🎨 Fix some typos about NeuralNetwork::Optimizer

yoshoku · May 23, 2020 · af299df · af299df
1 parent 3fa073d
commit af299df
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Showing 2 changed files with 2 additions and 2 deletions.
diff --git a/lib/rumale/neural_network/adam.rb b/lib/rumale/neural_network/adam.rb
@@ -32,7 +32,7 @@ def initialize(learning_rate: 0.001, decay1: 0.9, decay2: 0.999)
         end
 
         # @!visibility private
-        # Calculate the updated weight with Nadam adaptive learning rate.
+        # Calculate the updated weight with Adam adaptive learning rate.
         #
         # @param weight [Numo::DFloat] (shape: [n_features]) The weight to be updated.
         # @param gradient [Numo::DFloat] (shape: [n_features]) The gradient for updating the weight.

diff --git a/spec/rumale/neural_network/layer/affine_spec.rb b/spec/rumale/neural_network/layer/affine_spec.rb
@@ -8,7 +8,7 @@
   let(:z) { Numo::DFloat[[1, 2, 3, 4], [5, 6, 7, 8], [9, 8, 7, 6]] }
   let(:n_inputs) { x.shape[1] }
   let(:n_outputs) { z.shape[1] }
-  let(:adam) { Rumale::Optimizer::Adam.new }
+  let(:adam) { Rumale::NeuralNetwork::Optimizer::Adam.new }
   let(:affine) { described_class.new(n_inputs: n_inputs, n_outputs: n_outputs, optimizer: adam, rng: rng.dup) }
   let(:rand_mat) { 0.01 * Rumale::Utils.rand_normal([n_inputs, n_outputs], rng.dup) }
   let(:out) { affine.forward(x)[0] }