import numpy as np

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

# 0층에서 1층
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

Z1 = sigmoid(A1)
print(A1)
print(Z1)


# 1층에서 2층
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
Z2 = sigmoid(A2)

print(A2)
print(Z2)


