

"""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


_lowercase   :	Optional[Any]												=						logging.get_logger(__name__)

_lowercase   :	List[str]												=						'▁'

_lowercase   :	Optional[int]												=						{
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
}

_lowercase   :	str												=						{
    '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'
        )
    },
}

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

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

_lowercase   :	Union[str, Any]												=						{'mustc': MUSTC_LANGS}
class      _UpperCAmelCase   (							_lowerCAmelCase       ):
	a__		: Optional[Any]					=					VOCAB_FILES_NAMES
	a__		: str					=					PRETRAINED_VOCAB_FILES_MAP
	a__		: Any					=					MAX_MODEL_INPUT_SIZES
	a__		: int					=					["input_ids", "attention_mask"]

	a__		: List[int]					=					[]



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

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

		__UpperCAmelCase      		= load_json(_lowercase						)
		__UpperCAmelCase      		= {v: k for k, v in self.encoder.items()}
		__UpperCAmelCase      		= spm_file
		__UpperCAmelCase      		= load_spm(_lowercase			,    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        a  (  self     :       List[str]						):
		return len(self.encoder						)



	@property
	def        a  (  self     :       str						):
		return self._tgt_lang



	@tgt_lang.setter
	def        a  (  self     :       Optional[int]			,    _lowercase     :       Optional[int]						):
		__UpperCAmelCase      		= new_tgt_lang
		self.set_tgt_lang_special_tokens(_lowercase						)



	def        a  (  self     :       Any			,    _lowercase     :       str						):
		__UpperCAmelCase      		= self.lang_code_to_id[tgt_lang]
		__UpperCAmelCase      		= [lang_code_id]



	def        a  (  self     :       str			,    _lowercase     :       str						):
		return self.sp_model.encode(_lowercase			,    out_type=_lowercase						)



	def        a  (  self     :       List[Any]			,    _lowercase     :       Tuple						):
		return self.encoder.get(_lowercase			,    self.encoder[self.unk_token]						)



	def        a  (  self     :       List[Any]			,    _lowercase     :       int						):
		return self.decoder.get(_lowercase			,    self.unk_token						)



	def        a  (  self     :       Dict			,    _lowercase     :       List[str]						):
		__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(_lowercase						)
				out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
				__UpperCAmelCase      		= []
			else:
				current_sub_tokens.append(_lowercase						)
		__UpperCAmelCase      		= self.sp_model.decode(_lowercase						)
		out_string += decoded.upper() if self.do_upper_case else decoded
		return out_string.strip()



	def        a  (  self     :       Tuple			,    _lowercase     :       Optional[Any]			,    _lowercase     :       Any=None						):
		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        a  (  self     :       List[Any]			,    _lowercase     :       List[int]			,    _lowercase     :       Optional[List[int]] = None			,    _lowercase     :       bool = False						):

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

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



	def        a  (  self     :       Any						):
		__UpperCAmelCase      		= self.encoder.copy()
		vocab.update(self.added_tokens_encoder						)
		return vocab



	def __getstate__(  self     :       Union[str, Any]						):
		__UpperCAmelCase      		= self.__dict__.copy()
		__UpperCAmelCase      		= None
		return state



	def __setstate__(  self     :       Any			,    _lowercase     :       Dict						):
		__UpperCAmelCase      		= d

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

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



	def        a  (  self     :       Dict			,    _lowercase     :       str			,    _lowercase     :       Optional[str] = None						):
		__UpperCAmelCase      		= Path(_lowercase						)
		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			,    _lowercase						)

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

		return (str(_lowercase						), str(_lowercase						))






def       lowercase__						(       snake_case_   :str			,		snake_case_   :Dict[str, Any]    ):
	__UpperCAmelCase      		= sentencepiece.SentencePieceProcessor(**snake_case_    )
	spm.Load(str(snake_case_    )    )
	return spm





def       lowercase__						(       snake_case_   :str    ):
	with open(snake_case_			,		'''r'''    ) as f:
		return json.load(snake_case_    )





def       lowercase__						(       snake_case_   :Dict			,		snake_case_   :str    ):
	with open(snake_case_			,		'''w'''    ) as f:
		json.dump(snake_case_			,		snake_case_			,		indent=2    )








from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE   =  logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   =  {
    "uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json",
}






class 					SCREAMING_SNAKE_CASE_  (       _a ):
       """simple docstring"""


       __lowerCAmelCase    :		str					='''mra'''





       def __init__(				self	:Any,      snake_case	:List[str]=5_0265,      snake_case	:List[Any]=768,      snake_case	:Optional[Any]=12,      snake_case	:Optional[Any]=12,      snake_case	:str=3072,      snake_case	:Tuple="gelu",      snake_case	:Optional[int]=0.1,      snake_case	:int=0.1,      snake_case	:Any=512,      snake_case	:Union[str, Any]=1,      snake_case	:Union[str, Any]=0.0_2,      snake_case	:List[Any]=1e-5,      snake_case	:Optional[int]="absolute",      snake_case	:Optional[int]=4,      snake_case	:str="full",      snake_case	:Optional[int]=0,      snake_case	:List[Any]=0,      snake_case	:int=1,      snake_case	:List[Any]=0,      snake_case	:Dict=2,      **snake_case	:Dict,      ):



          """simple docstring"""

          super().__init__(pad_token_id=snake_case,      bos_token_id=snake_case,      eos_token_id=snake_case,      **snake_case)

          _lowercase              =vocab_size
          _lowercase              =max_position_embeddings
          _lowercase              =hidden_size
          _lowercase              =num_hidden_layers
          _lowercase              =num_attention_heads
          _lowercase              =intermediate_size
          _lowercase              =hidden_act
          _lowercase              =hidden_dropout_prob
          _lowercase              =attention_probs_dropout_prob
          _lowercase              =initializer_range
          _lowercase              =type_vocab_size
          _lowercase              =layer_norm_eps
          _lowercase              =position_embedding_type
          _lowercase              =block_per_row
          _lowercase              =approx_mode
          _lowercase              =initial_prior_first_n_blocks
          _lowercase              =initial_prior_diagonal_n_blocks


