Add FunctionCallOptions.

src/TensorFlowNET.Core/Contexts/Context.cs

@@ -35,6 +35,7 @@ namespace Tensorflow.Contexts
         public string ScopeName { get; set; } = "";
         bool initialized = false;
         ContextSwitchStack context_switches;
+        public FunctionCallOptions FunctionCallOptions { get; }
 
         public SafeContextHandle Handle { get; }
 
@@ -44,6 +45,7 @@ namespace Tensorflow.Contexts
             status.Check(true);
             context_switches = new ContextSwitchStack(defaultExecutionMode == EAGER_MODE, false);
             initialized = true;
+            FunctionCallOptions = new FunctionCallOptions();
         }
 
         /// <summary>

src/TensorFlowNET.Core/Contexts/FunctionCallOptions.cs

@@ -0,0 +1,20 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+using Google.Protobuf;
+using Google.Protobuf.Collections;
+
+namespace Tensorflow.Contexts
+{
+    public class FunctionCallOptions
+    {
+        public string config_proto_serialized()
+        {
+            var config = new ConfigProto
+            {
+                AllowSoftPlacement = true,
+            };
+            return config.ToByteString().ToStringUtf8();
+        }
+    }
+}

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

@@ -371,7 +371,7 @@ namespace Tensorflow.Eager
             switch (type)
             {
                 case TF_AttrType.TF_ATTR_STRING:
-                    c_api.TFE_OpSetAttrString(op, key, value.ToString(), (uint)value.ToString().Length);
+                    c_api.TFE_OpSetAttrString(op, key, value.ToString(), (ulong)value.ToString().Length);
                     break;
                 case TF_AttrType.TF_ATTR_TYPE:
                     c_api.TFE_OpSetAttrType(op, key, (TF_DataType)value);

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

@@ -241,7 +241,7 @@ namespace Tensorflow
         /// <param name="value">const void*</param>
         /// <param name="length">size_t</param>
         [DllImport(TensorFlowLibName)]
-        public static extern void TFE_OpSetAttrString(SafeOpHandle op, string attr_name, string value, uint length);
+        public static extern void TFE_OpSetAttrString(SafeOpHandle op, string attr_name, string value, ulong length);
 
         [DllImport(TensorFlowLibName)]
         public static extern void TFE_OpSetAttrTypeList(SafeOpHandle op, string attr_name, TF_DataType[] values, int num_values);

src/TensorFlowNET.Core/Functions/ConcreteFunction.cs

@@ -14,6 +14,7 @@ namespace Tensorflow.Functions
     {
         IntPtr _handle;
         FuncGraph func_graph;
+        public Tensor[] CapturedInputs => func_graph.external_captures();
 
         public string Name
         {
@@ -38,6 +39,8 @@ namespace Tensorflow.Functions
         public ConcreteFunction(FuncGraph graph, Dictionary<string, string> attrs)
         {
             func_graph = graph;
+
+            ToGraph(graph.Inputs, graph.Outputs);
         }
 
         public ConcreteFunction(Func<Tensor, Tensor> func, TF_DataType dtype)
@@ -124,6 +127,21 @@ namespace Tensorflow.Functions
             return flat_outputs;
         }
 
+        public Tensor[] CallFlat(Tensor[] args, Tensor[] captured_inputs)
+        {
+            var new_args = new List<Tensor>();
+            new_args.AddRange(args);
+            new_args.AddRange(captured_inputs);
+            args = new_args.ToArray();
+
+            var attrs = new object[] 
+            {
+                "executor_type", "", 
+                "config_proto", tf.Context.FunctionCallOptions.config_proto_serialized()
+            };
+            return tf.Runner.Execute(tf.Context, func_graph.FuncName, 1, args, attrs);
+        }
+
         ForwardBackwardCall SelectForwardAndBackwardFunctions(Tensors args, int possible_gradient_type, bool executing_eagerly)
         {
             var functions = new FirstOrderTapeGradientFunctions(func_graph, false);

src/TensorFlowNET.Core/Functions/TapeGradientFunctions.cs

@@ -48,7 +48,7 @@ namespace Tensorflow.Functions
                 getBackwardFunction: () => backward_function);
         }
 
-        (BackwardFunction, Tensors) _wrap_backward_function(FuncGraph forward_graph, ConcreteFunction backward, Tensors flat_outputs)
+        (BackwardFunction, Tensors) _wrap_backward_function(FuncGraph forward_graph, ConcreteFunction backward, Tensors outputs)
         {
             BackwardFunction _backward_function_wrapper = (output_grads, unneeded_gradients) =>
             {
@@ -61,10 +61,11 @@ namespace Tensorflow.Functions
                     processed_args.add(arg);
                     input_index += 1;
                 }
-                return output_grads;// backward.Invoke(processed_args.ToArray());
+
+                return backward.CallFlat(processed_args.ToArray(), outputs);
             };
 
-            return (_backward_function_wrapper, flat_outputs);
+            return (_backward_function_wrapper, outputs);
         }
 
         protected (EagerDefinedFunction, FuncGraph, ConcreteFunction, List<int>, int) 
@@ -82,7 +83,7 @@ namespace Tensorflow.Functions
             }
 
             var gradients_wrt_outputs = new List<Tensor>();
-            var backwards_graph = new FuncGraph($"{_BACKWARD_PREFIX}{_func_graph.FuncName}_{ops.uid()}");
+            var backwards_graph = new FuncGraph($"{_BACKWARD_PREFIX}_{ops.uid()}");
             foreach (var output in trainable_outputs)
                 gradients_wrt_outputs.Add(tf.placeholder(output.dtype, output.shape));
             var gradients_wrt_inputs = gradients_util._GradientsHelper(trainable_outputs.ToArray(),
@@ -90,16 +91,15 @@ namespace Tensorflow.Functions
                 grad_ys: gradients_wrt_outputs.ToArray(),
                 src_graph: _func_graph);
 
-            tf.Context.restore_mode();
-
-            var forward_function_name = $"{_FORWARD_PREFIX}{_func_graph.FuncName}_{ops.uid()}";
+            var forward_function_name = $"{_FORWARD_PREFIX}_{ops.uid()}";
             var backward_function_attr = new Dictionary<string, string>();
             backward_function_attr[FORWARD_FUNCTION_ATTRIBUTE_NAME] = forward_function_name;
+            gradients_wrt_outputs.append(backwards_graph.internal_captures());
             backwards_graph.Inputs = gradients_wrt_outputs;
             backwards_graph.Outputs = gradients_wrt_inputs;
 
             var backward_function = new ConcreteFunction(backwards_graph, backward_function_attr);
-
+            
             var forward_function_attr = new Dictionary<string, string>();
             forward_function_attr[BACKWARD_FUNCTION_ATTRIBUTE_NAME] = backward_function.Name;
             var forward_function = new EagerDefinedFunction(forward_function_name, _func_graph, 

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

@@ -49,14 +49,14 @@ namespace Tensorflow
                         RegisterGradientFunction(m.GetCustomAttribute<RegisterGradient>().Name,
                             (oper, out_grads) =>
                             {
-                                tf.Logger.Debug($"Caculate Gradient: {m.Name}");
+                                tf.Logger.Debug($"Caculate Gradient: {oper.name} {m.Name}");
                                 var results = g.InvokeMember(m.Name,
                                    BindingFlags.InvokeMethod,
                                    null,
                                    null,
                                    args: new object[] { oper, out_grads }) as Tensor[];
                                 foreach (var result in results.Where(x => x != null))
-                                    tf.Logger.Debug($"{result.TensorShape}");
+                                    tf.Logger.Debug($"Gradient: {result.name} {result.TensorShape}");
                                 return results;
                             }
                         );

src/TensorFlowNET.Core/Graphs/FuncGraph.cs

@@ -26,7 +26,9 @@ namespace Tensorflow.Graphs
         public Tensors Outputs { get; set; }
         public Dictionary<string, string> Attrs { get; set; }
 
-        Dictionary<long, (Tensor, Tensor)> _captures = new Dictionary<long, (Tensor, Tensor)>();
+        // new Dictionary<long, (Tensor, Tensor)> _captures = new Dictionary<long, (Tensor, Tensor)>();
+        // public new Tensor[] external_captures => _captures.Values.Select(x => x.Item1).ToArray();
+
         /// <summary>
         /// Construct a new FuncGraph.
         /// </summary>
@@ -129,7 +131,7 @@ namespace Tensorflow.Graphs
         Tensor _capture_helper(Tensor tensor, string name, TensorShape shape = null)
         {
             Tensor placeholder = null;
-            if (!_captures.ContainsKey(tensor.Id))
+            if (!_captures.Contains(tensor.Id))
             {
                 placeholder = _create_substitute_placeholder(tensor,
                     name: name,
@@ -139,7 +141,7 @@ namespace Tensorflow.Graphs
             }
             else
             {
-                placeholder = _captures[tensor.Id].Item1;
+                placeholder = (((Tensor, Tensor))_captures[tensor.Id]).Item2;
             }
 
             BackwardFunction _backward_function_wrapper = (output_grads, unneeded_gradients) =>

src/TensorFlowNET.Core/Graphs/Graph.cs

@@ -557,16 +557,16 @@ namespace Tensorflow
 
         public Tensor[] external_captures()
         {
-            Tensor[] captures = new Tensor[this._captures.Count];
-            ICollection inner = this._captures.Keys; // c[0]
+            Tensor[] captures = new Tensor[_captures.Count];
+            ICollection inner = _captures.Keys; // c[0]
             inner.CopyTo(captures, 0);
             return captures;
         }
 
         public Tensor[] internal_captures()
         {
-            Tensor[] captures = new Tensor[this._captures.Count];
-            ICollection inner = this._captures.Values; // c[1]
+            Tensor[] captures = new Tensor[_captures.Count];
+            ICollection inner = _captures.Values; // c[1]
             inner.CopyTo(captures, 0);
             return captures;
         }

src/TensorFlowNET.Keras/Engine/Functional.cs

@@ -340,7 +340,7 @@ namespace Tensorflow.Keras.Engine
                     tf.Logger.Debug($"{depth}: {node.Layer}: {node.Layer.Name}");
                     var outputs = node.Layer.Apply(layer_inputs, is_training: training);
                     foreach (var output in outputs.Where(x => x != null))
-                        tf.Logger.Debug($"{output.TensorShape}");
+                        tf.Logger.Debug($"{depth}: {node.Layer}: {node.Layer.Name} {output.TensorShape}");
                     // Update tensor_dict for next input
                     foreach (var (x_id, y) in zip(node.FlatOutputIds, outputs))
                         tensor_dict[x_id] = new Queue<Tensor>(Enumerable.Range(0, tensor_usage_count[x_id]).Select(x => y));