

from typing import List, Optional, Tuple

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


snake_case_			  = logging.get_logger(__name__)

snake_case_			  = {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

snake_case_			  = {
    "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"
    },
}

snake_case_			  = {"allegro/herbert-base-cased": 514}
snake_case_			  = {}


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):
    __lowerCamelCase						:       Optional[Any]														=     VOCAB_FILES_NAMES
    __lowerCamelCase						:       List[str]														=     PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase						:       Union[str, Any]														=     PRETRAINED_INIT_CONFIGURATION
    __lowerCamelCase						:       str														=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase						:       Optional[int]														=     HerbertTokenizer





    def __init__(      self						,   a=None						,   a=None						,   a=None						,   a="<s>"						,   a="<unk>"						,   a="<pad>"						,   a="<mask>"						,   a="</s>"						,   **a						,   ):
         super().__init__(
             _lowerCAmelCase						,   _lowerCAmelCase						,   tokenizer_file=_lowerCAmelCase						,   cls_token=_lowerCAmelCase						,   unk_token=_lowerCAmelCase						,   pad_token=_lowerCAmelCase						,   mask_token=_lowerCAmelCase						,   sep_token=_lowerCAmelCase						,   **_lowerCAmelCase						,   )





    def       snake_case_				(      self						,   a						,   a = None):
         lowercase__    :   Dict      =       [self.cls_token_id]
         lowercase__    :   List[str]      =       [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       snake_case_				(      self						,   a						,   a = None						,   a = 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 None:
              return [1] + ([0] * len(_lowerCAmelCase)) + [1]
         return [1] + ([0] * len(_lowerCAmelCase)) + [1] + ([0] * len(_lowerCAmelCase)) + [1]





    def       snake_case_				(      self						,   a						,   a = None):
         lowercase__    :   List[Any]      =       [self.sep_token_id]
         lowercase__    :   Optional[int]      =       [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						,   a						,   a = None):
         lowercase__    :   int      =       self._tokenizer.model.save(_lowerCAmelCase						,   name=_lowerCAmelCase)
         return tuple(_lowerCAmelCase)







from typing import TYPE_CHECKING

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


_UpperCAmelCase		:  int	=   {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  List[str]	=   [
         "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SwinForImageClassification",
         "SwinForMaskedImageModeling",
         "SwinModel",
         "SwinPreTrainedModel",
         "SwinBackbone",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  int	=   [
         "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFSwinForImageClassification",
         "TFSwinForMaskedImageModeling",
         "TFSwinModel",
         "TFSwinPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_swin import (
              SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwinBackbone,
              SwinForImageClassification,
              SwinForMaskedImageModeling,
              SwinModel,
              SwinPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_swin import (
              TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFSwinForImageClassification,
              TFSwinForMaskedImageModeling,
              TFSwinModel,
              TFSwinPreTrainedModel,
          )

else:
     import sys

     _UpperCAmelCase		:  int	=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



