From 112247f05f14a707d15111a17b6e72b22627167b Mon Sep 17 00:00:00 2001
From: Oceania2018 <haiping008@gmail.com>
Date: Wed, 5 Jun 2019 06:24:22 -0500
Subject: [PATCH] added tf.concat interface.

---
 src/TensorFlowNET.Core/APIs/tf.array.cs          | 16 ++++++++++++++++
 .../TextProcess/CnnTextClassification.cs         |  9 ++++++++-
 2 files changed, 24 insertions(+), 1 deletion(-)

diff --git a/src/TensorFlowNET.Core/APIs/tf.array.cs b/src/TensorFlowNET.Core/APIs/tf.array.cs
index dd385b4c..cbcfed28 100644
--- a/src/TensorFlowNET.Core/APIs/tf.array.cs
+++ b/src/TensorFlowNET.Core/APIs/tf.array.cs
@@ -1,11 +1,27 @@
 using System;
 using System.Collections.Generic;
+using System.Linq;
 using System.Text;
 
 namespace Tensorflow
 {
     public static partial class tf
     {
+        /// <summary>
+        /// Concatenates tensors along one dimension.
+        /// </summary>
+        /// <param name="values">A list of `Tensor` objects or a single `Tensor`.</param>
+        /// <param name="axis"></param>
+        /// <param name="name"></param>
+        /// <returns>A `Tensor` resulting from concatenation of the input tensors.</returns>
+        public static Tensor concat(IList<Tensor> values, int axis, string name = "concat")
+        {
+            if (values.Count == 1)
+                throw new NotImplementedException("tf.concat length is 1");
+
+            return gen_array_ops.concat_v2(values.ToArray(), axis, name: name);
+        }
+
         /// <summary>
         /// Inserts a dimension of 1 into a tensor's shape.
         /// </summary>
diff --git a/test/TensorFlowNET.Examples/TextProcess/CnnTextClassification.cs b/test/TensorFlowNET.Examples/TextProcess/CnnTextClassification.cs
index 503e74f6..a6d17a1e 100644
--- a/test/TensorFlowNET.Examples/TextProcess/CnnTextClassification.cs
+++ b/test/TensorFlowNET.Examples/TextProcess/CnnTextClassification.cs
@@ -195,7 +195,14 @@ namespace TensorFlowNET.Examples
                 pooled_outputs.Add(pool);
             }
 
-            // var h_pool = tf.concat(pooled_outputs, 3);
+            var h_pool = tf.concat(pooled_outputs, 3);
+            var h_pool_flat = tf.reshape(h_pool, new TensorShape(-1, num_filters * filter_sizes.Rank));
+
+            with(tf.name_scope("dropout"), delegate
+            {
+                // var h_drop = tf.nn.dropout(h_pool_flat, self.keep_prob);
+            });
+
             return graph;
         }