diff --git a/csharp/test/Microsoft.ML.OnnxRuntime.Tests/InferenceTest.cs b/csharp/test/Microsoft.ML.OnnxRuntime.Tests/InferenceTest.cs
index 3f974441288b6..0bf59ddc37e90 100644
--- a/csharp/test/Microsoft.ML.OnnxRuntime.Tests/InferenceTest.cs
+++ b/csharp/test/Microsoft.ML.OnnxRuntime.Tests/InferenceTest.cs
@@ -71,9 +71,9 @@ private void CanRunInferenceOnAModel()
                 var results = session.Run(container);  // results is an IReadOnlyList<NamedOnnxValue> container
 
                 Assert.Equal(1, results.Count);
-                
+
                 float[] expectedOutput = LoadTensorFromFile(@"bench.expected_out");
-                float errorMargin = 1e-6F; 
+                float errorMargin = 1e-6F;
                 // validate the results
                 foreach (var r in results)
                 {
@@ -82,7 +82,7 @@ private void CanRunInferenceOnAModel()
                     var resultTensor = r.AsTensor<float>();
                     int[] expectedDimensions = { 1, 1000, 1, 1 };  // hardcoded for now for the test data
                     Assert.Equal(expectedDimensions.Length, resultTensor.Rank);
-                    
+
                     var resultDimensions = resultTensor.Dimensions;
                     for (int i = 0; i < expectedDimensions.Length; i++)
                     {
@@ -113,8 +113,8 @@ private void ThrowWrongInputName()
             var container = new List<NamedOnnxValue>();
             container.Add(NamedOnnxValue.CreateFromTensor<float>("wrong_name", tensor));
             var ex = Assert.Throws<OnnxRuntimeException>(() => session.Run(container));
-            Assert.Equal("[ErrorCode:InvalidArgument] Missing required inputs: data_0", ex.Message);
-            session.Dispose(); 
+            Assert.Equal("[ErrorCode:InvalidArgument] Invalid Feed Input Names: wrong_name Valid input names are: data_0 ", ex.Message);
+            session.Dispose();
         }
 
         [Fact]
@@ -179,231 +179,204 @@ private void ThrowExtraInputs()
             container.Add(nov1);
             container.Add(nov2);
             var ex = Assert.Throws<OnnxRuntimeException>(() => session.Run(container));
-            Assert.StartsWith("[ErrorCode:InvalidArgument] Invalid Feed Input Names: extra. Valid input names are: ", ex.Message);
+            Assert.Equal("[ErrorCode:InvalidArgument] The number of feeds is not same as the number of the model input, expect 1 got 2", ex.Message);
             session.Dispose();
         }
 
+        [Fact] 
+        private void TestModelInputFloat()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_FLOAT.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var nov = NamedOnnxValue.CreateFromTensor("input", 
+                new DenseTensor<float>(new float[] {1.0f, 2.0f, -3.0f, float.MinValue, float.MaxValue }, 
+                new int[] { 1, 5 }) );
+            container.Add(nov);
+            var res = session.Run(container);  
+        }
+
+        [Fact(Skip = "Boolean tensor not supported yet")]
+        private void TestModelInputBOOL()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_BOOL.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<bool>(new bool[] { true, false, true, false, true }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<bool>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+        [Fact]
+
+        private void TestModelInputINT32()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_INT32.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<int>(new int[] { 1, -2, -3, int.MinValue, int.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<int>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+
         [Fact]
-        private void Yunsong()
+        private void TestModelInputDOUBLE()
         {
-            var session = new InferenceSession(@"model_181031_12.onnx");
-
-            float[] zerof = new float[] { 0 };
-            long[] zerol = new long[] { 1 };
-            var data = new List<NamedOnnxValue>() {
-                 NamedOnnxValue.CreateFromTensor<float>("input_0_0", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_0_1", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_1_0", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_1_1", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_1_2", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_1_3", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_1_4", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_2_0", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_2_1", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_2_2", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_2_3", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_2_4", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_2_5", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_3_0", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_3_1", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_0", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_1", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_2", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_3", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_4", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_5", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_6", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_7", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_8", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_9", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_10", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_11", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_12", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_13", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_14", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_15", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_16", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_17", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_18", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_19", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_20", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_21", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_22", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_23", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_24", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_25", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_26", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_27", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_28", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_29", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_30", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_31", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_32", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_33", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_34", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_35", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_36", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_37", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_38", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_39", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_40", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_41", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_42", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_43", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_44", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_45", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_46", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_47", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_48", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_49", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_50", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_51", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_52", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_53", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_54", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_55", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_56", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_57", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_58", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_59", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_60", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_61", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_62", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_63", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_64", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_65", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_66", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_67", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_68", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_69", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_70", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_71", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_72", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_73", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_74", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_75", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_76", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_77", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_78", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_79", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_80", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_81", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_82", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_83", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_84", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_85", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_86", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_87", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_88", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_89", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_90", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_91", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_92", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_93", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_94", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_95", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_96", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_97", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_98", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_99", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_100", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_101", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_102", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_103", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_104", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_105", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_106", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_107", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_108", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_109", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_110", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_111", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_112", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_113", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_114", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_115", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_116", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_117", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_118", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_119", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_120", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_121", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_122", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_123", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_124", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_125", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_126", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_127", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_128", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_129", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_130", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_131", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_132", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_133", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_134", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_135", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_136", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_137", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_138", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_139", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_140", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_141", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_142", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_143", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_144", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_145", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_146", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<float>("input_4_147", new DenseTensor<float>(zerof, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_0", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_1", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_2", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_3", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_4", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_5", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_6", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_7", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_8", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_9", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_10", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_11", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_12", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_13", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_14", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_15", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_16", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_17", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_18", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_19", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_20", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_21", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_22", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_23", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_24", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_25", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_26", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_27", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_28", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_29", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_30", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_31", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_32", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_33", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_34", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_35", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_36", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 NamedOnnxValue.CreateFromTensor<long>("input_5_37", new DenseTensor<long>(zerol, new int[] { 1 })),
-                 };
-
-            var result = session.Run(data);
-            Assert.NotNull(result);
-            Assert.Equal(1, result.Count);
-            var value = result.First<NamedOnnxValue>();
-            Assert.Equal("label", value.Name);
-            Assert.NotNull(value.AsTensor<long>());
-            Assert.Equal(1, value.AsTensor<long>().Length);
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_DOUBLE.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<double>(new double[] { 1.0, 2.0, -3.0, 5, 5},new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+                //new DenseTensor<double>(new double[] { 1.0, 2.0, -3.0, double.MinValue, double.MaxValue},
+                //new int[] { 1, 5 }));
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<double>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
         }
 
+        [Fact(Skip = "String tensor not supported yet")]
+        private void TestModelInputSTRING()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_STRING.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<string>(new string[] { "a", "c", "d", "z", "f" }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<string>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
 
+        [Fact(Skip = "Int8 not supported yet")]
+        private void TestModelInputINT8()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_INT8.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<sbyte>(new sbyte[] { 1, 2, -3, sbyte.MinValue, sbyte.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<sbyte>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+
+        [Fact]
+        private void TestModelInputUINT8()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_UINT8.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<byte>(new byte[] { 1, 2, 3, byte.MinValue, byte.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<byte>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+
+        [Fact]
+        private void TestModelInputUINT16()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_UINT16.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<UInt16>(new UInt16[] { 1, 2, 3, UInt16.MinValue, UInt16.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<UInt16>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+
+        [Fact]
+        private void TestModelInputINT16()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_INT16.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<Int16>(new Int16[] { 1, 2, 3, Int16.MinValue, Int16.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<Int16>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+
+        [Fact]
+        private void TestModelInputINT64()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_INT64.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<Int64>(new Int64[] { 1, 2, -3, Int64.MinValue, Int64.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<Int64>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+
+        [Fact]
+        private void TestModelInputUINT32()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_UINT32.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<UInt32>(new UInt32[] { 1, 2, 3, UInt32.MinValue, UInt32.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<UInt32>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+        [Fact]
+        private void TestModelInputUINT64()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_UINT64.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<UInt64>(new UInt64[] { 1, 2, 3, UInt64.MinValue, UInt64.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<UInt64>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
+
+        [Fact(Skip = "Boolean FLOAT16 not available in C#")]
+        private void TestModelInputFLOAT16()
+        {
+            // model takes 1x5 input of fixed type, echoes back
+            string modelPath = Directory.GetCurrentDirectory() + @"\test_types_FLOAT16.onnx";
+            var session = new InferenceSession(modelPath);
+            var container = new List<NamedOnnxValue>();
+            var tensorIn = new DenseTensor<float>(new float[] { 1.0f, 2.0f, -3.0f, float.MinValue, float.MaxValue }, new int[] { 1, 5 });
+            var nov = NamedOnnxValue.CreateFromTensor("input", tensorIn);
+            container.Add(nov);
+            var res = session.Run(container);
+            var tensorOut = res.First().AsTensor<float>();
+            Assert.True(tensorOut.SequenceEqual(tensorIn));
+        }
 
         static float[] LoadTensorFromFile(string filename)
         {
@@ -432,6 +405,5 @@ static Tuple<InferenceSession, float[], DenseTensor<float>> OpenSessionSqueezeNe
             var tensor = new DenseTensor<float>(inputData, inputMeta["data_0"].Dimensions);
             return new Tuple<InferenceSession, float[], DenseTensor<float>>(session, inputData, tensor);
         }
-
     }
 }
\ No newline at end of file
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