





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:	Any = logging.get_logger(__name__)

__UpperCamelCase:	Union[str, Any] = """▁"""

__UpperCamelCase:	Any = {"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

__UpperCamelCase:	Dict = {
    """vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model""",
    },
    """monolingual_vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt""",
    },
}

__UpperCamelCase:	Dict = {"""vinai/bartpho-syllable""": 1_0_2_4}


class       __lowerCAmelCase					(       _UpperCamelCase      ):


	'''simple docstring'''





	_A													=				VOCAB_FILES_NAMES
	_A													=				PRETRAINED_VOCAB_FILES_MAP
	_A													=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A													=				["input_ids", "attention_mask"]

	def __init__(						self:						Dict,					lowerCamelCase_:						List[Any],					lowerCamelCase_:						List[str],					lowerCamelCase_:						Union[str, Any]="<s>",					lowerCamelCase_:						Dict="</s>",					lowerCamelCase_:						Dict="</s>",					lowerCamelCase_:						Dict="<s>",					lowerCamelCase_:						Dict="<unk>",					lowerCamelCase_:						Union[str, Any]="<pad>",					lowerCamelCase_:						str="<mask>",					lowerCamelCase_:						Optional[Dict[str, Any]] = None,					**lowerCamelCase_:						List[str],					):
			# Mask token behave like a normal word, i.e. include the space before it
			lowercase__					:      str      =		AddedToken(lowerCamelCase_,					lstrip=lowerCamelCase_,					rstrip=lowerCamelCase_			) if isinstance(lowerCamelCase_,					lowerCamelCase_			) else mask_token

			lowercase__					:      List[str]      =		{} if sp_model_kwargs is None else sp_model_kwargs

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

			lowercase__					:      Union[str, Any]      =		vocab_file
			lowercase__					:      int      =		monolingual_vocab_file
			lowercase__					:      List[Any]      =		spm.SentencePieceProcessor(**self.sp_model_kwargs			)
			self.sp_model.Load(str(lowerCamelCase_			)			)

			# Load the reduced vocab

			# Keep order of special tokens for backward compatibility
			lowercase__					:      str      =		{}
			lowercase__					:      Dict      =		0
			for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
					if str(lowerCamelCase_			) not in self.fairseq_tokens_to_ids:
							lowercase__					:      List[Any]      =		cnt
							cnt += 1
			with open(lowerCamelCase_,					'r',					encoding='utf-8'			) as f:
					for line in f.readlines():
							lowercase__					:      str      =		line.strip().split()[0]
							lowercase__					:      Dict      =		len(self.fairseq_tokens_to_ids			)
			if str(lowerCamelCase_			) not in self.fairseq_tokens_to_ids:
					lowercase__					:      Optional[Any]      =		len(self.fairseq_tokens_to_ids			)

			lowercase__					:      Union[str, Any]      =		{v: k for k, v in self.fairseq_tokens_to_ids.items()}

	def __getstate__(						self:						Tuple			):
			lowercase__					:      Dict      =		self.__dict__.copy()
			lowercase__					:      List[Any]      =		None
			lowercase__					:      Optional[int]      =		self.sp_model.serialized_model_proto()
			return state

	def __setstate__(						self:						Optional[int],					lowerCamelCase_:						Tuple			):
			lowercase__					:      Optional[int]      =		d

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

			lowercase__					:      Tuple      =		spm.SentencePieceProcessor(**self.sp_model_kwargs			)
			self.sp_model.LoadFromSerializedProto(self.sp_model_proto			)

	def    snake_case__(						self:						Union[str, Any],					lowerCamelCase_:						List[int],					lowerCamelCase_:						Optional[List[int]] = None			):

			if token_ids_a is None:
					return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
			lowercase__					:      Optional[int]      =		[self.cls_token_id]
			lowercase__					:      Tuple      =		[self.sep_token_id]
			return cls + token_ids_a + sep + sep + token_ids_a + sep

	def    snake_case__(						self:						int,					lowerCamelCase_:						List[int],					lowerCamelCase_:						Optional[List[int]] = None,					lowerCamelCase_:						bool = False			):

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

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

	def    snake_case__(						self:						Optional[int],					lowerCamelCase_:						List[int],					lowerCamelCase_:						Optional[List[int]] = None			):
			lowercase__					:      Tuple      =		[self.sep_token_id]
			lowercase__					:      Optional[Any]      =		[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    snake_case__(						self:						str			):
			return len(self.fairseq_ids_to_tokens			)

	def    snake_case__(						self:						List[Any]			):
			lowercase__					:      str      =		{self.convert_ids_to_tokens(lowerCamelCase_			): i for i in range(self.vocab_size			)}
			vocab.update(self.added_tokens_encoder			)
			return vocab

	def    snake_case__(						self:						Any,					lowerCamelCase_:						str			):
			return self.sp_model.encode(lowerCamelCase_,					out_type=lowerCamelCase_			)

	def    snake_case__(						self:						Any,					lowerCamelCase_:						Any			):
			if token in self.fairseq_tokens_to_ids:
					return self.fairseq_tokens_to_ids[token]
			else:
					return self.unk_token_id

	def    snake_case__(						self:						str,					lowerCamelCase_:						int			):
			return self.fairseq_ids_to_tokens[index]

	def    snake_case__(						self:						Union[str, Any],					lowerCamelCase_:						str			):
			lowercase__					:      Any      =		''.join(lowerCamelCase_			).replace(lowerCamelCase_,					' '			).strip()
			return out_string





	def    snake_case__(						self:						List[str],					lowerCamelCase_:						str,					lowerCamelCase_:						Optional[str] = None			):
			if not os.path.isdir(lowerCamelCase_			):
					logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""			)
					return
			lowercase__					:      Optional[int]      =		os.path.join(
			    lowerCamelCase_,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)
			lowercase__					:      Union[str, Any]      =		os.path.join(
			    lowerCamelCase_,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['monolingual_vocab_file'],					)

			if os.path.abspath(self.vocab_file			) != os.path.abspath(lowerCamelCase_			) and os.path.isfile(self.vocab_file			):
					copyfile(self.vocab_file,					lowerCamelCase_			)
			elif not os.path.isfile(self.vocab_file			):
					with open(lowerCamelCase_,					'wb'			) as fi:
							lowercase__					:      Union[str, Any]      =		self.sp_model.serialized_model_proto()
							fi.write(lowerCamelCase_			)

			if os.path.abspath(self.monolingual_vocab_file			) != os.path.abspath(
			    lowerCamelCase_			) and os.path.isfile(self.monolingual_vocab_file			):
					copyfile(self.monolingual_vocab_file,					lowerCamelCase_			)
			elif not os.path.isfile(self.monolingual_vocab_file			):
					with open(lowerCamelCase_,					'w',					encoding='utf-8'			) as fp:
							for token in self.fairseq_tokens_to_ids:
									if token not in self.all_special_tokens:
											fp.write(F"""{str(lowerCamelCase_			)} \n"""			)

			return out_vocab_file, out_monolingual_vocab_file









from ..utils import DummyObject, requires_backends


class       __lowerCAmelCase					(       metaclass=_UpperCamelCase      ):


	'''simple docstring'''





	_A													=				["note_seq"]

	def __init__(						self:						int,					*lowerCamelCase_:						Optional[int],					**lowerCamelCase_:						Tuple			):
			requires_backends(self,					['note_seq']			)

	@classmethod
	def    snake_case__(						cls:						Optional[Any],					*lowerCamelCase_:						Tuple,					**lowerCamelCase_:						Optional[Any]			):
			requires_backends(cls,					['note_seq']			)





	@classmethod
	def    snake_case__(						cls:						Any,					*lowerCamelCase_:						Dict,					**lowerCamelCase_:						str			):
			requires_backends(cls,					['note_seq']			)


