


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 		_SCREAMING_SNAKE_CASE     (						A							,	unittest.TestCase     ):
     __SCREAMING_SNAKE_CASE     					=    BlenderbotSmallTokenizer
     __SCREAMING_SNAKE_CASE     					=    False


     def        __snake_case(  self    ):
       super().setUp()

       _UpperCAmelCase		:							Dict							=     ["""__start__""", """adapt""", """act""", """ap@@""", """te""", """__end__""", """__unk__"""]
       _UpperCAmelCase		:							List[str]							=     dict(zip(A_							,					range(len(A_    )    )    )    )

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

       _UpperCAmelCase		:							List[str]							=     os.path.join(self.tmpdirname							,					VOCAB_FILES_NAMES["""vocab_file"""]    )
       _UpperCAmelCase		:							List[Any]							=     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(A_    ) + """\n"""    )
       with open(self.merges_file							,					"""w"""							,					encoding="""utf-8"""    ) as fp:
         fp.write("""\n""".join(A_    )    )


     def        __snake_case(  self							,					**A_    ):
       kwargs.update(self.special_tokens_map    )
       return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname							,					**A_    )


     def        __snake_case(  self							,					A_    ):
       _UpperCAmelCase		:							Dict							=     """adapt act apte"""
       _UpperCAmelCase		:							Dict							=     """adapt act apte"""
       return input_text, output_text


     def        __snake_case(  self    ):
       _UpperCAmelCase		:							int							=     BlenderbotSmallTokenizer(self.vocab_file							,					self.merges_file							,					**self.special_tokens_map    )
       _UpperCAmelCase		:							List[str]							=     """adapt act apte"""
       _UpperCAmelCase		:							List[Any]							=     ["""adapt""", """act""", """ap@@""", """te"""]
       _UpperCAmelCase		:							Dict							=     tokenizer.tokenize(A_    )
       self.assertListEqual(A_							,					A_    )

       _UpperCAmelCase		:							Tuple							=     [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

       _UpperCAmelCase		:							int							=     [0, 1, 2, 3, 4, 5]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(A_    )							,					A_    )


     def        __snake_case(  self    ):
       _UpperCAmelCase		:							int							=     BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M"""    )
       assert tok("""sam"""    ).input_ids == [13_84]
       _UpperCAmelCase		:							int							=     """I am a small frog."""
       _UpperCAmelCase		:							Optional[int]							=     tok([src_text]							,					padding=A_							,					truncation=A_    )["""input_ids"""]
       _UpperCAmelCase		:							Any							=     tok.batch_decode(A_							,					skip_special_tokens=A_							,					clean_up_tokenization_spaces=A_    )[0]
       assert src_text != decoded  # I wish it did!
       assert decoded == "i am a small frog ."




     def        __snake_case(  self    ):
       _UpperCAmelCase		:							int							=     BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M"""    )
       _UpperCAmelCase		:							List[str]							=     """I am a small frog ."""
       _UpperCAmelCase		:							str							=     """."""
       _UpperCAmelCase		:							Dict							=     tok(A_    )["""input_ids"""]
       _UpperCAmelCase		:							Any							=     tok(A_    )["""input_ids"""]

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









from __future__ import annotations




def    a__    (		snake_case__					:							list[int]     ):
  if len(snake_case__     ) == 0:
    return array

  _UpperCAmelCase,_UpperCAmelCase		:							List[str]							=     min(snake_case__     ), max(snake_case__     )

  # Compute the variables
  _UpperCAmelCase		:							Tuple							=     _max - _min + 1
  _UpperCAmelCase,_UpperCAmelCase		:							Union[str, Any]							=     [0] * holes_range, [0] * holes_range

  # Make the sorting.
  for i in array:
    _UpperCAmelCase		:							Optional[int]							=     i - _min
    _UpperCAmelCase		:							Any							=     i
    holes_repeat[index] += 1

  # Makes the array back by replacing the numbers.
  _UpperCAmelCase		:							List[Any]							=     0
  for i in range(snake_case__     ):
    while holes_repeat[i] > 0:
      _UpperCAmelCase		:							Optional[Any]							=     holes[i]
      index += 1
      holes_repeat[i] -= 1

    # Returns the sorted array.
  return array


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 SCREAMING_SNAKE_CASE__					:     Dict       =     input('Enter numbers separated by comma:\n')
 SCREAMING_SNAKE_CASE__					:     Optional[int]       =     [int(x) for x in user_input.split(',')]
 print(pigeon_sort(unsorted))





