Merge pull request #1188 from hchen2020/master

Allow Model to cache weights.

Author: Oceania2018

src/TensorFlowNET.Keras/Engine/Model.Training.cs

@@ -10,8 +10,38 @@ namespace Tensorflow.Keras.Engine
 {
     public partial class Model
     {
+        static Dictionary<string, List<(string, NDArray)>> weightsCache
+            = new Dictionary<string, List<(string, NDArray)>>();
+
         public void load_weights(string filepath, bool by_name = false, bool skip_mismatch = false, object options = null)
         {
+            // Get from cache
+            if (weightsCache.ContainsKey(filepath))
+            {
+                var filtered_layers = new List<ILayer>();
+                foreach (var layer in Layers)
+                {
+                    var weights = hdf5_format._legacy_weights(layer);
+                    if (weights.Count > 0)
+                        filtered_layers.append(layer);
+                }
+
+                var weight_value_tuples = new List<(IVariableV1, NDArray)>();
+                filtered_layers.Select((layer, i) =>
+                {
+                    var symbolic_weights = hdf5_format._legacy_weights(layer);
+                    foreach(var weight in symbolic_weights)
+                    {
+                        var weight_value = weightsCache[filepath].First(x => x.Item1 == weight.Name).Item2;
+                        weight_value_tuples.Add((weight, weight_value));
+                    }
+                    return layer;
+                }).ToList();
+
+                keras.backend.batch_set_value(weight_value_tuples);
+                return;
+            }
+
             long fileId = Hdf5.OpenFile(filepath, true);
             if(fileId < 0)
             {
@@ -29,8 +59,11 @@ public void load_weights(string filepath, bool by_name = false, bool skip_mismat
                 throw new NotImplementedException("");
             else
             {
-                hdf5_format.load_weights_from_hdf5_group(fileId, Layers);
+                var weight_value_tuples = hdf5_format.load_weights_from_hdf5_group(fileId, Layers);
                 Hdf5.CloseFile(fileId);
+
+                weightsCache[filepath] = weight_value_tuples.Select(x => (x.Item1.Name, x.Item2)).ToList();
+                keras.backend.batch_set_value(weight_value_tuples);
             }
         }
 

src/TensorFlowNET.Keras/Saving/hdf5_format.cs

@@ -82,7 +82,7 @@ public static void load_optimizer_weights_from_hdf5_group(long filepath = -1, Di
 
         }
 
-        public static void load_weights_from_hdf5_group(long f, List<ILayer> layers)
+        public static List<(IVariableV1, NDArray)> load_weights_from_hdf5_group(long f, List<ILayer> layers)
         {
             string original_keras_version = "2.5.0";
             string original_backend = null;
@@ -152,7 +152,7 @@ public static void load_weights_from_hdf5_group(long f, List<ILayer> layers)
                 weight_value_tuples.AddRange(zip(symbolic_weights, weight_values));
             }
 
-            keras.backend.batch_set_value(weight_value_tuples);
+            return weight_value_tuples;
         }
 
         public static void toarrayf4(long filepath = -1, Dictionary<string, object> custom_objects = null, bool compile = false)