


import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

snake_case							:	List[Any]					      =				imread(r'''digital_image_processing/image_data/lena_small.jpg''')
snake_case							:	Optional[int]					      =				cvtColor(img, COLOR_BGR2GRAY)






def 							__lowercase       (			):
       a__					=					cn.convert_to_negative(__lowerCAmelCase       )
       # assert negative_img array for at least one True
       assert negative_img.any()






def 							__lowercase       (			):
       with Image.open('digital_image_processing/image_data/lena_small.jpg'       ) as img:
              # Work around assertion for response
              assert str(cc.change_contrast(__lowerCAmelCase ,   1_1_0       )       ).startswith(
                  '<PIL.Image.Image image mode=RGB size=100x100 at'       )






def 							__lowercase       (			):
       a__					=					canny.gen_gaussian_kernel(9 ,   sigma=1.4       )
       # Assert ambiguous array
       assert resp.all()






def 							__lowercase       (			):
       a__					=					imread('digital_image_processing/image_data/lena_small.jpg' ,   0       )
       # assert ambiguous array for all == True
       assert canny_img.all()
       a__					=					canny.canny(__lowerCAmelCase       )
       # assert canny array for at least one True
       assert canny_array.any()






def 							__lowercase       (			):
       assert gg.gaussian_filter(__lowerCAmelCase ,   5 ,   sigma=0.9       ).all()






def 							__lowercase       (			):
       # laplace diagonals
       a__					=					array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]       )
       a__					=					conv.img_convolve(__lowerCAmelCase ,   __lowerCAmelCase       ).astype(__lowerCAmelCase       )
       assert res.any()






def 							__lowercase       (			):
       assert med.median_filter(__lowerCAmelCase ,   3       ).any()






def 							__lowercase       (			):
       a__				, a__					=					sob.sobel_filter(__lowerCAmelCase       )
       assert grad.any() and theta.any()






def 							__lowercase       (			):
       a__					=					sp.make_sepia(__lowerCAmelCase ,   2_0       )
       assert sepia.all()






def 							__lowercase       (			__lowerCAmelCase							:    str = "digital_image_processing/image_data/lena_small.jpg"       ):
       a__					=					bs.Burkes(imread(__lowerCAmelCase ,   1       ) ,   1_2_0       )
       burkes.process()
       assert burkes.output_img.any()






def 							__lowercase       (			__lowerCAmelCase							:    str = "digital_image_processing/image_data/lena_small.jpg" ,   ):
       a__					=					rs.NearestNeighbour(imread(__lowerCAmelCase ,   1       ) ,   4_0_0 ,   2_0_0       )
       nn.process()
       assert nn.output.any()






def 							__lowercase       (			):
       a__					=					'digital_image_processing/image_data/lena.jpg'

       # Reading the image and converting it to grayscale.
       a__					=					imread(__lowerCAmelCase ,   0       )

       # Test for get_neighbors_pixel function() return not None
       a__					=					0
       a__					=					0
       a__					=					image[x_coordinate][y_coordinate]

       a__					=					lbp.get_neighbors_pixel(
           __lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase       )

       assert neighbors_pixels is not None

       # Test for local_binary_pattern function()
       # Create a numpy array as the same height and width of read image
       a__					=					np.zeros((image.shape[0], image.shape[1])       )

       # Iterating through the image and calculating the local binary pattern value
       # for each pixel.
       for i in range(0 ,   image.shape[0]       ):
              for j in range(0 ,   image.shape[1]       ):
                     a__					=					lbp.local_binary_value(__lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase       )

       assert lbp_image.any()








from typing import List

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


snake_case							:	Tuple					      =				logging.get_logger(__name__)

snake_case							:	List[Any]					      =				{
    '''snap-research/efficientformer-l1-300''': (
        '''https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json'''
    ),
}







class 	snake_case_       (lowerCamelCase_				):
					UpperCAmelCase__ :   int   				=      '''efficientformer'''
					def __init__(				self       :List[str]      ,__snake_case       :List[int] = [3, 2, 6, 4]      ,__snake_case       :List[int] = [48, 96, 2_24, 4_48]      ,__snake_case       :List[bool] = [True, True, True, True]      ,__snake_case       :int = 4_48      ,__snake_case       :int = 32      ,__snake_case       :int = 4      ,__snake_case       :int = 7      ,__snake_case       :int = 5      ,__snake_case       :int = 8      ,__snake_case       :int = 4      ,__snake_case       :float = 0.0      ,__snake_case       :int = 16      ,__snake_case       :int = 3      ,__snake_case       :int = 3      ,__snake_case       :int = 3      ,__snake_case       :int = 2      ,__snake_case       :int = 1      ,__snake_case       :float = 0.0      ,__snake_case       :int = 1      ,__snake_case       :bool = True      ,__snake_case       :bool = True      ,__snake_case       :float = 1E-5      ,__snake_case       :str = "gelu"      ,__snake_case       :float = 0.02      ,__snake_case       :float = 1E-12      ,__snake_case       :int = 2_24      ,__snake_case       :float = 1E-05      ,**__snake_case       :Dict      ,) ->   None:
												super().__init__(**__snake_case				)

												a__					=					hidden_act
												a__					=					hidden_dropout_prob
												a__					=					hidden_sizes
												a__					=					num_hidden_layers
												a__					=					num_attention_heads
												a__					=					initializer_range
												a__					=					layer_norm_eps
												a__					=					patch_size
												a__					=					num_channels
												a__					=					depths
												a__					=					mlp_expansion_ratio
												a__					=					downsamples
												a__					=					dim
												a__					=					key_dim
												a__					=					attention_ratio
												a__					=					resolution
												a__					=					pool_size
												a__					=					downsample_patch_size
												a__					=					downsample_stride
												a__					=					downsample_pad
												a__					=					drop_path_rate
												a__					=					num_metaad_blocks
												a__					=					distillation
												a__					=					use_layer_scale
												a__					=					layer_scale_init_value
												a__					=					image_size
												a__					=					batch_norm_eps




