




'''simple docstring'''






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_lowerCAmelCase      	=					logging.get_logger(__name__)

_lowerCAmelCase      	=					'''▁'''

_lowerCAmelCase      	=					{'''vocab_file''': '''sentencepiece.bpe.model'''}

_lowerCAmelCase      	=					{
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    }
}

_lowerCAmelCase      	=					{
    '''facebook/xglm-564M''': 2048,
}



class 					A		( snake_case_		):




				'''simple docstring'''





				A      	=				VOCAB_FILES_NAMES
				A      	=				PRETRAINED_VOCAB_FILES_MAP
				A      	=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				A      	=				['''input_ids''', '''attention_mask''']
				def __init__(self ,  _UpperCAmelCase ,  _UpperCAmelCase="<s>" ,  _UpperCAmelCase="</s>" ,  _UpperCAmelCase="</s>" ,  _UpperCAmelCase="<s>" ,  _UpperCAmelCase="<unk>" ,  _UpperCAmelCase="<pad>" ,  _UpperCAmelCase = None ,  **_UpperCAmelCase ,  )	->       None:
							__UpperCamelCase      :			Optional[Any]									=   {} if sp_model_kwargs is None else sp_model_kwargs

							# Compatibility with the original tokenizer
							__UpperCamelCase      :			Optional[Any]									=   7
							__UpperCamelCase      :			Dict									=   [f"<madeupword{i}>" for i in range(self.num_madeup_words			)]

							__UpperCamelCase      :			str									=   kwargs.get("additional_special_tokens" ,  []			)
							kwargs["additional_special_tokens"] += [
							    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
							]

							super().__init__(
							    bos_token=UpperCamelCase__ ,  eos_token=UpperCamelCase__ ,  unk_token=UpperCamelCase__ ,  sep_token=UpperCamelCase__ ,  cls_token=UpperCamelCase__ ,  pad_token=UpperCamelCase__ ,  sp_model_kwargs=self.sp_model_kwargs ,  **UpperCamelCase__ ,  )

							__UpperCamelCase      :			List[str]									=   spm.SentencePieceProcessor(**self.sp_model_kwargs			)
							self.sp_model.Load(str(UpperCamelCase__			)			)
							__UpperCamelCase      :			List[Any]									=   vocab_file

							# Original fairseq vocab and spm vocab must be "aligned":
							# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
							# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
							# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
							# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

							# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
							__UpperCamelCase      :			Union[str, Any]									=   1

							# Mimic fairseq token-to-id alignment for the first 4 token
							__UpperCamelCase      :			Union[str, Any]									=   {"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

							__UpperCamelCase      :			List[str]									=   len(self.sp_model			)
							__UpperCamelCase      :			int									=   {f"<madeupword{i}>": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words			)}
							self.fairseq_tokens_to_ids.update(UpperCamelCase__			)

							__UpperCamelCase      :			str									=   {v: k for k, v in self.fairseq_tokens_to_ids.items()}
				def __getstate__(self			)	->       Dict:
							__UpperCamelCase      :			int									=   self.__dict__.copy()
							__UpperCamelCase      :			Any									=   None
							__UpperCamelCase      :			List[str]									=   self.sp_model.serialized_model_proto()
							return state
				def __setstate__(self ,  _UpperCAmelCase			)	->       Optional[Any]:
							__UpperCamelCase      :			str									=   d

							# for backward compatibility
							if not hasattr(self ,  "sp_model_kwargs"			):
										__UpperCamelCase      :			Dict									=   {}

							__UpperCamelCase      :			List[Any]									=   spm.SentencePieceProcessor(**self.sp_model_kwargs			)
							self.sp_model.LoadFromSerializedProto(self.sp_model_proto			)
				def        a_       (self ,  _UpperCAmelCase ,  _UpperCAmelCase = None			)	->       List[int]:




							if token_ids_a is None:
										return [self.sep_token_id] + token_ids_a
							__UpperCamelCase      :			Tuple									=   [self.sep_token_id]
							return sep + token_ids_a + sep + sep + token_ids_a
				def        a_       (self ,  _UpperCAmelCase ,  _UpperCAmelCase = None ,  _UpperCAmelCase = False			)	->       List[int]:




							if already_has_special_tokens:
										return super().get_special_tokens_mask(
										    token_ids_a=UpperCamelCase__ ,  token_ids_a=UpperCamelCase__ ,  already_has_special_tokens=UpperCamelCase__			)

							if token_ids_a is None:
										return [1] + ([0] * len(UpperCamelCase__			))
							return [1] + ([0] * len(UpperCamelCase__			)) + [1, 1] + ([0] * len(UpperCamelCase__			))
				def        a_       (self ,  _UpperCAmelCase ,  _UpperCAmelCase = None			)	->       List[int]:
							__UpperCamelCase      :			Optional[int]									=   [self.sep_token_id]

							if token_ids_a is None:
										return len(sep + token_ids_a			) * [0]
							return len(sep + token_ids_a + sep + sep + token_ids_a			) * [0]
				@property
				def        a_       (self			)	->       str:
							return len(self.sp_model			) + self.fairseq_offset + self.num_madeup_words
				def        a_       (self			)	->       Optional[Any]:
							__UpperCamelCase      :			Optional[Any]									=   {self.convert_ids_to_tokens(UpperCamelCase__			): i for i in range(self.vocab_size			)}
							vocab.update(self.added_tokens_encoder			)
							return vocab
				def        a_       (self ,  _UpperCAmelCase			)	->       List[str]:
							return self.sp_model.encode(UpperCamelCase__ ,  out_type=UpperCamelCase__			)
				def        a_       (self ,  _UpperCAmelCase			)	->       Dict:




							if token in self.fairseq_tokens_to_ids:
										return self.fairseq_tokens_to_ids[token]
							__UpperCamelCase      :			List[Any]									=   self.sp_model.PieceToId(UpperCamelCase__			)

							# Need to return unknown token if the SP model returned 0
							return spm_id + self.fairseq_offset if spm_id else self.unk_token_id
				def        a_       (self ,  _UpperCAmelCase			)	->       Optional[int]:




							if index in self.fairseq_ids_to_tokens:
										return self.fairseq_ids_to_tokens[index]
							return self.sp_model.IdToPiece(index - self.fairseq_offset			)
				def        a_       (self ,  _UpperCAmelCase			)	->       Dict:
							__UpperCamelCase      :			List[Any]									=   "".join(UpperCamelCase__			).replace(UpperCamelCase__ ,  " "			).strip()
							return out_string





				def        a_       (self ,  _UpperCAmelCase ,  _UpperCAmelCase = None			)	->       Tuple[str]:




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

							if os.path.abspath(self.vocab_file			) != os.path.abspath(UpperCamelCase__			) and os.path.isfile(self.vocab_file			):
										copyfile(self.vocab_file ,  UpperCamelCase__			)
							elif not os.path.isfile(self.vocab_file			):
										with open(UpperCamelCase__ ,  "wb"			) as fi:
													__UpperCamelCase      :			Tuple									=   self.sp_model.serialized_model_proto()
													fi.write(UpperCamelCase__			)

							return (out_vocab_file,)







"""simple docstring"""



def   __lowerCAmelCase						(						lowercase  :  Union[str, Any] )	->						List[str]:


    """simple docstring"""





    snake_case    :      List[str]      					=    len(lowercase )
    for i in range(length - 1 ):
        snake_case    :      List[str]      					=    i
        for k in range(i + 1						,							lowercase ):
            if collection[k] < collection[least]:
                snake_case    :      List[str]      					=    k
        if least != i:
            snake_case					,snake_case    :      Union[str, Any]      					=    (collection[i], collection[least])
    return collection


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





