Simple XOR example

[bkmgit]

May be helpful to add a simple XOR example. Classification is one way to do this, but can add more traditional method if considered useful.

require 'numo/narray'
require 'chainer'

class XOR < Chainer::Chain
  L = Chainer::Links::Connection::Linear
  F = Chainer::Functions

  def initialize(n_units, n_out)
    super()
    init_scope do
      @l1 = L.new(nil, out_size: n_units)
      @l2 = L.new(nil, out_size: n_out)
    end
  end

  def call(x, y)
    return F::Loss::MeanSquaredError.mean_squared_error(fwd(x), y)
  end

  def fwd(x)
    h1 = F::Activation::Sigmoid.sigmoid(@l1.(x))
    h2 = @l2.(h1)
    return h2
  end
end

device = Chainer::Device.create(-1)
Chainer::Device.change_default(device)
xm = device.xm

model = XOR.new(4,2)

optimizer = Chainer::Optimizers::Adam.new
optimizer.setup(model)

x = [[0,0],[1,0],[0,1],[1,1]]

# target
y = [0,1,1,0]

y_onehot = xm::SFloat.eye(2)[y, false]

x = xm::SFloat.cast(x)
y = xm::SFloat.cast(y)
y_onehot = xm::SFloat.cast(y_onehot)

x_train = x 
y_train = y_onehot  
x_test = x       
y_test = y             

# Train
print("Training ")

10000.times{|i|
  print(".") if i % 1000 == 0
  x = Chainer::Variable.new(x_train)
  y = Chainer::Variable.new(y_train)
  model.cleargrads()
  loss = model.(x, y)
  loss.backward()
  optimizer.update()
}

puts

# Test
xt = Chainer::Variable.new(x_test)
yt = model.fwd(xt)
n_row, n_col = yt.data.shape

puts "Result : Correct Answer : Answer <= One-Hot"
ok = 0
n_row.times{|i|
  ans = yt.data[i, true].max_index()
  if ans == y_test[i]
    ok += 1
    printf("OK")
  else
    printf("--")
  end
  printf(" : #{y_test[i].to_i} :")

  puts " #{ans.to_i} <+{yt.data[i, 0..-1].to_a}"
}
puts "Row: #{n_row}, Column: #{n_col}"
puts "Accuracy rate : #{ok}/#{n_row} = #{ok.to_f / n_row}"