"""
    ############################################################################################################################################################################################################################
    # This algorithm represents a revolutionary new architecture of artificial neural networks created by Sapiens Technology®, which is significantly faster and more accurate than conventional neural network architectures. #
    # The HurNet network, which uses back-division calculations where the computation starts from the output layer and goes back to the previous layers up to the input layer,                                                 #
    # dividing each current neuron by the immediately previous one in a single iteration,                                                                                                                                      #
    # manages to be significantly faster than traditional neural networks that use several iterations of weight adjustment through backpropagation.                                                                            #
    # The neural network architecture in question has been named HurNet (Hur, from Ben-Hur Varriano, who designed the mathematical architecture and the network algorithm; and Net, from neural network).                      #
    # The HurNet neural network does not rely on backpropagation or gradient calculations, achieving optimal weight adjustments in a single iteration.                                                                         #
    # This approach dramatically reduces demands for computational processing and can potentially increase training speed.                                                                                                     #
    # This algorithm is protected by copyright, and any public commentary, disclosure, or distribution of the HurNet algorithm code without prior authorization from Sapiens Technology® is strictly prohibited.               #
    # Reverse engineering and the creation of derivative algorithms through adaptations or inspirations based on the original calculations and code are also not allowed.                                                      #
    # Any violation of these prohibitions will be subject to legal action by our legal department.                                                                                                                             #
    ############################################################################################################################################################################################################################
"""
from .hurnet import *
"""
    ############################################################################################################################################################################################################################
    # This algorithm represents a revolutionary new architecture of artificial neural networks created by Sapiens Technology®, which is significantly faster and more accurate than conventional neural network architectures. #
    # The HurNet network, which uses back-division calculations where the computation starts from the output layer and goes back to the previous layers up to the input layer,                                                 #
    # dividing each current neuron by the immediately previous one in a single iteration,                                                                                                                                      #
    # manages to be significantly faster than traditional neural networks that use several iterations of weight adjustment through backpropagation.                                                                            #
    # The neural network architecture in question has been named HurNet (Hur, from Ben-Hur Varriano, who designed the mathematical architecture and the network algorithm; and Net, from neural network).                      #
    # The HurNet neural network does not rely on backpropagation or gradient calculations, achieving optimal weight adjustments in a single iteration.                                                                         #
    # This approach dramatically reduces demands for computational processing and can potentially increase training speed.                                                                                                     #
    # This algorithm is protected by copyright, and any public commentary, disclosure, or distribution of the HurNet algorithm code without prior authorization from Sapiens Technology® is strictly prohibited.               #
    # Reverse engineering and the creation of derivative algorithms through adaptations or inspirations based on the original calculations and code are also not allowed.                                                      #
    # Any violation of these prohibitions will be subject to legal action by our legal department.                                                                                                                             #
    ############################################################################################################################################################################################################################
"""
