


"""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


__SCREAMING_SNAKE_CASE							:			int						=			logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE							:			Optional[int]						=			"▁"

__SCREAMING_SNAKE_CASE							:			Any						=			{"vocab_file": "sentencepiece.bpe.model"}

__SCREAMING_SNAKE_CASE							:			List[Any]						=			{
    "vocab_file": {
        "facebook/xglm-564M": "https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model",
    }
}

__SCREAMING_SNAKE_CASE							:			Tuple						=			{
    "facebook/xglm-564M": 2_048,
}





class    __A   (_lowerCamelCase):





							'''simple docstring'''

							__lowercase:						Optional[int]												=			VOCAB_FILES_NAMES
							__lowercase:						Optional[Any]												=			PRETRAINED_VOCAB_FILES_MAP
							__lowercase:						List[str]												=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowercase:						int												=			["""input_ids""", """attention_mask"""]



							def __init__( self							:					Dict						,				UpperCAmelCase_							:					Optional[Any]						,				UpperCAmelCase_							:					Any="<s>"						,				UpperCAmelCase_							:					str="</s>"						,				UpperCAmelCase_							:					List[str]="</s>"						,				UpperCAmelCase_							:					List[str]="<s>"						,				UpperCAmelCase_							:					List[Any]="<unk>"						,				UpperCAmelCase_							:					Dict="<pad>"						,				UpperCAmelCase_							:					str = None						,				**UpperCAmelCase_							:					Optional[int]						,				)    ->Dict:



														"""simple docstring"""



														snake_case_							=						{} if sp_model_kwargs is None else sp_model_kwargs

														# Compatibility with the original tokenizer
														snake_case_							=						7
														snake_case_							=						[F"""<madeupword{i}>""" for i in range(self.num_madeup_words				)]

														snake_case_							=						kwargs.get("""additional_special_tokens"""						,				[]				)
														kwargs["additional_special_tokens"] += [
														    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
														]

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

														snake_case_							=						spm.SentencePieceProcessor(**self.sp_model_kwargs				)
														self.sp_model.Load(str(lowerCAmelCase_				)				)
														snake_case_							=						vocab_file

														# Original fairseq vocab and spm vocab must be "aligned":
														# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
														# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
														# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
														# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

														# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
														snake_case_							=						1

														# Mimic fairseq token-to-id alignment for the first 4 token
														snake_case_							=						{"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

														snake_case_							=						len(self.sp_model				)
														snake_case_							=						{F"""<madeupword{i}>""": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words				)}
														self.fairseq_tokens_to_ids.update(lowerCAmelCase_				)

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



							def __getstate__( self							:					Optional[Any]				)    ->List[str]:



														"""simple docstring"""



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



							def __setstate__( self							:					Optional[int]						,				UpperCAmelCase_							:					Tuple				)    ->Optional[int]:



														"""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 						lowerCAmelCase				( self							:					Any						,				UpperCAmelCase_							:					Optional[int]						,				UpperCAmelCase_							:					Union[str, Any] = None				)    ->Optional[int]:



														"""simple docstring"""



														if token_ids_a is None:
																					return [self.sep_token_id] + token_ids_a
														snake_case_							=						[self.sep_token_id]
														return sep + token_ids_a + sep + sep + token_ids_a



							def 						lowerCAmelCase				( self							:					Optional[int]						,				UpperCAmelCase_							:					Optional[int]						,				UpperCAmelCase_							:					List[Any] = None						,				UpperCAmelCase_							:					List[Any] = False				)    ->str:



														"""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_				))
														return [1] + ([0] * len(lowerCAmelCase_				)) + [1, 1] + ([0] * len(lowerCAmelCase_				))



							def 						lowerCAmelCase				( self							:					List[str]						,				UpperCAmelCase_							:					List[str]						,				UpperCAmelCase_							:					List[Any] = None				)    ->int:



														"""simple docstring"""



														snake_case_							=						[self.sep_token_id]

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



							@property
							def 						lowerCAmelCase				( self							:					int				)    ->List[str]:



														"""simple docstring"""



														return len(self.sp_model				) + self.fairseq_offset + self.num_madeup_words



							def 						lowerCAmelCase				( self							:					Dict				)    ->Union[str, Any]:



														"""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 						lowerCAmelCase				( self							:					Tuple						,				UpperCAmelCase_							:					Optional[int]				)    ->List[Any]:



														"""simple docstring"""



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



							def 						lowerCAmelCase				( self							:					int						,				UpperCAmelCase_							:					Dict				)    ->Optional[int]:



														"""simple docstring"""



														if token in self.fairseq_tokens_to_ids:
																					return self.fairseq_tokens_to_ids[token]
														snake_case_							=						self.sp_model.PieceToId(lowerCAmelCase_				)

														# Need to return unknown token if the SP model returned 0
														return spm_id + self.fairseq_offset if spm_id else self.unk_token_id



							def 						lowerCAmelCase				( self							:					List[str]						,				UpperCAmelCase_							:					Optional[int]				)    ->List[str]:



														"""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 						lowerCAmelCase				( self							:					Tuple						,				UpperCAmelCase_							:					Tuple				)    ->Any:



														"""simple docstring"""



														snake_case_							=						"""""".join(lowerCAmelCase_				).replace(lowerCAmelCase_						,				""" """				).strip()
														return out_string



							def 						lowerCAmelCase				( self							:					List[Any]						,				UpperCAmelCase_							:					Dict						,				UpperCAmelCase_							:					List[Any] = None				)    ->Dict:



														"""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"""]				)

														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_				)

														return (out_vocab_file,)





'''simple docstring'''







def 				SCREAMING_SNAKE_CASE__	(   __A	)       ->	bool:
	return number & 1 == 0


if __name__ == "__main__":
					import doctest

					doctest.testmod()

