






'''simple docstring'''




from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


lowerCamelCase_												=					logging.get_logger(__name__)

lowerCamelCase_												=					{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

lowerCamelCase_												=					{
    '''vocab_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'''
    },
    '''tokenizer_config_file''': {
        '''facebook/blenderbot_small-90M''': (
            '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'''
        )
    },
}

lowerCamelCase_												=					{
    '''facebook/blenderbot_small-90M''': 5_12,
}

class    _UpperCAmelCase			(     snake_case_						):




   """simple docstring"""

   snake_case    				=						VOCAB_FILES_NAMES
   snake_case    				=						PRETRAINED_VOCAB_FILES_MAP
   snake_case    				=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   snake_case    				=						BlenderbotSmallTokenizer

   def __init__(		self :	Optional[int]      ,      __UpperCAmelCase :	str=None      ,      __UpperCAmelCase :	int=None      ,      __UpperCAmelCase :	Any="<|endoftext|>"      ,      __UpperCAmelCase :	Optional[int]="<|endoftext|>"      ,      __UpperCAmelCase :	Any="<|endoftext|>"      ,      __UpperCAmelCase :	List[Any]=False      ,      __UpperCAmelCase :	Dict=True      ,      **__UpperCAmelCase :	str      ,      ):





         '''simple docstring'''





         super().__init__(
             ByteLevelBPETokenizer(
                 vocab=__UpperCAmelCase      ,      merges=__UpperCAmelCase      ,      add_prefix_space=__UpperCAmelCase      ,      trim_offsets=__UpperCAmelCase      ,      )      ,      bos_token=__UpperCAmelCase      ,      eos_token=__UpperCAmelCase      ,      unk_token=__UpperCAmelCase      ,      **__UpperCAmelCase      ,      )
         _A			     =	add_prefix_space

   def 						lowerCAmelCase (		self :	Tuple      ,      __UpperCAmelCase :	int      ,      __UpperCAmelCase :	int=None		):





         '''simple docstring'''





         _A			     =	[self.bos_token_id] + token_ids_a + [self.eos_token_id]
         if token_ids_a is None:
               return output

         return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]

   def 						lowerCAmelCase (		self :	List[Any]      ,      __UpperCAmelCase :	List[int]      ,      __UpperCAmelCase :	Optional[List[int]] = None		):





         '''simple docstring'''





         _A			     =	[self.sep_token_id]
         _A			     =	[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]












"""simple docstring"""



import logging

from transformers.configuration_utils import PretrainedConfig


a_ =			logging.getLogger(__name__)






class 		__snake_case					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 _lowerCamelCase        =     """masked_bert"""

 def __init__(    self					,						__lowerCamelCase=3_0522					,						__lowerCamelCase=768					,						__lowerCamelCase=12					,						__lowerCamelCase=12					,						__lowerCamelCase=3072					,						__lowerCamelCase="gelu"					,						__lowerCamelCase=0.1					,						__lowerCamelCase=0.1					,						__lowerCamelCase=512					,						__lowerCamelCase=2					,						__lowerCamelCase=0.0_2					,						__lowerCamelCase=1e-1_2					,						__lowerCamelCase=0					,						__lowerCamelCase="topK"					,						__lowerCamelCase="constant"					,						__lowerCamelCase=0.0					,						**__lowerCamelCase					,						):



     '''simple docstring'''




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

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




