def __init__(self, layers, epsilon=0.154, learningRate = 0.1):
        self.layers = layers
        self.epsilon = epsilon
        self.learningRate = learningRate
        self.activation = None
        self.regLambda = 0.1
        
        # random.rand gives random number between 0,1, need between -eps, +eps
        length = len(layers)
        tht = np.empty((length-1), dtype = object)
        for i in range(0,length-1):
            tht[i]=np.random.rand(layers[i+1],layers[i]+1)            
        tht = tht * 2. * epsilon - epsilon
        self.theta = np.array([])
        for i in range(0,length-1):
            self.theta = np.append(self.theta, tht[i].flatten())
Constructor
dataset/ETHPy150Open dkotfis/NeuRL/src/nn.py/NeuralNet.__init__