



"""simple docstring"""






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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
	from transformers.pipelines.conversational import Conversation


__snake_case							:     Union[str, Any]   =					logging.get_logger(__name__)

__snake_case							:     Tuple   =					{'tokenizer_file': 'tokenizer.json'}

__snake_case							:     Union[str, Any]   =					{
    'tokenizer_file': {
        'bigscience/tokenizer': 'https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json',
        'bigscience/bloom-560m': 'https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json',
        'bigscience/bloom-1b1': 'https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json',
        'bigscience/bloom-1b7': 'https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json',
        'bigscience/bloom-3b': 'https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json',
        'bigscience/bloom-7b1': 'https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json',
        'bigscience/bloom': 'https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json',
    },
}



class     A__     (						__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE					   =			PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE					   =			['input_ids', 'attention_mask']
	SCREAMING_SNAKE_CASE					   =			None

	def __init__(  self:	List[Any] ,    _SCREAMING_SNAKE_CASE:	str=None ,    _SCREAMING_SNAKE_CASE:	Dict=None ,    _SCREAMING_SNAKE_CASE:	Optional[Any]=None ,    _SCREAMING_SNAKE_CASE:	int="<unk>" ,    _SCREAMING_SNAKE_CASE:	Dict="<s>" ,    _SCREAMING_SNAKE_CASE:	str="</s>" ,    _SCREAMING_SNAKE_CASE:	int="<pad>" ,    _SCREAMING_SNAKE_CASE:	List[str]=False ,    _SCREAMING_SNAKE_CASE:	List[Any]=False ,    **_SCREAMING_SNAKE_CASE:	List[Any] ,    )       -> Tuple:

				"""simple docstring"""

				super().__init__(
				    _SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    tokenizer_file=_SCREAMING_SNAKE_CASE ,    unk_token=_SCREAMING_SNAKE_CASE ,    bos_token=_SCREAMING_SNAKE_CASE ,    eos_token=_SCREAMING_SNAKE_CASE ,    pad_token=_SCREAMING_SNAKE_CASE ,    add_prefix_space=_SCREAMING_SNAKE_CASE ,    clean_up_tokenization_spaces=_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE ,    )
				__lowerCAmelCase   :						Dict				= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
				if pre_tok_state.get("add_prefix_space" ,    _SCREAMING_SNAKE_CASE) != add_prefix_space:
							__lowerCAmelCase   :						Union[str, Any]				= getattr(_SCREAMING_SNAKE_CASE ,    pre_tok_state.pop("type"))
							__lowerCAmelCase   :						Tuple				= add_prefix_space
							__lowerCAmelCase   :						Tuple				= pre_tok_class(**_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						str				= add_prefix_space

	def 							_SCREAMING_SNAKE_CASE     (  self:	str ,    *_SCREAMING_SNAKE_CASE:	Any ,    **_SCREAMING_SNAKE_CASE:	List[str])       -> BatchEncoding:

				"""simple docstring"""

				__lowerCAmelCase   :						Tuple				= kwargs.get("is_split_into_words" ,    _SCREAMING_SNAKE_CASE)
				if not (self.add_prefix_space or not is_split_into_words):
							raise Exception(
							    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
							    " pretokenized inputs.")

				return super()._batch_encode_plus(*_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict ,    *_SCREAMING_SNAKE_CASE:	Union[str, Any] ,    **_SCREAMING_SNAKE_CASE:	List[str])       -> BatchEncoding:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= kwargs.get("is_split_into_words" ,    _SCREAMING_SNAKE_CASE)

				if not (self.add_prefix_space or not is_split_into_words):
							raise Exception(
							    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
							    " pretokenized inputs.")

				return super()._encode_plus(*_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE     (  self:	int ,    _SCREAMING_SNAKE_CASE:	str ,    _SCREAMING_SNAKE_CASE:	Optional[str] = None)       -> Tuple[str]:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= self._tokenizer.model.save(_SCREAMING_SNAKE_CASE ,    name=_SCREAMING_SNAKE_CASE)
				return tuple(_SCREAMING_SNAKE_CASE)







	def 							_SCREAMING_SNAKE_CASE     (  self:	str ,    _SCREAMING_SNAKE_CASE:	"Conversation")       -> List[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						Any				= []
				for is_user, text in conversation.iter_texts():
							input_ids.extend(self.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE) + [self.eos_token_id])

				if len(_SCREAMING_SNAKE_CASE) > self.model_max_length:
							__lowerCAmelCase   :						Dict				= input_ids[-self.model_max_length :]
				return input_ids




"""simple docstring"""






import logging

from transformers.configuration_utils import PretrainedConfig


__snake_case							:     Tuple   =					logging.getLogger(__name__)



class     A__     (						__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			'masked_bert'

	def __init__(  self:	str ,    _SCREAMING_SNAKE_CASE:	Tuple=3_0522 ,    _SCREAMING_SNAKE_CASE:	Optional[int]=768 ,    _SCREAMING_SNAKE_CASE:	List[str]=12 ,    _SCREAMING_SNAKE_CASE:	Any=12 ,    _SCREAMING_SNAKE_CASE:	Optional[int]=3072 ,    _SCREAMING_SNAKE_CASE:	List[str]="gelu" ,    _SCREAMING_SNAKE_CASE:	List[str]=0.1 ,    _SCREAMING_SNAKE_CASE:	str=0.1 ,    _SCREAMING_SNAKE_CASE:	Dict=512 ,    _SCREAMING_SNAKE_CASE:	List[Any]=2 ,    _SCREAMING_SNAKE_CASE:	Tuple=0.02 ,    _SCREAMING_SNAKE_CASE:	int=1e-12 ,    _SCREAMING_SNAKE_CASE:	int=0 ,    _SCREAMING_SNAKE_CASE:	Tuple="topK" ,    _SCREAMING_SNAKE_CASE:	Any="constant" ,    _SCREAMING_SNAKE_CASE:	int=0.0 ,    **_SCREAMING_SNAKE_CASE:	Any ,    )       -> List[str]:

				"""simple docstring"""

				super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						Union[str, Any]				= vocab_size
				__lowerCAmelCase   :						List[str]				= hidden_size
				__lowerCAmelCase   :						Any				= num_hidden_layers
				__lowerCAmelCase   :						Dict				= num_attention_heads
				__lowerCAmelCase   :						Union[str, Any]				= hidden_act
				__lowerCAmelCase   :						Optional[Any]				= intermediate_size
				__lowerCAmelCase   :						int				= hidden_dropout_prob
				__lowerCAmelCase   :						List[Any]				= attention_probs_dropout_prob
				__lowerCAmelCase   :						int				= max_position_embeddings
				__lowerCAmelCase   :						str				= type_vocab_size
				__lowerCAmelCase   :						Any				= initializer_range
				__lowerCAmelCase   :						Optional[int]				= layer_norm_eps
				__lowerCAmelCase   :						Tuple				= pruning_method
				__lowerCAmelCase   :						Union[str, Any]				= mask_init
				__lowerCAmelCase   :						str				= mask_scale