
"""simple docstring"""





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								=						logging.get_logger(__name__)

_a								=						"""▁"""

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

_a								=						{
    """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								=						{
    """facebook/s2t-small-librispeech-asr""": 1024,
}

_a								=						["""pt""", """fr""", """ru""", """nl""", """ro""", """it""", """es""", """de"""]

_a								=						{"""mustc""": MUSTC_LANGS}






class        _UpperCAmelCase(       lowerCamelCase      ):
		lowercase__         = VOCAB_FILES_NAMES
		lowercase__         = PRETRAINED_VOCAB_FILES_MAP
		lowercase__         = MAX_MODEL_INPUT_SIZES
		lowercase__         = ['input_ids', 'attention_mask']

		lowercase__         = []



		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:






							'''simple docstring'''
							_UpperCamelCase									=    {} 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							,						)
							_UpperCamelCase									=    do_upper_case
							_UpperCamelCase									=    do_lower_case

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

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

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

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



		@property
		def 		UpperCAmelCase				(   self)			->			int:






							'''simple docstring'''
							return len(self.encoder)



		@property
		def 		UpperCAmelCase				(   self)			->			str:






							'''simple docstring'''
							return self._tgt_lang



		@tgt_lang.setter
		def 		UpperCAmelCase				(   self							,						__a)			->			None:






							'''simple docstring'''
							_UpperCamelCase									=    new_tgt_lang
							self.set_tgt_lang_special_tokens(__a)



		def 		UpperCAmelCase				(   self							,						__a)			->			None:






							'''simple docstring'''
							_UpperCamelCase									=    self.lang_code_to_id[tgt_lang]
							_UpperCamelCase									=    [lang_code_id]



		def 		UpperCAmelCase				(   self							,						__a)			->			List[str]:






							'''simple docstring'''
							return self.sp_model.encode(__a							,						out_type=__a)



		def 		UpperCAmelCase				(   self							,						__a)			->			Any:






							'''simple docstring'''
							return self.encoder.get(__a							,						self.encoder[self.unk_token])



		def 		UpperCAmelCase				(   self							,						__a)			->			str:






							'''simple docstring'''
							return self.decoder.get(__a							,						self.unk_token)



		def 		UpperCAmelCase				(   self							,						__a)			->			str:






							'''simple docstring'''
							_UpperCamelCase									=    []
							_UpperCamelCase									=    ''''''
							for token in tokens:
												# make sure that special tokens are not decoded using sentencepiece model
												if token in self.all_special_tokens:
																	_UpperCamelCase									=    self.sp_model.decode(__a)
																	out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
																	_UpperCamelCase									=    []
												else:
																	current_sub_tokens.append(__a)
							_UpperCamelCase									=    self.sp_model.decode(__a)
							out_string += decoded.upper() if self.do_upper_case else decoded
							return out_string.strip()



		def 		UpperCAmelCase				(   self							,						__a							,						__a=None)			->			List[int]:






							'''simple docstring'''
							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 		UpperCAmelCase				(   self							,						__a							,						__a = None							,						__a = False)			->			List[int]:






							'''simple docstring'''

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

							_UpperCamelCase									=    [1] * len(self.prefix_tokens)
							_UpperCamelCase									=    [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 		UpperCAmelCase				(   self)			->			Dict:






							'''simple docstring'''
							_UpperCamelCase									=    self.encoder.copy()
							vocab.update(self.added_tokens_encoder)
							return vocab



		def __getstate__(   self)			->			Dict:






							'''simple docstring'''
							_UpperCamelCase									=    self.__dict__.copy()
							_UpperCamelCase									=    None
							return state



		def __setstate__(   self							,						__a)			->			None:






							'''simple docstring'''
							_UpperCamelCase									=    d

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

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




		def 		UpperCAmelCase				(   self							,						__a							,						__a = None)			->			Tuple[str]:






							'''simple docstring'''
							_UpperCamelCase									=    Path(__a)
							assert save_dir.is_dir(), F'''{save_directory} should be a directory'''
							_UpperCamelCase									=    save_dir / (
							    (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''vocab_file''']
							)
							_UpperCamelCase									=    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:
																	_UpperCamelCase									=    self.sp_model.serialized_model_proto()
																	fi.write(__a)

							return (str(__a), str(__a))





def  lowerCamelCase__						(     __snake_case,	__snake_case      )				->						sentencepiece.SentencePieceProcessor:


					"""simple docstring"""





					_UpperCamelCase									=    sentencepiece.SentencePieceProcessor(**__snake_case      )
					spm.Load(str(__snake_case      )      )
					return spm



def  lowerCamelCase__						(     __snake_case      )				->						Union[Dict, List]:


					"""simple docstring"""





					with open(__snake_case,	'''r'''      ) as f:
										return json.load(__snake_case      )



def  lowerCamelCase__						(     __snake_case,	__snake_case      )				->						None:


					"""simple docstring"""





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











'''simple docstring'''

# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

__lowerCAmelCase		     =  TypeVar('''T''')

class       __magic_name__		(       Generic[T]  ):







							def __init__(				self   :			int      ,_UpperCAmelCase   :			bool = True						):
									_a	: dict[T, list[T]]								=				{}  # dictionary of lists
									_a	: Tuple								=				directed







							def 				__lowercase     (				self   :			Union[str, Any]      ,_UpperCAmelCase   :			T      ,_UpperCAmelCase   :			T						):

									if not self.directed:  # For undirected graphs
											# if both source vertex and destination vertex are both present in the
											# adjacency list, add destination vertex to source vertex list of adjacent
											# vertices and add source vertex to destination vertex list of adjacent
											# vertices.
											if source_vertex in self.adj_list and destination_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
													self.adj_list[destination_vertex].append(_UpperCAmelCase						)
											# if only source vertex is present in adjacency list, add destination vertex
											# to source vertex list of adjacent vertices, then create a new vertex with
											# destination vertex as key and assign a list containing the source vertex
											# as it's first adjacent vertex.
											elif source_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
													_a	: Optional[Any]								=				[source_vertex]
											# if only destination vertex is present in adjacency list, add source vertex
											# to destination vertex list of adjacent vertices, then create a new vertex
											# with source vertex as key and assign a list containing the source vertex
											# as it's first adjacent vertex.
											elif destination_vertex in self.adj_list:
													self.adj_list[destination_vertex].append(_UpperCAmelCase						)
													_a	: Union[str, Any]								=				[destination_vertex]
											# if both source vertex and destination vertex are not present in adjacency
											# list, create a new vertex with source vertex as key and assign a list
											# containing the destination vertex as it's first adjacent vertex also
											# create a new vertex with destination vertex as key and assign a list
											# containing the source vertex as it's first adjacent vertex.
											else:
													_a	: Union[str, Any]								=				[destination_vertex]
													_a	: Optional[int]								=				[source_vertex]
									else:  # For directed graphs
											# if both source vertex and destination vertex are present in adjacency
											# list, add destination vertex to source vertex list of adjacent vertices.
											if source_vertex in self.adj_list and destination_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
											# if only source vertex is present in adjacency list, add destination
											# vertex to source vertex list of adjacent vertices and create a new vertex
											# with destination vertex as key, which has no adjacent vertex
											elif source_vertex in self.adj_list:
													self.adj_list[source_vertex].append(_UpperCAmelCase						)
													_a	: int								=				[]
											# if only destination vertex is present in adjacency list, create a new
											# vertex with source vertex as key and assign a list containing destination
											# vertex as first adjacent vertex
											elif destination_vertex in self.adj_list:
													_a	: Tuple								=				[destination_vertex]
											# if both source vertex and destination vertex are not present in adjacency
											# list, create a new vertex with source vertex as key and a list containing
											# destination vertex as it's first adjacent vertex. Then create a new vertex
											# with destination vertex as key, which has no adjacent vertex
											else:
													_a	: Tuple								=				[destination_vertex]
													_a	: str								=				[]

									return self







							def __repr__(				self   :			int						):
									return pformat(self.adj_list						)




