import warnings
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_      =      logging.get_logger(__name__)

A_      =      {
    "nvidia/segformer-b0-finetuned-ade-512-512": (
        "https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}






class      __lowercase					(    _A    ):
      lowercase					 =     'segformer'

      def __init__(	self				:      Optional[int]							,							__lowerCamelCase				:      List[str]=3							,							__lowerCamelCase				:      List[str]=4							,							__lowerCamelCase				:      Optional[Any]=[2, 2, 2, 2]							,							__lowerCamelCase				:      Union[str, Any]=[8, 4, 2, 1]							,							__lowerCamelCase				:      Optional[int]=[32, 64, 1_60, 2_56]							,							__lowerCamelCase				:      Optional[int]=[7, 3, 3, 3]							,							__lowerCamelCase				:      int=[4, 2, 2, 2]							,							__lowerCamelCase				:      List[str]=[1, 2, 5, 8]							,							__lowerCamelCase				:      List[str]=[4, 4, 4, 4]							,							__lowerCamelCase				:      int="gelu"							,							__lowerCamelCase				:      List[str]=0.0							,							__lowerCamelCase				:      Optional[int]=0.0							,							__lowerCamelCase				:      Any=0.1							,							__lowerCamelCase				:      List[str]=0.02							,							__lowerCamelCase				:      Optional[int]=0.1							,							__lowerCamelCase				:      int=1E-6							,							__lowerCamelCase				:      str=2_56							,							__lowerCamelCase				:      Union[str, Any]=2_55							,							**__lowerCamelCase				:      Optional[int]							,							)							->		str:


         '''simple docstring'''

         super().__init__(**__lowerCamelCase   )

         if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
            warnings.warn(
                '''Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'''
                ''' removed, as the behaviour will default to that of reshape_last_stage = True.'''							,							__lowerCamelCase							,							)

         lowercase							=		num_channels
         lowercase							=		num_encoder_blocks
         lowercase							=		depths
         lowercase							=		sr_ratios
         lowercase							=		hidden_sizes
         lowercase							=		patch_sizes
         lowercase							=		strides
         lowercase							=		mlp_ratios
         lowercase							=		num_attention_heads
         lowercase							=		hidden_act
         lowercase							=		hidden_dropout_prob
         lowercase							=		attention_probs_dropout_prob
         lowercase							=		classifier_dropout_prob
         lowercase							=		initializer_range
         lowercase							=		drop_path_rate
         lowercase							=		layer_norm_eps
         lowercase							=		decoder_hidden_size
         lowercase							=		kwargs.get('''reshape_last_stage'''							,							__lowerCamelCase   )
         lowercase							=		semantic_loss_ignore_index






class      __lowercase					(    _A    ):
      lowercase					 =     version.parse('1.11'    )

      @property
      def        __a		(	self				:      Dict   )							->		Mapping[str, Mapping[int, str]]:


         '''simple docstring'''

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

      @property
      def        __a		(	self				:      Any   )							->		float:


         '''simple docstring'''

         return 1E-4



      @property
      def        __a		(	self				:      Any   )							->		int:


         '''simple docstring'''

         return 12






import math
import sys

import cva
import numpy as np






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase       )->       np.ndarray:



			"""simple docstring"""







			lowercase							=		math.sqrt(UpperCAmelCase       )
			lowercase							=		1 / (sigma * math.sqrt(2 * math.pi       ))
			return cons * np.exp(-((img / sigma) ** 2) * 0.5       )






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase       )->       np.ndarray:



			"""simple docstring"""







			lowercase							=		kernel_size // 2
			return img[x - half : x + half + 1, y - half : y + half + 1]






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase       )->       np.ndarray:



			"""simple docstring"""







			lowercase							=		np.zeros((kernel_size, kernel_size)       )
			for i in range(0,		UpperCAmelCase       ):
						for j in range(0,		UpperCAmelCase       ):
									lowercase							=		math.sqrt(
									    abs(i - kernel_size // 2       ) ** 2 + abs(j - kernel_size // 2       ) ** 2       )
			return vec_gaussian(UpperCAmelCase,		UpperCAmelCase       )






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase,		)->       np.ndarray:



			"""simple docstring"""







			lowercase							=		np.zeros(img.shape       )
			lowercase							=		get_gauss_kernel(UpperCAmelCase,		UpperCAmelCase       )
			lowercase		,lowercase							=		img.shape
			for i in range(kernel_size // 2,		size_x - kernel_size // 2       ):
						for j in range(kernel_size // 2,		size_y - kernel_size // 2       ):
									lowercase							=		get_slice(UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase       )
									lowercase							=		img_s - img_s[kernel_size // 2, kernel_size // 2]
									lowercase							=		vec_gaussian(UpperCAmelCase,		UpperCAmelCase       )
									lowercase							=		np.multiply(UpperCAmelCase,		UpperCAmelCase       )
									lowercase							=		np.multiply(UpperCAmelCase,		UpperCAmelCase       )
									lowercase							=		np.sum(UpperCAmelCase       ) / np.sum(UpperCAmelCase       )
									lowercase							=		val
			return imga






def        __UpperCAmelCase    (       UpperCAmelCase       )->       tuple:



			"""simple docstring"""







			lowercase							=		args[1] if args[1:] else '''../image_data/lena.jpg'''
			lowercase							=		float(args[2]       ) if args[2:] else 1.0
			lowercase							=		float(args[3]       ) if args[3:] else 1.0
			if args[4:]:
						lowercase							=		int(args[4]       )
						lowercase							=		kernel_size + abs(kernel_size % 2 - 1       )
			else:
						lowercase							=		5
			return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
						A_    ,    A_    ,    A_    ,    A_      =      parse_args(sys.argv)
						A_      =      cva.imread(filename, 0)
						cva.imshow("input image", img)

						A_      =      img / 255
						A_      =      out.astype("float32")
						A_      =      bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
						A_      =      out * 255
						A_      =      np.uinta(out)
						cva.imshow("output image", out)
						cva.waitKey(0)
						cva.destroyAllWindows()





