


import html

from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends


if is_bsa_available():
    import bsa
    from bsa import BeautifulSoup


__UpperCamelCase    :						Any     =							logging.get_logger(__name__)



class 							_UpperCamelCase (						A						):

   '''simple docstring'''







   def __init__(  self  : int       ,  **_lowerCamelCase  : str							):






         '''simple docstring'''



         requires_backends(self       ,  ["""bs4"""]							)
         super().__init__(**_lowerCamelCase							)

   def   _snake_case    (  self  : List[str]       ,  _lowerCamelCase  : Dict							):






         '''simple docstring'''



         __lowerCamelCase     :      int       						=						[]
         __lowerCamelCase     :      int       						=						[]
         __lowerCamelCase     :      List[Any]       						=						element if element.name else element.parent
         for parent in child.parents:  # type: bs4.element.Tag
               __lowerCamelCase     :      Union[str, Any]       						=						parent.find_all(child.name       ,  recursive=_lowerCamelCase							)
               xpath_tags.append(child.name							)
               xpath_subscripts.append(
                   0 if 1 == len(_lowerCamelCase							) else next(i for i, s in enumerate(_lowerCamelCase       ,  1							) if s is child							)							)
               __lowerCamelCase     :      Optional[Any]       						=						parent
         xpath_tags.reverse()
         xpath_subscripts.reverse()
         return xpath_tags, xpath_subscripts

   def   _snake_case    (  self  : List[Any]       ,  _lowerCamelCase  : Optional[Any]							):






         '''simple docstring'''



         __lowerCamelCase     :      Dict       						=						BeautifulSoup(_lowerCamelCase       ,  """html.parser"""							)

         __lowerCamelCase     :      Tuple       						=						[]
         __lowerCamelCase     :      List[Any]       						=						[]
         __lowerCamelCase     :      Union[str, Any]       						=						[]

         for element in html_code.descendants:
               if type(_lowerCamelCase							) == bsa.element.NavigableString:
                     if type(element.parent							) != bsa.element.Tag:
                           continue

                     __lowerCamelCase     :      int       						=						html.unescape(_lowerCamelCase							).strip()
                     if not text_in_this_tag:
                           continue

                     all_doc_strings.append(_lowerCamelCase							)

                     __lowerCamelCase						, __lowerCamelCase     :      Union[str, Any]       						=						self.xpath_soup(_lowerCamelCase							)
                     stringaxtag_seq.append(_lowerCamelCase							)
                     stringaxsubs_seq.append(_lowerCamelCase							)

         if len(_lowerCamelCase							) != len(_lowerCamelCase							):
               raise ValueError("""Number of doc strings and xtags does not correspond"""							)
         if len(_lowerCamelCase							) != len(_lowerCamelCase							):
               raise ValueError("""Number of doc strings and xsubs does not correspond"""							)

         return all_doc_strings, stringaxtag_seq, stringaxsubs_seq

   def   _snake_case    (  self  : Optional[int]       ,  _lowerCamelCase  : Any       ,  _lowerCamelCase  : List[str]							):






         '''simple docstring'''



         __lowerCamelCase     :      Optional[int]       						=						""""""
         for tagname, subs in zip(_lowerCamelCase       ,  _lowerCamelCase							):
               xpath += F"""/{tagname}"""
               if subs != 0:
                     xpath += F"""[{subs}]"""
         return xpath


   def __call__(  self  : Tuple       ,  _lowerCamelCase  : List[str]							):






         '''simple docstring'''



         __lowerCamelCase     :      Dict       						=						False

         # Check that strings has a valid type
         if isinstance(_lowerCamelCase       ,  _lowerCamelCase							):
               __lowerCamelCase     :      Dict       						=						True
         elif isinstance(_lowerCamelCase       ,  (list, tuple)							):
               if len(_lowerCamelCase							) == 0 or isinstance(html_strings[0]       ,  _lowerCamelCase							):
                     __lowerCamelCase     :      Tuple       						=						True

         if not valid_strings:
               raise ValueError(
                   """HTML strings must of type `str`, `List[str]` (batch of examples), """
                   F"""but is of type {type(_lowerCamelCase							)}."""							)

         __lowerCamelCase     :      str       						=						bool(isinstance(_lowerCamelCase       ,  (list, tuple)							) and (isinstance(html_strings[0]       ,  _lowerCamelCase							))							)

         if not is_batched:
               __lowerCamelCase     :      Dict       						=						[html_strings]

         # Get nodes + xpaths
         __lowerCamelCase     :      Optional[int]       						=						[]
         __lowerCamelCase     :      Any       						=						[]
         for html_string in html_strings:
               __lowerCamelCase						, __lowerCamelCase						, __lowerCamelCase     :      Dict       						=						self.get_three_from_single(_lowerCamelCase							)
               nodes.append(_lowerCamelCase							)
               __lowerCamelCase     :      Union[str, Any]       						=						[]
               for node, tag_list, sub_list in zip(_lowerCamelCase       ,  _lowerCamelCase       ,  _lowerCamelCase							):
                     __lowerCamelCase     :      Tuple       						=						self.construct_xpath(_lowerCamelCase       ,  _lowerCamelCase							)
                     xpath_strings.append(_lowerCamelCase							)
               xpaths.append(_lowerCamelCase							)

         # return as Dict
         __lowerCamelCase     :      Tuple       						=						{"""nodes""": nodes, """xpaths""": xpaths}
         __lowerCamelCase     :      Any       						=						BatchFeature(data=_lowerCamelCase       ,  tensor_type=_lowerCamelCase							)

         return encoded_inputs







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCamelCase    :						Optional[Any]     =							{
    'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						List[Any]     =							[
        'SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST',
        'Swinv2ForImageClassification',
        'Swinv2ForMaskedImageModeling',
        'Swinv2Model',
        'Swinv2PreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_swinva import (
            SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            SwinvaForImageClassification,
            SwinvaForMaskedImageModeling,
            SwinvaModel,
            SwinvaPreTrainedModel,
        )


else:
    import sys

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



