





from __future__ import annotations

from random import randrange





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE							)       ->   list:




    """simple docstring"""




    if len(_SCREAMING_SNAKE_CASE							) < 2:
        return collection
    _A    =       randrange(len(_SCREAMING_SNAKE_CASE							)							)  # Use random element as pivot
    _A    =       collection[pivot_index]
    _A    =       []  # All elements greater than pivot
    _A    =       []  # All elements less than or equal to pivot

    for element in collection[:pivot_index]:
        (greater if element > pivot else lesser).append(_SCREAMING_SNAKE_CASE							)

    for element in collection[pivot_index + 1 :]:
        (greater if element > pivot else lesser).append(_SCREAMING_SNAKE_CASE							)

    return [*quick_sort(_SCREAMING_SNAKE_CASE							), pivot, *quick_sort(_SCREAMING_SNAKE_CASE							)]


if __name__ == "__main__":
 __A       : Optional[int]						    = input("Enter numbers separated by a comma:\n").strip()
 __A       : List[str]						    = [int(item) for item in user_input.split(",")]
 print(quick_sort(unsorted))












from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest







@require_tokenizers
class     lowerCamelCase(	__snake_case  ):
     '''simple docstring'''


     __magic_name__        = SqueezeBertTokenizer
     __magic_name__        = SqueezeBertTokenizerFast
     __magic_name__        = True




     def 					lowerCAmelCase__		(						self							,    **snake_case_       ):
         return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname							,    **snake_case_       )




     @slow
     def 					lowerCAmelCase__		(						self       ):
         _A    =       SqueezeBertTokenizer.from_pretrained('squeezebert/squeezebert-mnli-headless'       )

         _A    =       tokenizer.encode('sequence builders'							,    add_special_tokens=snake_case_       )
         _A    =       tokenizer.encode('multi-sequence build'							,    add_special_tokens=snake_case_       )

         _A    =       tokenizer.build_inputs_with_special_tokens(snake_case_       )
         _A    =       tokenizer.build_inputs_with_special_tokens(snake_case_							,    snake_case_       )

         assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
         assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
             tokenizer.sep_token_id
         ]





