Move keras unit test in seperate project.

TensorFlow.NET.sln

@@ -19,6 +19,8 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Recommenders", "
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Native.UnitTest", "test\TensorFlowNET.Native.UnitTest\Tensorflow.Native.UnitTest.csproj", "{84CA35F8-99FC-408E-8DF3-5AA175E5EFD3}"
 EndProject
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Keras.UnitTest", "test\TensorFlowNET.Keras.UnitTest\Tensorflow.Keras.UnitTest.csproj", "{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}"
+EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
@@ -227,6 +229,30 @@ Global
 		{84CA35F8-99FC-408E-8DF3-5AA175E5EFD3}.Release|x64.Build.0 = Release|Any CPU
 		{84CA35F8-99FC-408E-8DF3-5AA175E5EFD3}.Release|x86.ActiveCfg = Release|Any CPU
 		{84CA35F8-99FC-408E-8DF3-5AA175E5EFD3}.Release|x86.Build.0 = Release|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug|x64.ActiveCfg = Debug|x64
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug|x64.Build.0 = Debug|x64
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug|x86.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug|x86.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug-Minimal|Any CPU.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug-Minimal|Any CPU.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug-Minimal|x64.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug-Minimal|x64.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug-Minimal|x86.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Debug-Minimal|x86.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Publish|Any CPU.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Publish|Any CPU.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Publish|x64.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Publish|x64.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Publish|x86.ActiveCfg = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Publish|x86.Build.0 = Debug|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Release|Any CPU.Build.0 = Release|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Release|x64.ActiveCfg = Release|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Release|x64.Build.0 = Release|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Release|x86.ActiveCfg = Release|Any CPU
+		{79EB56DF-E29E-4AE2-A7D9-FE403FD919BA}.Release|x86.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

src/TensorFlowNET.Core/Tensorflow.Binding.csproj

@@ -82,7 +82,7 @@ TensorFlow .NET v0.3x is focused on making more Keras API works</PackageReleaseN
   <ItemGroup>
     <PackageReference Include="MethodBoundaryAspect.Fody" Version="2.0.138" />
     <PackageReference Include="Microsoft.Extensions.DependencyInjection" Version="5.0.1" />
-    <PackageReference Include="NumSharp.Lite" Version="0.1.10" />
+    <PackageReference Include="NumSharp.Lite" Version="0.1.11" />
     <PackageReference Include="Protobuf.Text" Version="0.4.0" />
     <PackageReference Include="Serilog.Sinks.Console" Version="3.1.1" />
   </ItemGroup>

test/TensorFlowNET.Keras.UnitTest/EagerModeTestBase.cs

@@ -0,0 +1,50 @@
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using System;
+using static Tensorflow.Binding;
+
+namespace TensorFlowNET.Keras.UnitTest
+{
+    public class EagerModeTestBase
+    {
+        [TestInitialize]
+        public void TestInit()
+        {
+            if (!tf.executing_eagerly())
+                tf.enable_eager_execution();
+            tf.Context.ensure_initialized();
+        }
+
+        [TestCleanup]
+        public void TestClean()
+        {
+        }
+
+        public bool Equal(float[] f1, float[] f2)
+        {
+            bool ret = false;
+            var tolerance = .000001f;
+            for (var i = 0; i < f1.Length; i++)
+            {
+                ret = Math.Abs(f1[i] - f2[i]) <= tolerance;
+                if (!ret)
+                    break;
+            }
+
+            return ret;
+        }
+
+        public bool Equal(double[] d1, double[] d2)
+        {
+            bool ret = false;
+            var tolerance = .000000000000001f;
+            for (var i = 0; i < d1.Length; i++)
+            {
+                ret = Math.Abs(d1[i] - d2[i]) <= tolerance;
+                if (!ret)
+                    break;
+            }
+
+            return ret;
+        }
+    }
+}

test/TensorFlowNET.UnitTest/Keras/ActivationTest.cs → test/TensorFlowNET.Keras.UnitTest/Layers/ActivationTest.cs

@@ -6,7 +6,7 @@ using NumSharp;
 using static Tensorflow.KerasApi;
 using Tensorflow;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class ActivationTest : EagerModeTestBase
@@ -16,11 +16,7 @@ namespace TensorFlowNET.UnitTest.Keras
         {
             var layer = keras.layers.LeakyReLU();
             Tensor output = layer.Apply(np.array(-3.0f, -1.0f, 0.0f, 2.0f));
-            var outputArray = output.ToArray<float>();
-            assertFloat32Equal(-0.9f, outputArray[0], "Not equal");
-            assertFloat32Equal(-0.3f, outputArray[1], "Not equal");
-            assertFloat32Equal(0.0f, outputArray[2], "Not equal");
-            assertFloat32Equal(2.0f, outputArray[3], "Not equal");
+            Equal(new[] { -0.9f, -0.3f, 0.0f, 2.0f }, output.ToArray<float>());
         }
     }
 }

test/TensorFlowNET.UnitTest/Keras/CosineSimilarity.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/CosineSimilarity.Test.cs

@@ -5,7 +5,7 @@ using Tensorflow.Keras.Losses;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class CosineSimilarity

test/TensorFlowNET.UnitTest/Keras/Huber.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/Huber.Test.cs

@@ -5,7 +5,7 @@ using Tensorflow.Keras.Losses;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class Huber

test/TensorFlowNET.UnitTest/Keras/Layers.Merging.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/Layers.Merging.Test.cs

@@ -3,7 +3,7 @@ using NumSharp;
 using Tensorflow;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class LayersMergingTest : EagerModeTestBase

test/TensorFlowNET.UnitTest/Keras/Layers.Reshaping.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/Layers.Reshaping.Test.cs

@@ -3,7 +3,7 @@ using NumSharp;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class LayersReshapingTest : EagerModeTestBase

test/TensorFlowNET.UnitTest/Keras/LayersTest.cs → test/TensorFlowNET.Keras.UnitTest/Layers/LayersTest.cs

@@ -3,7 +3,7 @@ using NumSharp;
 using Tensorflow;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     /// <summary>
     /// https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/layers
@@ -24,7 +24,7 @@ namespace TensorFlowNET.UnitTest.Keras
             var layers = keras.layers;
 
             var inputs = keras.Input(shape: 784);
-            Assert.AreEqual((None, 784), inputs.TensorShape);
+            Assert.AreEqual((-1, 784), inputs.TensorShape);
 
             var dense = layers.Dense(64, activation: keras.activations.Relu);
             var x = dense.Apply(inputs);
@@ -59,7 +59,7 @@ namespace TensorFlowNET.UnitTest.Keras
             });
             // model.compile("rmsprop", "mse");
             var output_array = model.predict(input_array);
-            Assert.AreEqual((32, 10, 64), output_array.TensorShape);
+            Assert.AreEqual((32, 10, 64), output_array.shape);
         }
 
         /// <summary>

test/TensorFlowNET.UnitTest/Keras/LogCosh.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/LogCosh.Test.cs

@@ -5,7 +5,7 @@ using Tensorflow.Keras.Losses;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class LogCosh

test/TensorFlowNET.UnitTest/Keras/MeanAbsoluteError.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/MeanAbsoluteError.Test.cs

@@ -5,7 +5,7 @@ using Tensorflow.Keras.Losses;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class MeanAbsoluteError

test/TensorFlowNET.UnitTest/Keras/MeanAbsolutePercentageError.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/MeanAbsolutePercentageError.Test.cs

@@ -5,7 +5,7 @@ using Tensorflow.Keras.Losses;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class MeanAbsolutePercentageError

test/TensorFlowNET.UnitTest/Keras/MeanSquaredError.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/MeanSquaredError.Test.cs

@@ -5,7 +5,7 @@ using Tensorflow.Keras.Losses;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class MeanSquaredErrorTest 

test/TensorFlowNET.UnitTest/Keras/MeanSquaredLogarithmicError.Test.cs → test/TensorFlowNET.Keras.UnitTest/Layers/MeanSquaredLogarithmicError.Test.cs

@@ -5,7 +5,7 @@ using Tensorflow.Keras.Losses;
 using static Tensorflow.Binding;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     [TestClass]
     public class MeanSquaredLogarithmicError

test/TensorFlowNET.UnitTest/Keras/ModelSaveTest.cs → test/TensorFlowNET.Keras.UnitTest/Layers/ModelSaveTest.cs

@@ -2,7 +2,7 @@
 using Tensorflow.Keras.Engine;
 using static Tensorflow.KerasApi;
 
-namespace TensorFlowNET.UnitTest.Keras
+namespace TensorFlowNET.Keras.UnitTest
 {
     /// <summary>
     /// https://www.tensorflow.org/guide/keras/save_and_serialize

test/TensorFlowNET.Keras.UnitTest/Tensorflow.Keras.UnitTest.csproj

@@ -0,0 +1,28 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <TargetFramework>netcoreapp3.1</TargetFramework>
+
+    <IsPackable>false</IsPackable>
+
+    <Platforms>AnyCPU;x64</Platforms>
+  </PropertyGroup>
+
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
+    <DefineConstants>DEBUG;TRACE</DefineConstants>
+    <PlatformTarget>x64</PlatformTarget>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.7.1" />
+    <PackageReference Include="MSTest.TestAdapter" Version="2.1.1" />
+    <PackageReference Include="MSTest.TestFramework" Version="2.1.1" />
+    <PackageReference Include="coverlet.collector" Version="1.3.0" />
+    <PackageReference Include="SciSharp.TensorFlow.Redist" Version="2.3.1" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\src\TensorFlowNET.Keras\Tensorflow.Keras.csproj" />
+  </ItemGroup>
+
+</Project>