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:
     __snake_case			      =    None


__snake_case			      =    logging.get_logger(__name__)

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

__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'''
        ),
    },
}

__snake_case			      =    {
    '''facebook/mbart-large-50-one-to-many-mmt''': 10_24,
}

# fmt: off
__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__   ):
 __lowerCamelCase    :   Union[str, Any]     =      VOCAB_FILES_NAMES
 __lowerCamelCase    :   int     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCamelCase    :   Any     =      PRETRAINED_VOCAB_FILES_MAP
 __lowerCamelCase    :   Union[str, Any]     =      ["""input_ids""", """attention_mask"""]
 __lowerCamelCase    :   Optional[Any]     =      MBartaaTokenizer

 __lowerCamelCase    :   List[int]     =      []
 __lowerCamelCase    :   List[int]     =      []
 def __init__(  self		,   snake_case__=None		,   snake_case__=None		,   snake_case__=None		,   snake_case__=None		,   snake_case__="</s>"		,   snake_case__="</s>"		,   snake_case__="<s>"		,   snake_case__="<unk>"		,   snake_case__="<pad>"		,   snake_case__="<mask>"		,   **snake_case__		,   )	->							Union[str, Any]:
       '''simple docstring'''





       UpperCAmelCase    : List[Any]      =AddedToken(snake_case__		,   lstrip=snake_case__		,   rstrip=snake_case__						) if isinstance(snake_case__		,   snake_case__						) else mask_token

       UpperCAmelCase    : Dict      =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__(
           snake_case__		,   src_lang=snake_case__		,   tgt_lang=snake_case__		,   tokenizer_file=snake_case__		,   eos_token=snake_case__		,   sep_token=snake_case__		,   cls_token=snake_case__		,   unk_token=snake_case__		,   pad_token=snake_case__		,   mask_token=snake_case__		,   **snake_case__		,   )

       UpperCAmelCase    : int      =vocab_file
       UpperCAmelCase    : List[str]      =False if not self.vocab_file else True

       UpperCAmelCase    : Union[str, Any]      ={
           lang_code: self.convert_tokens_to_ids(snake_case__						) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }

       UpperCAmelCase    : Any      =src_lang if src_lang is not None else '''en_XX'''
       UpperCAmelCase    : Any      =tgt_lang
       UpperCAmelCase    : Optional[int]      =self.lang_code_to_id[self._src_lang]
       self.set_src_lang_special_tokens(self._src_lang						)
 @property
 def 	UpperCAmelCase__       (  self						)	->							str:
       '''simple docstring'''





       return self._src_lang
 @src_lang.setter
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							None:
       '''simple docstring'''





       UpperCAmelCase    : int      =new_src_lang
       self.set_src_lang_special_tokens(self._src_lang						)
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__ = None						)	->							List[int]:
       '''simple docstring'''





       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		,   snake_case__		,   snake_case__ = "en_XX"		,   snake_case__ = None		,   snake_case__ = "ro_RO"		,   **snake_case__		,   )	->							BatchEncoding:
       '''simple docstring'''





       UpperCAmelCase    : Union[str, Any]      =src_lang
       UpperCAmelCase    : Optional[int]      =tgt_lang
       return super().prepare_seqaseq_batch(snake_case__		,   snake_case__		,   **snake_case__						)
 def 	UpperCAmelCase__       (  self						)	->							Dict:
       '''simple docstring'''





       return self.set_src_lang_special_tokens(self.src_lang						)
 def 	UpperCAmelCase__       (  self						)	->							str:
       '''simple docstring'''





       return self.set_tgt_lang_special_tokens(self.tgt_lang						)
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							None:
       '''simple docstring'''





       UpperCAmelCase    : Optional[int]      =self.convert_tokens_to_ids(snake_case__						)
       UpperCAmelCase    : List[Any]      =[self.cur_lang_code_id]
       UpperCAmelCase    : Tuple      =[self.eos_token_id]

       UpperCAmelCase    : List[str]      =self.convert_ids_to_tokens(self.prefix_tokens						)
       UpperCAmelCase    : int      =self.convert_ids_to_tokens(self.suffix_tokens						)

       UpperCAmelCase    : List[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 	UpperCAmelCase__       (  self		,   snake_case__						)	->							None:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      =self.convert_tokens_to_ids(snake_case__						)
       UpperCAmelCase    : Tuple      =[self.cur_lang_code_id]
       UpperCAmelCase    : List[Any]      =[self.eos_token_id]

       UpperCAmelCase    : List[Any]      =self.convert_ids_to_tokens(self.prefix_tokens						)
       UpperCAmelCase    : Union[str, Any]      =self.convert_ids_to_tokens(self.suffix_tokens						)

       UpperCAmelCase    : Tuple      =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		,   snake_case__		,   snake_case__		,   snake_case__		,   snake_case__		,   **snake_case__						)	->							List[Any]:
       '''simple docstring'''





       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    : str      =src_lang
       UpperCAmelCase    : Dict      =self(snake_case__		,   add_special_tokens=snake_case__		,   return_tensors=snake_case__		,   **snake_case__						)
       UpperCAmelCase    : int      =self.convert_tokens_to_ids(snake_case__						)
       UpperCAmelCase    : Any      =tgt_lang_id
       return inputs






 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__ = None						)	->							Tuple[str]:
       '''simple docstring'''





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

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

       return (out_vocab_file,)

def   lowerCAmelCase_ (				__lowerCAmelCase		,					__lowerCAmelCase						)->  list[tuple[int, int, int]]:






      '''simple docstring'''





      UpperCAmelCase    : List[Any]      =sorted(__lowerCAmelCase		,					key=lambda __lowerCAmelCase						: edge[2]						)

      UpperCAmelCase    : Union[str, Any]      =list(range(__lowerCAmelCase						)						)

      def find_parent(__lowerCAmelCase						):
            if i != parent[i]:
                  UpperCAmelCase    : Optional[int]      =find_parent(parent[i]						)
            return parent[i]

      UpperCAmelCase    : Optional[Any]      =0
      UpperCAmelCase    : List[str]      =[]

      for edge in edges:
            UpperCAmelCase    : Dict      =find_parent(edge[0]						)
            UpperCAmelCase    : Optional[Any]      =find_parent(edge[1]						)
            if parent_a != parent_b:
                  minimum_spanning_tree_cost += edge[2]
                  minimum_spanning_tree.append(__lowerCAmelCase						)
                  UpperCAmelCase    : Optional[Any]      =parent_b

      return minimum_spanning_tree


if __name__ == "__main__":  # pragma: no cover
     __snake_case      ,  __snake_case			      =    list(map(int, input().strip().split()))
     __snake_case			      =    []

     for _ in range(num_edges):
          __snake_case      ,  __snake_case      ,  __snake_case			      =    (int(x) for x in input().strip().split())
          edges.append((nodea, nodea, cost))

     kruskal(num_nodes, edges)
