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diff --git a/eigen/unsupported/test/cxx11_tensor_scan.cpp b/eigen/unsupported/test/cxx11_tensor_scan.cpp
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+++ b/eigen/unsupported/test/cxx11_tensor_scan.cpp
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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 Igor Babuschkin <igor@babuschk.in>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <limits>
+#include <numeric>
+#include <Eigen/CXX11/Tensor>
+
+using Eigen::Tensor;
+
+template <int DataLayout, typename Type=float, bool Exclusive = false>
+static void test_1d_scan()
+{
+  int size = 50;
+  Tensor<Type, 1, DataLayout> tensor(size);
+  tensor.setRandom();
+  Tensor<Type, 1, DataLayout> result = tensor.cumsum(0, Exclusive);
+
+  VERIFY_IS_EQUAL(tensor.dimension(0), result.dimension(0));
+
+  float accum = 0;
+  for (int i = 0; i < size; i++) {
+    if (Exclusive) {
+      VERIFY_IS_EQUAL(result(i), accum);
+      accum += tensor(i);
+    } else {
+      accum += tensor(i);
+      VERIFY_IS_EQUAL(result(i), accum);
+    }
+  }
+
+  accum = 1;
+  result = tensor.cumprod(0, Exclusive);
+  for (int i = 0; i < size; i++) {
+    if (Exclusive) {
+      VERIFY_IS_EQUAL(result(i), accum);
+      accum *= tensor(i);
+    } else {
+      accum *= tensor(i);
+      VERIFY_IS_EQUAL(result(i), accum);
+    }
+  }
+}
+
+template <int DataLayout, typename Type=float>
+static void test_4d_scan()
+{
+  int size = 5;
+  Tensor<Type, 4, DataLayout> tensor(size, size, size, size);
+  tensor.setRandom();
+
+  Tensor<Type, 4, DataLayout> result(size, size, size, size);
+
+  result = tensor.cumsum(0);
+  float accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(i, 1, 2, 3);
+    VERIFY_IS_EQUAL(result(i, 1, 2, 3), accum);
+  }
+  result = tensor.cumsum(1);
+  accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(1, i, 2, 3);
+    VERIFY_IS_EQUAL(result(1, i, 2, 3), accum);
+  }
+  result = tensor.cumsum(2);
+  accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(1, 2, i, 3);
+    VERIFY_IS_EQUAL(result(1, 2, i, 3), accum);
+  }
+  result = tensor.cumsum(3);
+  accum = 0;
+  for (int i = 0; i < size; i++) {
+    accum += tensor(1, 2, 3, i);
+    VERIFY_IS_EQUAL(result(1, 2, 3, i), accum);
+  }
+}
+
+template <int DataLayout>
+static void test_tensor_maps() {
+  int inputs[20];
+  TensorMap<Tensor<int, 1, DataLayout> > tensor_map(inputs, 20);
+  tensor_map.setRandom();
+
+  Tensor<int, 1, DataLayout> result = tensor_map.cumsum(0);
+
+  int accum = 0;
+  for (int i = 0; i < 20; ++i) {
+    accum += tensor_map(i);
+    VERIFY_IS_EQUAL(result(i), accum);
+  }
+}
+
+void test_cxx11_tensor_scan() {
+  CALL_SUBTEST((test_1d_scan<ColMajor, float, true>()));
+  CALL_SUBTEST((test_1d_scan<ColMajor, float, false>()));
+  CALL_SUBTEST((test_1d_scan<RowMajor, float, true>()));
+  CALL_SUBTEST((test_1d_scan<RowMajor, float, false>()));
+  CALL_SUBTEST(test_4d_scan<ColMajor>());
+  CALL_SUBTEST(test_4d_scan<RowMajor>());
+  CALL_SUBTEST(test_tensor_maps<ColMajor>());
+  CALL_SUBTEST(test_tensor_maps<RowMajor>());
+}