added RandomShuffleQueue and docs updated.

docs/source/Queue.md

@@ -58,6 +58,32 @@ Creates a queue that dequeues elements in a first-in first-out order. A `FIFOQue
 
 A FIFOQueue that supports batching variable-sized tensors by padding. A `PaddingFIFOQueue` may contain components with dynamic shape, while also supporting `dequeue_many`. A `PaddingFIFOQueue` holds a list of up to `capacity` elements. Each element is a fixed-length tuple of tensors whose dtypes are described by `dtypes`, and whose shapes are described by the `shapes` argument.
 
+```chsarp
+[TestMethod]
+public void PaddingFIFOQueue()
+{
+	var numbers = tf.placeholder(tf.int32);
+	var queue = tf.PaddingFIFOQueue(10, tf.int32, new TensorShape(-1));
+	var enqueue = queue.enqueue(numbers);
+	var dequeue_many = queue.dequeue_many(n: 3);
+
+	using(var sess = tf.Session())
+	{
+		sess.run(enqueue, (numbers, new[] { 1 }));
+		sess.run(enqueue, (numbers, new[] { 2, 3 }));
+		sess.run(enqueue, (numbers, new[] { 3, 4, 5 }));
+
+		var result = sess.run(dequeue_many[0]);
+
+		Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 1, 0, 0 }, result[0].ToArray<int>()));
+		Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 2, 3, 0 }, result[1].ToArray<int>()));
+		Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 3, 4, 5 }, result[2].ToArray<int>()));
+	}
+}
+```
+
+
+
 #### PriorityQueue
 
 A queue implementation that dequeues elements in prioritized order. A `PriorityQueue` has bounded capacity; supports multiple concurrent producers and consumers; and provides exactly-once delivery. A `PriorityQueue` holds a list of up to `capacity` elements. Each element is a fixed-length tuple of tensors whose dtypes are described by `types`, and whose shapes are optionally described by the `shapes` argument.
@@ -93,6 +119,28 @@ public void PriorityQueue()
 
 A queue implementation that dequeues elements in a random order. A `RandomShuffleQueue` has bounded capacity; supports multiple concurrent producers and consumers; and provides exactly-once delivery. A `RandomShuffleQueue` holds a list of up to `capacity` elements. Each element is a fixed-length tuple of tensors whose dtypes are described by `dtypes`, and whose shapes are optionally described by the `shapes` argument.
 
+```csharp
+[TestMethod]
+public void RandomShuffleQueue()
+{
+	var queue = tf.RandomShuffleQueue(10, min_after_dequeue: 1, dtype: tf.int32);
+	var init = queue.enqueue_many(new[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 });
+	var x = queue.dequeue();
+
+	string results = "";
+	using (var sess = tf.Session())
+	{
+		init.run();
+
+		foreach(var i in range(9))
+			results += (int)sess.run(x) + ".";
+
+		// output in random order
+		// 1.2.3.4.5.6.7.8.9.
+	}
+}
+```
+
 
 
 Queue methods must run on the same device as the queue. `FIFOQueue` and `RandomShuffleQueue` are important TensorFlow objects for computing tensor asynchronously in a graph. For example, a typical input architecture is to use a `RandomShuffleQueue` to prepare inputs for training a model:

src/TensorFlowNET.Core/APIs/tf.queue.cs

@@ -108,5 +108,20 @@ namespace Tensorflow
                 new[] { shape ?? new TensorShape() },
                 shared_name: shared_name,
                 name: name);
+
+        public RandomShuffleQueue RandomShuffleQueue(int capacity,
+            int min_after_dequeue,
+            TF_DataType dtype,
+            TensorShape shape = null,
+            int? seed = null,
+            string shared_name = null,
+            string name = "random_shuffle_queue")
+            => new RandomShuffleQueue(capacity,
+                min_after_dequeue: min_after_dequeue,
+                new[] { dtype },
+                new[] { shape ?? new TensorShape() },
+                seed: seed,
+                shared_name: shared_name,
+                name: name);
     }
 }

src/TensorFlowNET.Core/Operations/Queues/FIFOQueue.cs

@@ -1,4 +1,20 @@
-using System;
+/*****************************************************************************
+   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;
 using System.Collections.Generic;
 using System.Linq;
 using System.Text;

src/TensorFlowNET.Core/Operations/Queues/PaddingFIFOQueue.cs

@@ -1,4 +1,20 @@
-using System;
+/*****************************************************************************
+   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;
 using System.Collections.Generic;
 using System.Linq;
 using System.Text;

src/TensorFlowNET.Core/Operations/Queues/PriorityQueue.cs

@@ -1,4 +1,20 @@
-using System;
+/*****************************************************************************
+   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;
 using System.Collections.Generic;
 using System.Linq;
 using System.Text;

src/TensorFlowNET.Core/Operations/Queues/QueueBase.cs

@@ -1,4 +1,20 @@
-using System;
+/*****************************************************************************
+   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;
 using System.Collections.Generic;
 using System.Linq;
 using System.Text;

src/TensorFlowNET.Core/Operations/Queues/RandomShuffleQueue.cs

@@ -1,24 +1,53 @@
-using System;
+/*****************************************************************************
+   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;
 using System.Collections.Generic;
 using System.Linq;
 using System.Text;
 
 namespace Tensorflow.Queues
 {
+    /// <summary>
+    /// Create a queue that dequeues elements in a random order.
+    /// </summary>
     public class RandomShuffleQueue : QueueBase
     {
         public RandomShuffleQueue(int capacity,
+            int min_after_dequeue,
             TF_DataType[] dtypes,
             TensorShape[] shapes,
             string[] names = null,
+            int? seed = null,
             string shared_name = null,
-            string name = "randomshuffle_fifo_queue")
+            string name = "random_shuffle_queue")
             : base(dtypes: dtypes, shapes: shapes, names: names)
         {
-            _queue_ref = gen_data_flow_ops.padding_fifo_queue_v2(
+            var(seed1, seed2) = random_seed.get_seed(seed);
+            if (!seed1.HasValue && !seed2.HasValue)
+                (seed1, seed2) = (0, 0);
+
+
+            _queue_ref = gen_data_flow_ops.random_shuffle_queue_v2(
                 component_types: dtypes,
                 shapes: shapes,
                 capacity: capacity,
+                min_after_dequeue: min_after_dequeue,
+                seed: seed1.Value,
+                seed2: seed2.Value,
                 shared_name: shared_name,
                 name: name);
 

src/TensorFlowNET.Core/Operations/gen_data_flow_ops.cs

@@ -93,6 +93,25 @@ namespace Tensorflow
             return _op.output;
         }
 
+        public static Tensor random_shuffle_queue_v2(TF_DataType[] component_types, TensorShape[] shapes,
+            int capacity = -1, int min_after_dequeue = 0, int seed = 0, int seed2 = 0,
+            string container = "", string shared_name = "", string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("RandomShuffleQueueV2", name, new
+            {
+                component_types,
+                shapes,
+                capacity,
+                min_after_dequeue,
+                seed,
+                seed2,
+                container,
+                shared_name
+            });
+
+            return _op.output;
+        }
+
         public static Operation queue_enqueue(Tensor handle, Tensor[] components, int timeout_ms = -1, string name = null)
         {
             var _op = _op_def_lib._apply_op_helper("QueueEnqueue", name, new

test/TensorFlowNET.UnitTest/QueueTest.cs

@@ -92,5 +92,25 @@ namespace TensorFlowNET.UnitTest
                 Assert.AreEqual(result[0].GetInt64(), 4L);
             }
         }
+
+        [TestMethod]
+        public void RandomShuffleQueue()
+        {
+            var queue = tf.RandomShuffleQueue(10, min_after_dequeue: 1, dtype: tf.int32);
+            var init = queue.enqueue_many(new[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 });
+            var x = queue.dequeue();
+
+            string results = "";
+            using (var sess = tf.Session())
+            {
+                init.run();
+
+                foreach(var i in range(9))
+                    results += (int)sess.run(x) + ".";
+
+                // output in random order
+                Assert.IsFalse(results == "1.2.3.4.5.6.7.8.9.");
+            }
+        }
     }
 }