tf.batch_to_space_nd #396

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

@@ -27,6 +27,18 @@ namespace Tensorflow
         /// </summary>
         public string newaxis = "";
 
+        /// <summary>
+        /// BatchToSpace for N-D tensors of type T.
+        /// </summary>
+        /// <typeparam name="T"></typeparam>
+        /// <param name="input"></param>
+        /// <param name="block_shape"></param>
+        /// <param name="crops"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public Tensor batch_to_space_nd<T>(T input, int[] block_shape, int[,] crops, string name = null)
+            => gen_array_ops.batch_to_space_nd(input, block_shape, crops, name: name);
+
         public Tensor check_numerics(Tensor tensor, string message, string name = null)
             => gen_array_ops.check_numerics(tensor, message, name: name);
 

src/TensorFlowNET.Core/Operations/gen_array_ops.cs

@@ -26,6 +26,13 @@ namespace Tensorflow
         public static OpDefLibrary _op_def_lib = new OpDefLibrary();
         public static Execute _execute = new Execute();
 
+        public static Tensor batch_to_space_nd<T>(T input, int[] block_shape, int[,] crops, string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("BatchToSpaceND", name: name, args: new { input, block_shape, crops });
+
+            return _op.output;
+        }
+        
         public static Tensor check_numerics(Tensor tensor, string message, string name = null)
         {
             var _op = _op_def_lib._apply_op_helper("CheckNumerics", name: name, args: new { tensor, message });

test/TensorFlowNET.UnitTest/TensorTest.cs

@@ -242,5 +242,23 @@ namespace TensorFlowNET.UnitTest
                 Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 0, 0, 0 }, result[2].ToArray<int>()));
             }
         }
+
+        [TestMethod]
+        public void batch_to_space_nd()
+        {
+            var inputs = np.arange(24).reshape(4, 2, 3);
+            var block_shape = new[] { 2, 2 };
+            int[,] crops = { { 0, 0 }, { 0, 0 } };
+            var tensor = tf.batch_to_space_nd(inputs, block_shape, crops);
+
+            using (var sess = tf.Session())
+            {
+                var result = sess.run(tensor);
+                Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 0, 6, 1, 7, 2, 8 }, result[0, 0].ToArray<int>()));
+                Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 12, 18, 13, 19, 14, 20 }, result[0, 1].ToArray<int>()));
+                Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 3, 9, 4, 10, 5, 11 }, result[0, 2].ToArray<int>()));
+                Assert.IsTrue(Enumerable.SequenceEqual(new int[] { 15, 21, 16, 22, 17, 23 }, result[0, 3].ToArray<int>()));
+            }
+        }
     }
 }