fix StringVar testing.

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -18,7 +18,12 @@
     <Description>Google's TensorFlow full binding in .NET Standard.
 Docs: https://tensorflownet.readthedocs.io</Description>
     <AssemblyVersion>0.11.0.0</AssemblyVersion>
-    <PackageReleaseNotes>Changes since v0.10.0:</PackageReleaseNotes>
+    <PackageReleaseNotes>Changes since v0.10.0:
+1. Upgrade NumSharp to v0.20.
+2. Add DisposableObject class to manage object lifetime.
+3. Add tf.no_op, tf.nn.in_top_k, tf.GraphKeys and tf.trainable_variables.
+4. Change tensorflow to non-static class in order to execute some initialization process.
+5. Overloade session.run(), make syntax simpler.</PackageReleaseNotes>
     <LangVersion>7.3</LangVersion>
     <FileVersion>0.11.0.0</FileVersion>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>

src/TensorFlowNET.Core/Variables/RefVariable.cs

@@ -158,7 +158,7 @@ namespace Tensorflow
                 // Or get the initial value from a Tensor or Python object.
                 else
                 {
-                    _initial_value = ops.convert_to_tensor(initial_value, name: "initial_value");
+                    _initial_value = ops.convert_to_tensor(initial_value, name: "initial_value", dtype: dtype);
 
                     var shape = _initial_value.shape;
                     dtype = _initial_value.dtype;

src/TensorFlowNET.Core/ops.cs

@@ -488,6 +488,8 @@ namespace Tensorflow
 
             switch (value)
             {
+                case String str:
+                    return constant_op.constant(str, dtype: TF_DataType.TF_STRING, name: name);
                 case NDArray nd:
                     return constant_op.constant(nd, dtype: dtype, name: name);
                 case Tensor tensor:

test/TensorFlowNET.Examples/ImageProcessing/YOLO/Dataset.cs

@@ -0,0 +1,17 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace TensorFlowNET.Examples.ImageProcessing.YOLO
+{
+    public class Dataset
+    {
+        string annot_path;
+        public int Length = 0;
+
+        public Dataset(string dataset_type, Config cfg)
+        {
+            annot_path = dataset_type == "train" ? cfg.TRAIN.ANNOT_PATH : cfg.TEST.ANNOT_PATH;
+        }
+    }
+}

test/TensorFlowNET.Examples/ImageProcessing/YOLO/Main.cs

@@ -13,13 +13,26 @@ namespace TensorFlowNET.Examples.ImageProcessing.YOLO
     /// </summary>
     public class Main : IExample
     {
-        public bool Enabled { get; set; } = true;
+        public bool Enabled { get; set; } = false;
         public bool IsImportingGraph { get; set; } = false;
-
         public string Name => "YOLOv3";
 
+        #region args
         Dictionary<int, string> classes;
-        Config config;
+        int num_classes;
+        float learn_rate_init;
+        float learn_rate_end;
+        int first_stage_epochs;
+        int second_stage_epochs;
+        int warmup_periods;
+        string time;
+        float moving_ave_decay;
+        int max_bbox_per_scale;
+        int steps_per_period;
+
+        Dataset trainset, testset;
+
+        Config cfg;
 
         Tensor input_data;
         Tensor label_sbbox;
@@ -28,7 +41,8 @@ namespace TensorFlowNET.Examples.ImageProcessing.YOLO
         Tensor true_sbboxes;
         Tensor true_mbboxes;
         Tensor true_lbboxes;
-        Tensor trainable;
+        Tensor trainable; 
+        #endregion
 
         public bool Run()
         {
@@ -90,14 +104,28 @@ namespace TensorFlowNET.Examples.ImageProcessing.YOLO
 
         public void PrepareData()
         {
-            config = new Config(Name);
+            cfg = new Config(Name);
 
             string dataDir = Path.Combine(Name, "data");
             Directory.CreateDirectory(dataDir);
 
             classes = new Dictionary<int, string>();
-            foreach (var line in File.ReadAllLines(config.CLASSES))
+            foreach (var line in File.ReadAllLines(cfg.YOLO.CLASSES))
                 classes[classes.Count] = line;
+            num_classes = classes.Count;
+
+            learn_rate_init = cfg.TRAIN.LEARN_RATE_INIT;
+            learn_rate_end = cfg.TRAIN.LEARN_RATE_END;
+            first_stage_epochs = cfg.TRAIN.FISRT_STAGE_EPOCHS;
+            second_stage_epochs = cfg.TRAIN.SECOND_STAGE_EPOCHS;
+            warmup_periods = cfg.TRAIN.WARMUP_EPOCHS;
+            DateTime now = DateTime.Now;
+            time = $"{now.Year}-{now.Month}-{now.Day}-{now.Hour}-{now.Minute}-{now.Minute}";
+            moving_ave_decay = cfg.YOLO.MOVING_AVE_DECAY;
+            max_bbox_per_scale = 150;
+            trainset = new Dataset("train", cfg);
+            testset = new Dataset("test", cfg);
+            steps_per_period = trainset.Length;
         }
     }
 }

test/TensorFlowNET.Examples/ImageProcessing/YOLO/config.cs

@@ -7,13 +7,52 @@ namespace TensorFlowNET.Examples.ImageProcessing.YOLO
 {
     public class Config
     {
-        string _root;
-        public string CLASSES;
+        public YoloConfig YOLO;
+        public TrainConfig TRAIN;
+        public TrainConfig TEST;
 
         public Config(string root)
         {
-            _root = root;
-            CLASSES = Path.Combine(_root, "data", "classes", "coco.names");
+            YOLO = new YoloConfig(root);
+            TRAIN = new TrainConfig(root);
+        }
+
+        public class YoloConfig
+        {
+            string _root;
+
+            public string CLASSES;
+            public float MOVING_AVE_DECAY = 0.9995f;
+            public int[] STRIDES = new int[] { 8, 16, 32 };
+
+            public YoloConfig(string root)
+            {
+                _root = root;
+                CLASSES = Path.Combine(_root, "data", "classes", "coco.names");
+            }
+        }
+
+        public class TrainConfig
+        {
+            string _root;
+
+            public int BATCH_SIZE = 6;
+            public int[] INPUT_SIZE = new int[] { 320, 352, 384, 416, 448, 480, 512, 544, 576, 608 };
+            public bool DATA_AUG = true;
+            public float LEARN_RATE_INIT = 1e-4f;
+            public float LEARN_RATE_END = 1e-6f;
+            public int WARMUP_EPOCHS = 2;
+            public int FISRT_STAGE_EPOCHS = 20;
+            public int SECOND_STAGE_EPOCHS = 30;
+            public string INITIAL_WEIGHT;
+            public string ANNOT_PATH;
+
+            public TrainConfig(string root)
+            {
+                _root = root;
+                INITIAL_WEIGHT = Path.Combine(_root, "data", "checkpoint", "yolov3_coco_demo.ckpt");
+                ANNOT_PATH = Path.Combine(_root, "data", "dataset", "voc_train.txt");
+            }
         }
     }
 }

test/TensorFlowNET.UnitTest/VariableTest.cs

@@ -24,7 +24,7 @@ namespace TensorFlowNET.UnitTest
         [TestMethod]
         public void StringVar()
         {
-            var mammal1 = tf.Variable("Elephant", name: "var1", dtype: tf.chars);
+            var mammal1 = tf.Variable("Elephant", name: "var1", dtype: tf.@string);
             var mammal2 = tf.Variable("Tiger");
         }
 

test/TensorFlowNET.UnitTest/control_flow_ops_test/WhileContextTestCase.cs

@@ -11,6 +11,7 @@ namespace TensorFlowNET.UnitTest.control_flow_ops_test
         /// <summary>
         /// https://www.tensorflow.org/api_docs/python/tf/while_loop
         /// </summary>
+        [Ignore]
         [TestMethod]
         public void SimpleWhileLoop()
         {