






import random







def 	_UpperCamelCase   (    UpperCamelCase_       :					Any    ,       UpperCamelCase_       :					Union[str, Any]    ,       UpperCamelCase_       :					Optional[Any]		)  ->   Union[str, Any]:

						"""simple docstring"""



						lowerCAmelCase__    						=						a[left_index]
						lowerCAmelCase__    						=						left_index + 1
						for j in range(left_index + 1    ,       _A		):
												if a[j] < pivot:
																		lowerCAmelCase__						,       lowerCAmelCase__    						=						a[i], a[j]
																		i += 1
						lowerCAmelCase__						,       lowerCAmelCase__    						=						a[i - 1], a[left_index]
						return i - 1







def 	_UpperCamelCase   (    UpperCamelCase_       :					Any    ,       UpperCamelCase_       :					Union[str, Any]    ,       UpperCamelCase_       :					Tuple		)  ->   List[Any]:

						"""simple docstring"""



						if left < right:
												lowerCAmelCase__    						=						random.randint(_A    ,       right - 1		)
												lowerCAmelCase__						,       lowerCAmelCase__    						=						(
												    a[left],
												    a[pivot],
												)  # switches the pivot with the left most bound
												lowerCAmelCase__    						=						partition(_A    ,       _A    ,       _A		)
												quick_sort_random(
												    _A    ,       _A    ,       _A		)  # recursive quicksort to the left of the pivot point
												quick_sort_random(
												    _A    ,       pivot_index + 1    ,       _A		)  # recursive quicksort to the right of the pivot point







def 	_UpperCamelCase   (    )  ->   str:

						"""simple docstring"""



						lowerCAmelCase__    						=						input('Enter numbers separated by a comma:\n'		).strip()
						lowerCAmelCase__    						=						[int(_A		) for item in user_input.split(','		)]

						quick_sort_random(_A    ,       0    ,       len(_A		)		)

						print(_A		)


if __name__ == "__main__":
					main()













import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
					from transformers.pipelines.conversational import Conversation


__snake_case    :    Any         =     logging.get_logger(__name__)

__snake_case    :    Tuple         =     {"""tokenizer_file""": """tokenizer.json"""}

__snake_case    :    str         =     {
    """tokenizer_file""": {
        """bigscience/tokenizer""": """https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json""",
        """bigscience/bloom-560m""": """https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json""",
        """bigscience/bloom-1b1""": """https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json""",
        """bigscience/bloom-1b7""": """https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json""",
        """bigscience/bloom-3b""": """https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json""",
        """bigscience/bloom-7b1""": """https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json""",
        """bigscience/bloom""": """https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json""",
    },
}


class     __SCREAMING_SNAKE_CASE					(   __lowercase):
						_SCREAMING_SNAKE_CASE	:       Dict   =					VOCAB_FILES_NAMES
						_SCREAMING_SNAKE_CASE	:       Union[str, Any]   =					PRETRAINED_VOCAB_FILES_MAP
						_SCREAMING_SNAKE_CASE	:       Union[str, Any]   =					['''input_ids''', '''attention_mask''']
						_SCREAMING_SNAKE_CASE	:       Union[str, Any]   =					None






						def __init__(	self     ,						_UpperCamelCase=None     ,						_UpperCamelCase=None     ,						_UpperCamelCase=None     ,						_UpperCamelCase="<unk>"     ,						_UpperCamelCase="<s>"     ,						_UpperCamelCase="</s>"     ,						_UpperCamelCase="<pad>"     ,						_UpperCamelCase=False     ,						_UpperCamelCase=False     ,						**_UpperCamelCase     ,						):






												"""simple docstring"""
												super().__init__(
												    _UpperCamelCase     ,						_UpperCamelCase     ,						tokenizer_file=_UpperCamelCase     ,						unk_token=_UpperCamelCase     ,						bos_token=_UpperCamelCase     ,						eos_token=_UpperCamelCase     ,						pad_token=_UpperCamelCase     ,						add_prefix_space=_UpperCamelCase     ,						clean_up_tokenization_spaces=_UpperCamelCase     ,						**_UpperCamelCase     ,						)
												lowerCAmelCase__    						=						json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
												if pre_tok_state.get('add_prefix_space'     ,						_UpperCamelCase   ) != add_prefix_space:
																		lowerCAmelCase__    						=						getattr(_UpperCamelCase     ,						pre_tok_state.pop('type'   )   )
																		lowerCAmelCase__    						=						add_prefix_space
																		lowerCAmelCase__    						=						pre_tok_class(**_UpperCamelCase   )

												lowerCAmelCase__    						=						add_prefix_space






						def       UpperCamelCase__      (	self     ,						*_UpperCamelCase     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						kwargs.get('is_split_into_words'     ,						_UpperCamelCase   )
												if not (self.add_prefix_space or not is_split_into_words):
																		raise Exception(
																		    F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"
																		    ' pretokenized inputs.'   )

												return super()._batch_encode_plus(*_UpperCamelCase     ,						**_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						*_UpperCamelCase     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						kwargs.get('is_split_into_words'     ,						_UpperCamelCase   )

												if not (self.add_prefix_space or not is_split_into_words):
																		raise Exception(
																		    F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"
																		    ' pretokenized inputs.'   )

												return super()._encode_plus(*_UpperCamelCase     ,						**_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						_UpperCamelCase     ,						_UpperCamelCase = None   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self._tokenizer.model.save(_UpperCamelCase     ,						name=_UpperCamelCase   )
												return tuple(_UpperCamelCase   )







						def       UpperCamelCase__      (	self     ,						_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						[]
												for is_user, text in conversation.iter_texts():
																		input_ids.extend(self.encode(_UpperCamelCase     ,						add_special_tokens=_UpperCamelCase   ) + [self.eos_token_id]   )

												if len(_UpperCamelCase   ) > self.model_max_length:
																		lowerCAmelCase__    						=						input_ids[-self.model_max_length :]
												return input_ids





