





from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


__lowerCamelCase :  Any										=  logging.get_logger(__name__)

__lowerCamelCase :  List[str]										=  {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

__lowerCamelCase :  Tuple										=  {
    """vocab_file""": {
        """allegro/herbert-base-cased""": """https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """allegro/herbert-base-cased""": """https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt"""
    },
}

__lowerCamelCase :  Optional[int]										=  {"""allegro/herbert-base-cased""": 514}
__lowerCamelCase :  Union[str, Any]										=  {}



class       A__     ( lowercase__    ):
      _UpperCAmelCase			:Optional[Any]							=     VOCAB_FILES_NAMES
      _UpperCAmelCase			:Dict							=     PRETRAINED_VOCAB_FILES_MAP
      _UpperCAmelCase			:int							=     PRETRAINED_INIT_CONFIGURATION
      _UpperCAmelCase			:Union[str, Any]							=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _UpperCAmelCase			:List[Any]							=     HerbertTokenizer





      def __init__(				self ,							A_=None ,							A_=None ,							A_=None ,							A_="<s>" ,							A_="<unk>" ,							A_="<pad>" ,							A_="<mask>" ,							A_="</s>" ,							**A_ ,							):
       '''simple docstring'''




       super().__init__(
           A_ ,							A_ ,							tokenizer_file=A_ ,							cls_token=A_ ,							unk_token=A_ ,							pad_token=A_ ,							mask_token=A_ ,							sep_token=A_ ,							**A_ ,							)





      def  __UpperCamelCase(				self ,							A_ ,							A_ = None     ):
       '''simple docstring'''




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

       return cls + token_ids_a + sep + token_ids_a + sep





      def  __UpperCamelCase(				self ,							A_ ,							A_ = None ,							A_ = 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 None:
        return [1] + ([0] * len(A_     )) + [1]
       return [1] + ([0] * len(A_     )) + [1] + ([0] * len(A_     )) + [1]





      def  __UpperCamelCase(				self ,							A_ ,							A_ = None     ):
       '''simple docstring'''




       UpperCamelCase			:      Tuple 			=     [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  __UpperCamelCase(				self ,							A_ ,							A_ = None     ):
       '''simple docstring'''




       UpperCamelCase			:      Tuple 			=     self._tokenizer.model.save(A_ ,							name=A_     )
       return tuple(A_     )







from typing import TYPE_CHECKING

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


__lowerCamelCase :  Union[str, Any]										=  {
    """configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig""", """VisionEncoderDecoderOnnxConfig"""]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase :  Dict										=  ["""VisionEncoderDecoderModel"""]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase :  List[str]										=  ["""TFVisionEncoderDecoderModel"""]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase :  int										=  ["""FlaxVisionEncoderDecoderModel"""]

if TYPE_CHECKING:
    from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
    import sys

    __lowerCamelCase :  str										=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
