

from typing import TYPE_CHECKING

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


_UpperCAmelCase        =				{
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase        =				["""BlipImageProcessor"""]


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase        =				[
         """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """BlipModel""",
         """BlipPreTrainedModel""",
         """BlipForConditionalGeneration""",
         """BlipForQuestionAnswering""",
         """BlipVisionModel""",
         """BlipTextModel""",
         """BlipForImageTextRetrieval""",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase        =				[
         """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TFBlipModel""",
         """TFBlipPreTrainedModel""",
         """TFBlipForConditionalGeneration""",
         """TFBlipForQuestionAnswering""",
         """TFBlipVisionModel""",
         """TFBlipTextModel""",
         """TFBlipForImageTextRetrieval""",
     ]

if TYPE_CHECKING:
     from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
     from .processing_blip import BlipProcessor

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_blip import BlipImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_blip import (
              BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
              BlipForConditionalGeneration,
              BlipForImageTextRetrieval,
              BlipForQuestionAnswering,
              BlipModel,
              BlipPreTrainedModel,
              BlipTextModel,
              BlipVisionModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_blip import (
              TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFBlipForConditionalGeneration,
              TFBlipForImageTextRetrieval,
              TFBlipForQuestionAnswering,
              TFBlipModel,
              TFBlipPreTrainedModel,
              TFBlipTextModel,
              TFBlipVisionModel,
          )

else:
     import sys

     _UpperCAmelCase        =				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








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        =				logging.get_logger(__name__)

_UpperCAmelCase        =				{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

_UpperCAmelCase        =				{
    '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        =				{
    'facebook/blenderbot_small-90M': 5_1_2,
}



class 							_UpperCamelCase					(	lowerCAmelCase_     ):
       _UpperCamelCase				:					Optional[Any]         =   VOCAB_FILES_NAMES
       _UpperCamelCase				:					str         =   PRETRAINED_VOCAB_FILES_MAP
       _UpperCamelCase				:					List[Any]         =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       _UpperCamelCase				:					str         =   BlenderbotSmallTokenizer

       def __init__(		self: Dict					,   _SCREAMING_SNAKE_CASE: Optional[int]=None					,   _SCREAMING_SNAKE_CASE: List[str]=None					,   _SCREAMING_SNAKE_CASE: Optional[int]="<|endoftext|>"					,   _SCREAMING_SNAKE_CASE: List[Any]="<|endoftext|>"					,   _SCREAMING_SNAKE_CASE: List[str]="<|endoftext|>"					,   _SCREAMING_SNAKE_CASE: Optional[Any]=False					,   _SCREAMING_SNAKE_CASE: int=True					,   **_SCREAMING_SNAKE_CASE: Optional[int]					,   )       -> int:




              """simple docstring"""


              super().__init__(
                  ByteLevelBPETokenizer(
                      vocab=_SCREAMING_SNAKE_CASE					,   merges=_SCREAMING_SNAKE_CASE					,   add_prefix_space=_SCREAMING_SNAKE_CASE					,   trim_offsets=_SCREAMING_SNAKE_CASE					,   )					,   bos_token=_SCREAMING_SNAKE_CASE					,   eos_token=_SCREAMING_SNAKE_CASE					,   unk_token=_SCREAMING_SNAKE_CASE					,   **_SCREAMING_SNAKE_CASE					,   )
              UpperCamelCase_          =  add_prefix_space

       def lowercase (		self: Any					,   _SCREAMING_SNAKE_CASE: Any					,   _SCREAMING_SNAKE_CASE: Any=None		)       -> List[str]:




              """simple docstring"""


              UpperCamelCase_          =  [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 lowercase (		self: int					,   _SCREAMING_SNAKE_CASE: List[int]					,   _SCREAMING_SNAKE_CASE: Optional[List[int]] = None		)       -> List[int]:




              """simple docstring"""


              UpperCamelCase_          =  [self.sep_token_id]
              UpperCamelCase_          =  [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]

