lib/dnn/core/model.rb in ruby-dnn-0.5.8 vs lib/dnn/core/model.rb in ruby-dnn-0.5.9

@@ -100,10 +100,13 @@
               batch_size: 1,
               test: nil,
               verbose: true,
               batch_proc: nil,
               &epoch_proc)
+      unless compiled?
+        raise DNN_Error.new("The model is not compiled.")
+      end
       @batch_size = batch_size
       num_train_data = x.shape[0]
       (1..epochs).each do |epoch|
         puts "【 epoch #{epoch}/#{epochs} 】" if verbose
         (num_train_data.to_f / @batch_size).ceil.times do |index|
@@ -166,11 +169,15 @@
           y_batch[j, false] = y[k, false]
         end
         x_batch, y_batch = batch_proc.call(x_batch, y_batch) if batch_proc
         out = forward(x_batch, false)
         @batch_size.times do |j|
-         correct += 1 if out[j, true].max_index == y_batch[j, true].max_index
+          if @layers[-1].shape == [1]
+            correct += 1 if out[j, 0].round == y_batch[j, 0].round
+          else
+            correct += 1 if out[j, true].max_index == y_batch[j, true].max_index
+          end
         end
       end
       correct.to_f / x.shape[0]
     end
   
@@ -181,9 +188,12 @@
     def predict1(x)
       predict(SFloat.cast([x]))[0, false]
     end
   
     def forward(x, training)
+      unless compiled?
+        raise DNN_Error.new("The model is not compiled.")
+      end
       @training = training
       @layers.each do |layer|
         x = layer.forward(x)
       end
       x