





from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase					)     ->	int:
    lowerCamelCase__       : Dict   					=						k_size // 2
    lowerCamelCase__					,				lowerCamelCase__       : int   					=						mgrid[0 - center : k_size - center, 0 - center : k_size - center]
    lowerCamelCase__       : List[Any]   					=						1 / (2 * pi * sigma) * exp(-(square(_UpperCAmelCase					) + square(_UpperCAmelCase					)) / (2 * square(_UpperCAmelCase					))					)
    return g


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	Union[str, Any]:
    lowerCamelCase__					,				lowerCamelCase__       : Union[str, Any]   					=						image.shape[0], image.shape[1]
    # dst image height and width
    lowerCamelCase__       : Any   					=						height - k_size + 1
    lowerCamelCase__       : int   					=						width - k_size + 1

    # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
    lowerCamelCase__       : List[Any]   					=						zeros((dst_height * dst_width, k_size * k_size)					)
    lowerCamelCase__       : int   					=						0
    for i, j in product(range(_UpperCAmelCase					)		,      range(_UpperCAmelCase					)					):
        lowerCamelCase__       : Union[str, Any]   					=						ravel(image[i : i + k_size, j : j + k_size]					)
        lowerCamelCase__       : str   					=						window
        row += 1

    #  turn the kernel into shape(k*k, 1)
    lowerCamelCase__       : Optional[Any]   					=						gen_gaussian_kernel(_UpperCAmelCase		,      _UpperCAmelCase					)
    lowerCamelCase__       : Optional[int]   					=						ravel(_UpperCAmelCase					)

    # reshape and get the dst image
    lowerCamelCase__       : Tuple   					=						dot(_UpperCAmelCase		,      _UpperCAmelCase					).reshape(_UpperCAmelCase		,      _UpperCAmelCase					).astype(_UpperCAmelCase					)

    return dst


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

    # get values with two different mask size
    _UpperCAmelCase							:			int        =							gaussian_filter(gray, 3, sigma=1)
    _UpperCAmelCase							:			Any        =							gaussian_filter(gray, 5, sigma=0.8)

    # show result images
    imshow("""gaussian filter with 3x3 mask""", gaussianaxa)
    imshow("""gaussian filter with 5x5 mask""", gaussianaxa)
    waitKey()












from typing import List

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


_UpperCAmelCase							:			Any        =							logging.get_logger(__name__)

_UpperCAmelCase							:			Union[str, Any]        =							{
    """snap-research/efficientformer-l1-300""": (
        """https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"""
    ),
}

class   lowerCAmelCase				(   __UpperCamelCase     ):
 UpperCAmelCase__						=						"""efficientformer"""
 def __init__( self    : Dict     ,	UpperCAmelCase    : List[int] = [3, 2, 6, 4]     ,	UpperCAmelCase    : List[int] = [48, 96, 224, 448]     ,	UpperCAmelCase    : List[bool] = [True, True, True, True]     ,	UpperCAmelCase    : int = 448     ,	UpperCAmelCase    : int = 32     ,	UpperCAmelCase    : int = 4     ,	UpperCAmelCase    : int = 7     ,	UpperCAmelCase    : int = 5     ,	UpperCAmelCase    : int = 8     ,	UpperCAmelCase    : int = 4     ,	UpperCAmelCase    : float = 0.0     ,	UpperCAmelCase    : int = 16     ,	UpperCAmelCase    : int = 3     ,	UpperCAmelCase    : int = 3     ,	UpperCAmelCase    : int = 3     ,	UpperCAmelCase    : int = 2     ,	UpperCAmelCase    : int = 1     ,	UpperCAmelCase    : float = 0.0     ,	UpperCAmelCase    : int = 1     ,	UpperCAmelCase    : bool = True     ,	UpperCAmelCase    : bool = True     ,	UpperCAmelCase    : float = 1e-5     ,	UpperCAmelCase    : str = "gelu"     ,	UpperCAmelCase    : float = 0.0_2     ,	UpperCAmelCase    : float = 1e-12     ,	UpperCAmelCase    : int = 224     ,	UpperCAmelCase    : float = 1e-05     ,	**UpperCAmelCase    : Tuple     ,	)     ->      None:
     super().__init__(**UpperCAmelCase      )

     lowerCamelCase__       : Optional[Any]   					=						hidden_act
     lowerCamelCase__       : int   					=						hidden_dropout_prob
     lowerCamelCase__       : List[Any]   					=						hidden_sizes
     lowerCamelCase__       : int   					=						num_hidden_layers
     lowerCamelCase__       : int   					=						num_attention_heads
     lowerCamelCase__       : Dict   					=						initializer_range
     lowerCamelCase__       : Optional[Any]   					=						layer_norm_eps
     lowerCamelCase__       : int   					=						patch_size
     lowerCamelCase__       : List[Any]   					=						num_channels
     lowerCamelCase__       : List[str]   					=						depths
     lowerCamelCase__       : Any   					=						mlp_expansion_ratio
     lowerCamelCase__       : Any   					=						downsamples
     lowerCamelCase__       : str   					=						dim
     lowerCamelCase__       : Tuple   					=						key_dim
     lowerCamelCase__       : int   					=						attention_ratio
     lowerCamelCase__       : int   					=						resolution
     lowerCamelCase__       : Dict   					=						pool_size
     lowerCamelCase__       : List[str]   					=						downsample_patch_size
     lowerCamelCase__       : Tuple   					=						downsample_stride
     lowerCamelCase__       : int   					=						downsample_pad
     lowerCamelCase__       : Optional[int]   					=						drop_path_rate
     lowerCamelCase__       : Optional[Any]   					=						num_metaad_blocks
     lowerCamelCase__       : Any   					=						distillation
     lowerCamelCase__       : Optional[int]   					=						use_layer_scale
     lowerCamelCase__       : Union[str, Any]   					=						layer_scale_init_value
     lowerCamelCase__       : Optional[int]   					=						image_size
     lowerCamelCase__       : Optional[Any]   					=						batch_norm_eps





