code: 
  
  
  
  
  
  
  """simple docstring"""
  
  from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  lowercase__      =				logging.get_logger(__name__)
  
  lowercase__      =				{
      """google/electra-small-generator""": """https://huggingface.co/google/electra-small-generator/resolve/main/config.json""",
      """google/electra-base-generator""": """https://huggingface.co/google/electra-base-generator/resolve/main/config.json""",
      """google/electra-large-generator""": """https://huggingface.co/google/electra-large-generator/resolve/main/config.json""",
      """google/electra-small-discriminator""": (
          """https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json"""
      ),
      """google/electra-base-discriminator""": (
          """https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json"""
      ),
      """google/electra-large-discriminator""": (
          """https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json"""
      ),
  }
  
  
  class 	__lowerCamelCase       (				A__    ):
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  		a_			:       List[Any]      =							"""electra"""
  
  
  
  
  
  		def __init__(     self							:			Tuple		,    a_							:			int=3_05_22		,    a_							:			Tuple=1_28		,    a_							:			str=2_56		,    a_							:			int=12		,    a_							:			str=4		,    a_							:			Optional[Any]=10_24		,    a_							:			Any="gelu"		,    a_							:			Any=0.1		,    a_							:			Optional[Any]=0.1		,    a_							:			Optional[int]=5_12		,    a_							:			List[Any]=2		,    a_							:			List[str]=0.02		,    a_							:			int=1e-1_2		,    a_							:			Any="first"		,    a_							:			List[str]=True		,    a_							:			int="gelu"		,    a_							:			Dict=0.1		,    a_							:			int=0		,    a_							:			Dict="absolute"		,    a_							:			List[str]=True		,    a_							:			Tuple=None		,    **a_							:			List[str]		,    ):
  				super().__init__(pad_token_id=a_		,    **a_			)
  
  				lowerCAmelCase_     :							Optional[int]             =    vocab_size
  				lowerCAmelCase_     :							int             =    embedding_size
  				lowerCAmelCase_     :							Dict             =    hidden_size
  				lowerCAmelCase_     :							str             =    num_hidden_layers
  				lowerCAmelCase_     :							Optional[Any]             =    num_attention_heads
  				lowerCAmelCase_     :							List[Any]             =    intermediate_size
  				lowerCAmelCase_     :							Optional[Any]             =    hidden_act
  				lowerCAmelCase_     :							List[str]             =    hidden_dropout_prob
  				lowerCAmelCase_     :							Optional[int]             =    attention_probs_dropout_prob
  				lowerCAmelCase_     :							Optional[int]             =    max_position_embeddings
  				lowerCAmelCase_     :							int             =    type_vocab_size
  				lowerCAmelCase_     :							List[str]             =    initializer_range
  				lowerCAmelCase_     :							str             =    layer_norm_eps
  
  				lowerCAmelCase_     :							List[Any]             =    summary_type
  				lowerCAmelCase_     :							Union[str, Any]             =    summary_use_proj
  				lowerCAmelCase_     :							Any             =    summary_activation
  				lowerCAmelCase_     :							List[Any]             =    summary_last_dropout
  				lowerCAmelCase_     :							Optional[Any]             =    position_embedding_type
  				lowerCAmelCase_     :							Optional[Any]             =    use_cache
  				lowerCAmelCase_     :							Optional[Any]             =    classifier_dropout
  
  
  
  
  
  
  
  class 	__lowerCamelCase       (				A__    ):
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  		@property
  		def      lowerCamelCase (     self							:			int			):
  				if self.task == "multiple-choice":
  						lowerCAmelCase_     :							Optional[Any]             =    {0: "batch", 1: "choice", 2: "sequence"}
  				else:
  						lowerCAmelCase_     :							Dict             =    {0: "batch", 1: "sequence"}
  				return OrderedDict(
  				    [
  				        ("input_ids", dynamic_axis),
  				        ("attention_mask", dynamic_axis),
  				        ("token_type_ids", dynamic_axis),
  				    ]			)
  
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
      is_vision_available,
  )
  
  
  lowercase__      =				{
      """configuration_mobilevitv2""": [
          """MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
          """MobileViTV2Config""",
          """MobileViTV2OnnxConfig""",
      ],
  }
  
  
  try:
  					if not is_torch_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					lowercase__      =				[
  					    """MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
  					    """MobileViTV2ForImageClassification""",
  					    """MobileViTV2ForSemanticSegmentation""",
  					    """MobileViTV2Model""",
  					    """MobileViTV2PreTrainedModel""",
  					]
  
  if TYPE_CHECKING:
  					from .configuration_mobilevitva import (
  					    MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
  					    MobileViTVaConfig,
  					    MobileViTVaOnnxConfig,
  					)
  
  					try:
  										if not is_torch_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .modeling_mobilevitva import (
  										    MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
  										    MobileViTVaForImageClassification,
  										    MobileViTVaForSemanticSegmentation,
  										    MobileViTVaModel,
  										    MobileViTVaPreTrainedModel,
  										)
  
  else:
  					import sys
  
  					lowercase__      =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  