diff --git a/src/TensorFlowNET.Core/APIs/tf.array.cs b/src/TensorFlowNET.Core/APIs/tf.array.cs
index aca13ed1..4d0a43df 100644
--- a/src/TensorFlowNET.Core/APIs/tf.array.cs
+++ b/src/TensorFlowNET.Core/APIs/tf.array.cs
@@ -128,6 +128,20 @@ namespace Tensorflow
         public Tensor stack(object values, int axis = 0, string name = "stack")
             => array_ops.stack(values, axis, name: name);
 
+        /// <summary>
+        /// Creates a tensor with all elements set to 1.
+        /// </summary>
+        /// <param name="tensor"></param>
+        /// <param name="dtype"></param>
+        /// <param name="name">A name for the operation (optional).</param>
+        /// <param name="optimize">
+        /// if true, attempt to statically determine the shape of 'tensor' and
+        /// encode it as a constant.
+        /// </param>
+        /// <returns>A `Tensor` with all elements set to 1.</returns>
+        public Tensor ones_like(Tensor tensor, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, bool optimize = true)
+            => array_ops.ones_like(tensor, dtype: dtype, name: name, optimize: optimize);
+
         public Tensor one_hot(Tensor indices, int depth,
             Tensor on_value = null,
             Tensor off_value = null,
@@ -191,5 +205,16 @@ namespace Tensorflow
         /// <returns></returns>
         public Tensor[] unstack(Tensor value, int? num = null, int axis = 0, string name = "unstack")
             => array_ops.unstack(value, num: num, axis: axis, name: name);
+
+        /// <summary>
+        /// Creates a tensor with all elements set to zero.
+        /// </summary>
+        /// <param name="tensor"></param>
+        /// <param name="dtype"></param>
+        /// <param name="name"></param>
+        /// <param name="optimize"></param>
+        /// <returns>A `Tensor` with all elements set to zero.</returns>
+        public Tensor zeros_like(Tensor tensor, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, bool optimize = true)
+            => array_ops.zeros_like(tensor, dtype: dtype, name: name, optimize: optimize);
     }
 }
diff --git a/src/TensorFlowNET.Core/APIs/tf.data_flow.cs b/src/TensorFlowNET.Core/APIs/tf.data_flow.cs
new file mode 100644
index 00000000..593596ff
--- /dev/null
+++ b/src/TensorFlowNET.Core/APIs/tf.data_flow.cs
@@ -0,0 +1,33 @@
+/*****************************************************************************
+   Copyright 2018 The TensorFlow.NET Authors. All Rights Reserved.
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
+******************************************************************************/
+
+using System;
+
+namespace Tensorflow
+{
+    public partial class tensorflow
+    {
+        /// <summary>
+        /// Interleave the values from the data tensors into a single tensor.
+        /// </summary>
+        /// <param name="indices"></param>
+        /// <param name="data"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public static Tensor dynamic_stitch(Tensor[] indices, Tensor[] data, string name = null)
+            => gen_data_flow_ops.dynamic_stitch(indices, data, name: name);
+    }
+}
diff --git a/src/TensorFlowNET.Core/APIs/tf.math.cs b/src/TensorFlowNET.Core/APIs/tf.math.cs
index 985e3f73..b89ab310 100644
--- a/src/TensorFlowNET.Core/APIs/tf.math.cs
+++ b/src/TensorFlowNET.Core/APIs/tf.math.cs
@@ -44,6 +44,15 @@ namespace Tensorflow
         public Tensor add<Tx, Ty>(Tx a, Ty b, string name = null) 
             => gen_math_ops.add(a, b, name: name);
 
+        /// <summary>
+        /// Adds all input tensors element-wise.
+        /// </summary>
+        /// <param name="inputs"></param>
+        /// <param name="name"></param>
+        /// <returns>A `Tensor` of same shape and type as the elements of `inputs`.</returns>
+        public Tensor add_n(Tensor[] inputs, string name = null)
+            => math_ops.add_n(inputs, name: name);
+
         /// <summary>
         /// Computes atan of x element-wise.
         /// </summary>
@@ -331,6 +340,16 @@ namespace Tensorflow
         public Tensor negative(Tensor x, string name = null)
             => gen_math_ops.neg(x, name);
 
+        /// <summary>
+        /// Returns the truth value of (x != y) element-wise.
+        /// </summary>
+        /// <param name="x"></param>
+        /// <param name="y"></param>
+        /// <param name="name"></param>
+        /// <returns>A `Tensor` of type bool with the same size as that of x or y.</returns>
+        public Tensor not_equal<Tx, Ty>(Tx x, Ty y, string name = null)
+            => math_ops.not_equal(x, y, name: name);
+
         /// <summary>
         /// Divides x / y elementwise (using Python 2 division operator semantics).
         /// </summary>
@@ -347,9 +366,40 @@ namespace Tensorflow
         public Tensor pow<T1, T2>(T1 x, T2 y) 
             => gen_math_ops.pow(x, y);
 
+        /// <summary>
+        /// Divides `x / y` elementwise, rounding toward the most negative integer.
+        /// </summary>
+        /// <param name="x"></param>
+        /// <param name="y"></param>
+        /// <param name="name"></param>
+        /// <returns>`x / y` rounded down.</returns>
+        public Tensor floordiv(Tensor x, Tensor y, string name = null)
+            => math_ops.floordiv(x, y, name: name);
+
+        /// <summary>
+        /// Divides x / y elementwise (using Python 3 division operator semantics).
+        /// </summary>
+        /// <param name="x"></param>
+        /// <param name="y"></param>
+        /// <param name="name"></param>
+        /// <returns>`x / y` evaluated in floating point.</returns>
+        public static Tensor truediv(Tensor x, Tensor y, string name = null)
+            => math_ops.truediv(x, y, name: name);
+
         public Tensor range(object start, object limit = null, object delta = null, TF_DataType dtype = TF_DataType.DtInvalid, string name = "range")
             => math_ops.range(start, limit: limit, delta: delta, dtype: dtype, name: name);
 
+        /// <summary>
+        /// Computes the "logical and" of elements across dimensions of a tensor.
+        /// </summary>
+        /// <param name="input_tensor"></param>
+        /// <param name="axis"></param>
+        /// <param name="keepdims"></param>
+        /// <param name="name"></param>
+        /// <returns>The reduced tensor.</returns>
+        public Tensor reduce_all(Tensor input_tensor, int[] axis = null, bool keepdims = false, string name = null)
+            => math_ops.reduce_all(input_tensor, axis: axis, keepdims: keepdims, name: name);
+
         /// <summary>
         /// Computes the sum of elements across dimensions of a tensor.
         /// </summary>