




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


__lowerCamelCase   :						List[str]				=			logging.get_logger(__name__)

__lowerCamelCase   :						Tuple				=			'''▁'''

__lowerCamelCase   :						Dict				=			{'''vocab_file''': '''sentencepiece.bpe.model''', '''monolingual_vocab_file''': '''dict.txt'''}

__lowerCamelCase   :						List[str]				=			{
    '''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''',
    },
}

__lowerCamelCase   :						Optional[Any]				=			{'''vinai/bartpho-syllable''': 10_24}


class    lowerCamelCase    (		_lowerCamelCase						):






			'''simple docstring'''





			UpperCamelCase__								=VOCAB_FILES_NAMES
			UpperCamelCase__								=PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase__								=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase__								=['''input_ids''', '''attention_mask''']

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

								__magic_name__							:	Tuple    							=							{} 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_       ,						)

								__magic_name__							:	List[str]    							=							vocab_file
								__magic_name__							:	Dict    							=							monolingual_vocab_file
								__magic_name__							:	Dict    							=							spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(str(lowerCamelCase_  )  )

								# Load the reduced vocab

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

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

			def __getstate__( self			:   List[Any]  )						->   Any:
								__magic_name__							:	List[Any]    							=							self.__dict__.copy()
								__magic_name__							:	List[Any]    							=							None
								__magic_name__							:	Tuple    							=							self.sp_model.serialized_model_proto()
								return state

			def __setstate__( self			:   Any       ,						lowerCamelCase_			:   List[Any]  )						->   Tuple:
								__magic_name__							:	List[Any]    							=							d

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

								__magic_name__							:	Union[str, Any]    							=							spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.LoadFromSerializedProto(self.sp_model_proto  )

			def 							UpperCAmelCase__       ( self			:   List[str]       ,						lowerCamelCase_			:   List[int]       ,						lowerCamelCase_			:   Optional[List[int]] = None  )						->   List[int]:

								if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								__magic_name__							:	List[str]    							=							[self.cls_token_id]
								__magic_name__							:	List[Any]    							=							[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep

			def 							UpperCAmelCase__       ( self			:   Tuple       ,						lowerCamelCase_			:   List[int]       ,						lowerCamelCase_			:   Optional[List[int]] = None       ,						lowerCamelCase_			:   bool = False  )						->   List[int]:

								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 							UpperCAmelCase__       ( self			:   Optional[int]       ,						lowerCamelCase_			:   List[int]       ,						lowerCamelCase_			:   Optional[List[int]] = None  )						->   List[int]:
								__magic_name__							:	Tuple    							=							[self.sep_token_id]
								__magic_name__							:	Optional[int]    							=							[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			:   List[str]  )						->   Any:
								return len(self.fairseq_ids_to_tokens  )

			def 							UpperCAmelCase__       ( self			:   Optional[Any]  )						->   int:
								__magic_name__							:	str    							=							{self.convert_ids_to_tokens(lowerCamelCase_  ): i for i in range(self.vocab_size  )}
								vocab.update(self.added_tokens_encoder  )
								return vocab

			def 							UpperCAmelCase__       ( self			:   Optional[int]       ,						lowerCamelCase_			:   str  )						->   List[str]:
								return self.sp_model.encode(lowerCamelCase_       ,						out_type=lowerCamelCase_  )

			def 							UpperCAmelCase__       ( self			:   int       ,						lowerCamelCase_			:   List[str]  )						->   Tuple:
								if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
								else:
													return self.unk_token_id

			def 							UpperCAmelCase__       ( self			:   List[Any]       ,						lowerCamelCase_			:   Tuple  )						->   List[str]:
								return self.fairseq_ids_to_tokens[index]

			def 							UpperCAmelCase__       ( self			:   Any       ,						lowerCamelCase_			:   Optional[int]  )						->   Tuple:
								__magic_name__							:	Tuple    							=							''''''.join(lowerCamelCase_  ).replace(lowerCamelCase_       ,						''' '''  ).strip()
								return out_string


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









import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin


class    lowerCamelCase    (		_lowerCamelCase				,unittest.TestCase						):






			'''simple docstring'''





			UpperCamelCase__								=BlenderbotSmallTokenizer
			UpperCamelCase__								=False

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]  )						->   str:
								super().setUp()

								__magic_name__							:	Union[str, Any]    							=							['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
								__magic_name__							:	Tuple    							=							dict(zip(lowerCamelCase_       ,						range(len(lowerCamelCase_  )  )  )  )

								__magic_name__							:	Tuple    							=							['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
								__magic_name__							:	List[Any]    							=							{'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

								__magic_name__							:	str    							=							os.path.join(self.tmpdirname       ,						VOCAB_FILES_NAMES['''vocab_file''']  )
								__magic_name__							:	List[str]    							=							os.path.join(self.tmpdirname       ,						VOCAB_FILES_NAMES['''merges_file''']  )
								with open(self.vocab_file       ,						'''w'''       ,						encoding='''utf-8'''  ) as fp:
													fp.write(json.dumps(lowerCamelCase_  ) + '''\n'''  )
								with open(self.merges_file       ,						'''w'''       ,						encoding='''utf-8'''  ) as fp:
													fp.write('''\n'''.join(lowerCamelCase_  )  )

			def 							UpperCAmelCase__       ( self			:   List[str]       ,						**lowerCamelCase_			:   Optional[Any]  )						->   List[Any]:
								kwargs.update(self.special_tokens_map  )
								return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname       ,						**lowerCamelCase_  )

			def 							UpperCAmelCase__       ( self			:   Dict       ,						lowerCamelCase_			:   Union[str, Any]  )						->   Optional[int]:
								__magic_name__							:	Union[str, Any]    							=							'''adapt act apte'''
								__magic_name__							:	Dict    							=							'''adapt act apte'''
								return input_text, output_text

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]  )						->   Any:
								__magic_name__							:	int    							=							BlenderbotSmallTokenizer(self.vocab_file       ,						self.merges_file       ,						**self.special_tokens_map  )
								__magic_name__							:	str    							=							'''adapt act apte'''
								__magic_name__							:	Any    							=							['''adapt''', '''act''', '''ap@@''', '''te''']
								__magic_name__							:	List[str]    							=							tokenizer.tokenize(lowerCamelCase_  )
								self.assertListEqual(lowerCamelCase_       ,						lowerCamelCase_  )

								__magic_name__							:	Union[str, Any]    							=							[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

								__magic_name__							:	List[Any]    							=							[0, 1, 2, 3, 4, 5]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase_  )       ,						lowerCamelCase_  )

			def 							UpperCAmelCase__       ( self			:   int  )						->   int:
								__magic_name__							:	Any    							=							BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''  )
								assert tok('''sam'''  ).input_ids == [1384]
								__magic_name__							:	Dict    							=							'''I am a small frog.'''
								__magic_name__							:	Tuple    							=							tok([src_text]       ,						padding=lowerCamelCase_       ,						truncation=lowerCamelCase_  )['''input_ids''']
								__magic_name__							:	Tuple    							=							tok.batch_decode(lowerCamelCase_       ,						skip_special_tokens=lowerCamelCase_       ,						clean_up_tokenization_spaces=lowerCamelCase_  )[0]
								assert src_text != decoded  # I wish it did!
								assert decoded == "i am a small frog ."


			def 							UpperCAmelCase__       ( self			:   Tuple  )						->   Dict:
								__magic_name__							:	Tuple    							=							BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''  )
								__magic_name__							:	Any    							=							'''I am a small frog .'''
								__magic_name__							:	List[str]    							=							'''.'''
								__magic_name__							:	Tuple    							=							tok(lowerCamelCase_  )['''input_ids''']
								__magic_name__							:	Optional[Any]    							=							tok(lowerCamelCase_  )['''input_ids''']

								assert encoded[-1] == encoded_dot[0]



