upgrade to tensorflow v1.13-rc1

src/TensorFlowNET.Core/Gradients/gradients_impl.py.cs

@@ -64,6 +64,8 @@ namespace Tensorflow
                 // Get a uid for this call to gradients that can be used to help
                 // cluster ops for compilation.
                 var gradient_uid = ops.get_default_graph().unique_name("uid");
+                ys = ops.convert_n_to_tensor_or_indexed_slices(ys, name: "y");
+                xs = ops.internal_convert_n_to_tensor_or_indexed_slices(xs, name: "x", as_ref: true);
                 grad_ys = _DefaultGradYs(grad_ys, ys, colocate_gradients_with_ops, gradient_uid);
 
                 /** 
@@ -148,7 +150,7 @@ namespace Tensorflow
                     }
                     else
                     {
-                        in_grads = _NonEagerInputs(op, xs).Select(x => new Tensor(IntPtr.Zero)).ToArray();
+                        in_grads = new Tensor[_NonEagerInputs(op, xs).Count()];
                     }
 
                     var inputs = _NonEagerInputs(op, xs).ToList();
@@ -226,6 +228,7 @@ namespace Tensorflow
 
         private static Tensor[] _MaybeCompile(string scope, Operation op, Tensor out_grads, Action func, Func<Operation, Tensor, Tensor[]> grad_fn)
         {
+            scope = scope.EndsWith("/") ? scope.Substring(0, scope.Length - 1) : scope;
             return grad_fn(op, out_grads);
         }
 

src/TensorFlowNET.Core/Gradients/math_grad.py.cs

@@ -72,9 +72,10 @@ namespace Tensorflow
 
         public static bool _ShapesFullySpecifiedAndEqual(Tensor x, Tensor y, Tensor grad)
         {
-            return false;
-            /*return string.Join(",", x.shape).Equals(string.Join(",", y.shape)) &&
-                   string.Join(",", x.shape).Equals(string.Join(",", grad.shape));*/
+            if (x.NDims == 0 && y.NDims == 0 && grad.NDims == 0) return true;
+
+            return string.Join(",", x.shape).Equals(string.Join(",", y.shape)) &&
+                   string.Join(",", x.shape).Equals(string.Join(",", grad.shape));
         }
 
         public static (Tensor, Tensor) _SumGrad(Operation op, Tensor grad)

src/TensorFlowNET.Core/Graphs/Graph.cs

@@ -41,17 +41,20 @@ namespace Tensorflow
             _graph_key = $"grap-key-{ops.uid()}/";
         }
 
-        public T as_graph_element<T>(T obj, bool allow_tensor = true, bool allow_operation = true)
+        public object as_graph_element(object obj, bool allow_tensor = true, bool allow_operation = true)
         {
             return _as_graph_element_locked(obj, allow_tensor, allow_operation);
         }
 
-        private Func<object> _as_graph_element(object obj)
+        private Tensor _as_graph_element(object obj)
         {
+            if (obj is RefVariable var)
+                return var._as_graph_element();
+
             return null;
         }
 
-        private T _as_graph_element_locked<T>(T obj, bool allow_tensor = true, bool allow_operation = true)
+        private object _as_graph_element_locked(object obj, bool allow_tensor = true, bool allow_operation = true)
         {
             string types_str = "";
 
@@ -69,12 +72,14 @@ namespace Tensorflow
             }
 
             var temp_obj = _as_graph_element(obj);
+            if (temp_obj != null)
+                obj = temp_obj;
 
             if (obj is Tensor tensor && allow_tensor)
             {
                 if (tensor.Graph.Equals(this))
                 {
-                    return obj;
+                    return tensor;
                 }
                 else
                 {
@@ -85,7 +90,7 @@ namespace Tensorflow
             {
                 if (op.Graph.Equals(this))
                 {
-                    return obj;
+                    return op;
                 }
                 else
                 {
@@ -93,7 +98,7 @@ namespace Tensorflow
                 }
             }
 
-            throw new Exception($"Can not convert a {typeof(T).Name} into a {types_str}.");
+            throw new Exception($"Can not convert a {obj.GetType().Name} into a {types_str}.");
         }
 
         public void add_to_collection<T>(string name, T value)

src/TensorFlowNET.Core/Sessions/BaseSession.cs

@@ -35,6 +35,11 @@ namespace Tensorflow
             c_api.TF_DeleteSessionOptions(opts);
         }
 
+        public virtual NDArray run(RefVariable fetches, FeedItem[] feed_dict = null)
+        {
+            return _run(fetches, feed_dict);
+        }
+
         public virtual NDArray run(Tensor fetches, FeedItem[] feed_dict = null)
         {
             return _run(fetches, feed_dict);

src/TensorFlowNET.Core/Variables/RefVariable.cs

@@ -109,20 +109,13 @@ namespace Tensorflow
             });
         }
 
-        public Tensor _ref()
-        {
-            return _variable;
-        }
+        public Tensor _ref() => _variable;
 
-        public Tensor value()
-        {
-            return _snapshot;
-        }
+        public Tensor value() => _snapshot;
 
-        public Tensor _AsTensor()
-        {
-            return _snapshot;
-        }
+        public Tensor _AsTensor() => _snapshot;
+
+        public Tensor _as_graph_element() => _variable;
 
         public Tensor _TensorConversionFunction(bool as_ref = false)
         {

src/TensorFlowNET.Core/ops.py.cs

@@ -329,6 +329,11 @@ namespace Tensorflow
             };
         }
 
+        public static Tensor[] convert_n_to_tensor_or_indexed_slices(Tensor[] values, TF_DataType dtype = TF_DataType.DtInvalid, string name = "")
+        {
+            return internal_convert_n_to_tensor_or_indexed_slices(values, dtype: dtype, name: name);
+        }
+
         public static Tensor convert_to_tensor_or_indexed_slices(Tensor value, TF_DataType dtype = TF_DataType.DtInvalid, string name = "")
         {
             return internal_convert_to_tensor_or_indexed_slices(value: value, dtype: dtype, name: name, as_ref: false);
@@ -339,6 +344,26 @@ namespace Tensorflow
             return value;
         }
 
+        public static Tensor[] internal_convert_n_to_tensor_or_indexed_slices(Tensor[] values, TF_DataType dtype = TF_DataType.DtInvalid, string name = "", bool as_ref = false)
+        {
+            var ret = new List<Tensor>();
+
+            foreach(var (i, value) in Python.enumerate(values))
+            {
+                if (value == null)
+                {
+                    ret.Add(value);
+                }
+                else
+                {
+                    var n = string.IsNullOrEmpty(name) ? "" : $"{name}_{i}";
+                    ret.Add(internal_convert_to_tensor_or_indexed_slices(value, dtype: dtype, name: n, as_ref: as_ref));
+                }
+            }
+
+            return ret.ToArray();
+        }
+
         public static Tensor[] internal_convert_n_to_tensor<T>(T[] values, DataType dtype = DataType.DtInvalid, 
             string name = "", DataType preferred_dtype = DataType.DtInvalid, 
             bool as_ref = false)

test/TensorFlowNET.Examples/LinearRegression.cs

@@ -80,9 +80,9 @@ namespace TensorFlowNET.Examples
                             new FeedItem(X, train_X),
                             new FeedItem(Y, train_Y)
                         });
-
+                        var rW = sess.run(W);
                         Console.WriteLine($"Epoch: {epoch + 1} cost={c} " +
-                                    $"W={sess.run(W)} b={sess.run(b)}");
+                                    $"W={rW} b={sess.run(b)}");
                     }
                 }
 

test/TensorFlowNET.UnitTest/GradientTest.cs

@@ -23,8 +23,7 @@ namespace TensorFlowNET.UnitTest
             Assert.AreEqual(ys.op.inputs[0].name, "Const:0");
             Assert.AreEqual(ys.op.inputs[1].name, "mul:0");
 
-            var xs = new Tensor[] { a, b };
-            var g = tf.gradients(ys, xs, stop_gradients: new Tensor[] { a, b });
+            var g = tf.gradients(ys, new Tensor[] { a, b }, stop_gradients: new Tensor[] { a, b });
             Assert.AreEqual(g[0].name, "gradients/Fill:0");
             Assert.AreEqual(g[1].name, "gradients/Fill:0");
         }