




'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A     =logging.get_logger(__name__)

A     ={
    'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/config.json',
    'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/config.json',
    'xlm-roberta-large-finetuned-conll02-dutch': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll02-spanish': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-english': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-german': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json'
    ),
}


class 			_a  (	__a ):
       __a				:     Union[str, Any]   				=					"""xlm-roberta"""
       def __init__(	self						:	List[str]   ,				lowercase						:	Any=30_522   ,				lowercase						:	Optional[Any]=768   ,				lowercase						:	Optional[int]=12   ,				lowercase						:	List[str]=12   ,				lowercase						:	Optional[Any]=3_072   ,				lowercase						:	Any="gelu"   ,				lowercase						:	Union[str, Any]=0.1   ,				lowercase						:	List[str]=0.1   ,				lowercase						:	Union[str, Any]=512   ,				lowercase						:	List[str]=2   ,				lowercase						:	Dict=0.02   ,				lowercase						:	Union[str, Any]=1E-12   ,				lowercase						:	Tuple=1   ,				lowercase						:	int=0   ,				lowercase						:	Dict=2   ,				lowercase						:	List[Any]="absolute"   ,				lowercase						:	List[str]=True   ,				lowercase						:	Dict=None   ,				**lowercase						:	str   ,				):



           '''simple docstring'''

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

           UpperCAmelCase			       =		vocab_size
           UpperCAmelCase			       =		hidden_size
           UpperCAmelCase			       =		num_hidden_layers
           UpperCAmelCase			       =		num_attention_heads
           UpperCAmelCase			       =		hidden_act
           UpperCAmelCase			       =		intermediate_size
           UpperCAmelCase			       =		hidden_dropout_prob
           UpperCAmelCase			       =		attention_probs_dropout_prob
           UpperCAmelCase			       =		max_position_embeddings
           UpperCAmelCase			       =		type_vocab_size
           UpperCAmelCase			       =		initializer_range
           UpperCAmelCase			       =		layer_norm_eps
           UpperCAmelCase			       =		position_embedding_type
           UpperCAmelCase			       =		use_cache
           UpperCAmelCase			       =		classifier_dropout






class 			_a  (	__a ):
       @property
       def     A      (	self						:	Optional[Any]				):



           '''simple docstring'''

           if self.task == "multiple-choice":
               UpperCAmelCase			       =		{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
           else:
               UpperCAmelCase			       =		{0: '''batch''', 1: '''sequence'''}
           return OrderedDict(
               [
                   ('''input_ids''', dynamic_axis),
                   ('''attention_mask''', dynamic_axis),
               ]				)








import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
						from transformers.pipelines.conversational import Conversation


__lowerCAmelCase	: Optional[int]  				=logging.get_logger(__name__)

__lowerCAmelCase	: Optional[Any]  				={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

__lowerCAmelCase	: List[str]  				={
    'tokenizer_file': {
        'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json',
    },
}

__lowerCAmelCase	: Optional[int]  				={
    'gpt-neox-20b': 2_0_4_8,
}
class        _lowercase      (			A__       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			str						=		VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE__				:			Dict						=		PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE__				:			Any						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE__				:			Optional[Any]						=		['''input_ids''', '''attention_mask''']


				def __init__(       self			:int			,			lowerCAmelCase__			:Any=None			,			lowerCAmelCase__			:Optional[Any]=None			,			lowerCAmelCase__			:List[Any]=None			,			lowerCAmelCase__			:str="<|endoftext|>"			,			lowerCAmelCase__			:str="<|endoftext|>"			,			lowerCAmelCase__			:Dict="<|endoftext|>"			,			lowerCAmelCase__			:Union[str, Any]=False			,			**lowerCAmelCase__			:List[str]			,			)		->			Any:
										super().__init__(
										    lowerCAmelCase__			,			lowerCAmelCase__			,			tokenizer_file=lowerCAmelCase__			,			unk_token=lowerCAmelCase__			,			bos_token=lowerCAmelCase__			,			eos_token=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			**lowerCAmelCase__			,			)

										__SCREAMING_SNAKE_CASE						:     List[Any]					=		json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
										if pre_tok_state.get('''add_prefix_space'''			,			lowerCAmelCase__	) != add_prefix_space:
																__SCREAMING_SNAKE_CASE						:     List[str]					=		getattr(lowerCAmelCase__			,			pre_tok_state.pop('''type'''	)	)
																__SCREAMING_SNAKE_CASE						:     str					=		add_prefix_space
																__SCREAMING_SNAKE_CASE						:     Any					=		pre_tok_class(**lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		add_prefix_space


				def 		__magic_name__(       self			:Union[str, Any]			,			lowerCAmelCase__			:str			,			lowerCAmelCase__			:Optional[str] = None	)		->			Tuple[str]:
										__SCREAMING_SNAKE_CASE						:     List[str]					=		self._tokenizer.model.save(lowerCAmelCase__			,			name=lowerCAmelCase__	)
										return tuple(lowerCAmelCase__	)



				def 		__magic_name__(       self			:Optional[Any]			,			lowerCAmelCase__			:"Conversation"	)		->			List[int]:
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		[]
										for is_user, text in conversation.iter_texts():
																input_ids.extend(self.encode(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	) + [self.eos_token_id]	)

										if len(lowerCAmelCase__	) > self.model_max_length:
																__SCREAMING_SNAKE_CASE						:     List[str]					=		input_ids[-self.model_max_length :]
										return input_ids
