add tf.nn.l2_loss

Author: Oceania2018

src/TensorFlowNET.Core/APIs/tf.nn.cs

@@ -157,6 +157,9 @@ public Tensor bias_add(Tensor value, IVariableV1 bias, string data_format = null
                 });
             }
 
+            public Tensor l2_loss(Tensor t, string name = null)
+                => nn_ops.l2_loss(t, name: name);
+
             /// <summary>
             /// Local Response Normalization.
             /// </summary>

src/TensorFlowNET.Core/Operations/nn_ops.cs

@@ -128,6 +128,9 @@ public static Tensor softmax(Tensor logits, int axis = -1, string name = null)
             return _softmax(logits, gen_nn_ops.softmax, axis, name);
         }
 
+        public static Tensor l2_loss(Tensor t, string name = null)
+            => tf.Context.ExecuteOp("L2Loss", name, new ExecuteOpArgs(t));
+
         public static Tensor leaky_relu(Tensor features, float alpha = 0.2f, string name = null)
         {
             return tf_with(ops.name_scope(name, "LeakyRelu", new { features, alpha }), scope =>

test/TensorFlowNET.UnitTest/ManagedAPI/ActivationFunctionTest.cs

@@ -2,7 +2,7 @@
 using Tensorflow;
 using static Tensorflow.Binding;
 
-namespace TensorFlowNET.UnitTest.nn_test
+namespace TensorFlowNET.UnitTest.NenuralNetwork
 {
     [TestClass]
     public class ActivationFunctionTest : EagerModeTestBase

test/TensorFlowNET.UnitTest/ManagedAPI/NeuralNetworkTest.cs

@@ -0,0 +1,18 @@
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using static Tensorflow.Binding;
+using Tensorflow.NumPy;
+
+namespace TensorFlowNET.UnitTest.NenuralNetwork
+{
+    [TestClass]
+    public class NeuralNetworkTest : EagerModeTestBase
+    {
+        [TestMethod]
+        public void l2_loss()
+        {
+            var x = tf.Variable(np.array(new[,] { { 1, 2, 3, 4 }, { 5, 6, 7, 8 } }), dtype: tf.float32);
+            var l2 = tf.nn.l2_loss(x);
+            Assert.AreEqual(l2.numpy(), 102f);
+        }
+    }
+}