






"""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


__lowerCamelCase :      int										=				logging.get_logger(__name__)



class 							SCREAMING_SNAKE_CASE__						(    lowercase__						):





					"""simple docstring"""






					def __init__( self					:  str							,		**__A					:  Tuple	):
						requires_backends(self							,		["bs4"]	)
						super().__init__(**lowercase_	)



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



					def 	_lowercase					( self					:  List[str]							,		__A					:  Union[str, Any]	):
						snake_case__			:				Dict       =  BeautifulSoup(lowercase_							,		"html.parser"	)

						snake_case__			:				int       =  []
						snake_case__			:				Any       =  []
						snake_case__			:				List[Any]       =  []

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

								snake_case__			:				List[str]       =  html.unescape(lowercase_	).strip()
								if not text_in_this_tag:
									continue

								all_doc_strings.append(lowercase_	)

								snake_case__			:				List[Any]       =  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					:  List[Any]							,		__A					:  Optional[int]							,		__A					:  str	):
						snake_case__			:				Dict       =  ""
						for tagname, subs in zip(lowercase_							,		lowercase_	):
							xpath += f'''/{tagname}'''
							if subs != 0:
								xpath += f'''[{subs}]'''
						return xpath






					def __call__( self					:  List[str]							,		__A					:  Union[str, Any]	):
						snake_case__			:				int       =  False

						# Check that strings has a valid type
						if isinstance(lowercase_							,		lowercase_	):
							snake_case__			:				List[str]       =  True
						elif isinstance(lowercase_							,		(list, tuple)	):
							if len(lowercase_	) == 0 or isinstance(html_strings[0]							,		lowercase_	):
								snake_case__			:				List[str]       =  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_	)}.'''	)

						snake_case__			:				str       =  bool(isinstance(lowercase_							,		(list, tuple)	) and (isinstance(html_strings[0]							,		lowercase_	))	)

						if not is_batched:
							snake_case__			:				Tuple       =  [html_strings]

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

						# return as Dict
						snake_case__			:				Optional[int]       =  {"nodes": nodes, "xpaths": xpaths}
						snake_case__			:				Union[str, Any]       =  BatchFeature(data=lowercase_							,		tensor_type=lowercase_	)

						return encoded_inputs











import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin



class 							SCREAMING_SNAKE_CASE__						(    UpperCamelCase_			,       unittest.TestCase						):





					"""simple docstring"""






					a_     =		PhobertTokenizer
					a_     =		False



					def 	_lowercase					( self					:  List[str]	):
						super().setUp()

						# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
						snake_case__			:				Optional[int]       =  ["T@@", "i", "I", "R@@", "r", "e@@"]
						snake_case__			:				int       =  dict(zip(__A							,		range(len(__A	)	)	)	)
						snake_case__			:				Dict       =  ["#version: 0.2", "l à</w>"]
						snake_case__			:				Optional[Any]       =  {"unk_token": "<unk>"}

						snake_case__			:				Tuple       =  os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["vocab_file"]	)
						snake_case__			:				Union[str, Any]       =  os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["merges_file"]	)

						with open(self.vocab_file							,		"w"							,		encoding="utf-8"	) as fp:
							for token in vocab_tokens:
								fp.write(f'''{token} {vocab_tokens[token]}\n'''	)
						with open(self.merges_file							,		"w"							,		encoding="utf-8"	) as fp:
							fp.write("\n".join(__A	)	)



					def 	_lowercase					( self					:  List[str]							,		**__A					:  Any	):
						kwargs.update(self.special_tokens_map	)
						return PhobertTokenizer.from_pretrained(self.tmpdirname							,		**__A	)



					def 	_lowercase					( self					:  Tuple							,		__A					:  List[Any]	):
						snake_case__			:				str       =  "Tôi là VinAI Research"
						snake_case__			:				int       =  "T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
						return input_text, output_text






					def 	_lowercase					( self					:  Optional[int]	):
						snake_case__			:				int       =  PhobertTokenizer(self.vocab_file							,		self.merges_file							,		**self.special_tokens_map	)
						snake_case__			:				Tuple       =  "Tôi là VinAI Research"
						snake_case__			:				List[Any]       =  "T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
						snake_case__			:				int       =  tokenizer.tokenize(__A	)
						print(__A	)
						self.assertListEqual(__A							,		__A	)

						snake_case__			:				Any       =  tokens + [tokenizer.unk_token]

						snake_case__			:				Any       =  [4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(__A	)							,		__A	)



