






"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_					=      logging.get_logger(__name__)

lowerCamelCase_					=      {
    '''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-430m-pile''': '''https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-1b5-pile''': '''https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-3b-pile''': '''https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-7b-pile''': '''https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-14b-pile''': '''https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-raven-1b5''': '''https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json''',
    '''RWKV/rwkv-raven-3b''': '''https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-7b''': '''https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-14b''': '''https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json''',
}







class 			UpperCamelCase_       (__A     ):
	__magic_name__	      =				'''rwkv'''
	__magic_name__	      =				{'''max_position_embeddings''': '''context_length'''}





	def __init__(      self					: str	,	lowerCAmelCase_					: str=50_277	,	lowerCAmelCase_					: Optional[int]=1_024	,	lowerCAmelCase_					: Optional[int]=4_096	,	lowerCAmelCase_					: Union[str, Any]=32	,	lowerCAmelCase_					: List[Any]=None	,	lowerCAmelCase_					: int=None	,	lowerCAmelCase_					: List[Any]=1e-5	,	lowerCAmelCase_					: str=0	,	lowerCAmelCase_					: Tuple=0	,	lowerCAmelCase_					: int=6	,	lowerCAmelCase_					: Optional[Any]=False	,	lowerCAmelCase_					: Any=True	,	**lowerCAmelCase_					: List[Any]	,	)						->			List[str]:
				UpperCAmelCase_     : Tuple			     =					vocab_size
				UpperCAmelCase_     : List[str]			     =					context_length
				UpperCAmelCase_     : Dict			     =					hidden_size
				UpperCAmelCase_     : Optional[int]			     =					num_hidden_layers
				UpperCAmelCase_     : Optional[int]			     =					attention_hidden_size if attention_hidden_size is not None else hidden_size
				UpperCAmelCase_     : Dict			     =					intermediate_size if intermediate_size is not None else 4 * hidden_size
				UpperCAmelCase_     : Any			     =					layer_norm_epsilon
				UpperCAmelCase_     : List[Any]			     =					rescale_every
				UpperCAmelCase_     : List[str]			     =					use_cache

				UpperCAmelCase_     : List[str]			     =					bos_token_id
				UpperCAmelCase_     : Union[str, Any]			     =					eos_token_id

				super().__init__(
				    tie_word_embeddings=lowerCAmelCase_	,	bos_token_id=lowerCAmelCase_	,	eos_token_id=lowerCAmelCase_	,	**lowerCAmelCase_						)











"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
			from .tokenization_mbart import MBartTokenizer
else:
			lowerCamelCase_					=      None


lowerCamelCase_					=      logging.get_logger(__name__)


lowerCamelCase_					=      {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCamelCase_					=      {
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-en-ro''': '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json''',
        '''facebook/mbart-large-cc25''': '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json''',
    },
}

lowerCamelCase_					=      {
    '''facebook/mbart-large-en-ro''': 1024,
    '''facebook/mbart-large-cc25''': 1024,
}

# fmt: off
lowerCamelCase_					=      ['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''']







class 			UpperCamelCase_       (__A     ):
	__magic_name__	      =				VOCAB_FILES_NAMES
	__magic_name__	      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__magic_name__	      =				PRETRAINED_VOCAB_FILES_MAP
	__magic_name__	      =				['''input_ids''', '''attention_mask''']
	__magic_name__	      =				MBartTokenizer

	__magic_name__	      =				[]
	__magic_name__	      =				[]





	def __init__(      self					: List[str]	,	lowerCAmelCase_					: List[Any]=None	,	lowerCAmelCase_					: str=None	,	lowerCAmelCase_					: List[Any]="<s>"	,	lowerCAmelCase_					: Optional[Any]="</s>"	,	lowerCAmelCase_					: str="</s>"	,	lowerCAmelCase_					: str="<s>"	,	lowerCAmelCase_					: List[Any]="<unk>"	,	lowerCAmelCase_					: Tuple="<pad>"	,	lowerCAmelCase_					: Union[str, Any]="<mask>"	,	lowerCAmelCase_					: List[Any]=None	,	lowerCAmelCase_					: str=None	,	lowerCAmelCase_					: Optional[Any]=None	,	**lowerCAmelCase_					: Any	,	)						->			Tuple:
				# Mask token behave like a normal word, i.e. include the space before it
				UpperCAmelCase_     : Union[str, Any]			     =					AddedToken(lowerCAmelCase_	,	lstrip=lowerCAmelCase_	,	rstrip=lowerCAmelCase_						) if isinstance(lowerCAmelCase_	,	lowerCAmelCase_						) else mask_token

				super().__init__(
				    vocab_file=lowerCAmelCase_	,	tokenizer_file=lowerCAmelCase_	,	bos_token=lowerCAmelCase_	,	eos_token=lowerCAmelCase_	,	sep_token=lowerCAmelCase_	,	cls_token=lowerCAmelCase_	,	unk_token=lowerCAmelCase_	,	pad_token=lowerCAmelCase_	,	mask_token=lowerCAmelCase_	,	src_lang=lowerCAmelCase_	,	tgt_lang=lowerCAmelCase_	,	additional_special_tokens=lowerCAmelCase_	,	**lowerCAmelCase_	,	)

				UpperCAmelCase_     : Tuple			     =					vocab_file
				UpperCAmelCase_     : str			     =					False if not self.vocab_file else True

				UpperCAmelCase_     : List[Any]			     =					FAIRSEQ_LANGUAGE_CODES.copy()

				if additional_special_tokens is not None:
							# Only add those special tokens if they are not already there.
							_additional_special_tokens.extend(
							    [t for t in additional_special_tokens if t not in _additional_special_tokens]						)

				self.add_special_tokens({"additional_special_tokens": _additional_special_tokens}						)
				UpperCAmelCase_     : Tuple			     =					{
				    lang_code: self.convert_tokens_to_ids(lowerCAmelCase_						) for lang_code in FAIRSEQ_LANGUAGE_CODES
				}

				UpperCAmelCase_     : int			     =					src_lang if src_lang is not None else "en_XX"
				UpperCAmelCase_     : Union[str, Any]			     =					self.convert_tokens_to_ids(self._src_lang						)
				UpperCAmelCase_     : Any			     =					tgt_lang
				self.set_src_lang_special_tokens(self._src_lang						)





	@property
	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[int]						)						->			str:
				return self._src_lang





	@src_lang.setter
	def      _SCREAMING_SNAKE_CASE      (      self					: Any	,	lowerCAmelCase_					: str						)						->			None:
				UpperCAmelCase_     : List[Any]			     =					new_src_lang
				self.set_src_lang_special_tokens(self._src_lang						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]	,	lowerCAmelCase_					: List[int]	,	lowerCAmelCase_					: Optional[List[int]] = None						)						->			List[int]:
				if token_ids_a is None:
							return self.prefix_tokens + token_ids_a + self.suffix_tokens
				# 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.suffix_tokens





	def      _SCREAMING_SNAKE_CASE      (      self					: List[Any]	,	lowerCAmelCase_					: List[int]	,	lowerCAmelCase_					: Optional[List[int]] = None						)						->			List[int]:
				UpperCAmelCase_     : List[str]			     =					[self.sep_token_id]
				UpperCAmelCase_     : Dict			     =					[self.cls_token_id]

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





	def      _SCREAMING_SNAKE_CASE      (      self					: Any	,	lowerCAmelCase_					: Tuple	,	lowerCAmelCase_					: str	,	lowerCAmelCase_					: Optional[str]	,	lowerCAmelCase_					: Optional[str]	,	**lowerCAmelCase_					: Union[str, Any]						)						->			Dict:
				if src_lang is None or tgt_lang is None:
							raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"						)
				UpperCAmelCase_     : str			     =					src_lang
				UpperCAmelCase_     : str			     =					self(lowerCAmelCase_	,	add_special_tokens=lowerCAmelCase_	,	return_tensors=lowerCAmelCase_	,	**lowerCAmelCase_						)
				UpperCAmelCase_     : Optional[int]			     =					self.convert_tokens_to_ids(lowerCAmelCase_						)
				UpperCAmelCase_     : Dict			     =					tgt_lang_id
				return inputs





	def      _SCREAMING_SNAKE_CASE      (      self					: List[Any]	,	lowerCAmelCase_					: List[str]	,	lowerCAmelCase_					: str = "en_XX"	,	lowerCAmelCase_					: Optional[List[str]] = None	,	lowerCAmelCase_					: str = "ro_RO"	,	**lowerCAmelCase_					: Dict	,	)						->			BatchEncoding:
				UpperCAmelCase_     : List[Any]			     =					src_lang
				UpperCAmelCase_     : Tuple			     =					tgt_lang
				return super().prepare_seqaseq_batch(lowerCAmelCase_	,	lowerCAmelCase_	,	**lowerCAmelCase_						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[int]						)						->			Any:
				return self.set_src_lang_special_tokens(self.src_lang						)





	def      _SCREAMING_SNAKE_CASE      (      self					: List[Any]						)						->			Dict:
				return self.set_tgt_lang_special_tokens(self.tgt_lang						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]	,	lowerCAmelCase_					: List[Any]						)						->			None:
				UpperCAmelCase_     : int			     =					self.convert_tokens_to_ids(lowerCAmelCase_						)
				UpperCAmelCase_     : str			     =					[]
				UpperCAmelCase_     : str			     =					[self.eos_token_id, self.cur_lang_code]

				UpperCAmelCase_     : Union[str, Any]			     =					self.convert_ids_to_tokens(self.prefix_tokens						)
				UpperCAmelCase_     : List[Any]			     =					self.convert_ids_to_tokens(self.suffix_tokens						)

				UpperCAmelCase_     : Optional[Any]			     =					processors.TemplateProcessing(
				    single=prefix_tokens_str + ["$A"] + suffix_tokens_str	,	pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str	,	special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str	,	self.prefix_tokens + self.suffix_tokens						)						)	,	)





	def      _SCREAMING_SNAKE_CASE      (      self					: Tuple	,	lowerCAmelCase_					: str						)						->			None:
				UpperCAmelCase_     : Union[str, Any]			     =					self.convert_tokens_to_ids(lowerCAmelCase_						)
				UpperCAmelCase_     : Dict			     =					[]
				UpperCAmelCase_     : Optional[int]			     =					[self.eos_token_id, self.cur_lang_code]

				UpperCAmelCase_     : Tuple			     =					self.convert_ids_to_tokens(self.prefix_tokens						)
				UpperCAmelCase_     : Tuple			     =					self.convert_ids_to_tokens(self.suffix_tokens						)

				UpperCAmelCase_     : Optional[Any]			     =					processors.TemplateProcessing(
				    single=prefix_tokens_str + ["$A"] + suffix_tokens_str	,	pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str	,	special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str	,	self.prefix_tokens + self.suffix_tokens						)						)	,	)





	def      _SCREAMING_SNAKE_CASE      (      self					: str	,	lowerCAmelCase_					: str	,	lowerCAmelCase_					: Optional[str] = None						)						->			Tuple[str]:
				if not self.can_save_slow_tokenizer:
							raise ValueError(
							    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
							    "tokenizer."						)

				if not os.path.isdir(lowerCAmelCase_						):
							logger.error(f"""Vocabulary path ({save_directory}) should be a directory."""						)
							return
				UpperCAmelCase_     : List[str]			     =					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_						):
							copyfile(self.vocab_file	,	lowerCAmelCase_						)

				return (out_vocab_file,)



