
'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase_       :   Any   =       {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig', 'DeiTOnnxConfig']}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCAmelCase_       :   Dict   =       ['DeiTFeatureExtractor']
      UpperCAmelCase_       :   Any   =       ['DeiTImageProcessor']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCAmelCase_       :   Optional[int]   =       [
          'DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'DeiTForImageClassification',
          'DeiTForImageClassificationWithTeacher',
          'DeiTForMaskedImageModeling',
          'DeiTModel',
          'DeiTPreTrainedModel',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCAmelCase_       :   Union[str, Any]   =       [
          'TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TFDeiTForImageClassification',
          'TFDeiTForImageClassificationWithTeacher',
          'TFDeiTForMaskedImageModeling',
          'TFDeiTModel',
          'TFDeiTPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_deit import DeiTFeatureExtractor
            from .image_processing_deit import DeiTImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_deit import (
                DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                DeiTForImageClassification,
                DeiTForImageClassificationWithTeacher,
                DeiTForMaskedImageModeling,
                DeiTModel,
                DeiTPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_deit import (
                TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFDeiTForImageClassification,
                TFDeiTForImageClassificationWithTeacher,
                TFDeiTForMaskedImageModeling,
                TFDeiTModel,
                TFDeiTPreTrainedModel,
            )


else:
      import sys

      UpperCAmelCase_       :   Optional[Any]   =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

'''simple docstring'''






from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


UpperCAmelCase_       :   Union[str, Any]   =       logging.get_logger(__name__)

UpperCAmelCase_       :   Optional[int]   =       {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

UpperCAmelCase_       :   Union[str, Any]   =       {
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

UpperCAmelCase_       :   Union[str, Any]   =       {
    'facebook/blenderbot_small-90M': 512,
}

class  UpperCAmelCase__						(       A ):
    lowerCAmelCase_				    =		VOCAB_FILES_NAMES
    lowerCAmelCase_				    =		PRETRAINED_VOCAB_FILES_MAP
    lowerCAmelCase_				    =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCAmelCase_				    =		BlenderbotSmallTokenizer



    def __init__(	self      :       Optional[Any],__A      :       str=None,__A      :       str=None,__A      :       int="<|endoftext|>",__A      :       List[str]="<|endoftext|>",__A      :       Optional[Any]="<|endoftext|>",__A      :       Union[str, Any]=False,__A      :       List[Any]=True,**__A      :       str,):
          super().__init__(
              ByteLevelBPETokenizer(
                  vocab=__A,merges=__A,add_prefix_space=__A,trim_offsets=__A,),bos_token=__A,eos_token=__A,unk_token=__A,**__A,)
          _lowerCamelCase				:   List[Any]								=   add_prefix_space



    def   lowerCamelCase_  (	self      :       Any,__A      :       Optional[Any],__A      :       Optional[int]=None     ):
          _lowerCamelCase				:   Any								=   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
                return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



    def   lowerCamelCase_  (	self      :       List[Any],__A      :       List[int],__A      :       Optional[List[int]] = None     ):
          _lowerCamelCase				:   Any								=   [self.sep_token_id]
          _lowerCamelCase				:   Union[str, 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 + sep + token_ids_a + sep     ) * [0]