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neutral.py
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neutral.py
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import numpy as np
import matplotlib.pyplot as plt
def sigmoid(x):
return 1 / (1 + np.exp(-x))
def identity_function(x):
return x
def init_newtwork():
network = {}
network['W1'] = np.array([ [0.1, 0.3, 0.5], [0.2, 0.4, 0.6] ])
network['b1'] = np.array([0.1, 0.2, 0.3])
network['W2'] = np.array([ [0.1, 0.4], [0.2, 0.5], [0.3, 0.6] ])
network['b2'] = np.array([0.1, 0.2])
network['W3'] = np.array([ [0.1, 0.3], [0.2, 0.4] ])
network['b3'] = np.array([0.1, 0.2])
return network
def forward(network, x):
W1, W2, W3 = network['W1'], network['W2'], network['W3']
b1, b2, b3 = network['b1'], network['b2'], network['b3']
A1 = np.dot(x, W1) + b1
Z1 = sigmoid(A1)
A2 = np.dot(Z1, W2) + b2
Z2 = sigmoid(A2)
A3 = np.dot(Z2, W3) + b3
return identity_function(A3)
x = np.array([ 1.0, 0.5])
print(forward(init_newtwork(), x))