	int						=      []
		__UpperCAmelCase       :	List[Any]						=      []

		for x in range(1					,  len(_UpperCAmelCase		) + 1		):
				# Performs a template of bit positions - who should be given,
				#  and who should be parity
				if qtd_bp < size_par and (np.log(_UpperCAmelCase		) / np.log(2		)).is_integer():
						data_out_gab.append('''P'''		)
						__UpperCAmelCase       :	Union[str, Any]						=      qtd_bp + 1
				else:
						data_out_gab.append('''D'''		)

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_output.append(data[cont_data]		)
				else:
						parity_received.append(data[cont_data]		)
				cont_data += 1

		# -----------calculates the parity with the data
		__UpperCAmelCase       :	Optional[int]						=      []
		__UpperCAmelCase       :	Dict						=      []
		__UpperCAmelCase       :	Union[str, Any]						=      [bin(_UpperCAmelCase		)[2:] for x in range(1					,  size_par + len(_UpperCAmelCase		) + 1		)]

		#  sorted information data for the size of the output data
		__UpperCAmelCase       :	str						=      []
		# Data position feedback + parity
		__UpperCAmelCase       :	Any						=      []
		# Parity bit counter
		__UpperCAmelCase       :	int						=      0
		# Counter p data bit reading
		__UpperCAmelCase       :	List[Any]						=      0

		for x in range(1					,  size_par + len(_UpperCAmelCase		) + 1		):
				# Performs a template position of bits - who should be given,
				# and who should be parity
				if qtd_bp < size_par and (np.log(_UpperCAmelCase		) / np.log(2		)).is_integer():
						data_out_gab.append('''P'''		)
						__UpperCAmelCase       :	Dict						=      qtd_bp + 1
				else:
						data_out_gab.append('''D'''		)

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data_output[cont_data]		)
						cont_data += 1
				else:
						data_ord.append(_UpperCAmelCase		)

    # Calculates parity
		__UpperCAmelCase       :	Union[str, Any]						=      0  # parity bit counter
		for bp in range(1					,  size_par + 1		):
				# Bit counter one for a certain parity
				__UpperCAmelCase       :	Union[str, Any]						=      0
				# Counter to control loop reading
				__UpperCAmelCase       :	Optional[Any]						=      0
				for x in data_ord:
						if x is not None:
								try:
										__UpperCAmelCase       :	int						=      (bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										__UpperCAmelCase       :	int						=      '''0'''
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(str(cont_bo % 2		)		)

				qtd_bp += 1

		# Mount the message
		__UpperCAmelCase       :	Any						=      0  # Parity bit counter
		for x in range(0					,  size_par + len(_UpperCAmelCase		)		):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp]		)		)
						cont_bp += 1
				else:
						data_out.append(data_ord[x]		)

		__UpperCAmelCase       :	Optional[Any]						=      parity_received == parity
		return data_output, ack





