diff --git a/dlib/dnn/layers.h b/dlib/dnn/layers.h
index 250df286d..460524ba7 100644
--- a/dlib/dnn/layers.h
+++ b/dlib/dnn/layers.h
@@ -1791,7 +1791,7 @@ namespace dlib
     }
 
     template <typename net_type>
-    void disable_duplicative_bias (
+    void disable_duplicative_biases (
         net_type& net
     )
     {
diff --git a/dlib/dnn/layers_abstract.h b/dlib/dnn/layers_abstract.h
index 2bfe06a86..b7963ab0b 100644
--- a/dlib/dnn/layers_abstract.h
+++ b/dlib/dnn/layers_abstract.h
@@ -1810,7 +1810,7 @@ namespace dlib
 // ----------------------------------------------------------------------------------------
 
     template <typename net_type>
-    void disable_duplicative_bias (
+    void disable_duplicative_biases (
         const net_type& net
     );
     /*!
diff --git a/dlib/test/dnn.cpp b/dlib/test/dnn.cpp
index a3ed2d14a..55e844a41 100644
--- a/dlib/test/dnn.cpp
+++ b/dlib/test/dnn.cpp
@@ -3918,7 +3918,7 @@ namespace
                         relu<bn_con<conp<4 * growth_rate, 1, 1,
                         relu<bn_con<tag1<SUBNET>>>>>>>>>;
     template <typename SUBNET> using dense_layer_32 = dense_layer<32, 8, SUBNET>;
-    void test_disable_duplicative_bias()
+    void test_disable_duplicative_biases()
     {
         using net_type = fc<10, relu<layer_norm<fc<15, relu<bn_fc<fc<20,
                          relu<layer_norm<conp<32, 3, 1,
@@ -3934,7 +3934,7 @@ namespace
         DLIB_TEST(layer<21>(net).layer_details().bias_is_disabled() == false);
         DLIB_TEST(layer<24>(net).layer_details().bias_is_disabled() == false);
         DLIB_TEST(layer<31>(net).layer_details().bias_is_disabled() == false);
-        disable_duplicative_bias(net);
+        disable_duplicative_biases(net);
         DLIB_TEST(layer<0>(net).layer_details().bias_is_disabled() == false);
         DLIB_TEST(layer<3>(net).layer_details().bias_is_disabled() == true);
         DLIB_TEST(layer<6>(net).layer_details().bias_is_disabled() == true);
@@ -4130,7 +4130,7 @@ namespace
             test_loss_multimulticlass_log();
             test_loss_mmod();
             test_layers_scale_and_scale_prev();
-            test_disable_duplicative_bias();
+            test_disable_duplicative_biases();
         }
 
         void perform_test()
diff --git a/examples/dnn_dcgan_train_ex.cpp b/examples/dnn_dcgan_train_ex.cpp
index bb155cb6f..9dab87633 100644
--- a/examples/dnn_dcgan_train_ex.cpp
+++ b/examples/dnn_dcgan_train_ex.cpp
@@ -134,8 +134,8 @@ int main(int argc, char** argv) try
     // setup all leaky_relu_ layers in the discriminator to have alpha = 0.2
     visit_computational_layers(discriminator, [](leaky_relu_& l){ l = leaky_relu_(0.2); });
     // Remove the bias learning from all bn_ inputs in both networks
-    disable_duplicative_bias(generator);
-    disable_duplicative_bias(discriminator);
+    disable_duplicative_biases(generator);
+    disable_duplicative_biases(discriminator);
     // Forward random noise so that we see the tensor size at each layer
     discriminator(generate_image(generator, make_noise(rnd)));
     cout << "generator (" << count_parameters(generator) << " parameters)" << endl;