fix: make the initialization of the layer's name correct

src/TensorFlowNET.Keras/Utils/generic_utils.cs

@@ -29,6 +29,7 @@ using Tensorflow.Keras.Engine;
 using Tensorflow.Keras.Layers;
 using Tensorflow.Keras.Saving;
 using Tensorflow.Train;
+using System.Text.RegularExpressions;
 
 namespace Tensorflow.Keras.Utils
 {
@@ -126,12 +127,15 @@ namespace Tensorflow.Keras.Utils
 
         public static string to_snake_case(string name)
         {
-            return string.Concat(name.Select((x, i) =>
+            string intermediate = Regex.Replace(name, "(.)([A-Z][a-z0-9]+)", "$1_$2");
+            string insecure = Regex.Replace(intermediate, "([a-z])([A-Z])", "$1_$2").ToLower();
+
+            if (insecure[0] != '_')
             {
-                return i > 0 && char.IsUpper(x) && !Char.IsDigit(name[i - 1]) ?
-                    "_" + x.ToString() :
-                    x.ToString();
-            })).ToLower();
+                return insecure;
+            }
+
+            return "private" + insecure;
         }
 
         /// <summary>

test/TensorFlowNET.Keras.UnitTest/InitLayerNameTest.cs

@@ -0,0 +1,33 @@
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using Tensorflow.Keras.Layers;
+using static Tensorflow.Binding;
+using static Tensorflow.KerasApi;
+
+namespace Tensorflow.Keras.UnitTest
+{
+    [TestClass]
+    public class InitLayerNameTest
+    {
+        [TestMethod]
+        public void RNNLayerNameTest() 
+        {
+            var simpleRnnCell = keras.layers.SimpleRNNCell(1);
+            Assert.AreEqual("simple_rnn_cell", simpleRnnCell.Name);
+            var simpleRnn = keras.layers.SimpleRNN(2);
+            Assert.AreEqual("simple_rnn", simpleRnn.Name);
+            var lstmCell = keras.layers.LSTMCell(2);
+            Assert.AreEqual("lstm_cell", lstmCell.Name);
+            var lstm = keras.layers.LSTM(3);
+            Assert.AreEqual("lstm", lstm.Name);
+        }
+
+        [TestMethod]
+        public void ConvLayerNameTest()
+        {
+            var conv2d = keras.layers.Conv2D(8, activation: "linear");
+            Assert.AreEqual("conv2d", conv2d.Name);
+            var conv2dTranspose = keras.layers.Conv2DTranspose(8);
+            Assert.AreEqual("conv2d_transpose", conv2dTranspose.Name);
+        }
+    }
+}