1 files changed, 125 insertions, 0 deletions
diff --git a/compiler/nnc/unittests/soft_backend/CPPHeaderTypes.cpp b/compiler/nnc/unittests/soft_backend/CPPHeaderTypes.cpp
new file mode 100644
index 000000000..3b071510b
--- /dev/null
+++ b/compiler/nnc/unittests/soft_backend/CPPHeaderTypes.cpp
@@ -0,0 +1,125 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. 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.
+ */
+
+#include <cstddef>
+#include <initializer_list>
+#include <functional>
+#include <numeric>
+
+#include "code_snippets/cpp_header_types.def"
+
+#include "gtest/gtest.h"
+
+template <class List> static inline void checkListShapeEq(List list, Shape shape, index_t volume)
+{
+  ASSERT_EQ(static_cast<size_t>(shape.getDims()), list.size());
+  index_t idx = 0;
+  for (auto el : list)
+  {
+    ASSERT_EQ(shape[idx], el);
+    idx++;
+  }
+  ASSERT_EQ(shape.getNumElems(), volume);
+}
+
+TEST(SOFT_BACKEND, shape_and_index)
+{
+  auto list = {2, 3, 4};
+  index_t volume = std::accumulate(list.begin(), list.end(), 1, std::multiplies<index_t>());
+  Shape s1(list);
+  checkListShapeEq(list, s1, volume);
+// This check must be performed only if assertions are enabled
+#ifndef NDEBUG
+  ASSERT_DEATH(s1[list.size()], "");
+#endif
+
+  Shape s2(s1);
+  checkListShapeEq(list, s2, volume);
+
+  Shape s3{1};
+  ASSERT_EQ(s3.getNumElems(), 1);
+  ASSERT_EQ(s3.getDims(), 1);
+  s3 = s1;
+  checkListShapeEq(list, s3, volume);
+
+  s3.setDims(4);
+  s3[3] = 2;
+  ASSERT_EQ(s3.getNumElems(), volume * 2);
+  s3.setDims(3);
+  ASSERT_EQ(s3.getNumElems(), volume);
+}
+
+TEST(SOFT_BACKEND, tensor)
+{
+  // test reshape
+  Tensor t1;
+  ASSERT_EQ(t1.getShape().getNumElems(), 1);
+  const index_t tensor1_height = 2;
+  const index_t tensor1_width = 4;
+  t1.reshape(Shape{tensor1_height, tensor1_width});
+  ASSERT_EQ(t1.getShape().getNumElems(), tensor1_height * tensor1_width);
+  // test at functions
+  float expected_sum = 0;
+  for (index_t i = 0; i < tensor1_height; ++i)
+    for (index_t j = 0; j < tensor1_width; ++j)
+    {
+      index_t elem = (i + 1) * (j + 1);
+      expected_sum += elem;
+      t1.at({i, j}) = elem;
+    }
+  float sum = 0;
+  for (index_t i = 0; i < tensor1_height; ++i)
+    for (index_t j = 0; j < tensor1_width; ++j)
+    {
+      sum += t1.at({i, j});
+    }
+  ASSERT_EQ(sum, expected_sum);
+
+  // test construction with shape
+  const index_t tensor2_height = 3;
+  const index_t tensor2_width = 4;
+  Tensor t2({tensor2_height, tensor2_width});
+  ASSERT_EQ(t2.getShape().getNumElems(), tensor2_height * tensor2_width);
+
+  // test unmanaged tensor
+  const index_t tensor3_depth = 2;
+  const index_t tensor3_height = 2;
+  const index_t tensor3_width = 3;
+  std::vector<float> data({1.0, 2.0, 4.0});
+  data.resize(tensor3_depth * tensor3_height * tensor3_width);
+  float *data_ptr = data.data();
+  Tensor t3(Shape({tensor3_depth, tensor3_height, tensor3_width}), data_ptr);
+  ASSERT_EQ(t3.getShape().getNumElems(), tensor3_depth * tensor3_height * tensor3_width);
+  sum = 0;
+  for (index_t k = 0; k < tensor3_depth; ++k)
+    for (index_t i = 0; i < tensor3_height; ++i)
+      for (index_t j = 0; j < tensor3_width; ++j)
+      {
+        sum += t3.at({k, i, j});
+      }
+  ASSERT_EQ(sum, std::accumulate(data_ptr, data_ptr + t3.getShape().getNumElems(), 0.0f));
+
+  // test tensor copy
+  const index_t t4Width = 4;
+  Tensor t4({t4Width});
+  t4 = t3;
+  for (index_t k = 0; k < tensor3_depth; ++k)
+    for (index_t i = 0; i < tensor3_height; ++i)
+      for (index_t j = 0; j < tensor3_height; ++j)
+      {
+        ASSERT_EQ(t3.at({k, i, j}), t4.at({k, i, j}));
+      }
+}