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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_UpperCAmelCase :			Union[str, Any]              =	logging.get_logger(__name__)

_UpperCAmelCase :			Dict              =	{"vocab_file": "sentencepiece.bpe.model"}

_UpperCAmelCase :			List[str]              =	{
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

_UpperCAmelCase :			List[Any]              =	{
    "camembert-base": 512,
}

_UpperCAmelCase :			List[str]              =	"▁"


class     lowercase (		_SCREAMING_SNAKE_CASE       ):
		__lowercase	:	Tuple     					=    VOCAB_FILES_NAMES
		__lowercase	:	int     					=    PRETRAINED_VOCAB_FILES_MAP
		__lowercase	:	Tuple     					=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		__lowercase	:	str     					=    ["input_ids", "attention_mask"]



		def __init__(			self    ,				A_    ,				A_="<s>"    ,				A_="</s>"    ,				A_="</s>"    ,				A_="<s>"    ,				A_="<unk>"    ,				A_="<pad>"    ,				A_="<mask>"    ,				A_=["<s>NOTUSED", "</s>NOTUSED"]    ,				A_ = None    ,				**A_    ,				)  -> None:
				"""simple docstring"""
				# Mask token behave like a normal word, i.e. include the space before it
				UpperCamelCase          =					AddedToken(A_    ,				lstrip=A_    ,				rstrip=A_	) if isinstance(A_    ,				A_	) else mask_token

				UpperCamelCase          =					{} if sp_model_kwargs is None else sp_model_kwargs

				super().__init__(
				    bos_token=A_    ,				eos_token=A_    ,				unk_token=A_    ,				sep_token=A_    ,				cls_token=A_    ,				pad_token=A_    ,				mask_token=A_    ,				additional_special_tokens=A_    ,				sp_model_kwargs=self.sp_model_kwargs    ,				**A_    ,				)
				UpperCamelCase          =					spm.SentencePieceProcessor(**self.sp_model_kwargs	)
				self.sp_model.Load(str(A_	)	)
				UpperCamelCase          =					vocab_file
				# HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
				# sentencepiece vocabulary (this is the case for <s> and </s>
				UpperCamelCase          =					{'<s>NOTUSED': 0, '<pad>': 1, '</s>NOTUSED': 2, '<unk>': 3}
				UpperCamelCase          =					len(self.fairseq_tokens_to_ids	)
				UpperCamelCase          =					len(self.sp_model	) + len(self.fairseq_tokens_to_ids	)
				UpperCamelCase          =					{v: k for k, v in self.fairseq_tokens_to_ids.items()}



		def __UpperCamelCase			(			self    ,				A_    ,				A_ = None	)  -> List[int]:
				"""simple docstring"""

				if token_ids_a is None:
						return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
				UpperCamelCase          =					[self.cls_token_id]
				UpperCamelCase          =					[self.sep_token_id]
				return cls + token_ids_a + sep + sep + token_ids_a + sep



		def __UpperCamelCase			(			self    ,				A_    ,				A_ = None    ,				A_ = False	)  -> List[int]:
				"""simple docstring"""
				if already_has_special_tokens:
						return super().get_special_tokens_mask(
						    token_ids_a=A_    ,				token_ids_a=A_    ,				already_has_special_tokens=A_	)

				if token_ids_a is None:
						return [1] + ([0] * len(A_	)) + [1]
				return [1] + ([0] * len(A_	)) + [1, 1] + ([0] * len(A_	)) + [1]



		def __UpperCamelCase			(			self    ,				A_    ,				A_ = None	)  -> List[int]:
				"""simple docstring"""
				UpperCamelCase          =					[self.sep_token_id]
				UpperCamelCase          =					[self.cls_token_id]

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



		@property
		def __UpperCamelCase			(			self	)  -> str:
				"""simple docstring"""
				return len(self.fairseq_tokens_to_ids	) + len(self.sp_model	)



		def __UpperCamelCase			(			self	)  -> Any:
				"""simple docstring"""
				UpperCamelCase          =					{self.convert_ids_to_tokens(A_	): i for i in range(self.vocab_size	)}
				vocab.update(self.added_tokens_encoder	)
				return vocab



		def __UpperCamelCase			(			self    ,				A_	)  -> List[str]:
				"""simple docstring"""
				return self.sp_model.encode(A_    ,				out_type=A_	)



		def __UpperCamelCase			(			self    ,				A_	)  -> Union[str, Any]:
				"""simple docstring"""
				if token in self.fairseq_tokens_to_ids:
						return self.fairseq_tokens_to_ids[token]
				elif self.sp_model.PieceToId(A_	) == 0:
						# Convert sentence piece unk token to fairseq unk token index
						return self.unk_token_id
				return self.fairseq_offset + self.sp_model.PieceToId(A_	)



		def __UpperCamelCase			(			self    ,				A_	)  -> Optional[int]:
				"""simple docstring"""
				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 __UpperCamelCase			(			self    ,				A_	)  -> int:
				"""simple docstring"""
				UpperCamelCase          =					[]
				UpperCamelCase          =					''
				UpperCamelCase          =					False
				for token in tokens:
						# make sure that special tokens are not decoded using sentencepiece model
						if token in self.all_special_tokens:
								if not prev_is_special:
										out_string += " "
								out_string += self.sp_model.decode(A_	) + token
								UpperCamelCase          =					True
								UpperCamelCase          =					[]
						else:
								current_sub_tokens.append(A_	)
								UpperCamelCase          =					False
				out_string += self.sp_model.decode(A_	)
				return out_string.strip()



		def __getstate__(			self	)  -> Any:
				"""simple docstring"""
				UpperCamelCase          =					self.__dict__.copy()
				UpperCamelCase          =					None
				return state



		def __setstate__(			self    ,				A_	)  -> int:
				"""simple docstring"""
				UpperCamelCase          =					d

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

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



		def __UpperCamelCase			(			self    ,				A_    ,				A_ = None	)  -> Tuple[str]:
				"""simple docstring"""
				if not os.path.isdir(A_	):
						logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''	)
						return
				UpperCamelCase          =					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_	) and os.path.isfile(self.vocab_file	):
						copyfile(self.vocab_file    ,				A_	)
				elif not os.path.isfile(self.vocab_file	):
						with open(A_    ,				'wb'	) as fi:
								UpperCamelCase          =					self.sp_model.serialized_model_proto()
								fi.write(A_	)

				return (out_vocab_file,)


from __future__ import annotations


def 				A	( lowercase   ,	lowercase   ,	lowercase   ,	lowercase			)       ->  list:
		'''simple docstring'''

		UpperCamelCase          =					[]
		UpperCamelCase     ,  UpperCamelCase          =					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			)			)
		UpperCamelCase          =					result + left + right
		return input_list


def 				A	( lowercase			)       ->  list:
		'''simple docstring'''

		if len(lowercase			) <= 1:
				return input_list
		UpperCamelCase          =					list(lowercase			)

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

		return input_list


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