import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin




class 	__snake_case	( __lowerCAmelCase ,  unittest.TestCase		):





      '''simple docstring'''






      _snake_case    		=       BlenderbotSmallTokenizer
      _snake_case    		=       False



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any])				->Union[str, Any]:


          """simple docstring"""


          super().setUp()

          _lowerCamelCase     :		Union[str, Any] 						=						["""__start__""", """adapt""", """act""", """ap@@""", """te""", """__end__""", """__unk__"""]
          _lowerCamelCase     :		List[Any] 						=						dict(zip(_UpperCamelCase    ,  range(len(_UpperCamelCase))))

          _lowerCamelCase     :		Optional[Any] 						=						["""#version: 0.2""", """a p""", """t e</w>""", """ap t</w>""", """a d""", """ad apt</w>""", """a c""", """ac t</w>""", """"""]
          _lowerCamelCase     :		List[str] 						=						{"""unk_token""": """__unk__""", """bos_token""": """__start__""", """eos_token""": """__end__"""}

          _lowerCamelCase     :		str 						=						os.path.join(self.tmpdirname    ,  VOCAB_FILES_NAMES["""vocab_file"""])
          _lowerCamelCase     :		Tuple 						=						os.path.join(self.tmpdirname    ,  VOCAB_FILES_NAMES["""merges_file"""])
          with open(self.vocab_file    ,  """w"""    ,  encoding="""utf-8""") as fp:
              fp.write(json.dumps(_UpperCamelCase) + """\n""")
          with open(self.merges_file    ,  """w"""    ,  encoding="""utf-8""") as fp:
              fp.write("""\n""".join(_UpperCamelCase))



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any]    ,  **_UpperCamelCase     :				int)				->Optional[int]:


          """simple docstring"""


          kwargs.update(self.special_tokens_map)
          return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname    ,  **_UpperCamelCase)



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any]    ,  _UpperCamelCase     :				List[Any])				->List[Any]:


          """simple docstring"""


          _lowerCamelCase     :		Any 						=						"""adapt act apte"""
          _lowerCamelCase     :		Any 						=						"""adapt act apte"""
          return input_text, output_text



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[int])				->Union[str, Any]:


          """simple docstring"""


          _lowerCamelCase     :		List[str] 						=						BlenderbotSmallTokenizer(self.vocab_file    ,  self.merges_file    ,  **self.special_tokens_map)
          _lowerCamelCase     :		Any 						=						"""adapt act apte"""
          _lowerCamelCase     :		List[Any] 						=						["""adapt""", """act""", """ap@@""", """te"""]
          _lowerCamelCase     :		Union[str, Any] 						=						tokenizer.tokenize(_UpperCamelCase)
          self.assertListEqual(_UpperCamelCase    ,  _UpperCamelCase)

          _lowerCamelCase     :		int 						=						[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

          _lowerCamelCase     :		List[str] 						=						[0, 1, 2, 3, 4, 5]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase)    ,  _UpperCamelCase)



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any])				->Optional[int]:


          """simple docstring"""


          _lowerCamelCase     :		Optional[int] 						=						BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M""")
          assert tok("""sam""").input_ids == [1384]
          _lowerCamelCase     :		int 						=						"""I am a small frog."""
          _lowerCamelCase     :		Tuple 						=						tok([src_text]    ,  padding=_UpperCamelCase    ,  truncation=_UpperCamelCase)["""input_ids"""]
          _lowerCamelCase     :		List[Any] 						=						tok.batch_decode(_UpperCamelCase    ,  skip_special_tokens=_UpperCamelCase    ,  clean_up_tokenization_spaces=_UpperCamelCase)[0]
          assert src_text != decoded  # I wish it did!
          assert decoded == "i am a small frog ."




      def 	_SCREAMING_SNAKE_CASE    (					self     :				Tuple)				->int:


          """simple docstring"""


          _lowerCamelCase     :		Tuple 						=						BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M""")
          _lowerCamelCase     :		str 						=						"""I am a small frog ."""
          _lowerCamelCase     :		str 						=						"""."""
          _lowerCamelCase     :		Any 						=						tok(_UpperCamelCase)["""input_ids"""]
          _lowerCamelCase     :		Tuple 						=						tok(_UpperCamelCase)["""input_ids"""]

          assert encoded[-1] == encoded_dot[0]





lowerCAmelCase			:							Tuple     =0  # The first color of the flag.
lowerCAmelCase			:							Union[str, Any]     =1  # The second color of the flag.
lowerCAmelCase			:							Any     =2  # The third color of the flag.
lowerCAmelCase			:							List[str]     =(red, white, blue)







def 						A__  (					__A	):







    '''simple docstring'''
    if not sequence:
        return []
    if len(__A	) == 1:
        return list(__A	)
    _lowerCamelCase     :		int 						=						0
    _lowerCamelCase     :		Dict 						=						len(__A	) - 1
    _lowerCamelCase     :		str 						=						0
    while mid <= high:
        if sequence[mid] == colors[0]:
            _lowerCamelCase						,							_lowerCamelCase     :		Tuple 						=						sequence[mid], sequence[low]
            low += 1
            mid += 1
        elif sequence[mid] == colors[1]:
            mid += 1
        elif sequence[mid] == colors[2]:
            _lowerCamelCase						,							_lowerCamelCase     :		str 						=						sequence[high], sequence[mid]
            high -= 1
        else:
            _lowerCamelCase     :		int 						=						F"""The elements inside the sequence must contains only {colors} values"""
            raise ValueError(__A	)
    return sequence


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    lowerCAmelCase			:							List[str]     =input("Enter numbers separated by commas:\n").strip()
    lowerCAmelCase			:							Dict     =[int(item.strip()) for item in user_input.split(",")]
    print(F"""{dutch_national_flag_sort(unsorted)}""")




