朱莉娅的简单神经网络

Question

I am try to rewrite code from this tutorial on python to julia and getting unexpected result - [0.5; 0.5; 0.5; 0.5] [0.5; 0.5; 0.5; 0.5] [0.5; 0.5; 0.5; 0.5] I look to the line again and again but not see difference.

Python code:

from numpy import exp, array, random, dot
training_set_inputs = array([[0, 0, 1], [1, 1, 1], [1, 0, 1], [0, 1, 1]])
training_set_outputs = array([[0, 1, 1, 0]]).T
random.seed(1)
synaptic_weights = 2 * random.random((3, 1)) - 1
for iteration in xrange(10000):
    output = 1 / (1 + exp(-(dot(training_set_inputs, synaptic_weights))))
    synaptic_weights += dot(training_set_inputs.T, (training_set_outputs - output) * output * (1 - output))
print 1 / (1 + exp(-(dot(array([1, 0, 0]), synaptic_weights))))

My julia code:

function activate(x)
    return 1./(1+exp(-x))
end

function g_activate(x)
    return x.*(1-x)
end

function test(iter)

Input = [0 0 1;0 1 1;1 0 1;1 1 1]
TInput = transpose(Input)
Test = [0, 1, 1, 0]
Weights = 2 * rand(3, 1) - 1

for i in 1:iter

output = activate(Input*Weights)
error = Test - output
delta = error.*g_activate(output)
Weights +=  TInput*delta

end

println(activate(Input*Weights))
end

What I am doing wrong and how do it more idiomatic way in Julia

Answer 1

You are using wrong input data in Julia code. To match the Python example

Input = [0 0 1;0 1 1;1 0 1;1 1 1]

should be

Input = [0 0 1;1 1 1;1 0 1;0 1 1]

That's what I'm getting with corrected input:

julia> test(10000)
[0.00966854; 0.992117; 0.993589; 0.00786553]

And if I'm running Python code with training_set_inputs = array([[0, 0, 1], [0, 1, 1], [1, 0, 1], [1, 1, 1]]) I'm getting [ 0.5] .