


'''simple docstring'''






import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english






@require_tokenizers
class    __snake_case       (   _SCREAMING_SNAKE_CASE	,unittest.TestCase):







    """simple docstring"""



    lowercase    =					RoCBertTokenizer
    lowercase    =					None
    lowercase    =					False
    lowercase    =					True
    lowercase    =					filter_non_english

    def __lowercase   (   self    :  Tuple		)   ->  int:
      super().setUp()

      lowerCAmelCase_			:      Tuple			=   ["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """你""", """好""", """是""", """谁""", """a""", """b""", """c""", """d"""]
      lowerCAmelCase_			:      List[str]			=   {}
      lowerCAmelCase_			:      List[str]			=   {}
      for i, value in enumerate(lowerCamelCase		):
        lowerCAmelCase_			:      List[str]			=   i
        lowerCAmelCase_			:      List[str]			=   i
      lowerCAmelCase_			:      Dict			=   os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["""vocab_file"""]		)
      lowerCAmelCase_			:      int			=   os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["""word_shape_file"""]		)
      lowerCAmelCase_			:      List[Any]			=   os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["""word_pronunciation_file"""]		)
      with open(self.vocab_file    ,						"""w"""    ,						encoding="""utf-8"""		) as vocab_writer:
        vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]		)		)
      with open(self.word_shape_file    ,						"""w"""    ,						encoding="""utf-8"""		) as word_shape_writer:
        json.dump(lowerCamelCase    ,						lowerCamelCase    ,						ensure_ascii=lowerCamelCase		)
      with open(self.word_pronunciation_file    ,						"""w"""    ,						encoding="""utf-8"""		) as word_pronunciation_writer:
        json.dump(lowerCamelCase    ,						lowerCamelCase    ,						ensure_ascii=lowerCamelCase		)

    def __lowercase   (   self    :  int		)   ->  int:
      lowerCAmelCase_			:      Tuple			=   self.tokenizer_class(self.vocab_file    ,						self.word_shape_file    ,						self.word_pronunciation_file		)

      lowerCAmelCase_			:      List[str]			=   tokenizer.tokenize("""你好[SEP]你是谁"""		)
      self.assertListEqual(lowerCamelCase    ,						["""你""", """好""", """[SEP]""", """你""", """是""", """谁"""]		)
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase		)    ,						[5, 6, 2, 5, 7, 8]		)
      self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(lowerCamelCase		)    ,						[5, 6, 2, 5, 7, 8]		)
      self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(lowerCamelCase		)    ,						[5, 6, 2, 5, 7, 8]		)

    def __lowercase   (   self    :  Tuple		)   ->  Union[str, Any]:
      lowerCAmelCase_			:      Tuple			=   RoCBertBasicTokenizer()

      self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz"""		)    ,						["""ah""", """\u535A""", """\u63A8""", """zz"""]		)

    def __lowercase   (   self    :  str		)   ->  Optional[Any]:
      lowerCAmelCase_			:      int			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """		)    ,						["""hello""", """!""", """how""", """are""", """you""", """?"""]		)
      self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""		)    ,						["""hello"""]		)

    def __lowercase   (   self    :  Optional[int]		)   ->  Optional[int]:
      lowerCAmelCase_			:      Optional[Any]			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase    ,						strip_accents=lowerCamelCase		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """		)    ,						["""hällo""", """!""", """how""", """are""", """you""", """?"""]		)
      self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""		)    ,						["""h\u00E9llo"""]		)

    def __lowercase   (   self    :  Dict		)   ->  Tuple:
      lowerCAmelCase_			:      Union[str, Any]			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase    ,						strip_accents=lowerCamelCase		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """		)    ,						["""hallo""", """!""", """how""", """are""", """you""", """?"""]		)
      self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""		)    ,						["""hello"""]		)

    def __lowercase   (   self    :  Dict		)   ->  List[Any]:
      lowerCAmelCase_			:      Optional[int]			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """		)    ,						["""hallo""", """!""", """how""", """are""", """you""", """?"""]		)
      self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""		)    ,						["""hello"""]		)

    def __lowercase   (   self    :  Tuple		)   ->  str:
      lowerCAmelCase_			:      List[Any]			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """		)    ,						["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]		)

    def __lowercase   (   self    :  Tuple		)   ->  List[str]:
      lowerCAmelCase_			:      List[str]			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase    ,						strip_accents=lowerCamelCase		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """		)    ,						["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""]		)

    def __lowercase   (   self    :  Any		)   ->  List[Any]:
      lowerCAmelCase_			:      str			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase    ,						strip_accents=lowerCamelCase		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """		)    ,						["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""]		)

    def __lowercase   (   self    :  Union[str, Any]		)   ->  Dict:
      lowerCAmelCase_			:      Any			=   RoCBertBasicTokenizer(do_lower_case=lowerCamelCase    ,						never_split=["""[UNK]"""]		)

      self.assertListEqual(
          tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]"""		)    ,						["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""]		)

    def __lowercase   (   self    :  List[str]		)   ->  Tuple:
      lowerCAmelCase_			:      Tuple			=   ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

      lowerCAmelCase_			:      Optional[Any]			=   {}
      for i, token in enumerate(lowerCamelCase		):
        lowerCAmelCase_			:      int			=   i
      lowerCAmelCase_			:      Any			=   RoCBertWordpieceTokenizer(vocab=lowerCamelCase    ,						unk_token="""[UNK]"""		)

      self.assertListEqual(tokenizer.tokenize(""""""		)    ,						[]		)

      self.assertListEqual(tokenizer.tokenize("""unwanted running"""		)    ,						["""un""", """##want""", """##ed""", """runn""", """##ing"""]		)

      self.assertListEqual(tokenizer.tokenize("""unwantedX running"""		)    ,						["""[UNK]""", """runn""", """##ing"""]		)

    def __lowercase   (   self    :  str		)   ->  str:
      self.assertTrue(_is_whitespace(""" """		)		)
      self.assertTrue(_is_whitespace("""\t"""		)		)
      self.assertTrue(_is_whitespace("""\r"""		)		)
      self.assertTrue(_is_whitespace("""\n"""		)		)
      self.assertTrue(_is_whitespace("""\u00A0"""		)		)

      self.assertFalse(_is_whitespace("""A"""		)		)
      self.assertFalse(_is_whitespace("""-"""		)		)

    def __lowercase   (   self    :  List[str]		)   ->  Optional[Any]:
      self.assertTrue(_is_control("""\u0005"""		)		)

      self.assertFalse(_is_control("""A"""		)		)
      self.assertFalse(_is_control(""" """		)		)
      self.assertFalse(_is_control("""\t"""		)		)
      self.assertFalse(_is_control("""\r"""		)		)

    def __lowercase   (   self    :  Any		)   ->  Optional[Any]:
      self.assertTrue(_is_punctuation("""-"""		)		)
      self.assertTrue(_is_punctuation("""$"""		)		)
      self.assertTrue(_is_punctuation("""`"""		)		)
      self.assertTrue(_is_punctuation("""."""		)		)

      self.assertFalse(_is_punctuation("""A"""		)		)
      self.assertFalse(_is_punctuation(""" """		)		)

    def __lowercase   (   self    :  str		)   ->  Union[str, Any]:
      lowerCAmelCase_			:      List[str]			=   self.get_tokenizer()

      # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
      self.assertListEqual([tokenizer.tokenize(lowerCamelCase		) for t in ["""Test""", """\xad""", """test"""]]    ,						[["""[UNK]"""], [], ["""[UNK]"""]]		)

      if self.test_rust_tokenizer:
        lowerCAmelCase_			:      Optional[int]			=   self.get_rust_tokenizer()
        self.assertListEqual(
            [rust_tokenizer.tokenize(lowerCamelCase		) for t in ["""Test""", """\xad""", """test"""]]    ,						[["""[UNK]"""], [], ["""[UNK]"""]]		)

    def __lowercase   (   self    :  Optional[int]		)   ->  Union[str, Any]:
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'		):
          lowerCAmelCase_			:      str			=   self.rust_tokenizer_class.from_pretrained(lowerCamelCase    ,						**lowerCamelCase		)

          lowerCAmelCase_			:      List[str]			=   F'A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'
          lowerCAmelCase_			:      Tuple			=   tokenizer_r.encode_plus(
              lowerCamelCase    ,						return_attention_mask=lowerCamelCase    ,						return_token_type_ids=lowerCamelCase    ,						return_offsets_mapping=lowerCamelCase    ,						add_special_tokens=lowerCamelCase    ,						)

          lowerCAmelCase_			:      Any			=   tokenizer_r.do_lower_case if hasattr(lowerCamelCase    ,						"""do_lower_case"""		) else False
          lowerCAmelCase_			:      Tuple			=   (
              [
                  ((0, 0), tokenizer_r.cls_token),
                  ((0, 1), """A"""),
                  ((1, 2), ""","""),
                  ((3, 5), """na"""),
                  ((5, 6), """##ï"""),
                  ((6, 8), """##ve"""),
                  ((9, 15), tokenizer_r.mask_token),
                  ((16, 21), """Allen"""),
                  ((21, 23), """##NL"""),
                  ((23, 24), """##P"""),
                  ((25, 33), """sentence"""),
                  ((33, 34), """."""),
                  ((0, 0), tokenizer_r.sep_token),
              ]
              if not do_lower_case
              else [
                  ((0, 0), tokenizer_r.cls_token),
                  ((0, 1), """a"""),
                  ((1, 2), ""","""),
                  ((3, 8), """naive"""),
                  ((9, 15), tokenizer_r.mask_token),
                  ((16, 21), """allen"""),
                  ((21, 23), """##nl"""),
                  ((23, 24), """##p"""),
                  ((25, 33), """sentence"""),
                  ((33, 34), """."""),
                  ((0, 0), tokenizer_r.sep_token),
              ]
          )

          self.assertEqual(
              [e[1] for e in expected_results]    ,						tokenizer_r.convert_ids_to_tokens(tokens["""input_ids"""]		)		)
          self.assertEqual([e[0] for e in expected_results]    ,						tokens["""offset_mapping"""]		)

    def __lowercase   (   self    :  Union[str, Any]		)   ->  List[Any]:
      lowerCAmelCase_			:      int			=   ["""的""", """人""", """有"""]
      lowerCAmelCase_			:      List[str]			=   """""".join(lowerCamelCase		)
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'		):
          lowerCAmelCase_			:      List[str]			=   True
          lowerCAmelCase_			:      Optional[Any]			=   self.tokenizer_class.from_pretrained(lowerCamelCase    ,						**lowerCamelCase		)
          lowerCAmelCase_			:      Optional[Any]			=   self.rust_tokenizer_class.from_pretrained(lowerCamelCase    ,						**lowerCamelCase		)

          lowerCAmelCase_			:      Any			=   tokenizer_p.encode(lowerCamelCase    ,						add_special_tokens=lowerCamelCase		)
          lowerCAmelCase_			:      str			=   tokenizer_r.encode(lowerCamelCase    ,						add_special_tokens=lowerCamelCase		)

          lowerCAmelCase_			:      str			=   tokenizer_r.convert_ids_to_tokens(lowerCamelCase		)
          lowerCAmelCase_			:      Optional[Any]			=   tokenizer_p.convert_ids_to_tokens(lowerCamelCase		)

          # it is expected that each Chinese character is not preceded by "##"
          self.assertListEqual(lowerCamelCase    ,						lowerCamelCase		)
          self.assertListEqual(lowerCamelCase    ,						lowerCamelCase		)

          lowerCAmelCase_			:      List[str]			=   False
          lowerCAmelCase_			:      Dict			=   self.rust_tokenizer_class.from_pretrained(lowerCamelCase    ,						**lowerCamelCase		)
          lowerCAmelCase_			:      str			=   self.tokenizer_class.from_pretrained(lowerCamelCase    ,						**lowerCamelCase		)

          lowerCAmelCase_			:      Tuple			=   tokenizer_r.encode(lowerCamelCase    ,						add_special_tokens=lowerCamelCase		)
          lowerCAmelCase_			:      Any			=   tokenizer_p.encode(lowerCamelCase    ,						add_special_tokens=lowerCamelCase		)

          lowerCAmelCase_			:      int			=   tokenizer_r.convert_ids_to_tokens(lowerCamelCase		)
          lowerCAmelCase_			:      Optional[int]			=   tokenizer_p.convert_ids_to_tokens(lowerCamelCase		)

          # it is expected that only the first Chinese character is not preceded by "##".
          lowerCAmelCase_			:      int			=   [
              F'##{token}' if idx != 0 else token for idx, token in enumerate(lowerCamelCase		)
          ]
          self.assertListEqual(lowerCamelCase    ,						lowerCamelCase		)
          self.assertListEqual(lowerCamelCase    ,						lowerCamelCase		)

    @slow
    def __lowercase   (   self    :  Dict		)   ->  Dict:
      lowerCAmelCase_			:      int			=   self.tokenizer_class(self.vocab_file    ,						self.word_shape_file    ,						self.word_pronunciation_file		)

      lowerCAmelCase_			:      Optional[Any]			=   tokenizer.encode("""你好"""    ,						add_special_tokens=lowerCamelCase		)
      lowerCAmelCase_			:      List[Any]			=   tokenizer.encode("""你是谁"""    ,						add_special_tokens=lowerCamelCase		)

      lowerCAmelCase_			:      Tuple			=   tokenizer.build_inputs_with_special_tokens(lowerCamelCase		)
      lowerCAmelCase_			:      Tuple			=   tokenizer.build_inputs_with_special_tokens(lowerCamelCase    ,						lowerCamelCase		)

      assert encoded_sentence == [1] + text + [2]
      assert encoded_pair == [1] + text + [2] + text_a + [2]





    def __lowercase   (   self    :  str		)   ->  Tuple:
      lowerCAmelCase_			:      str			=   self.get_tokenizers(do_lower_case=lowerCamelCase		)
      for tokenizer in tokenizers:
        with self.subTest(F'{tokenizer.__class__.__name__}'		):
          lowerCAmelCase_			:      List[Any]			=   """你好，你是谁"""
          lowerCAmelCase_			:      Any			=   tokenizer.tokenize(lowerCamelCase		)
          lowerCAmelCase_			:      int			=   tokenizer.convert_tokens_to_ids(lowerCamelCase		)
          lowerCAmelCase_			:      Any			=   tokenizer.convert_tokens_to_shape_ids(lowerCamelCase		)
          lowerCAmelCase_			:      Tuple			=   tokenizer.convert_tokens_to_pronunciation_ids(lowerCamelCase		)
          lowerCAmelCase_			:      Union[str, Any]			=   tokenizer.prepare_for_model(
              lowerCamelCase    ,						lowerCamelCase    ,						lowerCamelCase    ,						add_special_tokens=lowerCamelCase		)

          lowerCAmelCase_			:      List[Any]			=   tokenizer.encode_plus(lowerCamelCase    ,						add_special_tokens=lowerCamelCase		)

          self.assertEqual(lowerCamelCase    ,						lowerCamelCase		)







'''simple docstring'''






import re
import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase    =					['image_processor', 'tokenizer']
    lowercase    =					'AutoImageProcessor'
    lowercase    =					'AutoTokenizer'

    def __init__(   self    :  int    ,						lowerCamelCase    :  List[str]=None    ,						lowerCamelCase    :  Union[str, Any]=None    ,						**lowerCamelCase    :  str		)   ->  Tuple:
      lowerCAmelCase_			:      str			=   None
      if "feature_extractor" in kwargs:
        warnings.warn(
            """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
            """ instead."""    ,						lowerCamelCase    ,						)
        lowerCAmelCase_			:      Tuple			=   kwargs.pop("""feature_extractor"""		)

      lowerCAmelCase_			:      Tuple			=   image_processor if image_processor is not None else feature_extractor
      if image_processor is None:
        raise ValueError("""You need to specify an `image_processor`."""		)
      if tokenizer is None:
        raise ValueError("""You need to specify a `tokenizer`."""		)

      super().__init__(lowerCamelCase    ,						lowerCamelCase		)
      lowerCAmelCase_			:      Optional[int]			=   self.image_processor
      lowerCAmelCase_			:      Any			=   False

    def __call__(   self    :  List[Any]    ,						*lowerCamelCase    :  str    ,						**lowerCamelCase    :  Tuple		)   ->  Union[str, Any]:
      # For backward compatibility
      if self._in_target_context_manager:
        return self.current_processor(*lowerCamelCase    ,						**lowerCamelCase		)

      lowerCAmelCase_			:      Any			=   kwargs.pop("""images"""    ,						lowerCamelCase		)
      lowerCAmelCase_			:      Dict			=   kwargs.pop("""text"""    ,						lowerCamelCase		)
      if len(lowerCamelCase		) > 0:
        lowerCAmelCase_			:      str			=   args[0]
        lowerCAmelCase_			:      Dict			=   args[1:]

      if images is None and text is None:
        raise ValueError("""You need to specify either an `images` or `text` input to process."""		)

      if images is not None:
        lowerCAmelCase_			:      Any			=   self.image_processor(lowerCamelCase    ,						*lowerCamelCase    ,						**lowerCamelCase		)
      if text is not None:
        lowerCAmelCase_			:      str			=   self.tokenizer(lowerCamelCase    ,						**lowerCamelCase		)

      if text is None:
        return inputs
      elif images is None:
        return encodings
      else:
        lowerCAmelCase_			:      Dict			=   encodings["""input_ids"""]
        return inputs

    def __lowercase   (   self    :  str    ,						*lowerCamelCase    :  Union[str, Any]    ,						**lowerCamelCase    :  Union[str, Any]		)   ->  List[str]:
      return self.tokenizer.batch_decode(*lowerCamelCase    ,						**lowerCamelCase		)

    def __lowercase   (   self    :  List[Any]    ,						*lowerCamelCase    :  Any    ,						**lowerCamelCase    :  Union[str, Any]		)   ->  List[str]:
      return self.tokenizer.decode(*lowerCamelCase    ,						**lowerCamelCase		)

    @contextmanager
    def __lowercase   (   self    :  str		)   ->  Union[str, Any]:
      warnings.warn(
          """`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your """
          """labels by using the argument `text` of the regular `__call__` method (either in the same call as """
          """your images inputs, or in a separate call."""		)
      lowerCAmelCase_			:      List[str]			=   True
      lowerCAmelCase_			:      Optional[Any]			=   self.tokenizer
      yield
      lowerCAmelCase_			:      List[Any]			=   self.image_processor
      lowerCAmelCase_			:      List[str]			=   False

    def __lowercase   (   self    :  Dict    ,						lowerCamelCase    :  List[str]    ,						lowerCamelCase    :  str=False    ,						lowerCamelCase    :  List[Any]=None		)   ->  Optional[int]:
      if added_vocab is None:
        lowerCAmelCase_			:      str			=   self.tokenizer.get_added_vocab()

      lowerCAmelCase_			:      Union[str, Any]			=   {}

      while tokens:
        lowerCAmelCase_			:      Dict			=   re.search(R"""<s_(.*?)>"""    ,						lowerCamelCase    ,						re.IGNORECASE		)
        if start_token is None:
          break
        lowerCAmelCase_			:      Tuple			=   start_token.group(1		)
        lowerCAmelCase_			:      Tuple			=   re.search(RF'</s_{key}>'    ,						lowerCamelCase    ,						re.IGNORECASE		)
        lowerCAmelCase_			:      Tuple			=   start_token.group()
        if end_token is None:
          lowerCAmelCase_			:      str			=   tokens.replace(lowerCamelCase    ,						""""""		)
        else:
          lowerCAmelCase_			:      List[str]			=   end_token.group()
          lowerCAmelCase_			:      Dict			=   re.escape(lowerCamelCase		)
          lowerCAmelCase_			:      int			=   re.escape(lowerCamelCase		)
          lowerCAmelCase_			:      Dict			=   re.search(F'{start_token_escaped}(.*?){end_token_escaped}'    ,						lowerCamelCase    ,						re.IGNORECASE		)
          if content is not None:
            lowerCAmelCase_			:      str			=   content.group(1		).strip()
            if r"<s_" in content and r"</s_" in content:  # non-leaf node
              lowerCAmelCase_			:      str			=   self.tokenajson(lowerCamelCase    ,						is_inner_value=lowerCamelCase    ,						added_vocab=lowerCamelCase		)
              if value:
                if len(lowerCamelCase		) == 1:
                  lowerCAmelCase_			:      List[Any]			=   value[0]
                lowerCAmelCase_			:      Optional[Any]			=   value
            else:  # leaf nodes
              lowerCAmelCase_			:      List[str]			=   []
              for leaf in content.split(R"""<sep/>"""		):
                lowerCAmelCase_			:      Union[str, Any]			=   leaf.strip()
                if leaf in added_vocab and leaf[0] == "<" and leaf[-2:] == "/>":
                  lowerCAmelCase_			:      Any			=   leaf[1:-2]  # for categorical special tokens
                output[key].append(lowerCamelCase		)
              if len(output[key]		) == 1:
                lowerCAmelCase_			:      Optional[Any]			=   output[key][0]

          lowerCAmelCase_			:      List[Any]			=   tokens[tokens.find(lowerCamelCase		) + len(lowerCamelCase		) :].strip()
          if tokens[:6] == r"<sep/>":  # non-leaf nodes
            return [output] + self.tokenajson(tokens[6:]    ,						is_inner_value=lowerCamelCase    ,						added_vocab=lowerCamelCase		)

      if len(lowerCamelCase		):
        return [output] if is_inner_value else output
      else:
        return [] if is_inner_value else {"text_sequence": tokens}

    @property
    def __lowercase   (   self    :  Dict		)   ->  int:
      warnings.warn(
          """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""    ,						lowerCamelCase    ,						)
      return self.image_processor_class





    @property
    def __lowercase   (   self    :  Dict		)   ->  Optional[Any]:
      warnings.warn(
          """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""    ,						lowerCamelCase    ,						)
      return self.image_processor



