1 files changed, 90 insertions, 0 deletions
diff --git a/onert-micro/luci-interpreter/src/kernels/Rsqrt.test.cpp b/onert-micro/luci-interpreter/src/kernels/Rsqrt.test.cpp
new file mode 100644
index 000000000..3c6494232
--- /dev/null
+++ b/onert-micro/luci-interpreter/src/kernels/Rsqrt.test.cpp
@@ -0,0 +1,90 @@
+/*
+ * Copyright (c) 2020 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 "kernels/Rsqrt.h"
+#include "kernels/TestUtils.h"
+#include "luci_interpreter/TestMemoryManager.h"
+
+namespace luci_interpreter
+{
+namespace kernels
+{
+namespace
+{
+
+using namespace testing;
+
+void Check(std::initializer_list<int32_t> input_shape, std::initializer_list<int32_t> output_shape,
+           std::initializer_list<float> input_data, std::initializer_list<float> output_data)
+{
+  std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
+
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Rsqrt kernel(&input_tensor, &output_tensor);
+  kernel.configure();
+  memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(output_data));
+  EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape));
+}
+
+TEST(RsqrtTest, SimpleRsqrt)
+{
+  Check(
+    /*input_shape=*/{1, 2, 4, 1}, /*output_shape=*/{1, 2, 4, 1},
+    /*input_data=*/
+    {
+      5, 4, 8, 2,     //
+      6, 7.5, 9, 0.3, //
+    },
+    /*output_data=*/
+    {
+      0.44721360, 0.5, 0.35355339, 0.70710678,       //
+      0.40824829, 0.36514837, 0.33333333, 1.8257419, //
+    });
+}
+
+TEST(RsqrtTest, Input_Output_Type_NEG)
+{
+  std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
+
+  Tensor input_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1.f}, memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::S32);
+
+  Rsqrt kernel(&input_tensor, &output_tensor);
+  EXPECT_ANY_THROW(kernel.configure());
+}
+
+TEST(RsqrtTest, Invalid_Input_Type_NEG)
+{
+  std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
+
+  Tensor input_tensor = makeInputTensor<DataType::S64>({1}, {1}, memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::S64);
+
+  Rsqrt kernel(&input_tensor, &output_tensor);
+  kernel.configure();
+  memory_manager->allocate_memory(output_tensor);
+  EXPECT_ANY_THROW(kernel.execute());
+}
+
+} // namespace
+} // namespace kernels
+} // namespace luci_interpreter