Contents

require "dnn"

include DNN::Layers
include DNN::Activations
include DNN::Optimizers
include DNN::Losses
include DNN::Models

x = Numo::SFloat[[0, 0], [1, 0], [0, 1], [1, 1]]
y = Numo::SFloat[[0], [1], [1], [0]]

model = Sequential.new

model << InputLayer.new(2)
model << Dense.new(16)
model << ReLU.new
model << Dense.new(1)

model.setup(SGD.new, SigmoidCrossEntropy.new)

model.train(x, y, 20000, batch_size: 4, verbose: false)

p DNN::Utils.sigmoid(model.predict(x))

Version data entries

6 entries across 6 versions & 1 rubygems

Version	Path
ruby-dnn-0.13.4	examples/xor_example.rb
ruby-dnn-0.13.3	examples/xor_example.rb
ruby-dnn-0.13.2	examples/xor_example.rb
ruby-dnn-0.13.1	examples/xor_example.rb
ruby-dnn-0.13.0	examples/xor_example.rb
ruby-dnn-0.12.4	examples/xor_example.rb