



'''simple docstring'''

import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_ta import TaTokenizer
else:
				UpperCAmelCase     		=   None


UpperCAmelCase     		=   logging.get_logger(__name__)

UpperCAmelCase     		=   {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

UpperCAmelCase     		=   {
    'vocab_file': {
        't5-small': 'https://huggingface.co/t5-small/resolve/main/spiece.model',
        't5-base': 'https://huggingface.co/t5-base/resolve/main/spiece.model',
        't5-large': 'https://huggingface.co/t5-large/resolve/main/spiece.model',
        't5-3b': 'https://huggingface.co/t5-3b/resolve/main/spiece.model',
        't5-11b': 'https://huggingface.co/t5-11b/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        't5-small': 'https://huggingface.co/t5-small/resolve/main/tokenizer.json',
        't5-base': 'https://huggingface.co/t5-base/resolve/main/tokenizer.json',
        't5-large': 'https://huggingface.co/t5-large/resolve/main/tokenizer.json',
        't5-3b': 'https://huggingface.co/t5-3b/resolve/main/tokenizer.json',
        't5-11b': 'https://huggingface.co/t5-11b/resolve/main/tokenizer.json',
    },
}


# TODO(PVP) - this should be removed in Transformers v5
UpperCAmelCase     		=   {
    't5-small': 512,
    't5-base': 512,
    't5-large': 512,
    't5-3b': 512,
    't5-11b': 512,
}

class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						UpperCAmelCase							:   Dict									=		VOCAB_FILES_NAMES
						UpperCAmelCase							:   Optional[Any]									=		PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase							:   List[str]									=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase							:   Optional[int]									=		["input_ids", "attention_mask"]
						UpperCAmelCase							:   List[Any]									=		TaTokenizer

						UpperCAmelCase							:   List[int]									=		[]


						def __init__( self     ,	A_=None     ,	A_=None     ,	A_="</s>"     ,	A_="<unk>"     ,	A_="<pad>"     ,	A_=100     ,	A_=None     ,	**A_     ,	)     ->     List[str]:
							# Add extra_ids to the special token list
							if extra_ids > 0 and additional_special_tokens is None:
								lowerCAmelCase   =     [f'<extra_id_{i}>' for i in range(A_				)]
							elif extra_ids > 0 and additional_special_tokens is not None:
								# Check that we have the right number of extra special tokens
								lowerCAmelCase   =     len(set(filter(lambda A_				: bool("""extra_id_""" in str(A_				)				)     ,	A_				)				)				)
								if extra_tokens != extra_ids:
									raise ValueError(
									    f'Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are'
									    """ provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids"""
									    """ tokens"""				)

							super().__init__(
							    A_     ,	tokenizer_file=A_     ,	eos_token=A_     ,	unk_token=A_     ,	pad_token=A_     ,	extra_ids=A_     ,	additional_special_tokens=A_     ,	**A_     ,	)

							lowerCAmelCase   =     vocab_file
							lowerCAmelCase   =     False if not self.vocab_file else True
							lowerCAmelCase   =     extra_ids


						@staticmethod
						def     __snake_case   ( A_     ,	A_     ,	A_				)     ->     Any:
							if pretrained_model_name_or_path in TaTokenizerFast.max_model_input_sizes:
								lowerCAmelCase   =     TaTokenizerFast.max_model_input_sizes[pretrained_model_name_or_path]
								if init_max_model_length is not None and init_max_model_length != max_model_length:
									return init_max_model_length
								elif init_max_model_length is None:
									warnings.warn(
									    """This tokenizer was incorrectly instantiated with a model max length of"""
									    f' {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this'
									    """ behavior is kept to avoid breaking backwards compatibility when padding/encoding with"""
									    """ `truncation is True`.\n- Be aware that you SHOULD NOT rely on"""
									    f' {pretrained_model_name_or_path} automatically truncating your input to'
									    f' {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences'
									    f' longer than {deprecated_max_model_length} you can either instantiate this tokenizer with'
									    """ `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please"""
									    """ instantiate this tokenizer with `model_max_length` set to your preferred value."""     ,	A_     ,	)

							return max_model_length


						def     __snake_case   ( self     ,	A_     ,	A_ = None				)     ->     Tuple[str]:
							if not self.can_save_slow_tokenizer:
								raise ValueError(
								    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
								    """tokenizer."""				)

							if not os.path.isdir(A_				):
								logger.error(f'Vocabulary path ({save_directory}) should be a directory'				)
								return
							lowerCAmelCase   =     os.path.join(
							    A_     ,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

							if os.path.abspath(self.vocab_file				) != os.path.abspath(A_				):
								copyfile(self.vocab_file     ,	A_				)
								logger.info(f'Copy vocab file to {out_vocab_file}'				)

							return (out_vocab_file,)


						def     __snake_case   ( self     ,	A_     ,	A_ = None				)     ->     List[int]:
							lowerCAmelCase   =     token_ids_a + [self.eos_token_id]
							if token_ids_a is None:
								return self.prefix_tokens + token_ids_a
							else:
								lowerCAmelCase   =     token_ids_a + [self.eos_token_id]
								return self.prefix_tokens + token_ids_a + token_ids_a


						def     __snake_case   ( self     ,	A_     ,	A_ = None				)     ->     List[int]:
							lowerCAmelCase   =     [self.eos_token_id]

							if token_ids_a is None:
								return len(token_ids_a + eos				) * [0]
							return len(token_ids_a + eos + token_ids_a + eos				) * [0]


						def     __snake_case   ( self				)     ->     str:
							return list(
							    set(filter(lambda A_				: bool(re.search(r"""<extra_id_\d+>"""     ,	A_				)				) is not None     ,	self.additional_special_tokens				)				)				)




						def     __snake_case   ( self				)     ->     int:
							return [self.convert_tokens_to_ids(A_				) for token in self.get_sentinel_tokens()]




'''simple docstring'''

def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						list							)      ->						list:







	"""simple docstring"""

	if len(_SCREAMING_SNAKE_CASE							) < 2:
		return collection

	def circle_sort_util(_SCREAMING_SNAKE_CASE					:						list							,		_SCREAMING_SNAKE_CASE					:						int							,		_SCREAMING_SNAKE_CASE					:						int							) -> bool:
		lowerCAmelCase   =     False

		if low == high:
			return swapped

		lowerCAmelCase   =     low
		lowerCAmelCase   =     high

		while left < right:
			if collection[left] > collection[right]:
				lowerCAmelCase,       lowerCAmelCase   =     (
				    collection[right],
				    collection[left],
				)
				lowerCAmelCase   =     True

			left += 1
			right -= 1

		if left == right and collection[left] > collection[right + 1]:
			lowerCAmelCase,       lowerCAmelCase   =     (
			    collection[right + 1],
			    collection[left],
			)

			lowerCAmelCase   =     True

		lowerCAmelCase   =     low + int((high - low) / 2							)
		lowerCAmelCase   =     circle_sort_util(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)
		lowerCAmelCase   =     circle_sort_util(_SCREAMING_SNAKE_CASE							,		mid + 1							,		_SCREAMING_SNAKE_CASE							)

		return swapped or left_swap or right_swap

	lowerCAmelCase   =     True

	while is_not_sorted is True:
		lowerCAmelCase   =     circle_sort_util(_SCREAMING_SNAKE_CASE							,		0							,		len(_SCREAMING_SNAKE_CASE							) - 1							)

	return collection


if __name__ == "__main__":
				UpperCAmelCase     		=   input('Enter numbers separated by a comma:\n').strip()
				UpperCAmelCase     		=   [int(item) for item in user_input.split(',')]
				print(circle_sort(unsorted))