code: 
  
  
  from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfigWithPast
  from ...utils import logging
  
  
  UpperCamelCase__				       =			logging.get_logger(__name__)
  
  UpperCamelCase__				       =			{
      'uclanlp/plbart-base': 'https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json',
      # See all PLBART models at https://huggingface.co/models?filter=plbart
  }
  
  class 						UpperCAmelCase__   (      A_		):
  
  
  
       '''simple docstring'''
       UpperCAmelCase_         =  '''plbart'''
       UpperCAmelCase_         =  ['''past_key_values''']
       UpperCAmelCase_         =  {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}
  
  
  
  
       def __init__( self       :       List[Any]	,      UpperCamelCase       :       int=5_00_05	,      UpperCamelCase       :       Tuple=10_24	,      UpperCamelCase       :       Optional[int]=6	,      UpperCamelCase       :       Any=30_72	,      UpperCamelCase       :       Any=12	,      UpperCamelCase       :       List[str]=6	,      UpperCamelCase       :       Any=30_72	,      UpperCamelCase       :       Optional[int]=12	,      UpperCamelCase       :       Any=0.0	,      UpperCamelCase       :       Optional[Any]=0.0	,      UpperCamelCase       :       str=True	,      UpperCamelCase       :       List[Any]=True	,      UpperCamelCase       :       List[str]="gelu"	,      UpperCamelCase       :       List[Any]=7_68	,      UpperCamelCase       :       Tuple=0.1	,      UpperCamelCase       :       Optional[Any]=0.1	,      UpperCamelCase       :       int=0.0	,      UpperCamelCase       :       Any=0.02	,      UpperCamelCase       :       int=0.0	,      UpperCamelCase       :       Dict=True	,      UpperCamelCase       :       Any=1	,      UpperCamelCase       :       Optional[Any]=0	,      UpperCamelCase       :       List[str]=2	,      UpperCamelCase       :       Optional[Any]=2	,      **UpperCamelCase       :       int	,      ):
  
  
  
  
  
              """simple docstring"""
  
  
  
              _lowercase					:				Tuple           =			vocab_size
              _lowercase					:				Tuple           =			max_position_embeddings
              _lowercase					:				Union[str, Any]           =			d_model
              _lowercase					:				int           =			encoder_ffn_dim
              _lowercase					:				Tuple           =			encoder_layers
              _lowercase					:				Optional[int]           =			encoder_attention_heads
              _lowercase					:				List[str]           =			decoder_ffn_dim
              _lowercase					:				Union[str, Any]           =			decoder_layers
              _lowercase					:				str           =			decoder_attention_heads
              _lowercase					:				List[Any]           =			dropout
              _lowercase					:				Optional[Any]           =			attention_dropout
              _lowercase					:				Optional[int]           =			activation_dropout
              _lowercase					:				Dict           =			activation_function
              _lowercase					:				Tuple           =			init_std
              _lowercase					:				List[Any]           =			encoder_layerdrop
              _lowercase					:				Union[str, Any]           =			decoder_layerdrop
              _lowercase					:				Union[str, Any]           =			classifier_dropout
              _lowercase					:				List[Any]           =			use_cache
              _lowercase					:				Any           =			encoder_layers
              _lowercase					:				Optional[int]           =			scale_embedding  # scale factor will be sqrt(d_model) if True
              super().__init__(
                  pad_token_id=UpperCamelCase	,      bos_token_id=UpperCamelCase	,      eos_token_id=UpperCamelCase	,      is_encoder_decoder=UpperCamelCase	,      forced_eos_token_id=UpperCamelCase	,      **UpperCamelCase	,      )
  
  
  
  
  class 						UpperCAmelCase__   (      A_		):
  
  
  
       '''simple docstring'''
  
  
  
  
       @property
       def   lowerCAmelCase_   ( self       :       Optional[int]		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              return OrderedDict(
                  [
                      ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
                      ('''attention_mask''', {0: '''batch''', 1: '''sequence'''}),
                  ]		)
  
  
  
  
       @property
       def   lowerCAmelCase_   ( self       :       Tuple		):
  
  
  
  
  
              """simple docstring"""
  
  
  
              if self.use_past:
                     return OrderedDict(
                         [
                             ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                             ('''past_keys''', {0: '''batch''', 2: '''sequence'''}),
                             ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                         ]		)
              else:
                     return OrderedDict(
                         [
                             ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                             ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                         ]		)
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  UpperCamelCase__				       =			{
      'configuration_realm': ['REALM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RealmConfig'],
      'tokenization_realm': ['RealmTokenizer'],
  }
  
  try:
     if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     UpperCamelCase__				       =			['RealmTokenizerFast']
  
  try:
     if not is_torch_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     UpperCamelCase__				       =			[
         'REALM_PRETRAINED_MODEL_ARCHIVE_LIST',
         'RealmEmbedder',
         'RealmForOpenQA',
         'RealmKnowledgeAugEncoder',
         'RealmPreTrainedModel',
         'RealmReader',
         'RealmScorer',
         'load_tf_weights_in_realm',
     ]
     UpperCamelCase__				       =			['RealmRetriever']
  
  
  if TYPE_CHECKING:
     from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
     from .tokenization_realm import RealmTokenizer
  
     try:
        if not is_tokenizers_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .tokenization_realm import RealmTokenizerFast
  
     try:
        if not is_torch_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .modeling_realm import (
            REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
            RealmEmbedder,
            RealmForOpenQA,
            RealmKnowledgeAugEncoder,
            RealmPreTrainedModel,
            RealmReader,
            RealmScorer,
            load_tf_weights_in_realm,
        )
        from .retrieval_realm import RealmRetriever
  
  
  else:
     import sys
  
     UpperCamelCase__				       =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)