




"""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:
  SCREAMING_SNAKE_CASE_      =					None


SCREAMING_SNAKE_CASE_      =					logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE_      =					{
    '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'
        ),
    },
}

SCREAMING_SNAKE_CASE_      =					{
    'facebook/mbart-large-50-one-to-many-mmt': 1024,
}

# fmt: off
SCREAMING_SNAKE_CASE_      =					['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 							snake_case_ (				lowerCamelCase_ ):







   """simple docstring"""




   A_										=					VOCAB_FILES_NAMES
   A_										=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A_										=					PRETRAINED_VOCAB_FILES_MAP
   A_										=					['''input_ids''', '''attention_mask''']
   A_										=					MBartaaTokenizer

   A_										=					[]
   A_										=					[]







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

       UpperCamelCase										=  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_					,				)

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

       UpperCamelCase										=  {
           lang_code: self.convert_tokens_to_ids(lowerCamelCase_) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }

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







   @property
   def      UpperCAmelCase__ (		self)							->      str:
       return self._src_lang







   @src_lang.setter
   def      UpperCAmelCase__ (		self					,				lowerCamelCase_)							->      None:
       UpperCamelCase										=  new_src_lang
       self.set_src_lang_special_tokens(self._src_lang)







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_					,				lowerCamelCase_ = 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      UpperCAmelCase__ (		self					,				lowerCamelCase_					,				lowerCamelCase_ = "en_XX"					,				lowerCamelCase_ = None					,				lowerCamelCase_ = "ro_RO"					,				**lowerCamelCase_					,				)							->      BatchEncoding:
       UpperCamelCase										=  src_lang
       UpperCamelCase										=  tgt_lang
       return super().prepare_seqaseq_batch(lowerCamelCase_					,				lowerCamelCase_					,				**lowerCamelCase_)







   def      UpperCAmelCase__ (		self)							->      Optional[int]:
       return self.set_src_lang_special_tokens(self.src_lang)







   def      UpperCAmelCase__ (		self)							->      Union[str, Any]:
       return self.set_tgt_lang_special_tokens(self.tgt_lang)







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_)							->      None:
       UpperCamelCase										=  self.convert_tokens_to_ids(lowerCamelCase_)
       UpperCamelCase										=  [self.cur_lang_code_id]
       UpperCamelCase										=  [self.eos_token_id]

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

       UpperCamelCase										=  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_)							->      None:
       UpperCamelCase										=  self.convert_tokens_to_ids(lowerCamelCase_)
       UpperCamelCase										=  [self.cur_lang_code_id]
       UpperCamelCase										=  [self.eos_token_id]

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

       UpperCamelCase										=  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_)							->      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''')
       UpperCamelCase										=  src_lang
       UpperCamelCase										=  self(lowerCamelCase_					,				add_special_tokens=lowerCamelCase_					,				return_tensors=lowerCamelCase_					,				**lowerCamelCase_)
       UpperCamelCase										=  self.convert_tokens_to_ids(lowerCamelCase_)
       UpperCamelCase										=  tgt_lang_id
       return inputs







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_					,				lowerCamelCase_ = 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(lowerCamelCase_):
           logger.error(F'Vocabulary path ({save_directory}) should be a directory')
           return
       UpperCamelCase										=  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 							snake_case_ :







   """simple docstring"""




   def __init__(		self					,				lowerCamelCase_=None)							->      Tuple:
       UpperCamelCase										=  data
       UpperCamelCase										=  None







   def __repr__(		self)							->      Union[str, Any]:
       UpperCamelCase										=  ''''''
       UpperCamelCase										=  self
       while temp:
           string_rep += F'<{temp.data}> ---> '
           UpperCamelCase										=  temp.next
       string_rep += "<END>"
       return string_rep





def     __snake_case   (							_lowercase						):


    """simple docstring"""







    if not elements_list:
        raise Exception('''The Elements List is empty'''						)

    # Set first element as Head
    UpperCamelCase										=  Node(elements_list[0]						)
    UpperCamelCase										=  head
    # Loop through elements from position 1
    for data in elements_list[1:]:
        UpperCamelCase										=  Node(_lowercase						)
        UpperCamelCase										=  current.next
    return head


SCREAMING_SNAKE_CASE_      =					[1, 3, 5, 32, 44, 12, 43]
print(f'List: {list_data}')
print('Creating Linked List from List.')
SCREAMING_SNAKE_CASE_      =					make_linked_list(list_data)
print('Linked List:')


print(linked_list)