add Tensor.Operator +

docs/source/FrontCover.md

@@ -1,5 +1,5 @@
-# The Definitive Guide to Tensorflow.NET
-# Tensorflow.NET 权威指南
+# The Definitive Guide to TensorFlow.NET
+# TensorFlow.NET 权威指南
 
 
 

docs/source/Preface.md

@@ -14,9 +14,9 @@
 
 
 
-Why do I start the Tensorflow.NET project?
+Why do I start the TensorFlow.NET project?
 
-我为什么会写Tensorflow.NET?
+我为什么会写TensorFlow.NET?
 
 再过几天就是2018年圣诞节，看着孩子一天天长大并懂事，感慨时间过得太快。IT技术更新换代比以往任何时候都更快，各种前后端技术纷纷涌现。大数据，人工智能和区块链，容器技术和微服务，分布式计算和无服务器技术，让人眼花缭乱。Amazon AI服务接口宣称不需要具有任何机器学习经验的工程师就能使用，让像我这样刚静下心来学习了两年并打算将来转行做AI架构的想法泼了一桶凉水。
 

src/TensorFlowNET.Core/APIs/tf.constant.cs

@@ -9,12 +9,7 @@ namespace Tensorflow
     {
         public static Tensor constant(NDArray nd, string name = "Const", bool verify_shape = false)
         {
-            var t = constant_op.Create(nd, name, verify_shape);
-            /*var graph = tf.get_default_graph();
-            var tensor = new Tensor(nd);
-            var op = graph.NewOperation("Const", name, tensor);*/
-            
-            return t;
+            return constant_op.Create(nd, name, verify_shape);
         }
     }
 }

src/TensorFlowNET.Core/Operations/OpDefLibrary.cs

@@ -59,7 +59,7 @@ namespace Tensorflow
 
                 if (!String.IsNullOrEmpty(input_arg.TypeAttr))
                 {
-                    attrs[input_arg.TypeAttr] = DataType.DtFloat;
+                    attrs[input_arg.TypeAttr] = (keywords[input_name] as Tensor).dtype;
                 }
 
                 if (input_arg.IsRef)
@@ -92,7 +92,7 @@ namespace Tensorflow
                 switch (attr_def.Type)
                 {
                     case "type":
-                        attr_value.Type = _MakeType(value, attr_def);
+                        attr_value.Type = _MakeType((TF_DataType)value, attr_def);
                         break;
                     case "shape":
                         attr_value.Shape = new TensorShapeProto();
@@ -127,9 +127,9 @@ namespace Tensorflow
             return op;
         }
 
-        public DataType _MakeType(Object v, AttrDef attr_def)
+        public DataType _MakeType(TF_DataType v, AttrDef attr_def)
         {
-            return DataType.DtFloat;
+            return v.as_datatype_enum();
         }
     }
 }

src/TensorFlowNET.Core/Operations/gen_array_ops.cs

@@ -37,7 +37,6 @@ namespace Tensorflow
 
         private static OpDefLibrary _InitOpDefLibrary()
         {
-            // c_api.TF_GraphGetOpDef(g.Handle, op_type_name, buffer.Handle, status.Handle);
             var bytes = File.ReadAllBytes("Operations/op_list_proto_array.bin");
             var op_list = OpList.Parser.ParseFrom(bytes);
             var op_def_lib = new OpDefLibrary();

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -17,9 +17,7 @@ namespace Tensorflow
 
             var _op = _op_def_lib._apply_op_helper("Add", name: "add", keywords: keywords);
 
-            var tensor = new Tensor(_op, 0, TF_DataType.TF_FLOAT);
-
-            return tensor;
+            return new Tensor(_op, 0, _op.OutputType(0));
         }
 
         private static OpDefLibrary _InitOpDefLibrary()

src/TensorFlowNET.Core/Operations/ops.cs

@@ -28,14 +28,20 @@ namespace Tensorflow
             var op_desc = graph.NewOperation(node_def.Op, node_def.Name);
 
             // Add inputs
-            if(inputs != null && inputs.Count > 0)
+            if(inputs != null)
             {
-                /*foreach (var op_input in inputs)
+                foreach (var op_input in inputs)
                 {
-                    c_api.TF_AddInput(op_desc, op_input._as_tf_output());
-                }*/
-
-                c_api.TF_AddInputList(op_desc, inputs.Select(x => x._as_tf_output()).ToArray(), inputs.Count);
+                    bool isList = false;
+                    if (!isList)
+                    {
+                        c_api.TF_AddInput(op_desc, op_input._as_tf_output());
+                    }
+                    else
+                    {
+                        c_api.TF_AddInputList(op_desc, inputs.Select(x => x._as_tf_output()).ToArray(), inputs.Count);
+                    }
+                }
             }
 
             var status = new Status();

src/TensorFlowNET.Core/Sessions/BaseSession.cs

@@ -131,6 +131,9 @@ namespace Tensorflow
                     case TF_DataType.TF_FLOAT:
                         result[i] = *(float*)c_api.TF_TensorData(output_values[i]);
                         break;
+                    case TF_DataType.TF_INT32:
+                        result[i] = *(int*)c_api.TF_TensorData(output_values[i]);
+                        break;
                     default:
                         throw new NotImplementedException("can't get output");
                         break;

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -18,6 +18,7 @@
 Docs: https://tensorflownet.readthedocs.io</Description>
     <AssemblyVersion>0.0.2.0</AssemblyVersion>
     <PackageReleaseNotes></PackageReleaseNotes>
+    <LangVersion>7.2</LangVersion>
   </PropertyGroup>
 
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">

src/TensorFlowNET.Core/Tensors/Tensor.Operators.cs

@@ -0,0 +1,14 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow
+{
+    public partial class Tensor
+    {
+        public static Tensor operator +(Tensor t1, Tensor t2)
+        {
+            return gen_math_ops.add(t1, t2);
+        }
+    }
+}

src/TensorFlowNET.Core/Tensors/Tensor.cs

@@ -11,7 +11,7 @@ namespace Tensorflow
     /// A tensor is a generalization of vectors and matrices to potentially higher dimensions. 
     /// Internally, TensorFlow represents tensors as n-dimensional arrays of base datatypes.
     /// </summary>
-    public class Tensor : IDisposable
+    public partial class Tensor : IDisposable
     {
         private readonly IntPtr _handle;
 
@@ -22,7 +22,8 @@ namespace Tensorflow
         public object value;
         public int value_index { get; }
 
-        public TF_DataType dtype => _handle == IntPtr.Zero ? TF_DataType.DtInvalid : c_api.TF_TensorType(_handle);
+        private TF_DataType _dtype = TF_DataType.DtInvalid;
+        public TF_DataType dtype => _handle == IntPtr.Zero ? _dtype : c_api.TF_TensorType(_handle);
         public ulong bytesize => _handle == IntPtr.Zero ? 0 : c_api.TF_TensorByteSize(_handle);
         public ulong dataTypeSize => _handle == IntPtr.Zero ? 0 : c_api.TF_DataTypeSize(dtype);
         public ulong size => _handle == IntPtr.Zero ? 0 : bytesize / dataTypeSize;
@@ -118,6 +119,7 @@ namespace Tensorflow
         {
             this.op = op;
             this.value_index = value_index;
+            this._dtype = dtype;
         }
 
         public TF_Output _as_tf_output()

test/TensorFlowNET.Examples/BasicOperations.cs

@@ -0,0 +1,31 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+using Tensorflow;
+
+namespace TensorFlowNET.Examples
+{
+    /// <summary>
+    /// Basic Operations example using TensorFlow library.
+    /// https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1_Introduction/basic_operations.py
+    /// </summary>
+    public class BasicOperations : IExample
+    {
+        public void Run()
+        {
+            // Basic constant operations
+            // The value returned by the constructor represents the output
+            // of the Constant op.
+            var a = tf.constant(2);
+            var b = tf.constant(3);
+
+            // Launch the default graph.
+            using (var sess = tf.Session())
+            {
+                Console.WriteLine("a=2, b=3");
+                Console.WriteLine($"Addition with constants: {sess.run(a + b)}");
+                //Console.WriteLine($"Multiplication with constants: {sess.run(a * b)}");
+            }
+        }
+    }
+}

test/TensorFlowNET.Examples/Program.cs

@@ -11,6 +11,9 @@ namespace TensorFlowNET.Examples
             var assembly = Assembly.GetEntryAssembly();
             foreach(Type type in assembly.GetTypes().Where(x => x.GetInterfaces().Contains(typeof(IExample))))
             {
+                if (args.Length > 0 && !args.Contains(type.Name))
+                    continue;
+                
                 var example = (IExample)Activator.CreateInstance(type);
 
                 try
@@ -22,6 +25,8 @@ namespace TensorFlowNET.Examples
                     Console.WriteLine(ex);
                 }
             }
+
+            Console.ReadLine();
         }
     }
 }