






"""simple docstring"""



import math
import sys

import cva
import numpy as np



def 						lowercase    (				__snake_case				: np.ndarray		,					__snake_case				: float	):
		# For applying gaussian function for each element in matrix.
		lowercase_ : Union[str, Any]							       =   math.sqrt(__snake_case	)
		lowercase_ : Any							       =   1 / (sigma * math.sqrt(2 * math.pi	))
		return cons * np.exp(-((img / sigma) ** 2) * 0.5	)



def 						lowercase    (				__snake_case				: np.ndarray		,					__snake_case				: int		,					__snake_case				: int		,					__snake_case				: int	):
		lowercase_ : List[str]							       =   kernel_size // 2
		return img[x - half : x + half + 1, y - half : y + half + 1]



def 						lowercase    (				__snake_case				: int		,					__snake_case				: float	):
		# Creates a gaussian kernel of given dimension.
		lowercase_ : Tuple							       =   np.zeros((kernel_size, kernel_size)	)
		for i in range(0		,					__snake_case	):
				for j in range(0		,					__snake_case	):
						lowercase_ : List[str]							       =   math.sqrt(
						    abs(i - kernel_size // 2	) ** 2 + abs(j - kernel_size // 2	) ** 2	)
		return vec_gaussian(__snake_case		,					__snake_case	)



def 						lowercase    (				__snake_case				: np.ndarray		,					__snake_case				: float		,					__snake_case				: float		,					__snake_case				: int		,					):
		lowercase_ : Tuple							       =   np.zeros(img.shape	)
		lowercase_ : Union[str, Any]							       =   get_gauss_kernel(__snake_case		,					__snake_case	)
		lowercase_       ,					lowercase_ : List[Any]							       =   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_ : str							       =   get_slice(__snake_case		,					__snake_case		,					__snake_case		,					__snake_case	)
						lowercase_ : Any							       =   img_s - img_s[kernel_size // 2, kernel_size // 2]
						lowercase_ : List[Any]							       =   vec_gaussian(__snake_case		,					__snake_case	)
						lowercase_ : List[Any]							       =   np.multiply(__snake_case		,					__snake_case	)
						lowercase_ : Union[str, Any]							       =   np.multiply(__snake_case		,					__snake_case	)
						lowercase_ : Any							       =   np.sum(__snake_case	) / np.sum(__snake_case	)
						lowercase_ : Optional[Any]							       =   val
		return imga



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


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

						__A		:       str  				=		img / 255
						__A		:       Any  				=		out.astype('''float32''')
						__A		:       List[Any]  				=		bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
						__A		:       Any  				=		out * 255
						__A		:       Optional[int]  				=		np.uinta(out)
						cva.imshow('''output image''', out)
						cva.waitKey(0)
						cva.destroyAllWindows()







"""simple docstring"""







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__      				=   logging.get_logger(__name__)

lowerCAmelCase__      				=   {
    '''facebook/dpr-ctx_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-ctx_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json'''
    ),
}


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				int   ="dpr"

       def __init__(						self		,     snake_case__=30_522		,     snake_case__=768		,     snake_case__=12		,     snake_case__=12		,     snake_case__=3_072		,     snake_case__="gelu"		,     snake_case__=0.1		,     snake_case__=0.1		,     snake_case__=512		,     snake_case__=2		,     snake_case__=0.02		,     snake_case__=1e-12		,     snake_case__=0		,     snake_case__="absolute"		,     snake_case__ = 0		,     **snake_case__		,     ):






         """simple docstring"""





         super().__init__(pad_token_id=snake_case__		,     **snake_case__						)

         lowerCAmelCase     :     Union[str, Any]								=							vocab_size
         lowerCAmelCase     :     str								=							hidden_size
         lowerCAmelCase     :     Any								=							num_hidden_layers
         lowerCAmelCase     :     Optional[int]								=							num_attention_heads
         lowerCAmelCase     :     Union[str, Any]								=							hidden_act
         lowerCAmelCase     :     Dict								=							intermediate_size
         lowerCAmelCase     :     Union[str, Any]								=							hidden_dropout_prob
         lowerCAmelCase     :     Dict								=							attention_probs_dropout_prob
         lowerCAmelCase     :     Dict								=							max_position_embeddings
         lowerCAmelCase     :     Tuple								=							type_vocab_size
         lowerCAmelCase     :     Any								=							initializer_range
         lowerCAmelCase     :     Any								=							layer_norm_eps
         lowerCAmelCase     :     Dict								=							projection_dim
         lowerCAmelCase     :     Dict								=							position_embedding_type





