"""simple docstring"""
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


SCREAMING_SNAKE_CASE__      						=  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      						=  "▁"

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

SCREAMING_SNAKE_CASE__      						=  {
    "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",
    },
}

SCREAMING_SNAKE_CASE__      						=  {"vinai/bartpho-syllable": 1_024}



class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""
				_lowerCAmelCase     :    Any			  =						VOCAB_FILES_NAMES
				_lowerCAmelCase     :    Optional[int]			  =						PRETRAINED_VOCAB_FILES_MAP
				_lowerCAmelCase     :    Tuple			  =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_lowerCAmelCase     :    Optional[Any]			  =						["""input_ids""", """attention_mask"""]

				def __init__(				self		,    lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase="<s>"		,    lowerCAmelCase="</s>"		,    lowerCAmelCase="</s>"		,    lowerCAmelCase="<s>"		,    lowerCAmelCase="<unk>"		,    lowerCAmelCase="<pad>"		,    lowerCAmelCase="<mask>"		,    lowerCAmelCase = None		,    **lowerCAmelCase		,    ):






										"""simple docstring"""

										snake_case								=			AddedToken(lowerCAmelCase		,    lstrip=lowerCAmelCase		,    rstrip=lowerCAmelCase    ) if isinstance(lowerCAmelCase		,    lowerCAmelCase    ) else mask_token

										snake_case								=			{} 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		,    )

										snake_case								=			vocab_file
										snake_case								=			monolingual_vocab_file
										snake_case								=			spm.SentencePieceProcessor(**self.sp_model_kwargs    )
										self.sp_model.Load(str(lowerCAmelCase    )    )

										# Load the reduced vocab

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

										snake_case								=			{v: k for k, v in self.fairseq_tokens_to_ids.items()}

				def __getstate__(				self    ):






										"""simple docstring"""

										snake_case								=			self.__dict__.copy()
										snake_case								=			None
										snake_case								=			self.sp_model.serialized_model_proto()
										return state

				def __setstate__(				self		,    lowerCAmelCase    ):






										"""simple docstring"""

										snake_case								=			d

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

										snake_case								=			spm.SentencePieceProcessor(**self.sp_model_kwargs    )
										self.sp_model.LoadFromSerializedProto(self.sp_model_proto    )

				def 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = None    ):






										"""simple docstring"""

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

				def 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = None		,    lowerCAmelCase = False    ):






										"""simple docstring"""

										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		,    lowerCAmelCase		,    lowerCAmelCase = None    ):






										"""simple docstring"""

										snake_case								=			[self.sep_token_id]
										snake_case								=			[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    ):






										"""simple docstring"""

										return len(self.fairseq_ids_to_tokens    )

				def 		snake_case (				self    ):






										"""simple docstring"""

										snake_case								=			{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		,    lowerCAmelCase    ):






										"""simple docstring"""

										return self.sp_model.encode(lowerCAmelCase		,    out_type=lowerCAmelCase    )

				def 		snake_case (				self		,    lowerCAmelCase    ):






										"""simple docstring"""

										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		,    lowerCAmelCase    ):






										"""simple docstring"""

										return self.fairseq_ids_to_tokens[index]

				def 		snake_case (				self		,    lowerCAmelCase    ):






										"""simple docstring"""

										snake_case								=			''.join(lowerCAmelCase    ).replace(lowerCAmelCase		,    ' '    ).strip()
										return out_string

				def 		snake_case (				self		,    lowerCAmelCase		,    lowerCAmelCase = None    ):






										"""simple docstring"""

										if not os.path.isdir(lowerCAmelCase    ):
																logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""    )
																return
										snake_case								=			os.path.join(
										    lowerCAmelCase		,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )
										snake_case								=			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:
																						snake_case								=			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



"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


SCREAMING_SNAKE_CASE__      						=  get_logger(__name__)



class   lowerCAmelCase_    (			enum.Enum					):



				"""simple docstring"""
				_lowerCAmelCase     :    Union[str, Any]			  =						"""all_checks"""
				_lowerCAmelCase     :    Optional[Any]			  =						"""basic_checks"""
				_lowerCAmelCase     :    Optional[int]			  =						"""no_checks"""





class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





def    lowerCAmelCase__    (			_UpperCamelCase       :				Optional[dict] ,			_UpperCamelCase       :				dict ,			_UpperCamelCase       :				str=None					)					->				Dict:





						"""simple docstring"""






						if expected_checksums is None:
												logger.info('Unable to verify checksums.'					)
												return
						if len(set(_UpperCamelCase					) - set(_UpperCamelCase					)					) > 0:
												raise ExpectedMoreDownloadedFiles(str(set(_UpperCamelCase					) - set(_UpperCamelCase					)					)					)
						if len(set(_UpperCamelCase					) - set(_UpperCamelCase					)					) > 0:
												raise UnexpectedDownloadedFile(str(set(_UpperCamelCase					) - set(_UpperCamelCase					)					)					)
						snake_case								=			[url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
						snake_case								=			' for ' + verification_name if verification_name is not None else ''
						if len(_UpperCamelCase					) > 0:
												raise NonMatchingChecksumError(
												    f"""Checksums didn't match{for_verification_name}:\n"""
												    f"""{bad_urls}\n"""
												    'Set `verification_mode=\'no_checks\'` to skip checksums verification and ignore this error'					)
						logger.info('All the checksums matched successfully' + for_verification_name					)



class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""





def    lowerCAmelCase__    (			_UpperCamelCase       :				Optional[dict] ,			_UpperCamelCase       :				dict					)					->				Tuple:





						"""simple docstring"""






						if expected_splits is None:
												logger.info('Unable to verify splits sizes.'					)
												return
						if len(set(_UpperCamelCase					) - set(_UpperCamelCase					)					) > 0:
												raise ExpectedMoreSplits(str(set(_UpperCamelCase					) - set(_UpperCamelCase					)					)					)
						if len(set(_UpperCamelCase					) - set(_UpperCamelCase					)					) > 0:
												raise UnexpectedSplits(str(set(_UpperCamelCase					) - set(_UpperCamelCase					)					)					)
						snake_case								=			[
						    {'expected': expected_splits[name], 'recorded': recorded_splits[name]}
						    for name in expected_splits
						    if expected_splits[name].num_examples != recorded_splits[name].num_examples
						]
						if len(_UpperCamelCase					) > 0:
												raise NonMatchingSplitsSizesError(str(_UpperCamelCase					)					)
						logger.info('All the splits matched successfully.'					)





def    lowerCAmelCase__    (			_UpperCamelCase       :				str ,			_UpperCamelCase       :				bool = True					)					->				dict:





						"""simple docstring"""






						if record_checksum:
												snake_case								=			shaaaa()
												with open(_UpperCamelCase ,			'rb'					) as f:
																		for chunk in iter(lambda: f.read(1 << 2_0					) ,			B''					):
																								m.update(_UpperCamelCase					)
																		snake_case								=			m.hexdigest()
						else:
												snake_case								=			None
						return {"num_bytes": os.path.getsize(_UpperCamelCase					), "checksum": checksum}





def    lowerCAmelCase__    (			_UpperCamelCase       :				Optional[int]					)					->				int:





						"""simple docstring"""






						if dataset_size and config.IN_MEMORY_MAX_SIZE:
												return dataset_size < config.IN_MEMORY_MAX_SIZE
						else:
												return False


