




"""simple docstring"""
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

a_				:    Tuple							=     imread(R'''digital_image_processing/image_data/lena_small.jpg''')
a_				:    List[Any]							=     cvtColor(img, COLOR_BGR2GRAY)





def 						UpperCAmelCase				(			)  ->     List[Any]:
			__lowerCamelCase					:	Any	       =				cn.convert_to_negative(A__     )
			# assert negative_img array for at least one True
			assert negative_img.any()





def 						UpperCAmelCase				(			)  ->     List[str]:



			with Image.open('digital_image_processing/image_data/lena_small.jpg'     ) as img:
						# Work around assertion for response
						assert str(cc.change_contrast(A__							,				110     )     ).startswith(
						    '<PIL.Image.Image image mode=RGB size=100x100 at'     )





def 						UpperCAmelCase				(			)  ->     Optional[Any]:
			__lowerCamelCase					:	int	       =				canny.gen_gaussian_kernel(9							,				sigma=1.4     )
			# Assert ambiguous array
			assert resp.all()





def 						UpperCAmelCase				(			)  ->     List[Any]:
			__lowerCamelCase					:	str	       =				imread('digital_image_processing/image_data/lena_small.jpg'							,				0     )
			# assert ambiguous array for all == True
			assert canny_img.all()
			__lowerCamelCase					:	Any	       =				canny.canny(A__     )
			# assert canny array for at least one True
			assert canny_array.any()





def 						UpperCAmelCase				(			)  ->     int:
			assert gg.gaussian_filter(A__							,				5							,				sigma=0.9     ).all()





def 						UpperCAmelCase				(			)  ->     Tuple:
			__lowerCamelCase					:	Union[str, Any]	       =				array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]     )
			__lowerCamelCase					:	Optional[int]	       =				conv.img_convolve(A__							,				A__     ).astype(A__     )
			assert res.any()





def 						UpperCAmelCase				(			)  ->     Optional[int]:
			assert med.median_filter(A__							,				3     ).any()





def 						UpperCAmelCase				(			)  ->     List[str]:
			__lowerCamelCase					:	List[str]	       =				sob.sobel_filter(A__     )
			assert grad.any() and theta.any()





def 						UpperCAmelCase				(			)  ->     Optional[Any]:
			__lowerCamelCase					:	Dict	       =				sp.make_sepia(A__							,				20     )
			assert sepia.all()





def 						UpperCAmelCase				(			A__:    str = "digital_image_processing/image_data/lena_small.jpg"     )  ->     Any:
			__lowerCamelCase					:	int	       =				bs.Burkes(imread(A__							,				1     )							,				120     )
			burkes.process()
			assert burkes.output_img.any()





def 						UpperCAmelCase				(			A__:    str = "digital_image_processing/image_data/lena_small.jpg"							,				)  ->     int:
			__lowerCamelCase					:	int	       =				rs.NearestNeighbour(imread(A__							,				1     )							,				400							,				200     )
			nn.process()
			assert nn.output.any()






def 						UpperCAmelCase				(			)  ->     Tuple:
			__lowerCamelCase					:	Union[str, Any]	       =				'''digital_image_processing/image_data/lena.jpg'''

			# Reading the image and converting it to grayscale.
			__lowerCamelCase					:	int	       =				imread(A__							,				0     )

			# Test for get_neighbors_pixel function() return not None
			__lowerCamelCase					:	Any	       =				0
			__lowerCamelCase					:	Union[str, Any]	       =				0
			__lowerCamelCase					:	int	       =				image[x_coordinate][y_coordinate]

			__lowerCamelCase					:	Optional[int]	       =				lbp.get_neighbors_pixel(
			    A__							,				A__							,				A__							,				A__     )

			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
			__lowerCamelCase					:	List[Any]	       =				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]     ):
									__lowerCamelCase					:	int	       =				lbp.local_binary_value(A__							,				A__							,				A__     )

			assert lbp_image.any()









"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_				:    Tuple										=     logging.get_logger(__name__)

a_				:    str										=     {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}

class __lowercase(      lowercase__				):




					'''simple docstring'''


					__a						:						Union[str, Any]     		= 'openai-gpt'
					__a						:						List[Any]     		= {
					    'max_position_embeddings': 'n_positions',
					    'hidden_size': 'n_embd',
					    'num_attention_heads': 'n_head',
					    'num_hidden_layers': 'n_layer',
					}
					def __init__(    self						,	__a=40478						,	__a=512						,	__a=768						,	__a=12						,	__a=12						,	__a="gelu"						,	__a=0.1						,	__a=0.1						,	__a=0.1						,	__a=1E-5						,	__a=0.02						,	__a="cls_index"						,	__a=True						,	__a=None						,	__a=True						,	__a=0.1						,	**__a						,	):
								__lowerCamelCase					:	List[str]	       =				vocab_size
								__lowerCamelCase					:	Union[str, Any]	       =				n_positions
								__lowerCamelCase					:	Optional[Any]	       =				n_embd
								__lowerCamelCase					:	int	       =				n_layer
								__lowerCamelCase					:	List[str]	       =				n_head
								__lowerCamelCase					:	Dict	       =				afn
								__lowerCamelCase					:	Optional[Any]	       =				resid_pdrop
								__lowerCamelCase					:	int	       =				embd_pdrop
								__lowerCamelCase					:	int	       =				attn_pdrop
								__lowerCamelCase					:	Dict	       =				layer_norm_epsilon
								__lowerCamelCase					:	List[str]	       =				initializer_range
								__lowerCamelCase					:	Any	       =				summary_type
								__lowerCamelCase					:	Tuple	       =				summary_use_proj
								__lowerCamelCase					:	List[Any]	       =				summary_activation
								__lowerCamelCase					:	str	       =				summary_first_dropout
								__lowerCamelCase					:	Tuple	       =				summary_proj_to_labels
								super().__init__(**__a     )



