src/perceptron/NeuralNetwork/NeuralNetwork.py
def __calc_layer_values(self, input_set: Union[list, np.ndarray], layers: list):
        """
        Calculates input and weights.

        Returns
        -------
        Value of outer layer.
        """
        layer = layers[0]
        layer.values = input_set
        values = layer.think(input_set)
        if len(layers) == 1:
            return values
        return self.__calc_layer_values(values, layers[1:])

        Calculates input and weights.

        Returns
        -------
        Value of outer layer.
        
Calculates input and weights.
Returns

Value of outer layer.
Calculates input and weights . Returns Value of outer layer .
def __calc_layer_values(self, input_set: Union[list, np.ndarray], layers: list):
        layer = layers[0]
        layer.values = input_set
        values = layer.think(input_set)
        if len(layers) == 1:
            return values
        return self.__calc_layer_values(values, layers[1:])
def __calc_layer_values ( self , input_set : Union [ list , np . ndarray ] , layers : list ) : layer = layers [ 0 ] layer . values = input_set values = layer . think ( input_set ) if len ( layers ) == 1 : return values return self . __calc_layer_values ( values , layers [ 1 : ] )
Calculates input and weights.
Calculates input and weights .
"""
        Calculates input and weights.

        Returns
        -------
        Value of outer layer.
        """
self
input_set
Union[list, np.ndarray]
layers
list