

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


_a:      List[Any]								=     logging.get_logger(__name__)

_a:      int								=     {
    """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   __UpperCamelCase      (   lowercase  ):
	SCREAMING_SNAKE_CASE__      			=       'mobilevit'




	def __init__(						self		:  str						,		lowerCAmelCase		:  Union[str, Any]=3						,		lowerCAmelCase		:  List[str]=256						,		lowerCAmelCase		:  Optional[int]=2						,		lowerCAmelCase		:  List[Any]=[144, 192, 240]						,		lowerCAmelCase		:  Tuple=[16, 32, 64, 96, 128, 160, 640]						,		lowerCAmelCase		:  int=4						,		lowerCAmelCase		:  Any=2.0						,		lowerCAmelCase		:  Dict=4.0						,		lowerCAmelCase		:  str="silu"						,		lowerCAmelCase		:  str=3						,		lowerCAmelCase		:  List[Any]=32						,		lowerCAmelCase		:  Any=0.1						,		lowerCAmelCase		:  Tuple=0.0						,		lowerCAmelCase		:  Dict=0.1						,		lowerCAmelCase		:  Dict=0.02						,		lowerCAmelCase		:  Optional[int]=1e-5						,		lowerCAmelCase		:  List[str]=True						,		lowerCAmelCase		:  Dict=256						,		lowerCAmelCase		:  Any=[6, 12, 18]						,		lowerCAmelCase		:  Dict=0.1						,		lowerCAmelCase		:  int=255						,		**lowerCAmelCase		:  List[Any]						,		):


		'''simple docstring'''







		super().__init__(**lowerCAmelCase							)

		UpperCAmelCase_    			=     num_channels
		UpperCAmelCase_    			=     image_size
		UpperCAmelCase_    			=     patch_size
		UpperCAmelCase_    			=     hidden_sizes
		UpperCAmelCase_    			=     neck_hidden_sizes
		UpperCAmelCase_    			=     num_attention_heads
		UpperCAmelCase_    			=     mlp_ratio
		UpperCAmelCase_    			=     expand_ratio
		UpperCAmelCase_    			=     hidden_act
		UpperCAmelCase_    			=     conv_kernel_size
		UpperCAmelCase_    			=     output_stride
		UpperCAmelCase_    			=     hidden_dropout_prob
		UpperCAmelCase_    			=     attention_probs_dropout_prob
		UpperCAmelCase_    			=     classifier_dropout_prob
		UpperCAmelCase_    			=     initializer_range
		UpperCAmelCase_    			=     layer_norm_eps
		UpperCAmelCase_    			=     qkv_bias

		# decode head attributes for semantic segmentation
		UpperCAmelCase_    			=     aspp_out_channels
		UpperCAmelCase_    			=     atrous_rates
		UpperCAmelCase_    			=     aspp_dropout_prob
		UpperCAmelCase_    			=     semantic_loss_ignore_index


class   __UpperCamelCase      (   lowercase  ):
	SCREAMING_SNAKE_CASE__      			=       version.parse('1.11'  )




	@property
	def  __A   (						self		:  Tuple							):


		'''simple docstring'''







		return OrderedDict([("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"})]							)




	@property
	def  __A   (						self		:  Union[str, Any]							):


		'''simple docstring'''







		if self.task == "image-classification":
			return OrderedDict([("logits", {0: "batch"})]							)
		else:
			return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]							)




	@property
	def  __A   (						self		:  Union[str, Any]							):


		'''simple docstring'''







		return 1e-4


from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import divide, inta, multiply, ravel, sort, zeros_like



def  __lowerCAmelCase (  A    ,       A=3      ):
	UpperCAmelCase_    			=     int(mask / 2      )
	# copy image size
	UpperCAmelCase_    			=     zeros_like(A      )
	for i in range(A    ,       gray_img.shape[0] - bd      ):
		for j in range(A    ,       gray_img.shape[1] - bd      ):
			# get mask according with mask
			UpperCAmelCase_    			=     ravel(gray_img[i - bd : i + bd + 1, j - bd : j + bd + 1]      )
			# calculate mask median
			UpperCAmelCase_    			=     sort(A      )[inta(divide((multiply(A    ,       A      ))    ,       2      ) + 1      )]
			UpperCAmelCase_    			=     median
	return median_img


if __name__ == "__main__":
				# read original image
				_a:      Optional[int]								=     imread("""../image_data/lena.jpg""")
				# turn image in gray scale value
				_a:      Dict								=     cvtColor(img, COLOR_BGR2GRAY)

				# get values with two different mask size
				_a:      Tuple								=     median_filter(gray, 3)
				_a:      Dict								=     median_filter(gray, 5)

				# show result images
				imshow("""median filter with 3x3 mask""", medianaxa)
				imshow("""median filter with 5x5 mask""", medianaxa)
				waitKey(0)