

'''simple docstring'''
import math
import sys

import cva
import numpy as np


def 	_lowerCAmelCase (						_UpperCamelCase						:					np.ndarray							,			_UpperCamelCase						:					float    )				->      np.ndarray:
     """simple docstring"""




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


def 	_lowerCAmelCase (						_UpperCamelCase						:					np.ndarray							,			_UpperCamelCase						:					int							,			_UpperCamelCase						:					int							,			_UpperCamelCase						:					int    )				->      np.ndarray:
     """simple docstring"""




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


def 	_lowerCAmelCase (						_UpperCamelCase						:					int							,			_UpperCamelCase						:					float    )				->      np.ndarray:
     """simple docstring"""




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


def 	_lowerCAmelCase (						_UpperCamelCase						:					np.ndarray							,			_UpperCamelCase						:					float							,			_UpperCamelCase						:					float							,			_UpperCamelCase						:					int							,			)				->      np.ndarray:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   =np.zeros(img.shape    )
     _SCREAMING_SNAKE_CASE							   =get_gauss_kernel(_UpperCamelCase							,			_UpperCamelCase    )
     _SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE							   =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    ):
               _SCREAMING_SNAKE_CASE							   =get_slice(_UpperCamelCase							,			_UpperCamelCase							,			_UpperCamelCase							,			_UpperCamelCase    )
               _SCREAMING_SNAKE_CASE							   =img_s - img_s[kernel_size // 2, kernel_size // 2]
               _SCREAMING_SNAKE_CASE							   =vec_gaussian(_UpperCamelCase							,			_UpperCamelCase    )
               _SCREAMING_SNAKE_CASE							   =np.multiply(_UpperCamelCase							,			_UpperCamelCase    )
               _SCREAMING_SNAKE_CASE							   =np.multiply(_UpperCamelCase							,			_UpperCamelCase    )
               _SCREAMING_SNAKE_CASE							   =np.sum(_UpperCamelCase    ) / np.sum(_UpperCamelCase    )
               _SCREAMING_SNAKE_CASE							   =val
     return imga


def 	_lowerCAmelCase (						_UpperCamelCase						:					list    )				->      tuple:
     """simple docstring"""




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


if __name__ == "__main__":
     lowerCamelCase			,   lowerCamelCase			,   lowerCamelCase			,   lowerCamelCase			:				Dict 			=					parse_args(sys.argv)
     lowerCamelCase			:				List[Any] 			=					cva.imread(filename, 0)
     cva.imshow("input image", img)

     lowerCamelCase			:				List[str] 			=					img / 2_5_5
     lowerCamelCase			:				Optional[int] 			=					out.astype("float32")
     lowerCamelCase			:				Dict 			=					bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
     lowerCamelCase			:				Any 			=					out * 2_5_5
     lowerCamelCase			:				Any 			=					np.uinta(out)
     cva.imshow("output image", out)
     cva.waitKey(0)
     cva.destroyAllWindows()



'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


lowerCamelCase			:				Optional[Any] 			=					logging.get_logger(__name__)

lowerCamelCase			:				Optional[Any] 			=					"T5Config"







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig
