from conx import Network
inputs = [[0, 0],
[0, 1],
[1, 0],
[1, 1]]
def xor(inputs):
a = inputs[0]
b = inputs[1]
return [[0.1, 0.9][int((a or b) and not(a and b))]]
net = Network(2, 2, 1)
net.set_inputs(inputs)
net.set_target_function(xor)
net.train()
net.test()
net = Network(2, 2, 2, 1)
net.set_inputs(inputs)
net.set_target_function(xor)
net.train(max_training_epochs=10000)
net.test()
inputs = [[[0, 0], [0, 0]],
[[0, 1], [1, 1]],
[[1, 0], [1, 1]],
[[1, 1], [0, 0]]]
net = Network(2, 10, 2)
net.set_inputs(inputs)
net = Network(784, 100, 1)
inputs = [train_set[0][i] for i in range(len(train_set[0]))]
targets = [[train_set[1][i]/9.0] for i in range(len(train_set[0]))]
inputs = inputs[:100]
targets = targets[:100]
def display_digit(vector):
for r in range(28):
for c in range(28):
v = int(vector[r * 28 + c] * 10)
ch = " .23456789"[v]
print(ch, end="")
print()
net.display_test_input = display_digit
net.set_inputs(list(zip(inputs, targets)))
net.test(2)
net.train(report_rate=1, tolerance=0.05)
net.test(2)
for i in range(100):
output = net.propagate(inputs[i])
target = int(targets[i][0] * 9)
print("target:", target,
"output:", output,
"correct?", int(output * 10) == target)
