basic gradient works and switch to r2.2 native.

TensorFlow.NET.sln

@@ -16,95 +16,51 @@ EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
-		Debug|x64 = Debug|x64
 		Debug-Minimal|Any CPU = Debug-Minimal|Any CPU
-		Debug-Minimal|x64 = Debug-Minimal|x64
 		Publish|Any CPU = Publish|Any CPU
-		Publish|x64 = Publish|x64
 		Release|Any CPU = Release|Any CPU
-		Release|x64 = Release|x64
 	EndGlobalSection
 	GlobalSection(ProjectConfigurationPlatforms) = postSolution
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug|x64.ActiveCfg = Debug|x64
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug|x64.Build.0 = Debug|x64
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug-Minimal|Any CPU.ActiveCfg = Debug|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug-Minimal|Any CPU.Build.0 = Debug|Any CPU
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug-Minimal|x64.ActiveCfg = Debug|Any CPU
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug-Minimal|x64.Build.0 = Debug|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Publish|Any CPU.ActiveCfg = Release|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Publish|Any CPU.Build.0 = Release|Any CPU
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Publish|x64.ActiveCfg = Release|Any CPU
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Publish|x64.Build.0 = Release|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|Any CPU.Build.0 = Release|Any CPU
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|x64.ActiveCfg = Release|Any CPU
-		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|x64.Build.0 = Release|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug|x64.ActiveCfg = Debug|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug|x64.Build.0 = Debug|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug-Minimal|Any CPU.ActiveCfg = Debug|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug-Minimal|Any CPU.Build.0 = Debug|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug-Minimal|x64.ActiveCfg = Debug|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Debug-Minimal|x64.Build.0 = Debug|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Publish|Any CPU.ActiveCfg = Release|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Publish|Any CPU.Build.0 = Release|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Publish|x64.ActiveCfg = Release|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Publish|x64.Build.0 = Release|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Release|Any CPU.Build.0 = Release|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Release|x64.ActiveCfg = Release|Any CPU
-		{3A6EB896-604F-4E25-B677-B8103BCF3D2E}.Release|x64.Build.0 = Release|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug|x64.ActiveCfg = Debug|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug|x64.Build.0 = Debug|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug-Minimal|Any CPU.ActiveCfg = Debug|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug-Minimal|Any CPU.Build.0 = Debug|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug-Minimal|x64.ActiveCfg = Debug|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Debug-Minimal|x64.Build.0 = Debug|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Publish|Any CPU.ActiveCfg = Release|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Publish|Any CPU.Build.0 = Release|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Publish|x64.ActiveCfg = Release|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Publish|x64.Build.0 = Release|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Release|Any CPU.Build.0 = Release|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Release|x64.ActiveCfg = Release|Any CPU
-		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Release|x64.Build.0 = Release|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|x64.ActiveCfg = Debug|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|x64.Build.0 = Debug|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug-Minimal|Any CPU.ActiveCfg = Debug|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug-Minimal|Any CPU.Build.0 = Debug|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug-Minimal|x64.ActiveCfg = Debug|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug-Minimal|x64.Build.0 = Debug|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Publish|Any CPU.ActiveCfg = Release|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Publish|Any CPU.Build.0 = Release|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Publish|x64.ActiveCfg = Release|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Publish|x64.Build.0 = Release|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|Any CPU.Build.0 = Release|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|x64.ActiveCfg = Release|Any CPU
-		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|x64.Build.0 = Release|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|x64.ActiveCfg = Debug|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|x64.Build.0 = Debug|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug-Minimal|Any CPU.ActiveCfg = Debug|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug-Minimal|Any CPU.Build.0 = Debug|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug-Minimal|x64.ActiveCfg = Debug|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug-Minimal|x64.Build.0 = Debug|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Publish|Any CPU.ActiveCfg = Release|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Publish|Any CPU.Build.0 = Release|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Publish|x64.ActiveCfg = Release|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Publish|x64.Build.0 = Release|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|Any CPU.Build.0 = Release|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|x64.ActiveCfg = Release|Any CPU
-		{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|x64.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

src/TensorFlowNET.Core/APIs/c_api.cs

@@ -43,7 +43,7 @@ namespace Tensorflow
     /// </summary>
     public partial class c_api
     {
-        public const string TensorFlowLibName = "tensorflow";
+        public const string TensorFlowLibName = @"D:\SciSharp\tensorflow-google\bazel-bin\tensorflow\tensorflow.dll";
 
         public static string StringPiece(IntPtr handle)
         {

src/TensorFlowNET.Core/Eager/EagerOperation.cs

@@ -0,0 +1,34 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Eager
+{
+    public class EagerOperation : Operation
+    {
+        public int NumInputs;
+        public Tensor[] Inputs { get; set; }
+
+        public EagerOperation() : base(IntPtr.Zero) { }
+
+        public override InputList inputs
+        {
+            get
+            {
+                if (_inputs_val == null)
+                {
+                    var retval = new Tensor[NumInputs];
+
+                    for (int i = 0; i < NumInputs; i++)
+                    {
+
+                    }
+
+                    _inputs_val = new InputList(Inputs);
+                }
+
+                return _inputs_val;
+            }
+        }
+    }
+}

src/TensorFlowNET.Core/Eager/EagerTensor.Implicit.cs

@@ -10,5 +10,8 @@ namespace Tensorflow.Eager
     {
         public static explicit operator TFE_TensorHandle(EagerTensor tensor)
             => tensor.tfe_tensor_handle;
+
+        public static implicit operator IntPtr(EagerTensor tensor)
+            => tensor.EagerTensorHandle;
     }
 }

src/TensorFlowNET.Core/Eager/EagerTensor.cs

@@ -24,31 +24,10 @@ namespace Tensorflow.Eager
             tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
         }
 
-        public EagerTensor(int value, string device_name) : base(value)
-        {
-            tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
-            EagerTensorHandle = c_api.TFE_EagerTensorFromHandle(tf.context, tfe_tensor_handle);
-        }
-
-        public EagerTensor(float value, string device_name) : base(value)
-        {
-            tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
-            EagerTensorHandle = c_api.TFE_EagerTensorFromHandle(tf.context, tfe_tensor_handle);
-        }
-
-        public EagerTensor(float[] value, string device_name) : base(value)
-        {
-            tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
-        }
-
-        public EagerTensor(double[] value, string device_name) : base(value)
-        {
-            tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
-        }
-
         public EagerTensor(NDArray value, string device_name) : base(value)
         {
             tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
+            EagerTensorHandle = c_api.TFE_EagerTensorFromHandle(tf.context, tfe_tensor_handle);
         }
 
         public override string ToString()
@@ -56,23 +35,24 @@ namespace Tensorflow.Eager
             switch (rank)
             {
                 case -1:
-                    return $"tf.Tensor: shape=<unknown>, dtype={dtype.as_numpy_name()}, numpy={GetFormattedString()}";
+                    return $"tf.Tensor: shape=<unknown>, dtype={dtype.as_numpy_name()}, numpy={GetFormattedString(dtype, numpy())}";
                 case 0:
-                    return $"tf.Tensor: shape=(), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString()}";
+                    return $"tf.Tensor: shape=(), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString(dtype, numpy())}";
                 default:
-                    return $"tf.Tensor: shape=({string.Join(",", shape)}), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString()}";
+                    return $"tf.Tensor: shape=({string.Join(",", shape)}), dtype={dtype.as_numpy_name()}, numpy={GetFormattedString(dtype, numpy())}";
             }
         }
 
-        private string GetFormattedString()
+        public static string GetFormattedString(TF_DataType dtype, NDArray nd)
         {
-            var nd = numpy();
             switch (dtype)
             {
                 case TF_DataType.TF_STRING:
                     return $"b'{(string)nd}'";
                 case TF_DataType.TF_BOOL:
                     return (nd.GetByte(0) > 0).ToString();
+                case TF_DataType.TF_RESOURCE:
+                    return "<unprintable>";
                 default:
                     return nd.ToString();
             }

src/TensorFlowNET.Core/Eager/c_api.eager.cs

@@ -11,8 +11,18 @@ namespace Tensorflow
         public static extern void TFE_RegisterGradientFunction(_gradient_function_callback callbackPointer);
 
         [UnmanagedFunctionPointer(CallingConvention.StdCall)]
-        public delegate void _gradient_function_callback(string op_name, int num_inputs, IntPtr attrs, int num_attrs);
+        public delegate IntPtr _gradient_function_callback(string op_name, int num_inputs, IntPtr[] op_inputs, int num_attrs, IntPtr[] output_grads);
 
+        [DllImport(TensorFlowLibName)]
+        public static extern IntPtr VSpace_Handle(VSpace_callback_Ones ones, VSpace_callback_AggregateGrads aggregate_grads);
+        [UnmanagedFunctionPointer(CallingConvention.StdCall)]
+        public delegate IntPtr VSpace_callback_Ones(long[] shape, int dims, TF_DataType dtype);
+        [UnmanagedFunctionPointer(CallingConvention.StdCall)]
+        public delegate IntPtr VSpace_callback_AggregateGrads(IntPtr gradients, int num_grads);
+
+        [DllImport(TensorFlowLibName)]
+        public static extern void TFE_RegisterVSpace(IntPtr vspace);
+        
         /// <summary>
         /// Return a new options object.
         /// </summary>
@@ -330,7 +340,10 @@ namespace Tensorflow
             string name,
             IntPtr[] args,
             int input_size,
+            TFE_FastPathExecute_SetOpAttrs set_op_attrs,
             IntPtr status);
+        [UnmanagedFunctionPointer(CallingConvention.StdCall)]
+        public delegate void TFE_FastPathExecute_SetOpAttrs(IntPtr op);
 
         [DllImport(TensorFlowLibName)]
         public static extern IntPtr TFE_TapeSetNew(bool persistent, bool watch_accessed_variables);
@@ -342,7 +355,8 @@ namespace Tensorflow
         public static extern void TFE_TapeWatch(IntPtr tape, IntPtr tensor);
 
         [DllImport(TensorFlowLibName)]
-        public static extern IntPtr TFE_TapeGradient(IntPtr tape, IntPtr[] target, int target_size, 
+        public static extern IntPtr TFE_TapeGradient(IntPtr tape, 
+            IntPtr[] target, int target_size, 
             IntPtr[] sources, int source_size, 
             IntPtr status);
     }

src/TensorFlowNET.Core/Eager/wrap_tfe_src.TFE_FastPathExecute.cs

@@ -11,6 +11,8 @@ namespace Tensorflow.Eager
     public partial class wrap_tfe_src
     {
         static int kFastPathExecuteInputStartIndex = 0;
+
+        [Obsolete]
         public static EagerTensor TFE_FastPathExecute(Context ctx, 
             string device_name, 
             string opName, 
@@ -203,7 +205,7 @@ namespace Tensorflow.Eager
         /// <param name="attr_value"></param>
         /// <param name="attr_list_sizes"></param>
         /// <param name="status"></param>
-        private static void SetOpAttrWithDefaults(Context ctx, IntPtr op, AttrDef attr, 
+        public static void SetOpAttrWithDefaults(Context ctx, IntPtr op, AttrDef attr, 
             string attr_name, object attr_value,  
             Dictionary<string, long> attr_list_sizes,
             Status status)

src/TensorFlowNET.Core/Gradients/GradientActor.cs

@@ -74,12 +74,12 @@ namespace Tensorflow.Gradients
             }
 
             using var status = new Status();
-            var et = c_api.TFE_TapeGradient(_tape, 
-                new IntPtr[] { (target as EagerTensor).EagerTensorHandle }, 1,
-                new IntPtr[] { (sources as EagerTensor).EagerTensorHandle }, 1,
+            var et = c_api.TFE_TapeGradient(_tape,
+                new [] { (target as EagerTensor).EagerTensorHandle }, 1,
+                new [] { (sources as EagerTensor).EagerTensorHandle }, 1,
                 status);
             status.Check(true);
-            return et;
+            return new EagerTensor(et);
         }
 
         public void Dispose()

src/TensorFlowNET.Core/Gradients/ops.gradient_function_mapping.cs

@@ -24,9 +24,9 @@ namespace Tensorflow
 {
     public partial class ops
     {
-        static Dictionary<string, Func<Operation, Tensor[], Tensor[]>> gradientFunctions = null;
+        public static Dictionary<string, Func<Operation, Tensor[], Tensor[]>> gradientFunctions = null;
 
-        private static void RegisterFromAssembly()
+        public static void RegisterFromAssembly()
         {
             if (gradientFunctions == null)
             {

src/TensorFlowNET.Core/Operations/Operation.Input.cs

@@ -40,9 +40,9 @@ namespace Tensorflow
         public int NumInputs => c_api.TF_OperationNumInputs(_handle);
         private TF_DataType[] _input_types => _inputs_val._inputs.Select(x => x.dtype).ToArray();
 
-        private InputList _inputs_val;
+        protected InputList _inputs_val;
 
-        public InputList inputs
+        public virtual InputList inputs
         {
             get
             {

src/TensorFlowNET.Core/Operations/gen_array_ops.cs

@@ -152,8 +152,14 @@ namespace Tensorflow
         {
             if(tf.context.executing_eagerly())
             {
-                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name, "Pack", name, null, values, "axis", axis);
-                return _result;
+                using var status = new Status();
+                var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name, 
+                    "Pack", name,
+                    values.Select(x => (x as EagerTensor).EagerTensorHandle).ToArray(), 1, 
+                    (op) => wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "axis", axis, null, status),
+                    status);
+                status.Check(true);
+                return new EagerTensor(tensor);
             }
 
             var _op = _op_def_lib._apply_op_helper("Pack", name: name, args: new { values, axis });

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -41,6 +41,18 @@ namespace Tensorflow
         /// <returns></returns>
         public static Tensor add_n(Tensor[] inputs, string name = null)
         {
+            if (tf.context.executing_eagerly())
+            {
+                using var status = new Status();
+                var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "AddN", name,
+                    inputs.Select(x => (x as EagerTensor).EagerTensorHandle).ToArray(), inputs.Length,
+                    null,
+                    status);
+                status.Check(true);
+                return new EagerTensor(_result);
+            }
+
             var _op = _op_def_lib._apply_op_helper("AddN", name, args: new { inputs });
 
             return _op.outputs[0];
@@ -121,10 +133,18 @@ namespace Tensorflow
             {
                 try
                 {
-                    var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name, 
-                        "Mean", name, null, 
-                        input, axis, "keep_dims", keep_dims);
-                    return _result;
+                    using var status = new Status();
+                    var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                        "Mean", name,
+                        new IntPtr[]
+                        {
+                            (input as EagerTensor).EagerTensorHandle,
+                            (axis as EagerTensor).EagerTensorHandle
+                        }, 2,
+                        (op) => wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "keep_dims", keep_dims, null, status),
+                        status);
+                    status.Check(true);
+                    return new EagerTensor(tensor);
                 }
                 catch (Exception)
                 {
@@ -196,17 +216,15 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                using (var status = new Status())
-                {
-                    var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
-                        "Add", name, new IntPtr[] 
-                        {
-                            (x as EagerTensor).EagerTensorHandle,
-                            (y as EagerTensor).EagerTensorHandle
-                        }, 2, status);
-                    status.Check(true);
-                    return new EagerTensor(_result);
-                }
+                using var status = new Status();
+                var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "Add", name, new IntPtr[] 
+                    {
+                        (x as EagerTensor).EagerTensorHandle,
+                        (y as EagerTensor).EagerTensorHandle
+                    }, 2, null, status);
+                status.Check(true);
+                return new EagerTensor(_result);
             }
 
             var _op = _op_def_lib._apply_op_helper("Add", name, args: new { x, y });
@@ -574,10 +592,18 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name, 
-                    "Cast", name, null, 
-                    x, "DstT", DstT, "Truncate", Truncate);
-                return _result;
+                using var status = new Status();
+                var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "Cast", name,
+                    new IntPtr[] { (x as EagerTensor).EagerTensorHandle }, 1,
+                    (op) =>
+                    {
+                        wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "DstT", DstT, null, status);
+                        wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "Truncate", Truncate, null, status);
+                    },
+                    status);
+                status.Check(true);
+                return new EagerTensor(tensor);
             }
 
             var _op = _op_def_lib._apply_op_helper("Cast", name, args: new { x, DstT, Truncate });
@@ -619,17 +645,15 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                using (var status = new Status())
-                {
-                        var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
-                        "Sub", name, new IntPtr[]
-                        {
-                            (x as EagerTensor).EagerTensorHandle,
-                            (y as EagerTensor).EagerTensorHandle
-                        }, 2, status);
-                    status.Check(true);
-                    return new EagerTensor(_result);
-                }
+                using var status = new Status();
+                var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "Sub", name, new IntPtr[]
+                    {
+                        (x as EagerTensor).EagerTensorHandle,
+                        (y as EagerTensor).EagerTensorHandle
+                    }, 2, null, status);
+                status.Check(true);
+                return new EagerTensor(_result);
             }
 
             var _op = _op_def_lib._apply_op_helper("Sub", name, args: new { x, y });
@@ -717,11 +741,11 @@ namespace Tensorflow
             {
                 using var status = new Status();
                 var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
-                "Mul", name, new IntPtr[]
-                {
-                    (x as EagerTensor).EagerTensorHandle,
-                    (y as EagerTensor).EagerTensorHandle
-                }, 2, status);
+                    "Mul", name, new IntPtr[]
+                    {
+                        (x as EagerTensor).EagerTensorHandle,
+                        (y as EagerTensor).EagerTensorHandle
+                    }, 2, null, status);
                 status.Check(true);
                 return new EagerTensor(_result);
             }
@@ -757,17 +781,15 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                using (var status = new Status())
-                {
-                    var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                using var status = new Status();
+                var _result = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
                     "RealDiv", name, new IntPtr[]
                     {
                         (x as EagerTensor).EagerTensorHandle,
                         (y as EagerTensor).EagerTensorHandle
-                    }, 2, status);
-                    status.Check(true);
-                    return new EagerTensor(_result);
-                }
+                    }, 2, null, status);
+                status.Check(true);
+                return new EagerTensor(_result);
             }
 
             var _op = _op_def_lib._apply_op_helper("RealDiv", name, args: new { x, y });
@@ -962,8 +984,16 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name, "Range", name, null, start, limit, delta);
-                return _result;
+                using var status = new Status();
+                var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "Range", name, new IntPtr[]
+                    {
+                        (start as EagerTensor).EagerTensorHandle,
+                        (limit as EagerTensor).EagerTensorHandle,
+                        (delta as EagerTensor).EagerTensorHandle
+                    }, 3, null, status);
+                status.Check(true);
+                return new EagerTensor(tensor);
             }
 
             var _op = _op_def_lib._apply_op_helper("Range", name, new { start, limit, delta });

src/TensorFlowNET.Core/Operations/gen_resource_variable_ops.cs

@@ -14,6 +14,8 @@
    limitations under the License.
 ******************************************************************************/
 
+using System;
+using System.Linq;
 using Tensorflow.Eager;
 using static Tensorflow.Binding;
 
@@ -27,10 +29,16 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
-                    "AssignVariableOp", name, null,
-                    resource, value);
-                return _result;
+                using var status = new Status();
+                var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "AssignVariableOp", name,
+                    new[]
+                    {
+                        (resource as EagerTensor).EagerTensorHandle,
+                        (value as EagerTensor).EagerTensorHandle
+                    }, 2, null, status);
+                status.Check(true);
+                return tensor;
             }
 
             var _op = _op_def_lib._apply_op_helper("AssignVariableOp", name, new { resource, value });
@@ -42,10 +50,13 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
-                    "VarIsInitializedOp", name, null,
-                    resource);
-                return _result;
+                using var status = new Status();
+                var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "VarIsInitializedOp", name, 
+                    new[] { (resource as EagerTensor).EagerTensorHandle }, 
+                    1, null, status);
+                status.Check(true);
+                return new EagerTensor(tensor);
             }
 
             var _op = _op_def_lib._apply_op_helper("VarIsInitializedOp", name, new { resource });
@@ -67,10 +78,17 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
-                    "VarHandleOp", name, null,
-                    "container", container, "shared_name", shared_name, "dtype", dtype, "shape", shape.dims);
-                return _result;
+                using var status = new Status();
+                var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "VarHandleOp", name, null, 0, op =>
+                    {
+                        wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "container", container, null, status);
+                        wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "shared_name", shared_name, null, status);
+                        wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "dtype", dtype, null, status);
+                        wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "shape", shape.dims, null, status);
+                    }, status);
+                status.Check(true);
+                return new EagerTensor(tensor);
             }
 
             var _op = _op_def_lib._apply_op_helper("VarHandleOp", name, new {
@@ -94,10 +112,13 @@ namespace Tensorflow
         {
             if (tf.context.executing_eagerly())
             {
-                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
-                    "ReadVariableOp", name, null,
-                    resource, "dtype", dtype);
-                return _result;
+                using var status = new Status();
+                var tensor = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "ReadVariableOp", name, new IntPtr[] { (resource as EagerTensor).EagerTensorHandle }, 1,
+                    (op) => wrap_tfe_src.SetOpAttrWithDefaults(tf.context, op, null, "dtype", dtype, null, status),
+                    status);
+                status.Check(true);
+                return new EagerTensor(tensor);
             }
 
             var _op = _op_def_lib._apply_op_helper("ReadVariableOp", name, new

src/TensorFlowNET.Core/TensorFlow.Binding.csproj

@@ -31,7 +31,7 @@ https://tensorflownet.readthedocs.io</Description>
     <PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance>
     <SignAssembly>true</SignAssembly>
     <AssemblyOriginatorKeyFile>Open.snk</AssemblyOriginatorKeyFile>
-    <Platforms>AnyCPU;x64</Platforms>
+    <Platforms>AnyCPU</Platforms>
   </PropertyGroup>
 
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
@@ -40,20 +40,10 @@ https://tensorflownet.readthedocs.io</Description>
     <PlatformTarget>x64</PlatformTarget>
   </PropertyGroup>
 
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
-    <AllowUnsafeBlocks>true</AllowUnsafeBlocks>
-    <DefineConstants>TRACE;DEBUG;SERIALIZABLE_</DefineConstants>
-    <PlatformTarget>x64</PlatformTarget>
-  </PropertyGroup>
-
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|AnyCPU'">
     <AllowUnsafeBlocks>true</AllowUnsafeBlocks>
   </PropertyGroup>
 
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
-    <AllowUnsafeBlocks>true</AllowUnsafeBlocks>
-  </PropertyGroup>
-
   <ItemGroup>
     <Compile Remove="Distribute\**" />
     <Compile Remove="Models\**" />

src/TensorFlowNET.Core/Tensors/constant_op.cs

@@ -127,6 +127,8 @@ namespace Tensorflow
                     return new EagerTensor(val, ctx.device_name);
                 case float val:
                     return new EagerTensor(val, ctx.device_name);
+                case float[,] val:
+                    return new EagerTensor(val, ctx.device_name);
                 case double val:
                     return new EagerTensor(val, ctx.device_name);
                 case float[] val:

src/TensorFlowNET.Core/Tensors/dtypes.cs

@@ -202,6 +202,7 @@ namespace Tensorflow
                 TF_DataType.TF_INT32 => "int32",
                 TF_DataType.TF_FLOAT => "float32",
                 TF_DataType.TF_BOOL => "bool",
+                TF_DataType.TF_RESOURCE => "resource",
                 _ => type.ToString()
             };
 

src/TensorFlowNET.Core/Variables/ResourceVariable.cs

@@ -18,6 +18,7 @@ using Google.Protobuf;
 using NumSharp;
 using System;
 using System.Collections.Generic;
+using Tensorflow.Eager;
 using static Tensorflow.Binding;
 
 namespace Tensorflow
@@ -221,5 +222,10 @@ namespace Tensorflow
                 return array_ops.identity(value);
             });
         }
+
+        public override string ToString()
+        {
+            return $"tf.Variable: '{name}' shape={string.Join(",", shape)}, dtype={dtype.as_numpy_name()}, numpy={EagerTensor.GetFormattedString(dtype, numpy())}";
+        }
     }
 }

src/TensorFlowNET.Core/tensorflow.cs

@@ -14,6 +14,9 @@
    limitations under the License.
 ******************************************************************************/
 
+using System;
+using System.Linq;
+using System.Runtime.InteropServices;
 using System.Threading;
 using Tensorflow.Eager;
 
@@ -39,6 +42,45 @@ namespace Tensorflow
         public tensorflow()
         {
             _constructThreadingObjects();
+            InitGradientEnvironment();
+        }
+
+        private unsafe void InitGradientEnvironment()
+        {
+            var vspace = c_api.VSpace_Handle((shape, dims, dtype) =>
+            {
+                var ones = constant_op.constant(1.0f, dtype: dtype) as EagerTensor;
+                return ones.EagerTensorHandle;
+            }, (gradients, num_grads) =>
+            {
+                var input_grads = new EagerTensor[num_grads];
+                for (int i = 0; i < num_grads; i++)
+                    input_grads[i] = new EagerTensor(*((IntPtr*)gradients + i));
+
+                var add_n = gen_math_ops.add_n(input_grads);
+                return (add_n as EagerTensor).EagerTensorHandle;
+            });
+
+            ops.RegisterFromAssembly();
+            c_api.TFE_RegisterGradientFunction((op_name, num_inputs, op_inputs, num_attrs, output_grads) =>
+            {
+                var output_grad_tensors = output_grads.Select(x => new EagerTensor(x)).ToArray();
+
+                var input_tensors = new EagerTensor[num_inputs];
+                for (int i = 0; i < num_inputs; i++)
+                    input_tensors[i] = new EagerTensor(op_inputs[op_inputs.Length == 1 ? 0 : i]);
+
+                var gradients = ops.gradientFunctions[op_name](new EagerOperation
+                {
+                    NumInputs = num_inputs,
+                    Inputs = input_tensors
+                }, output_grad_tensors);
+
+                var ret_tensors = Marshal.AllocHGlobal(sizeof(IntPtr) * num_inputs);
+                Marshal.Copy(gradients.Select(x => (x as EagerTensor).EagerTensorHandle).ToArray(), 0, ret_tensors, 2);
+                // Marshal.FreeHGlobal(ret_tensors);
+                return ret_tensors;
+            });
         }
 
         public ResourceVariable Variable<T>(T data,

test/TensorFlowNET.UnitTest/Eager/GradientEagerTest.cs

@@ -0,0 +1,27 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using Tensorflow;
+using static Tensorflow.Binding;
+
+namespace TensorFlowNET.UnitTest.Gradient
+{
+    [TestClass]
+    public class GradientEagerTest : PythonTest
+    {
+        [TestMethod]
+        public void ConstantSq()
+        {
+            // Calcute the gradient of w * w 
+            // by Automatic Differentiation in Eager mode
+            // in tensorflow.net 2.x that is in development intensively
+            var w = tf.constant(1.5f);
+            using var tape = tf.GradientTape();
+            tape.watch(w);
+            var loss = w * w;
+            var grad = tape.gradient(loss, w);
+            print(grad);
+        }
+    }
+}

test/TensorFlowNET.UnitTest/Tensorflow.UnitTest.csproj

@@ -30,11 +30,10 @@
 
   <ItemGroup>
     <PackageReference Include="FluentAssertions" Version="5.10.3" />
-    <PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.5.0" />
+    <PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.6.1" />
     <PackageReference Include="MSTest.TestAdapter" Version="2.1.1" />
     <PackageReference Include="MSTest.TestFramework" Version="2.1.1" />
     <PackageReference Include="NumSharp.Lite" Version="0.1.7" />
-    <PackageReference Include="SciSharp.TensorFlow.Redist" Version="2.1.0" />
   </ItemGroup>
 
   <ItemGroup>

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

@@ -7,7 +7,7 @@
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.5.0" />
+    <PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.6.1" />
     <PackageReference Include="MSTest.TestAdapter" Version="2.1.1" />
     <PackageReference Include="MSTest.TestFramework" Version="2.1.1" />
     <PackageReference Include="coverlet.collector" Version="1.2.1">