




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


__SCREAMING_SNAKE_CASE 						=logging.get_logger(__name__)






class  __magic_name__						(  __UpperCAmelCase):
				'''simple docstring'''







				def __init__(							self:   Optional[Any]		,					**_lowerCamelCase:   str		):
											requires_backends(self		,					['''bs4''']		)
											super().__init__(**_lowerCamelCase		)


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


				def     _A							(							self:   List[Any]		,					_lowerCamelCase:   List[Any]		):
											SCREAMING_SNAKE_CASE_   	=    BeautifulSoup(_lowerCamelCase		,					'''html.parser'''		)

											SCREAMING_SNAKE_CASE_   	=    []
											SCREAMING_SNAKE_CASE_   	=    []
											SCREAMING_SNAKE_CASE_   	=    []

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

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

																									all_doc_strings.append(_lowerCamelCase		)

																									SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_   	=    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:   Union[str, Any]		,					_lowerCamelCase:   Optional[int]		,					_lowerCamelCase:   Optional[Any]		):
											SCREAMING_SNAKE_CASE_   	=    ''''''
											for tagname, subs in zip(_lowerCamelCase		,					_lowerCamelCase		):
																		xpath += f"/{tagname}"
																		if subs != 0:
																									xpath += f"[{subs}]"
											return xpath





				def __call__(							self:   Union[str, Any]		,					_lowerCamelCase:   Union[str, Any]		):
											SCREAMING_SNAKE_CASE_   	=    False

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

											SCREAMING_SNAKE_CASE_   	=    bool(isinstance(_lowerCamelCase		,					(list, tuple)		) and (isinstance(html_strings[0]		,					_lowerCamelCase		))		)

											if not is_batched:
																		SCREAMING_SNAKE_CASE_   	=    [html_strings]

											# Get nodes + xpaths
											SCREAMING_SNAKE_CASE_   	=    []
											SCREAMING_SNAKE_CASE_   	=    []
											for html_string in html_strings:
																		SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_   	=    self.get_three_from_single(_lowerCamelCase		)
																		nodes.append(_lowerCamelCase		)
																		SCREAMING_SNAKE_CASE_   	=    []
																		for node, tag_list, sub_list in zip(_lowerCamelCase		,					_lowerCamelCase		,					_lowerCamelCase		):
																									SCREAMING_SNAKE_CASE_   	=    self.construct_xpath(_lowerCamelCase		,					_lowerCamelCase		)
																									xpath_strings.append(_lowerCamelCase		)
																		xpaths.append(_lowerCamelCase		)

											# return as Dict
											SCREAMING_SNAKE_CASE_   	=    {'''nodes''': nodes, '''xpaths''': xpaths}
											SCREAMING_SNAKE_CASE_   	=    BatchFeature(data=_lowerCamelCase		,					tensor_type=_lowerCamelCase		)

											return encoded_inputs








from ...configuration_utils import PretrainedConfig
from ...utils import logging


__SCREAMING_SNAKE_CASE 						=logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE 						={
    """caidas/swin2sr-classicalsr-x2-64""": (
        """https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json"""
    ),
}






class  __magic_name__						(  __UpperCAmelCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							Optional[Any]	      =					"swin2sr"

				SCREAMING_SNAKE_CASE__					:							str	      =					{
				    "hidden_size": "embed_dim",
				    "num_attention_heads": "num_heads",
				    "num_hidden_layers": "num_layers",
				}


				def __init__(							self:   Optional[int]		,					_lowerCamelCase:   Dict=64		,					_lowerCamelCase:   str=1		,					_lowerCamelCase:   Optional[int]=3		,					_lowerCamelCase:   List[Any]=1_80		,					_lowerCamelCase:   Optional[int]=[6, 6, 6, 6, 6, 6]		,					_lowerCamelCase:   Union[str, Any]=[6, 6, 6, 6, 6, 6]		,					_lowerCamelCase:   Tuple=8		,					_lowerCamelCase:   List[Any]=2.0		,					_lowerCamelCase:   Dict=True		,					_lowerCamelCase:   Dict=0.0		,					_lowerCamelCase:   int=0.0		,					_lowerCamelCase:   Optional[int]=0.1		,					_lowerCamelCase:   Any="gelu"		,					_lowerCamelCase:   int=False		,					_lowerCamelCase:   Tuple=0.02		,					_lowerCamelCase:   List[str]=1E-5		,					_lowerCamelCase:   List[Any]=2		,					_lowerCamelCase:   str=1.0		,					_lowerCamelCase:   List[Any]="1conv"		,					_lowerCamelCase:   str="pixelshuffle"		,					**_lowerCamelCase:   List[str]		,					):
											super().__init__(**_lowerCamelCase		)

											SCREAMING_SNAKE_CASE_   	=    image_size
											SCREAMING_SNAKE_CASE_   	=    patch_size
											SCREAMING_SNAKE_CASE_   	=    num_channels
											SCREAMING_SNAKE_CASE_   	=    embed_dim
											SCREAMING_SNAKE_CASE_   	=    depths
											SCREAMING_SNAKE_CASE_   	=    len(_lowerCamelCase		)
											SCREAMING_SNAKE_CASE_   	=    num_heads
											SCREAMING_SNAKE_CASE_   	=    window_size
											SCREAMING_SNAKE_CASE_   	=    mlp_ratio
											SCREAMING_SNAKE_CASE_   	=    qkv_bias
											SCREAMING_SNAKE_CASE_   	=    hidden_dropout_prob
											SCREAMING_SNAKE_CASE_   	=    attention_probs_dropout_prob
											SCREAMING_SNAKE_CASE_   	=    drop_path_rate
											SCREAMING_SNAKE_CASE_   	=    hidden_act
											SCREAMING_SNAKE_CASE_   	=    use_absolute_embeddings
											SCREAMING_SNAKE_CASE_   	=    layer_norm_eps
											SCREAMING_SNAKE_CASE_   	=    initializer_range
											SCREAMING_SNAKE_CASE_   	=    upscale
											SCREAMING_SNAKE_CASE_   	=    img_range
											SCREAMING_SNAKE_CASE_   	=    resi_connection
											SCREAMING_SNAKE_CASE_   	=    upsampler


