






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_ :						Dict      =      logging.get_logger(__name__)

UpperCAmelCase_ :						Any      =      {
    '''kssteven/ibert-roberta-base''': '''https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large''': '''https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large-mnli''': (
        '''https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json'''
    ),
}

class     _SCREAMING_SNAKE_CASE       (			_a      ):
	snake_case__							:     Dict     	=  """ibert"""





	def __init__(		self				:					Dict ,  __lowerCamelCase				:					Dict=30_522 ,  __lowerCamelCase				:					Optional[Any]=768 ,  __lowerCamelCase				:					List[Any]=12 ,  __lowerCamelCase				:					Tuple=12 ,  __lowerCamelCase				:					int=3_072 ,  __lowerCamelCase				:					Union[str, Any]="gelu" ,  __lowerCamelCase				:					List[str]=0.1 ,  __lowerCamelCase				:					str=0.1 ,  __lowerCamelCase				:					str=512 ,  __lowerCamelCase				:					List[str]=2 ,  __lowerCamelCase				:					int=0.02 ,  __lowerCamelCase				:					int=1E-12 ,  __lowerCamelCase				:					Optional[Any]=1 ,  __lowerCamelCase				:					List[Any]=0 ,  __lowerCamelCase				:					Tuple=2 ,  __lowerCamelCase				:					int="absolute" ,  __lowerCamelCase				:					int=False ,  __lowerCamelCase				:					Union[str, Any]="none" ,  **__lowerCamelCase				:					Union[str, Any] ,  ):
		super().__init__(pad_token_id=__lowerCamelCase ,  bos_token_id=__lowerCamelCase ,  eos_token_id=__lowerCamelCase ,  **__lowerCamelCase	)

		UpperCamelCase     :List[Any]          =	vocab_size
		UpperCamelCase     :Optional[int]          =	hidden_size
		UpperCamelCase     :List[Any]          =	num_hidden_layers
		UpperCamelCase     :Optional[int]          =	num_attention_heads
		UpperCamelCase     :List[str]          =	hidden_act
		UpperCamelCase     :Tuple          =	intermediate_size
		UpperCamelCase     :Any          =	hidden_dropout_prob
		UpperCamelCase     :Union[str, Any]          =	attention_probs_dropout_prob
		UpperCamelCase     :Any          =	max_position_embeddings
		UpperCamelCase     :int          =	type_vocab_size
		UpperCamelCase     :List[str]          =	initializer_range
		UpperCamelCase     :str          =	layer_norm_eps
		UpperCamelCase     :int          =	position_embedding_type
		UpperCamelCase     :Optional[Any]          =	quant_mode
		UpperCamelCase     :int          =	force_dequant

class     _SCREAMING_SNAKE_CASE       (			_a      ):





	@property
	def 						_A (		self				:					int	):
		if self.task == "multiple-choice":
			UpperCamelCase     :Union[str, Any]          =	{0: """batch""", 1: """choice""", 2: """sequence"""}
		else:
			UpperCamelCase     :int          =	{0: """batch""", 1: """sequence"""}
		return OrderedDict(
		    [
		        ("""input_ids""", dynamic_axis),
		        ("""attention_mask""", dynamic_axis),
		    ]	)








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     _SCREAMING_SNAKE_CASE       (			_a      ):





	def __init__(		self				:					Optional[int] ,  **__lowerCamelCase				:					Optional[int]	):
		requires_backends(self ,  ["""bs4"""]	)
		super().__init__(**__lowerCamelCase	)





	def 						_A (		self				:					List[str] ,  __lowerCamelCase				:					Any	):
		UpperCamelCase     :Optional[int]          =	[]
		UpperCamelCase     :List[str]          =	[]
		UpperCamelCase     :Union[str, Any]          =	element if element.name else element.parent
		for parent in child.parents:  # type: bs4.element.Tag
			UpperCamelCase     :Optional[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	)	)
			UpperCamelCase     :Any          =	parent
		xpath_tags.reverse()
		xpath_subscripts.reverse()
		return xpath_tags, xpath_subscripts





	def 						_A (		self				:					Any ,  __lowerCamelCase				:					Tuple	):
		UpperCamelCase     :Any          =	BeautifulSoup(__lowerCamelCase ,  """html.parser"""	)

		UpperCamelCase     :Union[str, Any]          =	[]
		UpperCamelCase     :Tuple          =	[]
		UpperCamelCase     :Tuple          =	[]

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

				UpperCamelCase     :Any          =	html.unescape(__lowerCamelCase	).strip()
				if not text_in_this_tag:
					continue

				all_doc_strings.append(__lowerCamelCase	)

				UpperCamelCase     ,      UpperCamelCase     :Optional[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 						_A (		self				:					int ,  __lowerCamelCase				:					List[Any] ,  __lowerCamelCase				:					List[str]	):
		UpperCamelCase     :Tuple          =	""""""
		for tagname, subs in zip(__lowerCamelCase ,  __lowerCamelCase	):
			xpath += F"""/{tagname}"""
			if subs != 0:
				xpath += F"""[{subs}]"""
		return xpath





	def __call__(		self				:					Any ,  __lowerCamelCase				:					Dict	):
		UpperCamelCase     :Any          =	False

		# Check that strings has a valid type
		if isinstance(__lowerCamelCase ,  __lowerCamelCase	):
			UpperCamelCase     :List[Any]          =	True
		elif isinstance(__lowerCamelCase ,  (list, tuple)	):
			if len(__lowerCamelCase	) == 0 or isinstance(html_strings[0] ,  __lowerCamelCase	):
				UpperCamelCase     :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(__lowerCamelCase	)}."""	)

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

		if not is_batched:
			UpperCamelCase     :Any          =	[html_strings]

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

		# return as Dict
		UpperCamelCase     :Optional[int]          =	{"""nodes""": nodes, """xpaths""": xpaths}
		UpperCamelCase     :Any          =	BatchFeature(data=__lowerCamelCase ,  tensor_type=__lowerCamelCase	)

		return encoded_inputs
