


"""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     =  {'vocab_file': 'spm_char.model'}

_lowerCamelCase     =  {
    'vocab_file': {
        'microsoft/speecht5_asr': 'https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model',
        'microsoft/speecht5_tts': 'https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model',
        'microsoft/speecht5_vc': 'https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model',
    }
}

_lowerCamelCase     =  {
    'microsoft/speecht5_asr': 1024,
    'microsoft/speecht5_tts': 1024,
    'microsoft/speecht5_vc': 1024,
}


class 			lowerCamelCase_		(			lowercase   ):





				"""simple docstring"""







				_lowerCAmelCase      :      List[Any]      							=					VOCAB_FILES_NAMES
				_lowerCAmelCase      :      int      							=					PRETRAINED_VOCAB_FILES_MAP
				_lowerCAmelCase      :      List[Any]      							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_lowerCAmelCase      :      int      							=					["input_ids", "attention_mask"]



				def __init__(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__="<s>"       ,		UpperCAmelCase__="</s>"       ,		UpperCAmelCase__="<unk>"       ,		UpperCAmelCase__="<pad>"       ,		UpperCAmelCase__ = None       ,		**UpperCAmelCase__       ,		):
								SCREAMING_SNAKE_CASE__     							=				{} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    bos_token=UpperCAmelCase__       ,		eos_token=UpperCAmelCase__       ,		unk_token=UpperCAmelCase__       ,		pad_token=UpperCAmelCase__       ,		sp_model_kwargs=self.sp_model_kwargs       ,		**UpperCAmelCase__       ,		)

								SCREAMING_SNAKE_CASE__     							=				vocab_file

								SCREAMING_SNAKE_CASE__     							=				spm.SentencePieceProcessor(**self.sp_model_kwargs     )
								self.sp_model.Load(UpperCAmelCase__     )



				@property
				def   lowerCAmelCase__		(						self     ):
								return self.sp_model.get_piece_size()



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				{self.convert_ids_to_tokens(UpperCAmelCase__     ): i for i in range(self.vocab_size     )}
								vocab.update(self.added_tokens_encoder     )
								return vocab



				def __getstate__(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.__dict__.copy()
								SCREAMING_SNAKE_CASE__     							=				None
								return state



				def __setstate__(						self       ,		UpperCAmelCase__     ):
								SCREAMING_SNAKE_CASE__     							=				d

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

								SCREAMING_SNAKE_CASE__     							=				spm.SentencePieceProcessor(**self.sp_model_kwargs     )
								self.sp_model.Load(self.vocab_file     )



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__     ):
								return self.sp_model.encode(UpperCAmelCase__       ,		out_type=UpperCAmelCase__     )



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__     ):
								return self.sp_model.piece_to_id(UpperCAmelCase__     )



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__     ):
								SCREAMING_SNAKE_CASE__     							=				self.sp_model.IdToPiece(UpperCAmelCase__     )
								return token



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__     ):
								SCREAMING_SNAKE_CASE__     							=				[]
								SCREAMING_SNAKE_CASE__     							=				""
								for token in tokens:
												# make sure that special tokens are not decoded using sentencepiece model
												if token in self.all_special_tokens:
																out_string += self.sp_model.decode(UpperCAmelCase__     ) + token
																SCREAMING_SNAKE_CASE__     							=				[]
												else:
																current_sub_tokens.append(UpperCAmelCase__     )
								out_string += self.sp_model.decode(UpperCAmelCase__     )
								return out_string.strip()



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__=None     ):
								if token_ids_a is None:
												return token_ids_a + [self.eos_token_id]
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return token_ids_a + token_ids_a + [self.eos_token_id]



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = False     ):
								if already_has_special_tokens:
												return super().get_special_tokens_mask(
												    token_ids_a=UpperCAmelCase__       ,		token_ids_a=UpperCAmelCase__       ,		already_has_special_tokens=UpperCAmelCase__     )

								SCREAMING_SNAKE_CASE__     							=				[1]
								if token_ids_a is None:
												return ([0] * len(UpperCAmelCase__     )) + suffix_ones
								return ([0] * len(UpperCAmelCase__     )) + ([0] * len(UpperCAmelCase__     )) + suffix_ones






				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = None     ):
								if not os.path.isdir(UpperCAmelCase__     ):
												logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
												return
								SCREAMING_SNAKE_CASE__     							=				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:
																SCREAMING_SNAKE_CASE__     							=				self.sp_model.serialized_model_proto()
																fi.write(UpperCAmelCase__     )

								return (out_vocab_file,)




"""simple docstring"""






from __future__ import annotations


def __lowercase     (      lowerCamelCase_  :      list						,					lowerCamelCase_  :      int						,					lowerCamelCase_  :      int						,					lowerCamelCase_  :      int  ):
				SCREAMING_SNAKE_CASE__     							=				[]
				SCREAMING_SNAKE_CASE__							,      SCREAMING_SNAKE_CASE__     							=				input_list[low:mid], input_list[mid : high + 1]
				while left and right:
								result.append((left if left[0] <= right[0] else right).pop(0  )  )
				SCREAMING_SNAKE_CASE__     							=				result + left + right
				return input_list


def __lowercase     (      lowerCamelCase_  :      list  ):
				if len(lowerCamelCase_  ) <= 1:
								return input_list
				SCREAMING_SNAKE_CASE__     							=				list(lowerCamelCase_  )

				# iteration for two-way merging
				SCREAMING_SNAKE_CASE__     							=				2
				while p <= len(lowerCamelCase_  ):
								# getting low, high and middle value for merge-sort of single list
								for i in range(0						,					len(lowerCamelCase_  )						,					lowerCamelCase_  ):
												SCREAMING_SNAKE_CASE__     							=				i
												SCREAMING_SNAKE_CASE__     							=				i + p - 1
												SCREAMING_SNAKE_CASE__     							=				(low + high + 1) // 2
												SCREAMING_SNAKE_CASE__     							=				merge(lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_  )
								# final merge of last two parts
								if p * 2 >= len(lowerCamelCase_  ):
												SCREAMING_SNAKE_CASE__     							=				i
												SCREAMING_SNAKE_CASE__     							=				merge(lowerCamelCase_						,					0						,					lowerCamelCase_						,					len(lowerCamelCase_  ) - 1  )
												break
								p *= 2

				return input_list


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