code: from collections import OrderedDict
  from typing import Mapping
  
  from packaging import version
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  lowercase__    :       List[str]						=			logging.get_logger(__name__)
  
  lowercase__    :       Dict						=			{
      '''apple/mobilevit-small''': '''https://huggingface.co/apple/mobilevit-small/resolve/main/config.json''',
      '''apple/mobilevit-x-small''': '''https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json''',
      '''apple/mobilevit-xx-small''': '''https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json''',
      '''apple/deeplabv3-mobilevit-small''': (
          '''https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'''
      ),
      '''apple/deeplabv3-mobilevit-x-small''': (
          '''https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'''
      ),
      '''apple/deeplabv3-mobilevit-xx-small''': (
          '''https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'''
      ),
      # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
  }
  
  
  
  
  class      lowercase_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      str     =       """mobilevit"""
  
  
  	def __init__(							self	,    __SCREAMING_SNAKE_CASE=3	,    __SCREAMING_SNAKE_CASE=256	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=[144, 192, 240]	,    __SCREAMING_SNAKE_CASE=[16, 32, 64, 96, 128, 160, 640]	,    __SCREAMING_SNAKE_CASE=4	,    __SCREAMING_SNAKE_CASE=2.0	,    __SCREAMING_SNAKE_CASE=4.0	,    __SCREAMING_SNAKE_CASE="silu"	,    __SCREAMING_SNAKE_CASE=3	,    __SCREAMING_SNAKE_CASE=32	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.0_2	,    __SCREAMING_SNAKE_CASE=1e-5	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=256	,    __SCREAMING_SNAKE_CASE=[6, 12, 18]	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=255	,    **__SCREAMING_SNAKE_CASE	,    )		->Tuple:
  								super().__init__(**__SCREAMING_SNAKE_CASE       )
  
  								lowerCAmelCase				=	num_channels
  								lowerCAmelCase				=	image_size
  								lowerCAmelCase				=	patch_size
  								lowerCAmelCase				=	hidden_sizes
  								lowerCAmelCase				=	neck_hidden_sizes
  								lowerCAmelCase				=	num_attention_heads
  								lowerCAmelCase				=	mlp_ratio
  								lowerCAmelCase				=	expand_ratio
  								lowerCAmelCase				=	hidden_act
  								lowerCAmelCase				=	conv_kernel_size
  								lowerCAmelCase				=	output_stride
  								lowerCAmelCase				=	hidden_dropout_prob
  								lowerCAmelCase				=	attention_probs_dropout_prob
  								lowerCAmelCase				=	classifier_dropout_prob
  								lowerCAmelCase				=	initializer_range
  								lowerCAmelCase				=	layer_norm_eps
  								lowerCAmelCase				=	qkv_bias
  
  								# decode head attributes for semantic segmentation
  								lowerCAmelCase				=	aspp_out_channels
  								lowerCAmelCase				=	atrous_rates
  								lowerCAmelCase				=	aspp_dropout_prob
  								lowerCAmelCase				=	semantic_loss_ignore_index
  
  
  
  
  class      lowercase_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      Tuple     =       version.parse("""1.11"""		)
  
  
  	@property
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->Mapping[str, Mapping[int, str]]:
  								return OrderedDict([('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''})]       )
  
  
  	@property
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->Mapping[str, Mapping[int, str]]:
  								if self.task == "image-classification":
  															return OrderedDict([('''logits''', {0: '''batch'''})]       )
  								else:
  															return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]       )
  
  
  
  
  	@property
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->float:
  								return 1e-4
  
  
  
  
style_context: import glob
  import os
  
  from get_test_info import get_tester_classes
  
  
  if __name__ == "__main__":
  	lowercase__    :       List[Any]						=			[]
  
  	lowercase__    :       Optional[Any]						=			os.path.join('''tests''', '''models''', '''**''', '''test_modeling_*.py''')
  	lowercase__    :       Optional[int]						=			glob.glob(pattern)
  	# TODO: deal with TF/Flax too
  	lowercase__    :       Dict						=			[
  	    x for x in test_files if not (x.startswith('''test_modeling_tf_''') or x.startswith('''test_modeling_flax_'''))
  	]
  
  	for test_file in test_files:
  		lowercase__    :       Tuple						=			get_tester_classes(test_file)
  		for tester_class in tester_classes:
  			# A few tester classes don't have `parent` parameter in `__init__`.
  			# TODO: deal this better
  			try:
  				lowercase__    :       Union[str, Any]						=			tester_class(parent=None)
  			except Exception:
  				continue
  			if hasattr(tester, '''get_config'''):
  				lowercase__    :       Union[str, Any]						=			tester.get_config()
  				for k, v in config.to_dict().items():
  					if isinstance(v, int):
  						lowercase__    :       int						=			None
  						if k in ["vocab_size"]:
  							lowercase__    :       Optional[int]						=			1_0_0
  						elif k in ["max_position_embeddings"]:
  							lowercase__    :       Union[str, Any]						=			1_2_8
  						elif k in ["hidden_size", "d_model"]:
  							lowercase__    :       Optional[Any]						=			4_0
  						elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
  							lowercase__    :       Dict						=			5
  						if target is not None and v > target:
  							failures.append(
  							    f'{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'
  							    f' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'
  							    f' than {target}.'
  							)
  
  	if len(failures) > 0:
  		raise Exception(f'There were {len(failures)} failures:\n' + '''\n'''.join(failures))
  
  
  
  