



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

UpperCAmelCase   :							str							 =imread(r"""digital_image_processing/image_data/lena_small.jpg""")
UpperCAmelCase   :							Any							 =cvtColor(img, COLOR_BGR2GRAY)



def    _lowerCAmelCase    ():
					UpperCamelCase_		  =   cn.convert_to_negative(_lowerCAmelCase)
					# assert negative_img array for at least one True
					assert negative_img.any()



def    _lowerCAmelCase    ():
					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_10)).startswith(
										    "<PIL.Image.Image image mode=RGB size=100x100 at")



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



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



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



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



def    _lowerCAmelCase    ():
					assert med.median_filter(_lowerCAmelCase   ,	3).any()



def    _lowerCAmelCase    ():
					UpperCamelCase_  ,    UpperCamelCase_		  =   sob.sobel_filter(_lowerCAmelCase)
					assert grad.any() and theta.any()



def    _lowerCAmelCase    ():
					UpperCamelCase_		  =   sp.make_sepia(_lowerCAmelCase   ,	20)
					assert sepia.all()



def    _lowerCAmelCase    (_lowerCAmelCase = "digital_image_processing/image_data/lena_small.jpg"):
					UpperCamelCase_		  =   bs.Burkes(imread(_lowerCAmelCase   ,	1)   ,	1_20)
					burkes.process()
					assert burkes.output_img.any()



def    _lowerCAmelCase    (_lowerCAmelCase = "digital_image_processing/image_data/lena_small.jpg"   ,	):
					UpperCamelCase_		  =   rs.NearestNeighbour(imread(_lowerCAmelCase   ,	1)   ,	4_00   ,	2_00)
					nn.process()
					assert nn.output.any()






def    _lowerCAmelCase    ():
					UpperCamelCase_		  =   "digital_image_processing/image_data/lena.jpg"

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

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

					UpperCamelCase_		  =   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
					UpperCamelCase_		  =   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]):
															UpperCamelCase_		  =   lbp.local_binary_value(_lowerCAmelCase   ,	_lowerCAmelCase   ,	_lowerCAmelCase)

					assert lbp_image.any()





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


UpperCAmelCase   :							Union[str, Any]							 =logging.get_logger(__name__)

UpperCAmelCase   :							Dict							 ={"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}


class       _lowercase   (a_      ):
				'''simple docstring'''







				lowercase__   						=						"""ctrl"""
				lowercase__   						=						["""past_key_values"""]
				lowercase__   						=						{
				    """max_position_embeddings""": """n_positions""",
				    """hidden_size""": """n_embd""",
				    """num_attention_heads""": """n_head""",
				    """num_hidden_layers""": """n_layer""",
				}

				def __init__( self     , snake_case__=24_6534     , snake_case__=256     , snake_case__=1280     , snake_case__=8192     , snake_case__=48     , snake_case__=16     , snake_case__=0.1     , snake_case__=0.1     , snake_case__=1e-6     , snake_case__=0.02     , snake_case__=True     , **snake_case__     , ):

									'''simple docstring'''


									UpperCamelCase_		  =   vocab_size
									UpperCamelCase_		  =   n_positions
									UpperCamelCase_		  =   n_embd
									UpperCamelCase_		  =   n_layer
									UpperCamelCase_		  =   n_head
									UpperCamelCase_		  =   dff
									UpperCamelCase_		  =   resid_pdrop
									UpperCamelCase_		  =   embd_pdrop
									UpperCamelCase_		  =   layer_norm_epsilon
									UpperCamelCase_		  =   initializer_range

									UpperCamelCase_		  =   use_cache

									super().__init__(**snake_case__    )
