
'''simple docstring'''

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

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
   from .tokenization_deberta_va import DebertaVaTokenizer
else:
   lowerCAmelCase_			:			List[str]			   =     None

lowerCAmelCase_			:			List[str]			   =     logging.get_logger(__name__)

lowerCAmelCase_			:			List[str]			   =     {'''vocab_file''': '''spm.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase_			:			Any			   =     {
    '''vocab_file''': {
        '''microsoft/deberta-v2-xlarge''': '''https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xxlarge''': '''https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'''
        ),
        '''microsoft/deberta-v2-xxlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'''
        ),
    }
}

lowerCAmelCase_			:			Union[str, Any]			   =     {
    '''microsoft/deberta-v2-xlarge''': 512,
    '''microsoft/deberta-v2-xxlarge''': 512,
    '''microsoft/deberta-v2-xlarge-mnli''': 512,
    '''microsoft/deberta-v2-xxlarge-mnli''': 512,
}

lowerCAmelCase_			:			Optional[int]			   =     {
    '''microsoft/deberta-v2-xlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xlarge-mnli''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge-mnli''': {'''do_lower_case''': False},
}







class 	__lowerCAmelCase    (  __a				):
     snake_case   :    int							      =      VOCAB_FILES_NAMES
     snake_case   :    Any							      =      PRETRAINED_VOCAB_FILES_MAP
     snake_case   :    Tuple							      =      PRETRAINED_INIT_CONFIGURATION
     snake_case   :    Any							      =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     snake_case   :    Optional[int]							      =      DebertaVaTokenizer



     def __init__(self						,	lowerCAmelCase__=None						,	lowerCAmelCase__=None						,	lowerCAmelCase__=False						,	lowerCAmelCase__=False						,	lowerCAmelCase__="[CLS]"						,	lowerCAmelCase__="[SEP]"						,	lowerCAmelCase__="[UNK]"						,	lowerCAmelCase__="[SEP]"						,	lowerCAmelCase__="[PAD]"						,	lowerCAmelCase__="[CLS]"						,	lowerCAmelCase__="[MASK]"						,	**lowerCAmelCase__						,	):
          super().__init__(
              lowerCAmelCase__						,	tokenizer_file=lowerCAmelCase__						,	do_lower_case=lowerCAmelCase__						,	bos_token=lowerCAmelCase__						,	eos_token=lowerCAmelCase__						,	unk_token=lowerCAmelCase__						,	sep_token=lowerCAmelCase__						,	pad_token=lowerCAmelCase__						,	cls_token=lowerCAmelCase__						,	mask_token=lowerCAmelCase__						,	split_by_punct=lowerCAmelCase__						,	**lowerCAmelCase__						,	)

          _UpperCAmelCase					:  int         =    do_lower_case
          _UpperCAmelCase					:  Any         =    split_by_punct
          _UpperCAmelCase					:  List[Any]         =    vocab_file
          _UpperCAmelCase					:  List[str]         =    False if not self.vocab_file else True



     def     snake_case_ (self						,	lowerCAmelCase__						,	lowerCAmelCase__=None	):

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



     def     snake_case_ (self						,	lowerCAmelCase__						,	lowerCAmelCase__=None						,	lowerCAmelCase__=False	):

          if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=lowerCAmelCase__						,	token_ids_a=lowerCAmelCase__						,	already_has_special_tokens=lowerCAmelCase__	)

          if token_ids_a is not None:
               return [1] + ([0] * len(lowerCAmelCase__	)) + [1] + ([0] * len(lowerCAmelCase__	)) + [1]
          return [1] + ([0] * len(lowerCAmelCase__	)) + [1]



     def     snake_case_ (self						,	lowerCAmelCase__						,	lowerCAmelCase__=None	):
          _UpperCAmelCase					:  int         =    [self.sep_token_id]
          _UpperCAmelCase					:  Optional[Any]         =    [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	) * [0] + len(token_ids_a + sep	) * [1]



     def     snake_case_ (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
          _UpperCAmelCase					:  str         =    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'''

import io
import json
import subprocess


lowerCAmelCase_			:			Tuple			   =     [
    ['''en''', '''ru'''],
    ['''ru''', '''en'''],
    ['''en''', '''de'''],
    ['''de''', '''en'''],
]

lowerCAmelCase_			:			str			   =     8







def __A  (    lowerCAmelCase_ ,       lowerCAmelCase_       ):
     _UpperCAmelCase					:  Union[str, Any]         =    {}
     for src, tgt in pairs:
          _UpperCAmelCase					:  Union[str, Any]         =    f"{src}-{tgt}"
          _UpperCAmelCase					:  List[Any]         =    f"sacrebleu -t wmt19 -l {pair} --echo src".split()
          _UpperCAmelCase					:  List[str]         =    subprocess.run(lowerCAmelCase_ ,       stdout=subprocess.PIPE       ).stdout.decode("""utf-8"""       ).splitlines()
          _UpperCAmelCase					:  str         =    f"sacrebleu -t wmt19 -l {pair} --echo ref".split()
          _UpperCAmelCase					:  List[Any]         =    subprocess.run(lowerCAmelCase_ ,       stdout=subprocess.PIPE       ).stdout.decode("""utf-8"""       ).splitlines()
          _UpperCAmelCase					:  int         =    {"""src""": src_lines[:n_objs], """tgt""": tgt_lines[:n_objs]}
     return text


lowerCAmelCase_			:			Optional[int]			   =     get_all_data(pairs, n_objs)
lowerCAmelCase_			:			str			   =     '''./fsmt_val_data.json'''
with io.open(filename, '''w''', encoding='''utf-8''') as f:
   lowerCAmelCase_			:			Tuple			   =     json.dump(text, f, indent=2, ensure_ascii=False)


