code: 
  '''simple docstring'''
  
  
  
  from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  __A          =    logging.get_logger(__name__)
  
  __A          =    {
      "google/rembert": "https://huggingface.co/google/rembert/resolve/main/config.json",
      # See all RemBERT models at https://huggingface.co/models?filter=rembert
  }
  
  
  
  
  
  class 			A							(       _a				):
  			lowerCamelCase							:							Optional[Any]       		=  'rembert'
  
  
  
  			def __init__(					self       ,     lowerCamelCase__=250_300       ,     lowerCamelCase__=1_152       ,     lowerCamelCase__=32       ,     lowerCamelCase__=18       ,     lowerCamelCase__=256       ,     lowerCamelCase__=1_664       ,     lowerCamelCase__=4_608       ,     lowerCamelCase__="gelu"       ,     lowerCamelCase__=0.0       ,     lowerCamelCase__=0.0       ,     lowerCamelCase__=0.1       ,     lowerCamelCase__=512       ,     lowerCamelCase__=2       ,     lowerCamelCase__=0.02       ,     lowerCamelCase__=1e-12       ,     lowerCamelCase__=True       ,     lowerCamelCase__=0       ,     lowerCamelCase__=312       ,     lowerCamelCase__=313       ,     **lowerCamelCase__       ,     )			->		List[str]:
  
  
  
  
  									'''simple docstring'''
  
  
  
  									super().__init__(pad_token_id=lowerCamelCase__       ,     bos_token_id=lowerCamelCase__       ,     eos_token_id=lowerCamelCase__       ,     **lowerCamelCase__       )
  
  									lowercase__							 =       vocab_size
  									lowercase__							 =       input_embedding_size
  									lowercase__							 =       output_embedding_size
  									lowercase__							 =       max_position_embeddings
  									lowercase__							 =       hidden_size
  									lowercase__							 =       num_hidden_layers
  									lowercase__							 =       num_attention_heads
  									lowercase__							 =       intermediate_size
  									lowercase__							 =       hidden_act
  									lowercase__							 =       hidden_dropout_prob
  									lowercase__							 =       attention_probs_dropout_prob
  									lowercase__							 =       classifier_dropout_prob
  									lowercase__							 =       initializer_range
  									lowercase__							 =       type_vocab_size
  									lowercase__							 =       layer_norm_eps
  									lowercase__							 =       use_cache
  									lowercase__							 =       False
  
  
  
  
  
  class 			A							(       _a				):
  
  
  
  			@property
  			def A__ (					self       )			->		Mapping[str, Mapping[int, str]]:
  
  
  
  
  									'''simple docstring'''
  
  
  
  									if self.task == "multiple-choice":
  															lowercase__							 =       {0: """batch""", 1: """choice""", 2: """sequence"""}
  									else:
  															lowercase__							 =       {0: """batch""", 1: """sequence"""}
  									return OrderedDict(
  									    [
  									        ("""input_ids""", dynamic_axis),
  									        ("""attention_mask""", dynamic_axis),
  									        ("""token_type_ids""", dynamic_axis),
  									    ]       )
  
  
  
  			@property
  			def A__ (					self       )			->		float:
  
  
  
  
  									'''simple docstring'''
  
  
  
  									return 1e-4
  
  
  
  
  
  
  
style_context: 
  '''simple docstring'''
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  __A          =    {"configuration_detr": ["DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DetrConfig", "DetrOnnxConfig"]}
  
  try:
  				if not is_vision_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				pass
  else:
  				__A          =    ["DetrFeatureExtractor"]
  				__A          =    ["DetrImageProcessor"]
  
  try:
  				if not is_torch_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				pass
  else:
  				__A          =    [
  				    "DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
  				    "DetrForObjectDetection",
  				    "DetrForSegmentation",
  				    "DetrModel",
  				    "DetrPreTrainedModel",
  				]
  
  
  if TYPE_CHECKING:
  				from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig
  
  				try:
  								if not is_vision_available():
  												raise OptionalDependencyNotAvailable()
  				except OptionalDependencyNotAvailable:
  								pass
  				else:
  								from .feature_extraction_detr import DetrFeatureExtractor
  								from .image_processing_detr import DetrImageProcessor
  
  				try:
  								if not is_torch_available():
  												raise OptionalDependencyNotAvailable()
  				except OptionalDependencyNotAvailable:
  								pass
  				else:
  								from .modeling_detr import (
  								    DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
  								    DetrForObjectDetection,
  								    DetrForSegmentation,
  								    DetrModel,
  								    DetrPreTrainedModel,
  								)
  
  else:
  				import sys
  
  				__A          =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  