




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


__magic_name__  :  Tuple					=       logging.get_logger(__name__)

__magic_name__  :  Union[str, Any]					=       {"""tokenizer_file""": """tokenizer.json"""}

__magic_name__  :  str					=       {
    """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     SCREAMING_SNAKE_CASE__		(_a			):
     lowercase_ :      Optional[int]				= VOCAB_FILES_NAMES
     lowercase_ :      Dict				= PRETRAINED_VOCAB_FILES_MAP
     lowercase_ :      Union[str, Any]				= ["input_ids", "attention_mask"]
     lowercase_ :      Optional[int]				= None
     def __init__(						self	:		Union[str, Any]       ,						__lowerCamelCase	:		Union[str, Any]=None       ,						__lowerCamelCase	:		Tuple=None       ,						__lowerCamelCase	:		int=None       ,						__lowerCamelCase	:		List[str]="<unk>"       ,						__lowerCamelCase	:		Any="<s>"       ,						__lowerCamelCase	:		Dict="</s>"       ,						__lowerCamelCase	:		str="<pad>"       ,						__lowerCamelCase	:		List[Any]=False       ,						__lowerCamelCase	:		Any=False       ,						**__lowerCamelCase	:		Union[str, Any]       ,						):



       """simple docstring"""
       super().__init__(
           __lowerCamelCase       ,						__lowerCamelCase       ,						tokenizer_file=__lowerCamelCase       ,						unk_token=__lowerCamelCase       ,						bos_token=__lowerCamelCase       ,						eos_token=__lowerCamelCase       ,						pad_token=__lowerCamelCase       ,						add_prefix_space=__lowerCamelCase       ,						clean_up_tokenization_spaces=__lowerCamelCase       ,						**__lowerCamelCase       ,						)
       lowerCAmelCase__										=      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()						)
       if pre_tok_state.get('''add_prefix_space'''       ,						__lowerCamelCase						) != add_prefix_space:
         lowerCAmelCase__										=      getattr(__lowerCamelCase       ,						pre_tok_state.pop('''type'''						)						)
         lowerCAmelCase__										=      add_prefix_space
         lowerCAmelCase__										=      pre_tok_class(**__lowerCamelCase						)

       lowerCAmelCase__										=      add_prefix_space
     def        A__      (						self	:		Union[str, Any]       ,						*__lowerCamelCase	:		List[str]       ,						**__lowerCamelCase	:		List[Any]						):



       """simple docstring"""
       lowerCAmelCase__										=      kwargs.get('''is_split_into_words'''       ,						__lowerCamelCase						)
       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(*__lowerCamelCase       ,						**__lowerCamelCase						)
     def        A__      (						self	:		List[Any]       ,						*__lowerCamelCase	:		Dict       ,						**__lowerCamelCase	:		int						):



       """simple docstring"""
       lowerCAmelCase__										=      kwargs.get('''is_split_into_words'''       ,						__lowerCamelCase						)

       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(*__lowerCamelCase       ,						**__lowerCamelCase						)
     def        A__      (						self	:		Optional[int]       ,						__lowerCamelCase	:		str       ,						__lowerCamelCase	:		Optional[str] = None						):



       """simple docstring"""
       lowerCAmelCase__										=      self._tokenizer.model.save(__lowerCamelCase       ,						name=__lowerCamelCase						)
       return tuple(__lowerCamelCase						)



     def        A__      (						self	:		List[str]       ,						__lowerCamelCase	:		"Conversation"						):



       """simple docstring"""
       lowerCAmelCase__										=      []
       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:
         lowerCAmelCase__										=      input_ids[-self.model_max_length :]
       return input_ids







import logging

from transformers.configuration_utils import PretrainedConfig


__magic_name__  :  Tuple					=       logging.getLogger(__name__)





class     SCREAMING_SNAKE_CASE__		(_a			):
     lowercase_ :      Tuple				= "masked_bert"
     def __init__(						self	:		List[Any]       ,						__lowerCamelCase	:		Optional[Any]=3_05_22       ,						__lowerCamelCase	:		Dict=7_68       ,						__lowerCamelCase	:		Tuple=12       ,						__lowerCamelCase	:		int=12       ,						__lowerCamelCase	:		Tuple=30_72       ,						__lowerCamelCase	:		List[Any]="gelu"       ,						__lowerCamelCase	:		Union[str, Any]=0.1       ,						__lowerCamelCase	:		Dict=0.1       ,						__lowerCamelCase	:		Optional[int]=5_12       ,						__lowerCamelCase	:		List[Any]=2       ,						__lowerCamelCase	:		Union[str, Any]=0.02       ,						__lowerCamelCase	:		Optional[int]=1e-12       ,						__lowerCamelCase	:		Optional[int]=0       ,						__lowerCamelCase	:		List[str]="topK"       ,						__lowerCamelCase	:		Union[str, Any]="constant"       ,						__lowerCamelCase	:		Union[str, Any]=0.0       ,						**__lowerCamelCase	:		Tuple       ,						):



       """simple docstring"""
       super().__init__(pad_token_id=__lowerCamelCase       ,						**__lowerCamelCase						)

       lowerCAmelCase__										=      vocab_size
       lowerCAmelCase__										=      hidden_size
       lowerCAmelCase__										=      num_hidden_layers
       lowerCAmelCase__										=      num_attention_heads
       lowerCAmelCase__										=      hidden_act
       lowerCAmelCase__										=      intermediate_size
       lowerCAmelCase__										=      hidden_dropout_prob
       lowerCAmelCase__										=      attention_probs_dropout_prob
       lowerCAmelCase__										=      max_position_embeddings
       lowerCAmelCase__										=      type_vocab_size
       lowerCAmelCase__										=      initializer_range
       lowerCAmelCase__										=      layer_norm_eps
       lowerCAmelCase__										=      pruning_method
       lowerCAmelCase__										=      mask_init
       lowerCAmelCase__										=      mask_scale

