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
  
  
  SCREAMING_SNAKE_CASE__    :    List[Any]								=					logging.get_logger(__name__)
  
  SCREAMING_SNAKE_CASE__    :    Tuple								=					{
      "MBZUAI/swiftformer-xs": "https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json",
  }
  
  
  
  class 			a_					(    SCREAMING_SNAKE_CASE__    ):
  	A						       =   '''swiftformer'''
  
  
  
  
  
  	def __init__(       self			,    SCREAMING_SNAKE_CASE=3			,    SCREAMING_SNAKE_CASE=[3, 3, 6, 4]			,    SCREAMING_SNAKE_CASE=[48, 56, 112, 220]			,    SCREAMING_SNAKE_CASE=4			,    SCREAMING_SNAKE_CASE=[True, True, True, True]			,    SCREAMING_SNAKE_CASE="gelu"			,    SCREAMING_SNAKE_CASE=3			,    SCREAMING_SNAKE_CASE=2			,    SCREAMING_SNAKE_CASE=1			,    SCREAMING_SNAKE_CASE=0.0			,    SCREAMING_SNAKE_CASE=True			,    SCREAMING_SNAKE_CASE=1e-5			,    SCREAMING_SNAKE_CASE=1e-5			,    **SCREAMING_SNAKE_CASE			,    )     ->				str:
  
  
  
  
  				"""simple docstring"""
  
  
  
  				super().__init__(**SCREAMING_SNAKE_CASE			)
  				SCREAMING_SNAKE_CASE_			=	num_channels
  				SCREAMING_SNAKE_CASE_			=	depths
  				SCREAMING_SNAKE_CASE_			=	embed_dims
  				SCREAMING_SNAKE_CASE_			=	mlp_ratio
  				SCREAMING_SNAKE_CASE_			=	downsamples
  				SCREAMING_SNAKE_CASE_			=	hidden_act
  				SCREAMING_SNAKE_CASE_			=	down_patch_size
  				SCREAMING_SNAKE_CASE_			=	down_stride
  				SCREAMING_SNAKE_CASE_			=	down_pad
  				SCREAMING_SNAKE_CASE_			=	drop_path_rate
  				SCREAMING_SNAKE_CASE_			=	use_layer_scale
  				SCREAMING_SNAKE_CASE_			=	layer_scale_init_value
  				SCREAMING_SNAKE_CASE_			=	batch_norm_eps
  
  
  
  
  class 			a_					(    SCREAMING_SNAKE_CASE__    ):
  	A						       =   version.parse('''1.11'''    )
  
  
  
  
  
  	@property
  	def 	A_(       self			)     ->				Mapping[str, Mapping[int, str]]:
  
  
  
  
  				"""simple docstring"""
  
  
  
  				return OrderedDict(
  				    [
  				        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
  				    ]			)
  
  
  
  
  
  	@property
  	def 	A_(       self			)     ->				float:
  
  
  
  
  				"""simple docstring"""
  
  
  
  				return 1e-4
  
style_context: 
  
  
  
  
  from __future__ import annotations
  
  def lowercase						(     SCREAMING_SNAKE_CASE					,						SCREAMING_SNAKE_CASE					,						SCREAMING_SNAKE_CASE					,						SCREAMING_SNAKE_CASE   ) ->       None:
  
  
  			'''simple docstring'''
  
  
  
  
  
  
  
  			SCREAMING_SNAKE_CASE_	,		SCREAMING_SNAKE_CASE_			=	m - 1, 0
  			while i >= 0 and j < n:
  						if key == mat[i][j]:
  									print(F'Key {key} found at row- {i + 1} column- {j + 1}'   )
  									return
  						if key < mat[i][j]:
  									i -= 1
  						else:
  									j += 1
  			print(F'Key {key} not found'   )
  
  def lowercase						(     ) ->       None:
  
  
  			'''simple docstring'''
  
  
  
  
  
  
  
  			SCREAMING_SNAKE_CASE_			=	[[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
  			SCREAMING_SNAKE_CASE_			=	int(input('Enter the element to be searched:'   )   )
  			print(SCREAMING_SNAKE_CASE   )
  			search_in_a_sorted_matrix(SCREAMING_SNAKE_CASE					,						len(SCREAMING_SNAKE_CASE   )					,						len(mat[0]   )					,						SCREAMING_SNAKE_CASE   )
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  				main()
  