import random

def add(a, b):
    result = [a[i] + b[i] for i in range(len(a))]
    return result

def multiply(a, b):
    result = [0 for i in range(len(b))]
    for i, cur in enumerate(b):
        for x, nex in enumerate(a):
            result[i] = result[i] + cur * nex
    return result

class Neuro():
    def __init__(self, layers):
        self.layers = layers
        for i, layer in enumerate(layers):
            self.layers[i] = [0 for i in range(layer)]
        self.weights = []
        for i, layer in enumerate(layers):
            if i < len(layers) - 1:
                self.weights.append([random.random() for i in range(len(layer) * len(layers[i + 1]))])
    def run(self, inpu):
        self.layers[0] = inpu
        for i, layer in enumerate(layers):
            if i >= 1:
                res = multiply(self.layers[i - 1], self.weights[i - 1])
                self.layers[i] = add(layer, res)
        return self.layers[len(self.layers) - 1]
    def reweight(self):
        pass

layers = [1, 3, 3, 1]
nn = Neuro(layers)
print(nn.run([2]))