code: 
  
  
  """simple docstring"""
  
  
  
  
  
  
  
  import numpy as np
  from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
  
  from digital_image_processing.filters.convolve import img_convolve
  def _A		(		lowercase	):
  
  
  
  
  
  
  
      """simple docstring"""
      a					=np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]	)
      a					=np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]	)
  
      a					=np.abs(img_convolve(lowercase ,					lowercase	)	)
      a					=np.abs(img_convolve(lowercase ,					lowercase	)	)
      # modify the pix within [0, 255]
      a					=dst_x * 2_55 / np.max(lowercase	)
      a					=dst_y * 2_55 / np.max(lowercase	)
  
      a					=np.sqrt((np.square(lowercase	)) + (np.square(lowercase	))	)
      a					=dst_xy * 2_55 / np.max(lowercase	)
      a					=dst_xy.astype(np.uinta	)
  
      a					=np.arctana(lowercase ,					lowercase	)
      return dst, theta
  
  
  if __name__ == "__main__":
         # read original image
         lowerCamelCase_     :     Union[str, Any]    		=						imread("""../image_data/lena.jpg""")
         # turn image in gray scale value
         lowerCamelCase_     :     Optional[int]    		=						cvtColor(img, COLOR_BGR2GRAY)
  
         lowerCamelCase_     :     List[str]    		=						sobel_filter(gray)
  
         # show result images
         imshow("""sobel filter""", sobel_grad)
         imshow("""sobel theta""", sobel_theta)
         waitKey(0)
  
  
  
  
  
  
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  
  
  
  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
  
  
  lowerCamelCase_     :     Any    		=						logging.get_logger(__name__)
  
  lowerCamelCase_     :     Tuple    		=						{
      """apple/mobilevitv2-1.0""": """https://huggingface.co/apple/mobilevitv2-1.0/resolve/main/config.json""",
  }
  
  
  
  
  
  
  class    __A       ( _SCREAMING_SNAKE_CASE    ):
  
  
  
  
  
  
   """simple docstring"""
  
  
  
  
   __lowerCAmelCase				      =						"mobilevitv2"
  
  
   def __init__(	self				,					__A=3				,					__A=256				,					__A=2				,					__A=2.0				,					__A="swish"				,					__A=3				,					__A=32				,					__A=0.1				,					__A=0.02				,					__A=1E-5				,					__A=512				,					__A=[6, 12, 18]				,					__A=0.1				,					__A=255				,					__A=[2, 4, 3]				,					__A=[128, 192, 256]				,					__A=1.0				,					__A=2				,					__A=0.0				,					__A=0.0				,					**__A				,					)      ->  int:
       super().__init__(**__A		)
  
       a					=num_channels
       a					=image_size
       a					=patch_size
       a					=expand_ratio
       a					=hidden_act
       a					=conv_kernel_size
       a					=output_stride
       a					=initializer_range
       a					=layer_norm_eps
       a					=n_attn_blocks
       a					=base_attn_unit_dims
       a					=width_multiplier
       a					=ffn_multiplier
       a					=ffn_dropout
       a					=attn_dropout
       a					=classifier_dropout_prob
  
       # decode head attributes for semantic segmentation
       a					=aspp_out_channels
       a					=atrous_rates
       a					=aspp_dropout_prob
       a					=semantic_loss_ignore_index
  
  
  
  
  
  
  class    __A       ( _SCREAMING_SNAKE_CASE    ):
  
  
  
  
  
  
   """simple docstring"""
  
  
  
  
   __lowerCAmelCase				      =						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