





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


lowercase      :       Any									=  logging.get_logger(__name__)





class  A__    (							__UpperCAmelCase	):




   """simple docstring"""



   def __init__(					self					,  **lowercase)			->						Optional[Any]:







          '''simple docstring'''

          requires_backends(self					,  ['bs4'])
          super().__init__(**lowercase)

   def 							__lowercase		(					self					,  lowercase)			->						List[str]:







          '''simple docstring'''

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

   def 							__lowercase		(					self					,  lowercase)			->						str:







          '''simple docstring'''

          a__						:	int =				BeautifulSoup(lowercase					,  'html.parser')

          a__						:	List[str] =				[]
          a__						:	str =				[]
          a__						:	List[Any] =				[]

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

                        a__						:	Union[str, Any] =				html.unescape(lowercase).strip()
                        if not text_in_this_tag:
                               continue

                        all_doc_strings.append(lowercase)

                        a__ ,							a__						:	List[str] =				self.xpath_soup(lowercase)
                        stringaxtag_seq.append(lowercase)
                        stringaxsubs_seq.append(lowercase)

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

          return all_doc_strings, stringaxtag_seq, stringaxsubs_seq

   def 							__lowercase		(					self					,  lowercase					,  lowercase)			->						Union[str, Any]:







          '''simple docstring'''

          a__						:	int =				''
          for tagname, subs in zip(lowercase					,  lowercase):
                 xpath += F'/{tagname}'
                 if subs != 0:
                        xpath += F'[{subs}]'
          return xpath

   def __call__(					self					,  lowercase)			->						BatchFeature:







          '''simple docstring'''

          a__						:	List[str] =				False

          # Check that strings has a valid type
          if isinstance(lowercase					,  lowercase):
                 a__						:	Optional[int] =				True
          elif isinstance(lowercase					,  (list, tuple)):
                 if len(lowercase) == 0 or isinstance(html_strings[0]					,  lowercase):
                        a__						:	Dict =				True

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

          a__						:	Dict =				bool(isinstance(lowercase					,  (list, tuple)) and (isinstance(html_strings[0]					,  lowercase)))

          if not is_batched:
                 a__						:	Tuple =				[html_strings]

          # Get nodes + xpaths
          a__						:	Optional[int] =				[]
          a__						:	int =				[]
          for html_string in html_strings:
                 a__ ,							a__ ,							a__						:	int =				self.get_three_from_single(lowercase)
                 nodes.append(lowercase)
                 a__						:	Optional[Any] =				[]
                 for node, tag_list, sub_list in zip(lowercase					,  lowercase					,  lowercase):
                        a__						:	List[Any] =				self.construct_xpath(lowercase					,  lowercase)
                        xpath_strings.append(lowercase)
                 xpaths.append(lowercase)

          # return as Dict
          a__						:	Dict =				{'nodes': nodes, 'xpaths': xpaths}
          a__						:	int =				BatchFeature(data=lowercase					,  tensor_type=lowercase)

          return encoded_inputs









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase      :       List[Any]									=  {
    """configuration_nllb_moe""": [
        """NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """NllbMoeConfig""",
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowercase      :       Dict									=  [
        """NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """NllbMoeForConditionalGeneration""",
        """NllbMoeModel""",
        """NllbMoePreTrainedModel""",
        """NllbMoeTop2Router""",
        """NllbMoeSparseMLP""",
    ]


if TYPE_CHECKING:
    from .configuration_nllb_moe import (
        NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
        NllbMoeConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_nllb_moe import (
            NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
            NllbMoeForConditionalGeneration,
            NllbMoeModel,
            NllbMoePreTrainedModel,
            NllbMoeSparseMLP,
            NllbMoeTopaRouter,
        )


else:
    import sys

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


