diff --git a/src/TensorFlowNET.Core/Training/AutoTrackable.cs b/src/TensorFlowNET.Core/Training/AutoTrackable.cs
index 6f10fd2e..5dd9784f 100644
--- a/src/TensorFlowNET.Core/Training/AutoTrackable.cs
+++ b/src/TensorFlowNET.Core/Training/AutoTrackable.cs
@@ -6,7 +6,7 @@ using static Tensorflow.Binding;
 
 namespace Tensorflow.Train
 {
-    public abstract class AutoTrackable : Trackable
+    public class AutoTrackable : Trackable
     {
         public void _delete_tracking(string name)
         {
diff --git a/src/TensorFlowNET.Keras/Saving/SavedModel/serialized_attributes.cs b/src/TensorFlowNET.Keras/Saving/SavedModel/serialized_attributes.cs
index 6a163fec..ff3c7875 100644
--- a/src/TensorFlowNET.Keras/Saving/SavedModel/serialized_attributes.cs
+++ b/src/TensorFlowNET.Keras/Saving/SavedModel/serialized_attributes.cs
@@ -1,14 +1,279 @@
 using System;
 using System.Collections.Generic;
+using System.Linq;
 using System.Text;
+using Tensorflow.Keras.Engine;
+using Tensorflow.Keras.Layers.Rnn;
+using Tensorflow.Keras.Metrics;
+using Tensorflow.Train;
 
 namespace Tensorflow.Keras.Saving.SavedModel
 {
+    // TODO: revise the name of these "Attributes". Since "Attribute" is a significant feature of C#, 
+    // Using the name "Attributes" may be quite confusing.
     /// <summary>
     /// Class that tracks and validates all serialization attributes.
     /// </summary>
-    public class SerializedAttributes
+    public abstract class SerializedAttributes
     {
+        protected IDictionary<string, Trackable?> _object_dict;
+        protected IDictionary<string, Function?> _function_dict;
+        protected AutoTrackable _keras_trackable;
+        protected HashSet<string> _all_functions;
+        protected HashSet<string> _all_checkpointable_objects;
 
+        protected SerializedAttributes()
+        {
+            _object_dict= new Dictionary<string, Trackable?>();
+            _function_dict= new Dictionary<string, Function?>();
+            _keras_trackable= new AutoTrackable();
+            _all_functions= new HashSet<string>();
+            _all_checkpointable_objects= new HashSet<string>();
+        }
+
+        protected SerializedAttributes(IEnumerable<string> checkpointable_objects, IEnumerable<string> functions)
+        {
+            _object_dict = new Dictionary<string, Trackable?>();
+            _function_dict = new Dictionary<string, Function?>();
+            _keras_trackable = new AutoTrackable();
+
+            _all_checkpointable_objects = new HashSet<string>(checkpointable_objects);
+            _all_functions = new HashSet<string>(functions);
+        }
+
+        public IDictionary<string, Function> Functions => _function_dict.TakeWhile(x => x.Value is not null).ToDictionary(x => x.Key, x => x.Value!);
+
+        public IDictionary<string, Trackable> CheckpointableObjects => _object_dict.TakeWhile(x => x.Value is not null).ToDictionary(x => x.Key, x => x.Value!);
+
+        /// <summary>
+        /// Returns functions to attach to the root object during serialization.
+        /// </summary>
+        public IDictionary<string, Function> FunctionsToSerialize
+        {
+            get
+            {
+                Dictionary<string, Function> functions = new();
+                foreach(var pair in Functions)
+                {
+                    if (_all_functions.Contains(pair.Key))
+                    {
+                        // TODO: deal with `LayerCall`.
+                        functions[pair.Key] = pair.Value;
+                    }
+                }
+                return functions;
+            }
+        }
+
+        /// <summary>
+        /// Returns objects to attach to the root object during serialization.
+        /// </summary>
+        public IDictionary<string, Trackable> ObjectsToSerialize
+        {
+            get
+            {
+                var objects = CheckpointableObjects.TakeWhile( x=> _all_checkpointable_objects.Contains(x.Key)).ToDictionary(x => x.Key, x => x.Value);
+                objects[Constants.KERAS_ATTR] = _keras_trackable;
+                return objects;
+            }
+        }
+
+        /// <summary>
+        /// Saves function dictionary, and validates dictionary values.
+        /// </summary>
+        /// <param name="function_dict"></param>
+        public IDictionary<string, Function> set_and_validate_functions(IDictionary<string, Function> function_dict)
+        {
+            foreach(var key in _all_functions)
+            {
+                if (function_dict.ContainsKey(key))
+                {
+                    // TODO: deal with type `LayerCall`.
+                    var fn = function_dict[key];
+                    if (fn is not null && (fn is not Function))
+                    {
+                        throw new ValueError($"Function dictionary contained a non-function object: {function_dict[key]} (for key {key}).");
+                    }
+                    _function_dict[key] = fn;
+
+                    var tf_fn = fn; // TODO: deal with type `LayerCall`.
+
+                    // Warning: this implmentation should be considered again.
+                    var properties = _keras_trackable.GetType().GetProperties();
+                    foreach (var property in properties)
+                    {
+                        if(property.Name == key)
+                        {
+                            property.SetValue(_keras_trackable, tf_fn);
+                            break;
+                        }
+                    }
+                }
+                else
+                {
+                    throw new ValueError($"Function {key} missing from serialized function dict.");
+                }
+            }
+            return Functions;
+        }
+
+        /// <summary>
+        /// Saves objects to a dictionary, and validates the values.
+        /// </summary>
+        /// <param name="object_dict"></param>
+        public IDictionary<string, Trackable> set_and_validate_objects(IDictionary<string, Trackable> object_dict)
+        {
+            foreach(var key in _all_checkpointable_objects)
+            {
+                if (object_dict.ContainsKey(key))
+                {
+                    _object_dict[key] = object_dict[key];
+                    // Warning: this implmentation should be considered again.
+                    var properties = _keras_trackable.GetType().GetProperties();
+                    foreach (var property in properties)
+                    {
+                        if (property.Name == key)
+                        {
+                            property.SetValue(_keras_trackable, object_dict[key]);
+                            break;
+                        }
+                    }
+                }
+                else
+                {
+                    throw new ValueError($"Object {key} missing from serialized object dict.");
+                }
+            }
+            return CheckpointableObjects;
+        }
+
+        /// <summary>
+        /// Returns a new SerializedAttribute object (corresponding to `new` of tensorflow python).
+        /// </summary>
+        /// <returns></returns>
+        public static SerializedAttributes Create(Trackable obj)
+        {
+            if(obj is Model)
+            {
+                return new ModelAttributes();
+            }
+            else if(obj is Metric)
+            {
+                return new MetricAttributes();
+            }
+            else if(obj is RNN)
+            {
+                return new RNNAttributes();
+            }
+            else if(obj is Layer)
+            {
+                return new LayerAttributes();
+            }
+            else
+            {
+                throw new TypeError($"Internal error during serialization: Expected Keras Layer object, got {obj} of type {obj.GetType()}");
+            }
+        }
+
+        protected virtual (IEnumerable<string>, IEnumerable<string>) get_objects_and_functions_recursively(IEnumerable<string>? checkpointable_objects, IEnumerable<string>? functions)
+        {
+            return (checkpointable_objects ?? (new List<string>()), functions ?? (new List<string>()));
+        }
+    }
+
+    // Note that the current implementation still has some potential risks.
+    // The tensorflow python says that this class is "Common endpoints shared by all models loadable by Keras".
+    // However, currently it's just a normal class.
+    public class CommonEndPoints: SerializedAttributes
+    {
+        protected override (IEnumerable<string>, IEnumerable<string>) get_objects_and_functions_recursively(IEnumerable<string>? checkpointable_objects, IEnumerable<string>? functions)
+        {
+            if(checkpointable_objects is null)
+            {
+                checkpointable_objects = new List<string>();
+            }
+            if(functions is null)
+            {
+                functions = new List<string>();
+            }
+            return base.get_objects_and_functions_recursively(
+                checkpointable_objects.Concat(new string[] { "variables", "trainable_variables", "regularization_losses" }),
+                // TODO: remove the `__call__`.
+                functions.Concat(new string[] {"__call__", "call_and_return_all_conditional_losses", "_default_save_signature" })
+            );
+        }
+    }
+
+    public class LayerAttributes: CommonEndPoints
+    {
+        protected override (IEnumerable<string>, IEnumerable<string>) get_objects_and_functions_recursively(IEnumerable<string>? checkpointable_objects, IEnumerable<string>? functions)
+        {
+            if (checkpointable_objects is null)
+            {
+                checkpointable_objects = new List<string>();
+            }
+            if (functions is null)
+            {
+                functions = new List<string>();
+            }
+            return base.get_objects_and_functions_recursively(
+                checkpointable_objects.Concat(new string[] { "non_trainable_variables", "layers", "metrics", "layer_regularization_losses", "layer_metrics" }),
+                functions.Concat(new string[] { "call_and_return_conditional_losses", "activity_regularizer_fn" })
+            );
+        }
+    }
+
+    public class ModelAttributes: LayerAttributes
+    {
+        protected override (IEnumerable<string>, IEnumerable<string>) get_objects_and_functions_recursively(IEnumerable<string>? checkpointable_objects, IEnumerable<string>? functions)
+        {
+            if (checkpointable_objects is null)
+            {
+                checkpointable_objects = new List<string>();
+            }
+            if (functions is null)
+            {
+                functions = new List<string>();
+            }
+            return base.get_objects_and_functions_recursively(checkpointable_objects,functions);
+        }
+    }
+
+    public class MetricAttributes : SerializedAttributes
+    {
+        protected override (IEnumerable<string>, IEnumerable<string>) get_objects_and_functions_recursively(IEnumerable<string>? checkpointable_objects, IEnumerable<string>? functions)
+        {
+            if (checkpointable_objects is null)
+            {
+                checkpointable_objects = new List<string>();
+            }
+            if (functions is null)
+            {
+                functions = new List<string>();
+            }
+            return base.get_objects_and_functions_recursively(
+                checkpointable_objects.Concat(new string[] { "variables" }),
+                functions
+            );
+        }
+    }
+
+    public class RNNAttributes: LayerAttributes
+    {
+        protected override (IEnumerable<string>, IEnumerable<string>) get_objects_and_functions_recursively(IEnumerable<string>? checkpointable_objects, IEnumerable<string>? functions)
+        {
+            if (checkpointable_objects is null)
+            {
+                checkpointable_objects = new List<string>();
+            }
+            if (functions is null)
+            {
+                functions = new List<string>();
+            }
+            return base.get_objects_and_functions_recursively(
+                checkpointable_objects.Concat(new string[] { "states" }),
+                functions
+            );
+        }
     }
 }