diff --git a/src/TensorFlowNET.Core/Sessions/BaseSession.cs b/src/TensorFlowNET.Core/Sessions/BaseSession.cs
index 587aca5b..22339226 100644
--- a/src/TensorFlowNET.Core/Sessions/BaseSession.cs
+++ b/src/TensorFlowNET.Core/Sessions/BaseSession.cs
@@ -19,7 +19,7 @@ namespace Tensorflow
 
         public BaseSession(string target = "", Graph graph = null)
         {
-            if(graph is null)
+            if (graph is null)
             {
                 _graph = ops.get_default_graph();
             }
@@ -41,9 +41,9 @@ namespace Tensorflow
             return _run(fetches, feed_dict);
         }
 
-        public virtual NDArray run(ITensorOrOperation[] fetches, Hashtable feed_dict = null)
+        public virtual NDArray run(object fetches, Hashtable feed_dict = null)
         {
-            var feed_items = feed_dict == null ? new FeedItem[0] : 
+            var feed_items = feed_dict == null ? new FeedItem[0] :
                 feed_dict.Keys.OfType<object>().Select(key => new FeedItem(key, feed_dict[key])).ToArray();
             return _run(fetches, feed_items);
         }
@@ -98,7 +98,7 @@ namespace Tensorflow
                                 feed_dict_tensor[subfeed_t] = (NDArray)val;
                                 break;
                             case bool val:
-                                feed_dict_tensor[subfeed_t] = (NDArray) val;
+                                feed_dict_tensor[subfeed_t] = (NDArray)val;
                                 break;
                             case bool[] val:
                                 feed_dict_tensor[subfeed_t] = (NDArray)val;
@@ -106,8 +106,8 @@ namespace Tensorflow
                             default:
                                 Console.WriteLine($"can't handle data type of subfeed_val");
                                 throw new NotImplementedException("_run subfeed");
-                        }
-                        
+                        }
+
                         feed_map[subfeed_t.name] = (subfeed_t, subfeed_val);
                     }
                 }
@@ -146,9 +146,9 @@ namespace Tensorflow
         /// </returns>
         private NDArray[] _do_run(List<Operation> target_list, List<Tensor> fetch_list, Dictionary<object, object> feed_dict)
         {
-            var feeds = feed_dict.Select(x => 
+            var feeds = feed_dict.Select(x =>
             {
-                if(x.Key is Tensor tensor)
+                if (x.Key is Tensor tensor)
                 {
                     switch (x.Value)
                     {
diff --git a/src/TensorFlowNET.Core/Sessions/FeedDict.cs b/src/TensorFlowNET.Core/Sessions/FeedDict.cs
new file mode 100644
index 00000000..95e51b06
--- /dev/null
+++ b/src/TensorFlowNET.Core/Sessions/FeedDict.cs
@@ -0,0 +1,11 @@
+using System;
+using System.Collections;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Sessions
+{
+    public class FeedDict : Hashtable
+    {
+    }
+}
diff --git a/test/TensorFlowNET.Examples/TextProcess/TextClassificationTrain.cs b/test/TensorFlowNET.Examples/TextProcess/TextClassificationTrain.cs
index a8eb01c9..73c74e3f 100644
--- a/test/TensorFlowNET.Examples/TextProcess/TextClassificationTrain.cs
+++ b/test/TensorFlowNET.Examples/TextProcess/TextClassificationTrain.cs
@@ -8,6 +8,7 @@ using System.Text;
 using NumSharp;
 using Tensorflow;
 using Tensorflow.Keras.Engine;
+using Tensorflow.Sessions;
 using TensorFlowNET.Examples.Text.cnn_models;
 using TensorFlowNET.Examples.TextClassification;
 using TensorFlowNET.Examples.Utility;
@@ -91,7 +92,7 @@ namespace TensorFlowNET.Examples.CnnTextClassification
             foreach (var (x_batch, y_batch, total) in train_batches)
             {
                 i++;
-                var train_feed_dict = new Hashtable
+                var train_feed_dict = new FeedDict
                 {
                     [model_x] = x_batch,
                     [model_y] = y_batch,
@@ -113,25 +114,26 @@ namespace TensorFlowNET.Examples.CnnTextClassification
 
                 if (step % 100 == 0)
                 {
-                    continue;
                     // # Test accuracy with validation data for each epoch.
                     var valid_batches = batch_iter(valid_x, valid_y, BATCH_SIZE, 1);
-                    var (sum_accuracy, cnt) = (0, 0);
+                    var (sum_accuracy, cnt) = (0.0f, 0);
                     foreach (var (valid_x_batch, valid_y_batch, total_validation_batches) in valid_batches)
                     {
-                        //        valid_feed_dict = {
-                        //            model.x: valid_x_batch,
-                        //            model.y: valid_y_batch,
-                        //            model.is_training: False
-                        //        }
-
-                        //        accuracy = sess.run(model.accuracy, feed_dict = valid_feed_dict)
-                        //        sum_accuracy += accuracy
-                        //        cnt += 1
+                        var valid_feed_dict = new FeedDict
+                        {
+                            [model_x] = valid_x_batch,
+                            [model_y] = valid_y_batch,
+                            [is_training] = false
+                        };
+                        var result1 = sess.run(accuracy, valid_feed_dict);
+                        float accuracy_value = result1;
+                        sum_accuracy += accuracy_value;
+                        cnt += 1;
                     }
-                    //    valid_accuracy = sum_accuracy / cnt
 
-                    //    print("\nValidation Accuracy = {1}\n".format(step // num_batches_per_epoch, sum_accuracy / cnt))
+                    var valid_accuracy = sum_accuracy / cnt;
+
+                    print($"\nValidation Accuracy = {valid_accuracy}\n");
 
                     //    # Save model
                     //        if valid_accuracy > max_accuracy: