diff --git a/src/TensorFlowNET.Core/APIs/tf.math.cs b/src/TensorFlowNET.Core/APIs/tf.math.cs
index f18ece8c..d3b24373 100644
--- a/src/TensorFlowNET.Core/APIs/tf.math.cs
+++ b/src/TensorFlowNET.Core/APIs/tf.math.cs
@@ -57,6 +57,12 @@ namespace Tensorflow
         public static Tensor arg_min(Tensor input, int dimension, TF_DataType output_type = TF_DataType.TF_INT64, string name = null)
             => gen_math_ops.arg_min(input, dimension, output_type: output_type, name: name);
 
+        public static Tensor is_finite(Tensor input, string name = null)
+            => gen_math_ops.is_finite(input, name);
+
+        public static Tensor is_nan(Tensor input, string name = null)
+            => gen_math_ops.is_nan(input, name);
+
         /// <summary>
         /// Returns element-wise smallest integer not less than x.
         /// </summary>
diff --git a/src/TensorFlowNET.Core/Operations/gen_math_ops.cs b/src/TensorFlowNET.Core/Operations/gen_math_ops.cs
index 0999ad59..7ab6f858 100644
--- a/src/TensorFlowNET.Core/Operations/gen_math_ops.cs
+++ b/src/TensorFlowNET.Core/Operations/gen_math_ops.cs
@@ -376,6 +376,13 @@ namespace Tensorflow
             return _op.outputs[0];
         }
 
+        public static Tensor is_nan(Tensor x, string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("IsNan", name: name, args: new { x });
+
+            return _op.outputs[0];
+        }
+
         /// <summary>
         /// Computes exponential of x element-wise.  \\(y = e^x\\).
         /// </summary>
diff --git a/test/TensorFlowNET.UnitTest/OperationsTest.cs b/test/TensorFlowNET.UnitTest/OperationsTest.cs
index 0359e4c3..7f099fde 100644
--- a/test/TensorFlowNET.UnitTest/OperationsTest.cs
+++ b/test/TensorFlowNET.UnitTest/OperationsTest.cs
@@ -61,6 +61,34 @@ namespace TensorFlowNET.UnitTest
             }
         }
 
+        [TestMethod]
+        public void isFinite()
+        {
+            var a = tf.constant(new[] { 1, np.nan, 2, np.nan, 3, np.nan, 4, np.nan });
+            var b = tf.cast(tf.is_finite(a), tf.float32);
+            var check = np.array(1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f);
+
+            using (var sess = tf.Session())
+            {
+                var o = sess.run(b);
+                Assert.IsTrue(o.array_equal(check));
+            }
+        }
+
+        [TestMethod]
+        public void isNan()
+        {
+            var a = tf.constant(new[] { 1, np.nan, 2, np.nan, 3, np.nan, 4, np.nan });
+            var b = tf.cast(tf.is_nan(a), tf.float32);
+            var check = np.array(0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f);
+
+            using (var sess = tf.Session())
+            {
+                var o = sess.run(b);
+                Assert.IsTrue(o.array_equal(check));
+            }
+        }
+
         [TestMethod]
         public void addOpTests()
         {