1 files changed, 97 insertions, 0 deletions
diff --git a/onert-micro/luci-interpreter/src/kernels/InstanceNorm.test.cpp b/onert-micro/luci-interpreter/src/kernels/InstanceNorm.test.cpp
new file mode 100644
index 000000000..04400c3c0
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+++ b/onert-micro/luci-interpreter/src/kernels/InstanceNorm.test.cpp
@@ -0,0 +1,97 @@
+/*
+ * 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/InstanceNorm.h"
+#include "kernels/TestUtils.h"
+#include "luci_interpreter/TestMemoryManager.h"
+
+namespace luci_interpreter
+{
+namespace kernels
+{
+namespace
+{
+
+using namespace testing;
+
+class InstanceNormTest : public ::testing::Test
+{
+protected:
+  void SetUp() override { _memory_manager = std::make_unique<TestMemoryManager>(); }
+
+  std::unique_ptr<IMemoryManager> _memory_manager;
+};
+
+TEST_F(InstanceNormTest, Simple)
+{
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>({1, 2, 2, 1}, {1, 1, 1, 1}, _memory_manager.get());
+  Tensor gamma_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1}, _memory_manager.get());
+  Tensor beta_tensor = makeInputTensor<DataType::FLOAT32>({1}, {2}, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  InstanceNormParams params{};
+  params.epsilon = 0.1f;
+  params.activation = Activation::NONE;
+
+  InstanceNorm kernel(&input_tensor, &gamma_tensor, &beta_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear({2, 2, 2, 2}));
+  EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 2, 2, 1}));
+}
+
+TEST_F(InstanceNormTest, Single_gamma_beta)
+{
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>({1, 2, 1, 2}, {1, 1, 1, 1}, _memory_manager.get());
+  Tensor gamma_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1}, _memory_manager.get());
+  Tensor beta_tensor = makeInputTensor<DataType::FLOAT32>({1}, {2}, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  InstanceNormParams params{};
+  params.epsilon = 0.1f;
+  params.activation = Activation::NONE;
+
+  InstanceNorm kernel(&input_tensor, &gamma_tensor, &beta_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear({2, 2, 2, 2}));
+  EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 2, 1, 2}));
+}
+
+TEST_F(InstanceNormTest, Wrong_gamma_beta_dim_NEG)
+{
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>({1, 2, 1, 2}, {1, 1, 1, 1}, _memory_manager.get());
+  Tensor gamma_tensor = makeInputTensor<DataType::FLOAT32>({3}, {1, 1, 1}, _memory_manager.get());
+  Tensor beta_tensor = makeInputTensor<DataType::FLOAT32>({3}, {2, 2, 2}, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  InstanceNormParams params{};
+  params.epsilon = 0.1f;
+  params.activation = Activation::NONE;
+
+  InstanceNorm kernel(&input_tensor, &gamma_tensor, &beta_tensor, &output_tensor, params);
+  EXPECT_ANY_THROW(kernel.configure());
+}
+
+} // namespace
+} // namespace kernels
+} // namespace luci_interpreter