Fix NeuralNetXor example.

src/TensorFlowNET.Core/Tensorflow.Binding.csproj

@@ -107,8 +107,8 @@ https://tensorflownet.readthedocs.io</Description>
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.144" />
+    <PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.148" />
     <PackageReference Include="Protobuf.Text" Version="0.5.0" />
-    <PackageReference Include="Serilog.Sinks.Console" Version="4.0.1" />
+    <PackageReference Include="Serilog.Sinks.Console" Version="4.1.0" />
   </ItemGroup>
 </Project>

src/TensorFlowNET.Keras/Optimizers/OptimizerV2.cs

@@ -48,7 +48,7 @@ namespace Tensorflow.Keras.Optimizers
         public void apply_gradients((Tensor, ResourceVariable) grads_and_vars,
             string name = null,
             bool experimental_aggregate_gradients = true)
-            => apply_gradients(grads_and_vars,
+            => apply_gradients(new[] { grads_and_vars },
                 name: name,
                 experimental_aggregate_gradients: experimental_aggregate_gradients);
 

src/TensorFlowNET.Keras/Saving/hdf5_format.cs

@@ -84,23 +84,18 @@ namespace Tensorflow.Keras.Saving
         {
             string original_keras_version = "2.5.0";
             string original_backend = null;
-            if (Hdf5.AttributeExists(f, "keras_version"))
-            {
-                var (success, attr) = Hdf5.ReadStringAttributes(f, "keras_version", "");
-                if (success)
-                    original_keras_version = attr.First();
-                // keras version should be 2.5.0+
-                var ver_major = int.Parse(original_keras_version.Split('.')[0]);
-                var ver_minor = int.Parse(original_keras_version.Split('.')[1]);
-                if (ver_major < 2 || (ver_major == 2 && ver_minor < 5))
-                    throw new ValueError("keras version should be 2.5.0 or later.");
-            }
-            if (Hdf5.AttributeExists(f, "backend"))
-            {
-                var (success, attr) = Hdf5.ReadStringAttributes(f, "backend", "");
-                if (success)
-                    original_backend = attr.First();
-            }
+            var (success, attr) = Hdf5.ReadStringAttributes(f, "keras_version", "", true);
+            if (success)
+                original_keras_version = attr.First();
+            // keras version should be 2.5.0+
+            var ver_major = int.Parse(original_keras_version.Split('.')[0]);
+            var ver_minor = int.Parse(original_keras_version.Split('.')[1]);
+            if (ver_major < 2 || (ver_major == 2 && ver_minor < 5))
+                throw new ValueError("keras version should be 2.5.0 or later.");
+            
+            (success, attr) = Hdf5.ReadStringAttributes(f, "backend", "", true);
+            if (success)
+                original_backend = attr.First();
 
             var filtered_layers = new List<ILayer>();
             foreach (var layer in layers)
@@ -137,7 +132,7 @@ namespace Tensorflow.Keras.Saving
                 var weight_names = load_attributes_from_hdf5_group(g, "weight_names");
                 foreach (var i_ in weight_names)
                 {
-                    (bool success, Array result) = Hdf5.ReadDataset<float>(g, i_);
+                    (success, Array result) = Hdf5.ReadDataset<float>(g, i_);
                     if (success)
                         weight_values.Add(np.array(result));
                 }
@@ -329,12 +324,10 @@ namespace Tensorflow.Keras.Saving
 
         public static string[] load_attributes_from_hdf5_group(long group, string name)
         {
-            if (Hdf5.AttributeExists(group, name))
-            {
-                var (success, attr) = Hdf5.ReadStringAttributes(group, name, "");
-                if (success)
-                    return attr.ToArray();
-            }
+            var (success, attr) = Hdf5.ReadStringAttributes(group, name, "", true);
+            if (success)
+                return attr.ToArray();
+            
             return null;
         }
 

src/TensorFlowNET.Keras/Tensorflow.Keras.csproj

@@ -70,10 +70,10 @@ Keras is an API designed for human beings, not machines. Keras follows best prac
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="HDF5-CSharp" Version="1.12.5" />
-    <PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.144" />
+    <PackageReference Include="HDF5-CSharp" Version="1.16.2" />
+    <PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.148" />
     <PackageReference Include="Newtonsoft.Json" Version="13.0.1" />
-    <PackageReference Include="SharpZipLib" Version="1.3.3" />
+    <PackageReference Include="SharpZipLib" Version="1.4.1" />
   </ItemGroup>
 
   <ItemGroup>