


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

lowerCamelCase							:       Optional[Any]  						=     {'vocab_file': 'spm.model', 'tokenizer_file': 'tokenizer.json'}

lowerCamelCase							:       List[str]  						=     {
    '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							:       int  						=     {
    'microsoft/deberta-v2-xlarge': 512,
    'microsoft/deberta-v2-xxlarge': 512,
    'microsoft/deberta-v2-xlarge-mnli': 512,
    'microsoft/deberta-v2-xxlarge-mnli': 512,
}

lowerCamelCase							:       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						(lowerCAmelCase__					):





      '''simple docstring'''






      lowerCAmelCase__ :					Union[str, Any]   =							VOCAB_FILES_NAMES
      lowerCAmelCase__ :					List[Any]   =							PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__ :					Optional[Any]   =							PRETRAINED_INIT_CONFIGURATION
      lowerCAmelCase__ :					str   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__ :					str   =							DebertaVaTokenizer



      def __init__(self   :   int       ,						UpperCamelCase   :   Dict=None       ,						UpperCamelCase   :   str=None       ,						UpperCamelCase   :   str=False       ,						UpperCamelCase   :   Dict=False       ,						UpperCamelCase   :   Tuple="[CLS]"       ,						UpperCamelCase   :   Optional[int]="[SEP]"       ,						UpperCamelCase   :   Union[str, Any]="[UNK]"       ,						UpperCamelCase   :   Optional[int]="[SEP]"       ,						UpperCamelCase   :   Any="[PAD]"       ,						UpperCamelCase   :   Dict="[CLS]"       ,						UpperCamelCase   :   Tuple="[MASK]"       ,						**UpperCamelCase   :   Any       ,						):

             '''simple docstring'''







             super().__init__(
                 _A       ,						tokenizer_file=_A       ,						do_lower_case=_A       ,						bos_token=_A       ,						eos_token=_A       ,						unk_token=_A       ,						sep_token=_A       ,						pad_token=_A       ,						cls_token=_A       ,						mask_token=_A       ,						split_by_punct=_A       ,						**_A       ,						)

             lowercase__				      =			do_lower_case
             lowercase__				      =			split_by_punct
             lowercase__				      =			vocab_file
             lowercase__				      =			False if not self.vocab_file else True



      def 				UpperCamelCase__		(self   :   List[Any]       ,						UpperCamelCase   :   int       ,						UpperCamelCase   :   List[Any]=None			):

             '''simple docstring'''







             if token_ids_a is None:
                    return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
             lowercase__				      =			[self.cls_token_id]
             lowercase__				      =			[self.sep_token_id]
             return cls + token_ids_a + sep + token_ids_a + sep



      def 				UpperCamelCase__		(self   :   Optional[int]       ,						UpperCamelCase   :   Optional[int]       ,						UpperCamelCase   :   Any=None       ,						UpperCamelCase   :   Union[str, Any]=False			):

             '''simple docstring'''







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

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



      def 				UpperCamelCase__		(self   :   Optional[Any]       ,						UpperCamelCase   :   List[str]       ,						UpperCamelCase   :   Tuple=None			):

             '''simple docstring'''







             lowercase__				      =			[self.sep_token_id]
             lowercase__				      =			[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 				UpperCamelCase__		(self   :   Union[str, Any]       ,						UpperCamelCase   :   str       ,						UpperCamelCase   :   Optional[str] = None			):

             '''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(_A			):
                    logger.error(f"Vocabulary path ({save_directory}) should be a directory"			)
                    return
             lowercase__				      =			os.path.join(
                 _A       ,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)

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

             return (out_vocab_file,)








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


lowerCamelCase							:       Tuple  						=     {'configuration_bert_generation': ['BertGenerationConfig']}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:       Union[str, Any]  						=     ['BertGenerationTokenizer']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:       Dict  						=     [
     'BertGenerationDecoder',
     'BertGenerationEncoder',
     'BertGenerationPreTrainedModel',
     'load_tf_weights_in_bert_generation',
 ]


if TYPE_CHECKING:
 from .configuration_bert_generation import BertGenerationConfig

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_bert_generation import BertGenerationTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_bert_generation import (
      BertGenerationDecoder,
      BertGenerationEncoder,
      BertGenerationPreTrainedModel,
      load_tf_weights_in_bert_generation,
  )

else:
 import sys

 lowerCamelCase							:       int  						=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




