Add tensor scan op

This is the initial implementation a generic scan operation.
Based on this, cumsum and cumprod method have been added to TensorBase.

1 files changed, 98 insertions, 0 deletions

diff --git a/unsupported/test/cxx11_tensor_scan.cpp b/unsupported/test/cxx11_tensor_scan.cpp
new file mode 100644
index 000000000..dbd3023d7
--- /dev/null
+++ b/unsupported/test/cxx11_tensor_scan.cpp
@@ -0,0 +1,98 @@
+// 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>
+static void test_1d_scan()
+{
+    int size = 50;
+    Tensor<Type, 1, DataLayout> tensor(size);
+    tensor.setRandom();
+    Tensor<Type, 1, DataLayout> result = tensor.cumsum(0);
+
+    VERIFY_IS_EQUAL(tensor.dimension(0), result.dimension(0));
+
+    float accum = 0;
+    for (int i = 0; i < size; i++) {
+      accum += tensor(i);
+      VERIFY_IS_EQUAL(result(i), accum);
+    }
+
+    accum = 1;
+    result = tensor.cumprod(0);
+    for (int i = 0; i < size; i++) {
+      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, 0, 0, 0);
+      VERIFY_IS_EQUAL(result(i, 0, 0, 0), accum);
+    }
+    result = tensor.cumsum(1);
+    accum = 0;
+    for (int i = 0; i < size; i++) {
+      accum += tensor(0, i, 0, 0);
+      VERIFY_IS_EQUAL(result(0, i, 0, 0), accum);
+    }
+    result = tensor.cumsum(2);
+    accum = 0;
+    for (int i = 0; i < size; i++) {
+      accum += tensor(0, 0, i, 0);
+      VERIFY_IS_EQUAL(result(0, 0, i, 0), accum);
+    }
+    result = tensor.cumsum(3);
+    accum = 0;
+    for (int i = 0; i < size; i++) {
+      accum += tensor(0, 0, 0, i);
+      VERIFY_IS_EQUAL(result(0, 0, 0, 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>());
+  CALL_SUBTEST(test_1d_scan<RowMajor>());
+  CALL_SUBTEST(test_4d_scan<ColMajor>());
+  CALL_SUBTEST(test_4d_scan<RowMajor>());
+  CALL_SUBTEST(test_tensor_maps<ColMajor>());
+  CALL_SUBTEST(test_tensor_maps<RowMajor>());
+}