class CooCoo::VectorLayer
Attributes
activation_function[RW]
bias[R]
weights[R]
Public Class Methods
from_hash(h, network = nil)
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# File lib/coo-coo/vector_layer.rb, line 147 def from_hash(h, network = nil) self.new(h[:neurons][0][:num_inputs], h[:outputs], ActivationFunctions.from_name(h[:neurons][0][:f])). update_from_hash!(h) end
new(num_inputs, size, activation_function = CooCoo.default_activation)
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# File lib/coo-coo/vector_layer.rb, line 16 def initialize(num_inputs, size, activation_function = CooCoo.default_activation) @activation_function = activation_function @num_inputs = num_inputs.to_i @size = size.to_i @weights = @activation_function.initial_weights(@num_inputs, @size) @bias = @activation_function.initial_bias(@size) end
Public Instance Methods
==(other)
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# File lib/coo-coo/vector_layer.rb, line 138 def ==(other) other.kind_of?(self.class) && size == other.size && bias == other.bias && weights == other.weights && activation_function == other.activation_function end
activate(input)
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# File lib/coo-coo/vector_layer.rb, line 40 def activate(input) @weights.dot(num_inputs, size, input, 1, num_inputs) + @bias end
add_inputs!(new_size)
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# File lib/coo-coo/vector_layer.rb, line 105 def add_inputs!(new_size) if new_size != num_inputs w = CooCoo::Vector.zeros(new_size * size) w.set2d!(new_size, @weights, num_inputs, 0, 0) w.set2d!(new_size, @activation_func.initial_weights(size, 1), 1, new_size - 1, 0) @weights = w @num_inputs = new_size end self end
add_neurons!(new_size)
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# File lib/coo-coo/vector_layer.rb, line 89 def add_neurons!(new_size) if new_size != @size w = CooCoo::Vector.zeros(num_inputs * new_size) w[0, @weights.size] = @weights w[@weights.size, num_inputs] = @activation_func.initial_weights(num_inputs, 1) @weights = w @bias = CooCoo::Vector.ones(new_size).set(@bias) @bias[-1] = @activation_func.initial_bias(1)[0] @size = new_size end self end
adjust_weights!(deltas)
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# File lib/coo-coo/vector_layer.rb, line 61 def adjust_weights!(deltas) @bias -= deltas.bias_deltas @weights -= deltas.weight_deltas self end
backprop(input, output, errors, hidden_state)
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# File lib/coo-coo/vector_layer.rb, line 44 def backprop(input, output, errors, hidden_state) # Properly: return errors * @activation_func.derivative(activate(input), output), hidden_state return errors * @activation_function.derivative(nil, output), hidden_state end
forward(input, hidden_state)
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# File lib/coo-coo/vector_layer.rb, line 32 def forward(input, hidden_state) return transfer(activate(input)), hidden_state end
neuron_hash()
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# File lib/coo-coo/vector_layer.rb, line 79 def neuron_hash @weights.each_slice(num_inputs).with_index.collect do |neuron_weights, i| { num_inputs: num_inputs, weights: neuron_weights.to_a, bias: @bias[i], f: @activation_function.name } end end
num_inputs()
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# File lib/coo-coo/vector_layer.rb, line 24 def num_inputs @num_inputs end
size()
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# File lib/coo-coo/vector_layer.rb, line 28 def size @size end
to_hash(network = nil)
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# File lib/coo-coo/vector_layer.rb, line 72 def to_hash(network = nil) { type: self.class.to_s, outputs: size, neurons: neuron_hash } end
transfer(activations)
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# File lib/coo-coo/vector_layer.rb, line 36 def transfer(activations) @activation_function.call(activations) end
transfer_error(deltas)
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# File lib/coo-coo/vector_layer.rb, line 49 def transfer_error(deltas) deltas.dot(size, 1, @weights, num_inputs, size) end
transfer_input_error(expecting)
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# File lib/coo-coo/vector_layer.rb, line 53 def transfer_input_error(expecting) (output - expecting).to_a end
update_from_hash!(h)
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# File lib/coo-coo/vector_layer.rb, line 126 def update_from_hash!(h) @activation_function = ActivationFunctions.from_name(h[:neurons][0][:f]) add_neurons!(h[:outputs]) add_inputs!(h[:neurons][0][:num_inputs]) h[:outputs].times do |i| update_neuron_from_hash!(i, h[:neurons][i]) end self end
update_neuron_from_hash!(neuron_index, h)
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# File lib/coo-coo/vector_layer.rb, line 117 def update_neuron_from_hash!(neuron_index, h) if neuron_index > size add_neurons!(neuron_index) end @weights[neuron_index * num_inputs, num_inputs] = h[:weights] @bias[neuron_index] = h[:bias] end
update_weights!(inputs, deltas)
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# File lib/coo-coo/vector_layer.rb, line 57 def update_weights!(inputs, deltas) adjust_weights!(weight_deltas(inputs, deltas)) end
weight_deltas(inputs, deltas)
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# File lib/coo-coo/vector_layer.rb, line 68 def weight_deltas(inputs, deltas) WeightDeltas.new(deltas, deltas.dot(1, size, inputs, num_inputs, 1)) end