eager Tape test

README.md

@@ -9,7 +9,7 @@
 [![Badge](https://img.shields.io/badge/link-996.icu-red.svg)](https://996.icu/#/en_US)
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/javiercp/BinderTF.NET/master?urlpath=lab)
 
-*master branch is based on tensorflow 2.1 now, v0.15-tensorflow1.15 is from tensorflow1.15.*
+*master branch is based on tensorflow 2.2 now, v0.15-tensorflow1.15 is from tensorflow1.15.*
 
 TF.NET is a member project of [SciSharp STACK](https://github.com/SciSharp).
 
@@ -28,7 +28,7 @@ In comparison to other projects, like for instance TensorFlowSharp which only pr
 
 ### How to use
 
-| TensorFlow  | tf 1.13 | tf 1.14 | tf 1.15 | tf 2.0 |
+| TensorFlow  | tf 1.13 | tf 1.14 | tf 1.15 | tf 2.2 |
 | ----------- | ------- | ------- | ------- | ------ |
 | tf.net 0.20 |         |         | x       | x      |
 | tf.net 0.15 |         | x       | x       |        |

src/TensorFlowNET.Core/Eager/EagerTensor.cs

@@ -13,31 +13,37 @@ namespace Tensorflow.Eager
         {
             tfe_tensor_handle = handle;
             _handle = c_api.TFE_TensorHandleResolve(handle, status);
+            _id = ops.uid();
         }
 
         public EagerTensor(string value, string device_name) : base(value)
         {
             tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
+            _id = ops.uid();
         }
 
         public EagerTensor(int value, string device_name) : base(value)
         {
             tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
+            _id = ops.uid();
         }
 
         public EagerTensor(float[] value, string device_name) : base(value)
         {
             tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
+            _id = ops.uid();
         }
 
         public EagerTensor(double[] value, string device_name) : base(value)
         {
             tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
+            _id = ops.uid();
         }
 
         public EagerTensor(NDArray value, string device_name) : base(value)
         {
             tfe_tensor_handle = c_api.TFE_NewTensorHandle(_handle, status);
+            _id = ops.uid();
         }
 
         public override string ToString()

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

@@ -102,14 +102,20 @@ namespace Tensorflow
         public static extern TFE_Op TFE_NewOp(IntPtr ctx, string op_or_function_name, IntPtr status);
 
         /// <summary>
-        /// 
+        /// Resets `op_to_reset` with `op_or_function_name` and `raw_device_name`. This
+        /// is for performance optimization by reusing an exiting unused op rather than
+        /// creating a new op every time. If `raw_device_name` is `NULL` or empty, it
+        /// does not set the device name. If it's not `NULL`, then it attempts to parse
+        /// and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster
+        /// than separately calling it because if the existing op has the same
+        /// `raw_device_name`, it skips parsing and just leave as it is.
         /// </summary>
-        /// <param name="ctx">TFE_Context*</param>
+        /// <param name="op_to_reset">TFE_Op*</param>
         /// <param name="op_or_function_name">const char*</param>
+        /// <param name="raw_device_name">const char*</param>
         /// <param name="status">TF_Status*</param>
-        /// <param name="op_to_reset">TFE_Op*</param>
         [DllImport(TensorFlowLibName)]
-        public static extern void TFE_OpReset(IntPtr ctx, string op_or_function_name, IntPtr status, IntPtr op_to_reset);
+        public static extern void TFE_OpReset(IntPtr op_to_reset, string op_or_function_name, string raw_device_name, IntPtr status);
 
         /// <summary>
         /// 
@@ -304,5 +310,17 @@ namespace Tensorflow
         /// <returns>TFE_Executor*</returns>
         [DllImport(TensorFlowLibName)]
         public static extern TFE_Executor TFE_ContextGetExecutorForThread(IntPtr ctx);
+
+        [DllImport(TensorFlowLibName)]
+        public static extern void TFE_Test();
+
+        [DllImport(TensorFlowLibName)]
+        public static extern IntPtr TFE_TapeSetNew(bool persistent, bool watch_accessed_variables);
+
+        [DllImport(TensorFlowLibName)]
+        public static extern void TFE_TapeWatch(IntPtr tape, IntPtr tensor, int tensor_id);
+
+        [DllImport(TensorFlowLibName)]
+        public static extern void TFE_TapeGradient(IntPtr tape, long[] targetTensorIds, IntPtr[] target, long[] sourcesTensorIds, IntPtr status);
     }
 }

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

@@ -0,0 +1,15 @@
+using System.Collections.Generic;
+using System.Linq;
+using System;
+using static Tensorflow.OpDef.Types;
+
+namespace Tensorflow.Eager
+{
+    /// <summary>
+    /// python\eager\pywrap_tfe_src.cc
+    /// </summary>
+    public partial class wrap_tfe_src
+    {
+
+    }
+}

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

@@ -110,7 +110,7 @@ namespace Tensorflow.Eager
             var maybe_op = ReleaseThreadLocalOp();
             if (maybe_op != IntPtr.Zero)
             {
-                c_api.TFE_OpReset(ctx, op_or_function_name, status, maybe_op);
+                c_api.TFE_OpReset(maybe_op, op_or_function_name, ctx.device_name, status);
             }
             else
             {

src/TensorFlowNET.Core/Gradients/GradientActor.cs

@@ -23,7 +23,6 @@ namespace Tensorflow.Gradients
         bool _watch_accessed_variables;
         bool _created_eagerly;
         Tape _tape;
-        int tape_nesting_id_counter = 0;
 
         public GradientActor(bool persistent = false,
             bool watch_accessed_variables = true)
@@ -41,18 +40,28 @@ namespace Tensorflow.Gradients
                     "re-enter an already-active tape.");
 
             if (_tape == null)
-            {
-                _tape = new Tape();
-                _tape.tape = new GradientTape(_persistent, _watch_accessed_variables);
-                _tape.nesting_id = tape_nesting_id_counter++;
-            }
+                _tape = new Tape(_persistent, _watch_accessed_variables);
+            else
+                throw new NotImplementedException("");
 
             _recording = true;
         }
 
+        /// <summary>
+        /// Marks this tensor to be watched by the given tape.
+        /// </summary>
+        /// <param name="x"></param>
         public void watch(Tensor x)
         {
+            _tape.watch(x);
+        }
 
+        public Tensor gradient(Tensor target, Tensor sources)
+        {
+            c_api.TFE_Test();
+            //using (var status = new Status())
+                //c_api.TFE_TapeGradient(_tape, new long[] { target.Id }, status);
+            return null;
         }
 
         public void Dispose()

src/TensorFlowNET.Core/Gradients/Tape.cs

@@ -4,11 +4,21 @@ using System.Text;
 
 namespace Tensorflow.Gradients
 {
-    public class Tape
+    public class Tape : DisposableObject
     {
         public GradientTape tape { get; set; }
         public int nesting_id { get; set; }
 
+        public Tape(bool persistent, bool watch_accessed_variables)
+        {
+            _handle = c_api.TFE_TapeSetNew(persistent, watch_accessed_variables);
+        }
+
+        public void watch(Tensor x)
+        {
+            c_api.TFE_TapeWatch(_handle, x, x.Id);
+        }
+
         public static bool IsDtypeTrainable(DataType dtype)
         {
             switch (dtype)
@@ -26,5 +36,12 @@ namespace Tensorflow.Gradients
                     return false;
             }
         }
+
+        protected override void DisposeUnmanagedResources(IntPtr handle)
+        {
+        }
+
+        public static implicit operator IntPtr(Tape tape)
+            => tape._handle;
     }
 }

src/TensorFlowNET.Core/Tensors/Tensor.cs

@@ -39,7 +39,7 @@ namespace Tensorflow
         IPackable<Tensor>,
         ICanBeFlattened
     {
-        private readonly int _id;
+        protected int _id;
         private readonly Operation _op;
         private readonly int _value_index;
         private TF_Output? _tf_output;

src/TensorFlowNET.Core/Variables/ResourceVariable.Operators.cs

@@ -30,6 +30,8 @@ namespace Tensorflow
         public static Tensor operator -(ResourceVariable x, double y) => op_helper("sub", x, y);
         public static Tensor operator -(ResourceVariable x, Tensor y) => op_helper("sub", x, y);
 
+        public static Tensor operator *(ResourceVariable x, ResourceVariable y) => gen_math_ops.mul(x, y);
+
         public static Tensor operator <(ResourceVariable x, Tensor y) => gen_math_ops.less(x.value(), y);
 
         public static Tensor operator >(ResourceVariable x, Tensor y) => gen_math_ops.greater(x.value(), y);

tensorflowlib/README.md

@@ -44,7 +44,9 @@ We can't found official prebuild binaries for each platform since tensorflow 2.0
 
 https://www.tensorflow.org/install/source_windows
 
-Download [Bazel 0.29.1](https://github.com/bazelbuild/bazel/releases/tag/0.29.1) to build tensorflow2.x. We build customized binary to export c_api from this [fork](https://github.com/SciSharp/tensorflow).
+Download [Bazel 2.0.0](https://github.com/bazelbuild/bazel/releases/tag/2.0.0) to build tensorflow2.x. We build customized binary to export c_api from this [fork](https://github.com/SciSharp/tensorflow).
+
+Set ENV `BAZEL_VC=C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC`.
 
 `pacman -S git patch unzip`
 

test/TensorFlowNET.UnitTest/Tensorflow.UnitTest.csproj

@@ -29,7 +29,7 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="FluentAssertions" Version="5.10.2" />
+    <PackageReference Include="FluentAssertions" Version="5.10.3" />
     <PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.5.0" />
     <PackageReference Include="MSTest.TestAdapter" Version="2.1.0" />
     <PackageReference Include="MSTest.TestFramework" Version="2.1.0" />