





from . import (
    albert,
    align,
    altclip,
    audio_spectrogram_transformer,
    auto,
    autoformer,
    bark,
    bart,
    barthez,
    bartpho,
    beit,
    bert,
    bert_generation,
    bert_japanese,
    bertweet,
    big_bird,
    bigbird_pegasus,
    biogpt,
    bit,
    blenderbot,
    blenderbot_small,
    blip,
    blip_a,
    bloom,
    bridgetower,
    byta,
    camembert,
    canine,
    chinese_clip,
    clap,
    clip,
    clipseg,
    codegen,
    conditional_detr,
    convbert,
    convnext,
    convnextva,
    cpm,
    cpmant,
    ctrl,
    cvt,
    dataavec,
    deberta,
    deberta_va,
    decision_transformer,
    deformable_detr,
    deit,
    deprecated,
    deta,
    detr,
    dialogpt,
    dinat,
    distilbert,
    dit,
    donut,
    dpr,
    dpt,
    efficientformer,
    efficientnet,
    electra,
    encodec,
    encoder_decoder,
    ernie,
    ernie_m,
    esm,
    falcon,
    flaubert,
    flava,
    fnet,
    focalnet,
    fsmt,
    funnel,
    git,
    glpn,
    gpta,
    gpt_bigcode,
    gpt_neo,
    gpt_neox,
    gpt_neox_japanese,
    gpt_swa,
    gptj,
    gptsan_japanese,
    graphormer,
    groupvit,
    herbert,
    hubert,
    ibert,
    imagegpt,
    informer,
    instructblip,
    jukebox,
    layoutlm,
    layoutlmva,
    layoutlmva,
    layoutxlm,
    led,
    levit,
    lilt,
    llama,
    longformer,
    longta,
    luke,
    lxmert,
    mam_aaa,
    marian,
    markuplm,
    maskaformer,
    maskformer,
    mbart,
    mbartaa,
    mega,
    megatron_bert,
    megatron_gpta,
    mgp_str,
    mluke,
    mobilebert,
    mobilenet_va,
    mobilenet_va,
    mobilevit,
    mobilevitva,
    mpnet,
    mra,
    mta,
    musicgen,
    mvp,
    nat,
    nezha,
    nllb,
    nllb_moe,
    nystromformer,
    oneformer,
    open_llama,
    openai,
    opt,
    owlvit,
    pegasus,
    pegasus_x,
    perceiver,
    phobert,
    pixastruct,
    plbart,
    poolformer,
    prophetnet,
    qdqbert,
    rag,
    realm,
    reformer,
    regnet,
    rembert,
    resnet,
    roberta,
    roberta_prelayernorm,
    roc_bert,
    roformer,
    rwkv,
    sam,
    segformer,
    sew,
    sew_d,
    speech_encoder_decoder,
    speech_to_text,
    speech_to_text_a,
    speechta,
    splinter,
    squeezebert,
    swiftformer,
    swin,
    swinasr,
    swinva,
    switch_transformers,
    ta,
    table_transformer,
    tapas,
    time_series_transformer,
    timesformer,
    timm_backbone,
    transfo_xl,
    trocr,
    tvlt,
    umta,
    unispeech,
    unispeech_sat,
    upernet,
    videomae,
    vilt,
    vision_encoder_decoder,
    vision_text_dual_encoder,
    visual_bert,
    vit,
    vit_hybrid,
    vit_mae,
    vit_msn,
    vivit,
    wavaveca,
    wavaveca_conformer,
    wavaveca_phoneme,
    wavaveca_with_lm,
    wavlm,
    whisper,
    x_clip,
    xglm,
    xlm,
    xlm_prophetnet,
    xlm_roberta,
    xlm_roberta_xl,
    xlnet,
    xmod,
    yolos,
    yoso,
)






"""simple docstring"""






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


A 			=  logging.get_logger(__name__)




class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					def __init__(						self	,			**_UpperCAmelCase     ):
									requires_backends(self	,			['''bs4''']     )
									super().__init__(**_UpperCAmelCase     )







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						Tuple			       =  []
									__a :						Dict			       =  []
									__a :						int			       =  element if element.name else element.parent
									for parent in child.parents:  # type: bs4.element.Tag
													__a :						Dict			       =  parent.find_all(child.name	,			recursive=_UpperCAmelCase     )
													xpath_tags.append(child.name     )
													xpath_subscripts.append(
													    0 if 1 == len(_UpperCAmelCase     ) else next(i for i, s in enumerate(_UpperCAmelCase	,			1     ) if s is child     )     )
													__a :						Any			       =  parent
									xpath_tags.reverse()
									xpath_subscripts.reverse()
									return xpath_tags, xpath_subscripts







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						Dict			       =  BeautifulSoup(_UpperCAmelCase	,			'''html.parser'''     )

									__a :						Any			       =  []
									__a :						Dict			       =  []
									__a :						Optional[int]			       =  []

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

																	__a :						Dict			       =  html.unescape(_UpperCAmelCase     ).strip()
																	if not text_in_this_tag:
																					continue

																	all_doc_strings.append(_UpperCAmelCase     )

																	__a       ,						__a :						List[Any]			       =  self.xpath_soup(_UpperCAmelCase     )
																	stringaxtag_seq.append(_UpperCAmelCase     )
																	stringaxsubs_seq.append(_UpperCAmelCase     )

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

									return all_doc_strings, stringaxtag_seq, stringaxsubs_seq







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									__a :						List[str]			       =  ''''''
									for tagname, subs in zip(_UpperCAmelCase	,			_UpperCAmelCase     ):
													xpath += f"""/{tagname}"""
													if subs != 0:
																	xpath += f"""[{subs}]"""
									return xpath







					def __call__(						self	,			_UpperCAmelCase     ):
									__a :						Optional[Any]			       =  False

									# Check that strings has a valid type
									if isinstance(_UpperCAmelCase	,			_UpperCAmelCase     ):
													__a :						str			       =  True
									elif isinstance(_UpperCAmelCase	,			(list, tuple)     ):
													if len(_UpperCAmelCase     ) == 0 or isinstance(html_strings[0]	,			_UpperCAmelCase     ):
																	__a :						Optional[Any]			       =  True

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

									__a :						List[str]			       =  bool(isinstance(_UpperCAmelCase	,			(list, tuple)     ) and (isinstance(html_strings[0]	,			_UpperCAmelCase     ))     )

									if not is_batched:
													__a :						List[Any]			       =  [html_strings]

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

									# return as Dict
									__a :						int			       =  {'''nodes''': nodes, '''xpaths''': xpaths}
									__a :						Any			       =  BatchFeature(data=_UpperCAmelCase	,			tensor_type=_UpperCAmelCase     )

									return encoded_inputs