diff --git a/test/TensorFlowNET.UnitTest/Basics/RandomTest.cs b/test/TensorFlowNET.UnitTest/Basics/RandomTest.cs
new file mode 100644
index 00000000..ed70fa35
--- /dev/null
+++ b/test/TensorFlowNET.UnitTest/Basics/RandomTest.cs
@@ -0,0 +1,106 @@
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using NumSharp;
+using System;
+using System.Linq;
+using Tensorflow;
+using static Tensorflow.Binding;
+
+namespace TensorFlowNET.UnitTest.Basics
+{
+    [TestClass]
+    public class RandomTest
+    {
+        /// <summary>
+        /// Test the function of setting random seed
+        /// This will help regenerate the same result
+        /// </summary>
+        [TestMethod, Ignore]
+        public void TFRandomSeedTest()
+        {
+            var initValue = np.arange(6).reshape(3, 2);
+            tf.set_random_seed(1234);
+            var a1 = tf.random_uniform(1);
+            var b1 = tf.random_shuffle(tf.constant(initValue));
+
+            // This part we consider to be a refresh
+            tf.set_random_seed(10);
+            tf.random_uniform(1);
+            tf.random_shuffle(tf.constant(initValue));
+
+            tf.set_random_seed(1234);
+            var a2 = tf.random_uniform(1);
+            var b2 = tf.random_shuffle(tf.constant(initValue));
+            Assert.IsTrue(a1.numpy().array_equal(a2.numpy()));
+            Assert.IsTrue(b1.numpy().array_equal(b2.numpy()));
+        }
+        
+        /// <summary>
+        /// compare to Test above, seed is also added in params
+        /// </summary>
+        [TestMethod, Ignore]
+        public void TFRandomSeedTest2()
+        {
+            var initValue = np.arange(6).reshape(3, 2);
+            tf.set_random_seed(1234);
+            var a1 = tf.random_uniform(1, seed:1234);
+            var b1 = tf.random_shuffle(tf.constant(initValue), seed: 1234);
+
+            // This part we consider to be a refresh
+            tf.set_random_seed(10);
+            tf.random_uniform(1);
+            tf.random_shuffle(tf.constant(initValue));
+
+            tf.set_random_seed(1234);
+            var a2 = tf.random_uniform(1);
+            var b2 = tf.random_shuffle(tf.constant(initValue));
+            Assert.IsTrue(a1.numpy().array_equal(a2.numpy()));
+            Assert.IsTrue(b1.numpy().array_equal(b2.numpy()));
+        }
+
+        /// <summary>
+        /// This part we use funcs in tf.random rather than only tf
+        /// </summary>
+        [TestMethod, Ignore]
+        public void TFRandomRaodomSeedTest()
+        {
+            tf.set_random_seed(1234);
+            var a1 = tf.random.normal(1);
+            var b1 = tf.random.truncated_normal(1);
+
+            // This part we consider to be a refresh
+            tf.set_random_seed(10);
+            tf.random.normal(1);
+            tf.random.truncated_normal(1);
+
+            tf.set_random_seed(1234);
+            var a2 = tf.random.normal(1);
+            var b2 = tf.random.truncated_normal(1);
+
+            Assert.IsTrue(a1.numpy().array_equal(a2.numpy()));
+            Assert.IsTrue(b1.numpy().array_equal(b2.numpy()));
+        }
+
+        /// <summary>
+        /// compare to Test above, seed is also added in params
+        /// </summary>
+        [TestMethod, Ignore]
+        public void TFRandomRaodomSeedTest2()
+        {
+            tf.set_random_seed(1234);
+            var a1 = tf.random.normal(1, seed:1234);
+            var b1 = tf.random.truncated_normal(1);
+
+            // This part we consider to be a refresh
+            tf.set_random_seed(10);
+            tf.random.normal(1);
+            tf.random.truncated_normal(1);
+
+            tf.set_random_seed(1234);
+            var a2 = tf.random.normal(1, seed:1234);
+            var b2 = tf.random.truncated_normal(1, seed:1234);
+
+            Assert.IsTrue(a1.numpy().array_equal(a2.numpy()));
+            Assert.IsTrue(b1.numpy().array_equal(b2.numpy()));
+        }
+    }
+}
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