






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


a_		:    Dict   							=     logging.get_logger(__name__)

a_		:    Tuple   							=     '▁'

a_		:    str   							=     {
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
}

a_		:    Optional[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'
        )
    },
}

a_		:    List[Any]   							=     {
    'facebook/s2t-small-librispeech-asr': 10_24,
}

a_		:    Any   							=     ['pt', 'fr', 'ru', 'nl', 'ro', 'it', 'es', 'de']

a_		:    Dict   							=     {'mustc': MUSTC_LANGS}

class 		_snake_case	(	A__       ):
			_lowercase		:     str        =				VOCAB_FILES_NAMES
			_lowercase		:     Dict        =				PRETRAINED_VOCAB_FILES_MAP
			_lowercase		:     Optional[int]        =				MAX_MODEL_INPUT_SIZES
			_lowercase		:     Optional[int]        =				['''input_ids''', '''attention_mask''']

			_lowercase		:     List[int]        =				[]






			def __init__(							self		,       a		,       a		,       a="<s>"		,       a="</s>"		,       a="<pad>"		,       a="<unk>"		,       a=False		,       a=False		,       a=None		,       a=None		,       a = None		,       **a		,       )   ->							None:
						SCREAMING_SNAKE_CASE							=			{} if sp_model_kwargs is None else sp_model_kwargs

						super().__init__(
						    bos_token=a		,       eos_token=a		,       unk_token=a		,       pad_token=a		,       do_upper_case=a		,       do_lower_case=a		,       tgt_lang=a		,       lang_codes=a		,       sp_model_kwargs=self.sp_model_kwargs		,       **a		,       )
						SCREAMING_SNAKE_CASE							=			do_upper_case
						SCREAMING_SNAKE_CASE							=			do_lower_case

						SCREAMING_SNAKE_CASE							=			load_json(a)
						SCREAMING_SNAKE_CASE							=			{v: k for k, v in self.encoder.items()}
						SCREAMING_SNAKE_CASE							=			spm_file
						SCREAMING_SNAKE_CASE							=			load_spm(a		,       self.sp_model_kwargs)

						if lang_codes is not None:
									SCREAMING_SNAKE_CASE							=			lang_codes
									SCREAMING_SNAKE_CASE							=			LANGUAGES[lang_codes]
									SCREAMING_SNAKE_CASE							=			[f'''<lang:{lang}>''' for lang in self.langs]
									SCREAMING_SNAKE_CASE							=			{lang: self.sp_model.PieceToId(f'''<lang:{lang}>''') for lang in self.langs}

									SCREAMING_SNAKE_CASE							=			self.lang_tokens
									SCREAMING_SNAKE_CASE							=			tgt_lang if tgt_lang is not None else self.langs[0]

									self.set_tgt_lang_special_tokens(self._tgt_lang)
						else:
									SCREAMING_SNAKE_CASE							=			{}






			@property
			def  SCREAMING_SNAKE_CASE__     (							self)   ->							int:
						return len(self.encoder)






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






			@tgt_lang.setter
			def  SCREAMING_SNAKE_CASE__     (							self		,       a)   ->							None:
						SCREAMING_SNAKE_CASE							=			new_tgt_lang
						self.set_tgt_lang_special_tokens(a)






			def  SCREAMING_SNAKE_CASE__     (							self		,       a)   ->							None:
						SCREAMING_SNAKE_CASE							=			self.lang_code_to_id[tgt_lang]
						SCREAMING_SNAKE_CASE							=			[lang_code_id]






			def  SCREAMING_SNAKE_CASE__     (							self		,       a)   ->							List[str]:
						return self.sp_model.encode(a		,       out_type=a)






			def  SCREAMING_SNAKE_CASE__     (							self		,       a)   ->							Tuple:
						return self.encoder.get(a		,       self.encoder[self.unk_token])






			def  SCREAMING_SNAKE_CASE__     (							self		,       a)   ->							str:
						return self.decoder.get(a		,       self.unk_token)






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






			def  SCREAMING_SNAKE_CASE__     (							self		,       a		,       a=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  SCREAMING_SNAKE_CASE__     (							self		,       a		,       a = None		,       a = False)   ->							List[int]:

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

						SCREAMING_SNAKE_CASE							=			[1] * len(self.prefix_tokens)
						SCREAMING_SNAKE_CASE							=			[1]
						if token_ids_a is None:
									return prefix_ones + ([0] * len(a)) + suffix_ones
						return prefix_ones + ([0] * len(a)) + ([0] * len(a)) + suffix_ones






			def  SCREAMING_SNAKE_CASE__     (							self)   ->							Dict:
						SCREAMING_SNAKE_CASE							=			self.encoder.copy()
						vocab.update(self.added_tokens_encoder)
						return vocab






			def __getstate__(							self)   ->							Dict:
						SCREAMING_SNAKE_CASE							=			self.__dict__.copy()
						SCREAMING_SNAKE_CASE							=			None
						return state






			def __setstate__(							self		,       a)   ->							None:
						SCREAMING_SNAKE_CASE							=			d

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

						SCREAMING_SNAKE_CASE							=			load_spm(self.spm_file		,       self.sp_model_kwargs)







			def  SCREAMING_SNAKE_CASE__     (							self		,       a		,       a = None)   ->							Tuple[str]:
						SCREAMING_SNAKE_CASE							=			Path(a)
						assert save_dir.is_dir(), f'''{save_directory} should be a directory'''
						SCREAMING_SNAKE_CASE							=			save_dir / (
						    (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
						)
						SCREAMING_SNAKE_CASE							=			save_dir / (
						    (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
						)

						save_json(self.encoder		,       a)

						if os.path.abspath(self.spm_file) != os.path.abspath(a) and os.path.isfile(self.spm_file):
									copyfile(self.spm_file		,       a)
						elif not os.path.isfile(self.spm_file):
									with open(a		,       'wb') as fi:
												SCREAMING_SNAKE_CASE							=			self.sp_model.serialized_model_proto()
												fi.write(a)

						return (str(a), str(a))






def 					lowerCamelCase__					(_UpperCAmelCase				,							_UpperCAmelCase):
			SCREAMING_SNAKE_CASE							=			sentencepiece.SentencePieceProcessor(**_UpperCAmelCase)
			spm.Load(str(_UpperCAmelCase))
			return spm






def 					lowerCamelCase__					(_UpperCAmelCase):
			with open(_UpperCAmelCase				,							'r') as f:
						return json.load(_UpperCAmelCase)







def 					lowerCamelCase__					(_UpperCAmelCase				,							_UpperCAmelCase):
			with open(_UpperCAmelCase				,							'w') as f:
						json.dump(_UpperCAmelCase				,							_UpperCAmelCase				,							indent=2)







from __future__ import annotations

from dataclasses import dataclass

@dataclass
class 							UpperCAmelCase_						:
							"""simple docstring"""







							UpperCAmelCase__			:		float
							UpperCAmelCase__			:		TreeNode | None             =       None
							UpperCAmelCase__			:		TreeNode | None             =       None



def   __UpperCAmelCase					(      __a :     TreeNode | None      )     ->	bool:

					"""simple docstring"""

					def is_valid_tree(__a :     TreeNode | None      ) -> bool:
										if node is None:
															return True

										if not isinstance(__a						,__a      ):
															return False

										try:
															float(node.data      )
										except (TypeError, ValueError):
															return False

										return is_valid_tree(node.left      ) and is_valid_tree(node.right      )

					if not is_valid_tree(__a      ):
										raise ValueError(
										    '''Each node should be type of TreeNode and data should be float.'''      )

					def is_binary_search_tree_recursive_check(
					    __a :     TreeNode | None						,__a :     float						,__a :     float      ) -> bool:

										if node is None:
															return True

										return (
										    left_bound < node.data < right_bound
										    and is_binary_search_tree_recursive_check(node.left						,__a						,node.data      )
										    and is_binary_search_tree_recursive_check(
										        node.right						,node.data						,__a      )
										)

					return is_binary_search_tree_recursive_check(__a						,-float('''inf'''      )						,float('''inf'''      )      )


if __name__ == "__main__":
			import doctest

			doctest.testmod()



