code: 
  
  
  '''simple docstring'''
  
  
  
  import copy
  from typing import Dict
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  from ..auto.configuration_auto import CONFIG_MAPPING
  from ..bit import BitConfig
  
  
  A__	:      Union[str, Any]				=						logging.get_logger(__name__)
  
  A__	:      List[Any]				=						{
      """google/vit-hybrid-base-bit-384""": """https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json""",
      # See all ViT hybrid models at https://huggingface.co/models?filter=vit
  }
  
  
  
  
  
  class      UpperCAmelCase_						(_UpperCAmelCase						):
  
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
      lowerCamelCase						:      Any							  =    'vit-hybrid'
  
  
  
  
  
  
  
      def __init__(							self    ,  SCREAMING_SNAKE_CASE_=None    ,  SCREAMING_SNAKE_CASE_=7_68    ,  SCREAMING_SNAKE_CASE_=12    ,  SCREAMING_SNAKE_CASE_=12    ,  SCREAMING_SNAKE_CASE_=30_72    ,  SCREAMING_SNAKE_CASE_="gelu"    ,  SCREAMING_SNAKE_CASE_=0.0    ,  SCREAMING_SNAKE_CASE_=0.0    ,  SCREAMING_SNAKE_CASE_=0.0_2    ,  SCREAMING_SNAKE_CASE_=1E-12    ,  SCREAMING_SNAKE_CASE_=2_24    ,  SCREAMING_SNAKE_CASE_=1    ,  SCREAMING_SNAKE_CASE_=3    ,  SCREAMING_SNAKE_CASE_=[1, 10_24, 24, 24]    ,  SCREAMING_SNAKE_CASE_=True    ,  **SCREAMING_SNAKE_CASE_    ,  )       ->  Union[str, Any]:
           super().__init__(**SCREAMING_SNAKE_CASE_			)
  
           if backbone_config is None:
                logger.info('`backbone_config` is `None`. Initializing the config with a `BiT` backbone.'			)
                __lowerCamelCase     :			Optional[int]              =	{
                    'global_padding': 'same',
                    'layer_type': 'bottleneck',
                    'depths': [3, 4, 9],
                    'out_features': ['stage3'],
                    'embedding_dynamic_padding': True,
                }
  
           if isinstance(SCREAMING_SNAKE_CASE_    ,  SCREAMING_SNAKE_CASE_			):
                if "model_type" in backbone_config:
                     __lowerCamelCase     :			Any              =	CONFIG_MAPPING[backbone_config['model_type']]
                else:
                     logger.info(
                         '`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class.'			)
                     __lowerCamelCase     :			List[str]              =	BitConfig
                __lowerCamelCase     :			Dict              =	backbone_config_class(**SCREAMING_SNAKE_CASE_			)
  
           __lowerCamelCase     :			List[Any]              =	backbone_featmap_shape
           __lowerCamelCase     :			Dict              =	backbone_config
           __lowerCamelCase     :			Any              =	hidden_size
           __lowerCamelCase     :			Union[str, Any]              =	num_hidden_layers
           __lowerCamelCase     :			List[str]              =	num_attention_heads
           __lowerCamelCase     :			List[str]              =	intermediate_size
           __lowerCamelCase     :			Any              =	hidden_act
           __lowerCamelCase     :			Tuple              =	hidden_dropout_prob
           __lowerCamelCase     :			Union[str, Any]              =	attention_probs_dropout_prob
           __lowerCamelCase     :			Union[str, Any]              =	initializer_range
           __lowerCamelCase     :			Union[str, Any]              =	layer_norm_eps
           __lowerCamelCase     :			Optional[Any]              =	image_size
           __lowerCamelCase     :			int              =	patch_size
           __lowerCamelCase     :			Any              =	num_channels
           __lowerCamelCase     :			Optional[Any]              =	qkv_bias
  
  
  
  
  
  
  
      def    lowercase_       (							self			)       ->  Dict[str, any]:
           __lowerCamelCase     :			List[Any]              =	copy.deepcopy(self.__dict__			)
           __lowerCamelCase     :			Union[str, Any]              =	self.backbone_config.to_dict()
           __lowerCamelCase     :			Tuple              =	self.__class__.model_type
           return output
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  from typing import Callable, Optional, Union
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  A__	:      Any				=						logging.get_logger(__name__)
  
  A__	:      str				=						{
      """microsoft/prophetnet-large-uncased""": (
          """https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"""
      ),
  }
  
  
  
  
  
  class      UpperCAmelCase_						(_UpperCAmelCase						):
  
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
      lowerCamelCase						:      Dict							  =    'prophetnet'
      lowerCamelCase						:      List[str]							  =    ['past_key_values']
      lowerCamelCase						:      List[str]							  =    {
          'num_attention_heads': 'num_encoder_attention_heads',
      }
  
  
  
  
  
  
  
      def __init__(							self    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = "gelu"    ,  SCREAMING_SNAKE_CASE_ = 3_05_22    ,  SCREAMING_SNAKE_CASE_ = 10_24    ,  SCREAMING_SNAKE_CASE_ = 40_96    ,  SCREAMING_SNAKE_CASE_ = 12    ,  SCREAMING_SNAKE_CASE_ = 16    ,  SCREAMING_SNAKE_CASE_ = 40_96    ,  SCREAMING_SNAKE_CASE_ = 12    ,  SCREAMING_SNAKE_CASE_ = 16    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = 5_12    ,  SCREAMING_SNAKE_CASE_ = 0.0_2    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = 0    ,  SCREAMING_SNAKE_CASE_ = 2    ,  SCREAMING_SNAKE_CASE_ = 32    ,  SCREAMING_SNAKE_CASE_ = 1_28    ,  SCREAMING_SNAKE_CASE_ = False    ,  SCREAMING_SNAKE_CASE_ = 0.0    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = 0    ,  SCREAMING_SNAKE_CASE_ = 1    ,  SCREAMING_SNAKE_CASE_ = 2    ,  **SCREAMING_SNAKE_CASE_    ,  )       ->  List[Any]:
           __lowerCamelCase     :			List[Any]              =	vocab_size
           __lowerCamelCase     :			Union[str, Any]              =	hidden_size
           __lowerCamelCase     :			Tuple              =	encoder_ffn_dim
           __lowerCamelCase     :			Any              =	num_encoder_layers
           __lowerCamelCase     :			int              =	num_encoder_attention_heads
           __lowerCamelCase     :			Optional[Any]              =	decoder_ffn_dim
           __lowerCamelCase     :			str              =	num_decoder_layers
           __lowerCamelCase     :			int              =	num_decoder_attention_heads
           __lowerCamelCase     :			Union[str, Any]              =	max_position_embeddings
           __lowerCamelCase     :			Optional[Any]              =	init_std  # Normal(0, this parameter)
           __lowerCamelCase     :			Union[str, Any]              =	activation_function
  
           # parameters for prophetnet
           __lowerCamelCase     :			int              =	ngram
           __lowerCamelCase     :			Optional[int]              =	num_buckets
           __lowerCamelCase     :			str              =	relative_max_distance
           __lowerCamelCase     :			Optional[Any]              =	disable_ngram_loss
           __lowerCamelCase     :			str              =	eps
  
           # 3 Types of Dropout
           __lowerCamelCase     :			Optional[Any]              =	attention_dropout
           __lowerCamelCase     :			str              =	activation_dropout
           __lowerCamelCase     :			Optional[Any]              =	dropout
  
           __lowerCamelCase     :			Optional[Any]              =	use_cache
  
           super().__init__(
               pad_token_id=SCREAMING_SNAKE_CASE_    ,  bos_token_id=SCREAMING_SNAKE_CASE_    ,  eos_token_id=SCREAMING_SNAKE_CASE_    ,  is_encoder_decoder=SCREAMING_SNAKE_CASE_    ,  add_cross_attention=SCREAMING_SNAKE_CASE_    ,  decoder_start_token_id=SCREAMING_SNAKE_CASE_    ,  **SCREAMING_SNAKE_CASE_    ,  )
  
  
  
  
  
  
  
      @property
      def    lowercase_       (							self			)       ->  int:
           return self.num_encoder_layers + self.num_decoder_layers
  
  
  
  
  
  
  
      @num_hidden_layers.setter
      def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_			)       ->  Union[str, Any]:
           raise NotImplementedError(
               'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
               ' `num_decoder_layers`.'			)
  
  
  
  
  
  
  