


import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_snake_case  :	int			      =       logging.get_logger(__name__)

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

_snake_case  :	Any			      =       {
    "vocab_file": "vocab.json",
    "spm_file": "sentencepiece.bpe.model",
}

_snake_case  :	Union[str, Any]			      =       {
    "vocab_file": {
        "facebook/s2t-small-librispeech-asr": (
            "https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json"
        ),
    },
    "spm_file": {
        "facebook/s2t-small-librispeech-asr": (
            "https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model"
        )
    },
}

_snake_case  :	int			      =       {
    "facebook/s2t-small-librispeech-asr": 1_024,
}

_snake_case  :	List[str]			      =       ["pt", "fr", "ru", "nl", "ro", "it", "es", "de"]

_snake_case  :	Optional[Any]			      =       {"mustc": MUSTC_LANGS}

class        a	(_lowerCAmelCase   ):




							"""simple docstring"""


							__UpperCAmelCase					:							Tuple  						=						VOCAB_FILES_NAMES
							__UpperCAmelCase					:							int  						=						PRETRAINED_VOCAB_FILES_MAP
							__UpperCAmelCase					:							List[Any]  						=						MAX_MODEL_INPUT_SIZES
							__UpperCAmelCase					:							List[str]  						=						["input_ids", "attention_mask"]

							__UpperCAmelCase					:							List[int]  						=						[]

							def __init__(	self :						Optional[int]					,			lowerCamelCase :						Any					,			lowerCamelCase :						Tuple					,			lowerCamelCase :						List[str]="<s>"					,			lowerCamelCase :						Dict="</s>"					,			lowerCamelCase :						Optional[int]="<pad>"					,			lowerCamelCase :						Dict="<unk>"					,			lowerCamelCase :						Union[str, Any]=False					,			lowerCamelCase :						int=False					,			lowerCamelCase :						int=None					,			lowerCamelCase :						str=None					,			lowerCamelCase :						Optional[Dict[str, Any]] = None					,			**lowerCamelCase :						List[Any]					,			)			->					None:
														__snake_case	:    Tuple											=     {} if sp_model_kwargs is None else sp_model_kwargs

														super().__init__(
														    bos_token=lowerCamelCase					,			eos_token=lowerCamelCase					,			unk_token=lowerCamelCase					,			pad_token=lowerCamelCase					,			do_upper_case=lowerCamelCase					,			do_lower_case=lowerCamelCase					,			tgt_lang=lowerCamelCase					,			lang_codes=lowerCamelCase					,			sp_model_kwargs=self.sp_model_kwargs					,			**lowerCamelCase					,			)
														__snake_case	:    Any											=     do_upper_case
														__snake_case	:    Optional[Any]											=     do_lower_case

														__snake_case	:    int											=     load_json(lowerCamelCase       )
														__snake_case	:    Union[str, Any]											=     {v: k for k, v in self.encoder.items()}
														__snake_case	:    Union[str, Any]											=     spm_file
														__snake_case	:    str											=     load_spm(lowerCamelCase					,			self.sp_model_kwargs       )

														if lang_codes is not None:
																					__snake_case	:    Optional[int]											=     lang_codes
																					__snake_case	:    str											=     LANGUAGES[lang_codes]
																					__snake_case	:    Dict											=     [F'<lang:{lang}>' for lang in self.langs]
																					__snake_case	:    Any											=     {lang: self.sp_model.PieceToId(F'<lang:{lang}>'       ) for lang in self.langs}

																					__snake_case	:    Optional[Any]											=     self.lang_tokens
																					__snake_case	:    str											=     tgt_lang if tgt_lang is not None else self.langs[0]

																					self.set_tgt_lang_special_tokens(self._tgt_lang       )
														else:
																					__snake_case	:    Union[str, Any]											=     {}

							@property
							def 					__snake_case      (	self :						List[Any]       )			->					int:
														return len(self.encoder       )

							@property
							def 					__snake_case      (	self :						Tuple       )			->					str:
														return self._tgt_lang

							@tgt_lang.setter
							def 					__snake_case      (	self :						int					,			lowerCamelCase :						List[str]       )			->					None:
														__snake_case	:    Union[str, Any]											=     new_tgt_lang
														self.set_tgt_lang_special_tokens(lowerCamelCase       )

							def 					__snake_case      (	self :						Tuple					,			lowerCamelCase :						str       )			->					None:
														__snake_case	:    Optional[Any]											=     self.lang_code_to_id[tgt_lang]
														__snake_case	:    int											=     [lang_code_id]

							def 					__snake_case      (	self :						Union[str, Any]					,			lowerCamelCase :						str       )			->					List[str]:
														return self.sp_model.encode(lowerCamelCase					,			out_type=lowerCamelCase       )

							def 					__snake_case      (	self :						List[str]					,			lowerCamelCase :						Optional[Any]       )			->					Optional[Any]:
														return self.encoder.get(lowerCamelCase					,			self.encoder[self.unk_token]       )

							def 					__snake_case      (	self :						List[Any]					,			lowerCamelCase :						int       )			->					str:
														return self.decoder.get(lowerCamelCase					,			self.unk_token       )

							def 					__snake_case      (	self :						List[Any]					,			lowerCamelCase :						List[str]       )			->					str:
														__snake_case	:    Union[str, Any]											=     []
														__snake_case	:    Any											=     ""
														for token in tokens:
																					# make sure that special tokens are not decoded using sentencepiece model
																					if token in self.all_special_tokens:
																												__snake_case	:    Dict											=     self.sp_model.decode(lowerCamelCase       )
																												out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
																												__snake_case	:    List[Any]											=     []
																					else:
																												current_sub_tokens.append(lowerCamelCase       )
														__snake_case	:    Any											=     self.sp_model.decode(lowerCamelCase       )
														out_string += decoded.upper() if self.do_upper_case else decoded
														return out_string.strip()

							def 					__snake_case      (	self :						Union[str, Any]					,			lowerCamelCase :						Optional[int]					,			lowerCamelCase :						int=None       )			->					List[int]:
														if token_ids_a is None:
																					return self.prefix_tokens + token_ids_a + [self.eos_token_id]
														# We don't expect to process pairs, but leave the pair logic for API consistency
														return self.prefix_tokens + token_ids_a + token_ids_a + [self.eos_token_id]

							def 					__snake_case      (	self :						Optional[Any]					,			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       )

														__snake_case	:    Tuple											=     [1] * len(self.prefix_tokens       )
														__snake_case	:    Union[str, Any]											=     [1]
														if token_ids_a is None:
																					return prefix_ones + ([0] * len(lowerCamelCase       )) + suffix_ones
														return prefix_ones + ([0] * len(lowerCamelCase       )) + ([0] * len(lowerCamelCase       )) + suffix_ones

							def 					__snake_case      (	self :						Optional[int]       )			->					Dict:
														__snake_case	:    Dict											=     self.encoder.copy()
														vocab.update(self.added_tokens_encoder       )
														return vocab

							def __getstate__(	self :						Tuple       )			->					Dict:
														__snake_case	:    Any											=     self.__dict__.copy()
														__snake_case	:    Union[str, Any]											=     None
														return state

							def __setstate__(	self :						List[str]					,			lowerCamelCase :						Dict       )			->					None:
														__snake_case	:    List[Any]											=     d

														# for backward compatibility
														if not hasattr(self					,			"sp_model_kwargs"       ):
																					__snake_case	:    Union[str, Any]											=     {}

														__snake_case	:    int											=     load_spm(self.spm_file					,			self.sp_model_kwargs       )






							def 					__snake_case      (	self :						Tuple					,			lowerCamelCase :						str					,			lowerCamelCase :						Optional[str] = None       )			->					Tuple[str]:
														__snake_case	:    List[str]											=     Path(lowerCamelCase       )
														assert save_dir.is_dir(), F'{save_directory} should be a directory'
														__snake_case	:    Optional[Any]											=     save_dir / (
														    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["vocab_file"]
														)
														__snake_case	:    Tuple											=     save_dir / (
														    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["spm_file"]
														)

														save_json(self.encoder					,			lowerCamelCase       )

														if os.path.abspath(self.spm_file       ) != os.path.abspath(lowerCamelCase       ) and os.path.isfile(self.spm_file       ):
																					copyfile(self.spm_file					,			lowerCamelCase       )
														elif not os.path.isfile(self.spm_file       ):
																					with open(lowerCamelCase					,			"wb"       ) as fi:
																												__snake_case	:    List[str]											=     self.sp_model.serialized_model_proto()
																												fi.write(lowerCamelCase       )

														return (str(lowerCamelCase       ), str(lowerCamelCase       ))







def        lowerCAmelCase_  (      __lowerCamelCase							,			__lowerCamelCase			):
							__snake_case	:    Optional[int]											=     sentencepiece.SentencePieceProcessor(**__lowerCamelCase			)
							spm.Load(str(__lowerCamelCase			)			)
							return spm







def        lowerCAmelCase_  (      __lowerCamelCase			):
							with open(__lowerCamelCase							,			"r"			) as f:
														return json.load(__lowerCamelCase			)







def        lowerCAmelCase_  (      __lowerCamelCase							,			__lowerCamelCase			):
							with open(__lowerCamelCase							,			"w"			) as f:
														json.dump(__lowerCamelCase							,			__lowerCamelCase							,			indent=2			)





import unittest

from transformers import DonutProcessor


_snake_case  :	Dict			      =       "naver-clova-ix/donut-base"

class        a	(unittest.TestCase   ):




							"""simple docstring"""


							def 					__snake_case      (							self :						Dict       )			->					int:
														__snake_case	:    Any											=     DonutProcessor.from_pretrained(lowerCamelCase       )






							def 					__snake_case      (							self :						str       )			->					List[Any]:
														__snake_case	:    Union[str, Any]											=     {
														    "name": "John Doe",
														    "age": "99",
														    "city": "Atlanta",
														    "state": "GA",
														    "zip": "30301",
														    "phone": "123-4567",
														    "nicknames": [{"nickname": "Johnny"}, {"nickname": "JD"}],
														}

														__snake_case	:    Union[str, Any]											=     (
														    "<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"
														    "<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"
														    "<s_nicknames><s_nickname>Johnny</s_nickname>"
														    "<sep/><s_nickname>JD</s_nickname></s_nicknames>"
														)
														__snake_case	:    Tuple											=     self.processor.tokenajson(lowerCamelCase       )

														self.assertDictEqual(lowerCamelCase					,			lowerCamelCase       )

