




import re
import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin





class 					__lowerCamelCase			(       UpperCamelCase__       ):




    """simple docstring"""

    snake_case__   = ["image_processor", "tokenizer"]
    snake_case__   = "AutoImageProcessor"
    snake_case__   = "AutoTokenizer"


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

         lowerCAmelCase__            =					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__(SCREAMING_SNAKE_CASE__  ,      SCREAMING_SNAKE_CASE__  )
         lowerCAmelCase__            =					self.image_processor
         lowerCAmelCase__            =					False


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

         lowerCAmelCase__            =					kwargs.pop("images"  ,      SCREAMING_SNAKE_CASE__  )
         lowerCAmelCase__            =					kwargs.pop("text"  ,      SCREAMING_SNAKE_CASE__  )
         if len(SCREAMING_SNAKE_CASE__  ) > 0:
              lowerCAmelCase__            =					args[0]
              lowerCAmelCase__            =					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__            =					self.image_processor(SCREAMING_SNAKE_CASE__  ,      *SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )
         if text is not None:
              lowerCAmelCase__            =					self.tokenizer(SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )

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


    def   a (			self	:	List[Any]  ,      *SCREAMING_SNAKE_CASE__	:	List[Any]  ,      **SCREAMING_SNAKE_CASE__	:	Union[str, Any]  ) ->			Optional[Any]:
         return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )


    def   a (			self	:	str  ,      *SCREAMING_SNAKE_CASE__	:	Optional[int]  ,      **SCREAMING_SNAKE_CASE__	:	Tuple  ) ->			str:
         return self.tokenizer.decode(*SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )


    @contextmanager
    def   a (			self	:	str  ) ->			Tuple:
         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__            =					True
         lowerCAmelCase__            =					self.tokenizer
         yield
         lowerCAmelCase__            =					self.image_processor
         lowerCAmelCase__            =					False


    def   a (			self	:	Optional[int]  ,      SCREAMING_SNAKE_CASE__	:	List[str]  ,      SCREAMING_SNAKE_CASE__	:	Any=False  ,      SCREAMING_SNAKE_CASE__	:	Union[str, Any]=None  ) ->			Optional[Any]:
         if added_vocab is None:
              lowerCAmelCase__            =					self.tokenizer.get_added_vocab()

         lowerCAmelCase__            =					{}

         while tokens:
              lowerCAmelCase__            =					re.search(r"<s_(.*?)>"  ,      SCREAMING_SNAKE_CASE__  ,      re.IGNORECASE  )
              if start_token is None:
                   break
              lowerCAmelCase__            =					start_token.group(1  )
              lowerCAmelCase__            =					re.search(rf'</s_{key}>'  ,      SCREAMING_SNAKE_CASE__  ,      re.IGNORECASE  )
              lowerCAmelCase__            =					start_token.group()
              if end_token is None:
                   lowerCAmelCase__            =					tokens.replace(SCREAMING_SNAKE_CASE__  ,      ""  )
              else:
                   lowerCAmelCase__            =					end_token.group()
                   lowerCAmelCase__            =					re.escape(SCREAMING_SNAKE_CASE__  )
                   lowerCAmelCase__            =					re.escape(SCREAMING_SNAKE_CASE__  )
                   lowerCAmelCase__            =					re.search(f'{start_token_escaped}(.*?){end_token_escaped}'  ,      SCREAMING_SNAKE_CASE__  ,      re.IGNORECASE  )
                   if content is not None:
                        lowerCAmelCase__            =					content.group(1  ).strip()
                        if r"<s_" in content and r"</s_" in content:  # non-leaf node
                             lowerCAmelCase__            =					self.tokenajson(SCREAMING_SNAKE_CASE__  ,      is_inner_value=SCREAMING_SNAKE_CASE__  ,      added_vocab=SCREAMING_SNAKE_CASE__  )
                             if value:
                                  if len(SCREAMING_SNAKE_CASE__  ) == 1:
                                       lowerCAmelCase__            =					value[0]
                                  lowerCAmelCase__            =					value
                        else:  # leaf nodes
                             lowerCAmelCase__            =					[]
                             for leaf in content.split(r"<sep/>"  ):
                                  lowerCAmelCase__            =					leaf.strip()
                                  if leaf in added_vocab and leaf[0] == "<" and leaf[-2:] == "/>":
                                       lowerCAmelCase__            =					leaf[1:-2]  # for categorical special tokens
                                  output[key].append(SCREAMING_SNAKE_CASE__  )
                             if len(output[key]  ) == 1:
                                  lowerCAmelCase__            =					output[key][0]

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

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


    @property
    def   a (			self	:	Union[str, Any]  ) ->			List[Any]:
         warnings.warn(
             "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."  ,      SCREAMING_SNAKE_CASE__  ,      )
         return self.image_processor_class


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




'''simple docstring'''

import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class     __lowerCAmelCase		(lowercase_    ,	unittest.TestCase	):





      '''simple docstring'''






      lowerCAmelCase__   :	str       =				RoFormerTokenizer
      lowerCAmelCase__   :	Dict       =				RoFormerTokenizerFast
      lowerCAmelCase__   :	List[str]       =				True
      lowerCAmelCase__   :	List[str]       =				True



      def  UpperCamelCase__						(self       :       Dict					):

             '''simple docstring'''







             super().setUp()



      def  UpperCamelCase__						(self       :       List[str]  ,		**UpperCamelCase       :       Dict					):

             '''simple docstring'''







             return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''  ,		**UpperCamelCase					)



      def  UpperCamelCase__						(self       :       List[str]  ,		**UpperCamelCase       :       int					):

             '''simple docstring'''







             return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''  ,		**UpperCamelCase					)



      def  UpperCamelCase__						(self       :       List[str]					):

             '''simple docstring'''







             lowercase__      =					'''永和服装饰品有限公司,今天天气非常好'''
             lowercase__      =					'''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
             return input_text, output_text



      def  UpperCamelCase__						(self       :       int					):

             '''simple docstring'''







             lowercase__      =					self.get_tokenizer()
             lowercase__     ,lowercase__      =					self.get_chinese_input_output_texts()
             lowercase__      =					tokenizer.tokenize(UpperCamelCase					)

             self.assertListEqual(UpperCamelCase  ,		output_text.split()					)

             lowercase__      =					tokens + [tokenizer.unk_token]
             lowercase__      =					[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase					)  ,		UpperCamelCase					)



      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             lowercase__      =					self.get_rust_tokenizer()
             lowercase__     ,lowercase__      =					self.get_chinese_input_output_texts()
             lowercase__      =					tokenizer.tokenize(UpperCamelCase					)
             self.assertListEqual(UpperCamelCase  ,		output_text.split()					)
             lowercase__      =					tokens + [tokenizer.unk_token]
             lowercase__      =					[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase					)  ,		UpperCamelCase					)



      def  UpperCamelCase__						(self       :       str					):

             '''simple docstring'''







             pass



      def  UpperCamelCase__						(self       :       Any					):

             '''simple docstring'''







             pass






      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             pass




