
"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase			=		logging.get_logger(__name__)

lowerCAmelCase			=		{
    """mnaylor/mega-base-wikitext""": """https://huggingface.co/mnaylor/mega-base-wikitext/resolve/main/config.json""",
}

class 					A_			(  A__     ):



							"""simple docstring"""






							SCREAMING_SNAKE_CASE_			   =     """mega"""





							def __init__(						self						:int  ,							lowerCamelCase_						:List[str]=30_522  ,							lowerCamelCase_						:Optional[int]=128  ,							lowerCamelCase_						:Any=4  ,							lowerCamelCase_						:int=256  ,							lowerCamelCase_						:List[str]=16  ,							lowerCamelCase_						:Optional[Any]=True  ,							lowerCamelCase_						:str=64  ,							lowerCamelCase_						:str=False  ,							lowerCamelCase_						:str=-1  ,							lowerCamelCase_						:Optional[Any]=None  ,							lowerCamelCase_						:Optional[Any]=True  ,							lowerCamelCase_						:List[str]="scalenorm"  ,							lowerCamelCase_						:Union[str, Any]=True  ,							lowerCamelCase_						:int="silu"  ,							lowerCamelCase_						:str="softmax"  ,							lowerCamelCase_						:Optional[Any]=0.1  ,							lowerCamelCase_						:Any=0.1  ,							lowerCamelCase_						:str=0.1  ,							lowerCamelCase_						:Union[str, Any]=False  ,							lowerCamelCase_						:int=True  ,							lowerCamelCase_						:List[str]=256  ,							lowerCamelCase_						:List[Any]=True  ,							lowerCamelCase_						:str=0.1  ,							lowerCamelCase_						:Any=2_048  ,							lowerCamelCase_						:str=False  ,							lowerCamelCase_						:List[str]=2  ,							lowerCamelCase_						:List[str]=0.02  ,							lowerCamelCase_						:Tuple=0.2  ,							lowerCamelCase_						:int=0.02  ,							lowerCamelCase_						:Any=1.0  ,							lowerCamelCase_						:Dict=1  ,							lowerCamelCase_						:Union[str, Any]=0  ,							lowerCamelCase_						:Union[str, Any]=2  ,							lowerCamelCase_						:Union[str, Any]="rotary"  ,							lowerCamelCase_						:List[str]=None  ,							lowerCamelCase_						:Union[str, Any]=True  ,							lowerCamelCase_						:Optional[int]=True  ,							**lowerCamelCase_						:Tuple  ,							):





										"""simple docstring"""

										super().__init__(pad_token_id=lowerCamelCase_  ,							bos_token_id=lowerCamelCase_  ,							eos_token_id=lowerCamelCase_  ,							**lowerCamelCase_ )

										lowerCamelCase__			:  Optional[Any]  =vocab_size
										lowerCamelCase__			:  Tuple  =hidden_size
										lowerCamelCase__			:  int  =num_hidden_layers
										lowerCamelCase__			:  Optional[Any]  =activation
										lowerCamelCase__			:  List[str]  =attention_activation
										lowerCamelCase__			:  List[str]  =intermediate_size
										lowerCamelCase__			:  Optional[int]  =ema_projection_size
										lowerCamelCase__			:  Union[str, Any]  =bidirectional
										lowerCamelCase__			:  Any  =shared_representation_size
										lowerCamelCase__			:  int  =use_chunking
										lowerCamelCase__			:  Any  =chunk_size
										lowerCamelCase__			:  Dict  =truncation
										lowerCamelCase__			:  Optional[int]  =normalize_before_mega
										lowerCamelCase__			:  Optional[Any]  =normalization_type
										lowerCamelCase__			:  List[str]  =norm_affine
										lowerCamelCase__			:  Optional[Any]  =dropout_prob
										lowerCamelCase__			:  Union[str, Any]  =hidden_dropout_prob
										lowerCamelCase__			:  Optional[int]  =attention_probs_dropout_prob
										lowerCamelCase__			:  Tuple  =use_feature_dropout
										lowerCamelCase__			:  Tuple  =use_normalized_ffn
										lowerCamelCase__			:  List[Any]  =nffn_hidden_size
										lowerCamelCase__			:  Tuple  =normalize_before_ffn
										lowerCamelCase__			:  List[str]  =nffn_activation_dropout_prob
										lowerCamelCase__			:  Optional[Any]  =max_positions
										lowerCamelCase__			:  Any  =add_token_type_embeddings
										lowerCamelCase__			:  Any  =type_vocab_size
										lowerCamelCase__			:  Tuple  =initializer_range
										lowerCamelCase__			:  Any  =ema_delta_alpha_range
										lowerCamelCase__			:  Dict  =ema_beta_range
										lowerCamelCase__			:  Optional[int]  =ema_gamma_omega_range
										lowerCamelCase__			:  int  =relative_positional_bias
										lowerCamelCase__			:  List[str]  =use_cache
										lowerCamelCase__			:  Union[str, Any]  =classifier_dropout
										lowerCamelCase__			:  int  =add_lm_hidden_dense_layer
										lowerCamelCase__			:  int  =1  # not used but required by Hugging Face






class 					A_			(  A__     ):



							"""simple docstring"""






							@property
							def    UpperCAmelCase__							(						self						:List[str] ):





										"""simple docstring"""

										if self.task == "multiple-choice":
													lowerCamelCase__			:  List[str]  ={0: 'batch', 1: 'choice', 2: 'sequence'}
										else:
													lowerCamelCase__			:  Union[str, Any]  ={0: 'batch', 1: 'sequence'}
										return OrderedDict(
										    [
										        ('input_ids', dynamic_axis),
										        ('attention_mask', dynamic_axis),
										    ] )

"""simple docstring"""


import cva
import numpy as np






def      lowerCAmelCase_     (	snake_case_	:    np.ndarray							,					snake_case_	:    int							,					snake_case_	:    int							,					snake_case_	:    int    )     ->int:

			try:
						return int(image[x_coordinate][y_coordinate] >= center    )
			except (IndexError, TypeError):
						return 0






def      lowerCAmelCase_     (	snake_case_	:    np.ndarray							,					snake_case_	:    int							,					snake_case_	:    int    )     ->int:
			lowerCamelCase__			:  Optional[int]  =image[x_coordinate][y_coordinate]
			lowerCamelCase__			:  int  =[1, 2, 4, 8, 1_6, 3_2, 6_4, 1_2_8]

			# skip get_neighbors_pixel if center is null
			if center is None:
						return 0

			# Starting from the top right, assigning value to pixels clockwise
			lowerCamelCase__			:  int  =[
			    get_neighbors_pixel(snake_case_							,					x_coordinate - 1							,					y_coordinate + 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					snake_case_							,					y_coordinate + 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate - 1							,					snake_case_							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate + 1							,					y_coordinate + 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate + 1							,					snake_case_							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate + 1							,					y_coordinate - 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					snake_case_							,					y_coordinate - 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate - 1							,					y_coordinate - 1							,					snake_case_    ),
			]

			# Converting the binary value to decimal.
			return sum(
			    binary_value * power for binary_value, power in zip(snake_case_							,					snake_case_    )    )


if __name__ == "__main__":
							# Reading the image and converting it to grayscale.
							lowerCAmelCase			=		cva.imread(
							    """digital_image_processing/image_data/lena.jpg""", cva.IMREAD_GRAYSCALE
							)

							# Create a numpy array as the same height and width of read image
							lowerCAmelCase			=		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			=		local_binary_value(image, i, j)

							cva.imshow("""local binary pattern""", lbp_image)
							cva.waitKey(0)
							cva.destroyAllWindows()