import numpy as np
import matplotlib.pylab as plt

def sigmoid(x):
    return 1 / (1 + np.exp(-x))

X = np.array([1.0, 0.5])
W1 = np.array([[0.1,0.3,0.5],[0.2,0.4,0.6]])
B1 = np.array([0.1,0.2,0.3])

A1 = np.dot(X, W1) + B1

print("A1: ")
print(A1)

Z1 = sigmoid(A1)
W2 = np.array([[0.1,0.4],[0.2,0.5],[0.3,0.6]])
B2 = np.array([0.1,0.2])

A2 = np.dot(Z1, W2) + B2

print("A2: ")
print(A2)

def identity_function(x):
    return x

Z2 = sigmoid(A2)
W3 = np.array([[0.1,0.3],[0.2,0.4]])
B3 = np.array([0.1,0.2])

A3 = np.dot(Z2, W3) + B3
Y = identity_function(A3)

print("Y: ")
print(Y)
