From: Inki Dae <inki.dae@samsung.com>
Date: Fri, 8 May 2020 06:46:40 +0000 (+0900)
Subject: test: use smart pointer instead of raw one
X-Git-Tag: submit/tizen/20200602.011936~21
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=a28e739d81d10e52805adc128358517464d8ab04;p=platform%2Fcore%2Fmultimedia%2Finference-engine-interface.git

test: use smart pointer instead of raw one

Change-Id: I04e4f4e2f887d1850b4e2440a6d2f06a6029b546
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---

diff --git a/test/src/inference_engine_profiler.cpp b/test/src/inference_engine_profiler.cpp
index 58324e5..d46ea1b 100644
--- a/test/src/inference_engine_profiler.cpp
+++ b/test/src/inference_engine_profiler.cpp
@@ -81,7 +81,7 @@ TEST_P(InferenceEngineTfliteTest, Inference)
 		.target_devices = target_devices
 	};
 
-	InferenceEngineCommon *engine = new InferenceEngineCommon();
+	auto engine = std::make_unique<InferenceEngineCommon>();
 	if (engine == nullptr) {
 		ASSERT_TRUE(engine);
 		return;
@@ -89,21 +89,18 @@ TEST_P(InferenceEngineTfliteTest, Inference)
 
 	int ret = engine->EnableProfiler(true);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->DumpProfileToFile("profile_data_" + backend_name + "_tflite_model.txt");
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->BindBackend(&config);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -118,7 +115,6 @@ TEST_P(InferenceEngineTfliteTest, Inference)
 	std::vector <std::string> models;
 	int model_type = GetModelInfo(model_paths, models);
 	if (model_type == -1) {
-		delete engine;
 		ASSERT_NE(model_type, -1);
 		return;
 	}
@@ -140,7 +136,6 @@ TEST_P(InferenceEngineTfliteTest, Inference)
 
 	ret = engine->SetInputLayerProperty(input_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -153,22 +148,19 @@ TEST_P(InferenceEngineTfliteTest, Inference)
 
 	ret = engine->SetOutputLayerProperty(output_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->Load(models, (inference_model_format_e)model_type);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	std::vector<inference_engine_tensor_buffer> inputs, outputs;
-	ret = PrepareTensorBuffers(engine, inputs, outputs);
+	ret = PrepareTensorBuffers(engine.get(), inputs, outputs);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -184,7 +176,7 @@ TEST_P(InferenceEngineTfliteTest, Inference)
 	}
 
 	tensor_t result;
-	FillOutputResult(engine, outputs, result);
+	FillOutputResult(engine.get(), outputs, result);
 
 	switch (test_type) {
 	case TEST_IMAGE_CLASSIFICATION:
@@ -215,8 +207,6 @@ TEST_P(InferenceEngineTfliteTest, Inference)
 
 	engine->UnbindBackend();
 	models.clear();
-
-	delete engine;
 }
 
 TEST_P(InferenceEngineCaffeTest, Inference)
@@ -266,7 +256,7 @@ TEST_P(InferenceEngineCaffeTest, Inference)
 		.target_devices = target_devices
 	};
 
-	InferenceEngineCommon *engine = new InferenceEngineCommon();
+	auto engine = std::make_unique<InferenceEngineCommon>();
 	if (engine == nullptr) {
 		ASSERT_TRUE(engine);
 		return;
@@ -274,21 +264,18 @@ TEST_P(InferenceEngineCaffeTest, Inference)
 
 	int ret = engine->EnableProfiler(true);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->DumpProfileToFile("profile_data_" + backend_name + "_caffe_model.txt");
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->BindBackend(&config);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -303,7 +290,6 @@ TEST_P(InferenceEngineCaffeTest, Inference)
 	std::vector <std::string> models;
 	int model_type = GetModelInfo(model_paths, models);
 	if (model_type == -1) {
-		delete engine;
 		ASSERT_NE(model_type, -1);
 		return;
 	}
@@ -325,7 +311,6 @@ TEST_P(InferenceEngineCaffeTest, Inference)
 
 	ret = engine->SetInputLayerProperty(input_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -338,22 +323,19 @@ TEST_P(InferenceEngineCaffeTest, Inference)
 
 	ret = engine->SetOutputLayerProperty(output_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->Load(models, (inference_model_format_e)model_type);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	std::vector<inference_engine_tensor_buffer> inputs, outputs;
-	ret = PrepareTensorBuffers(engine, inputs, outputs);
+	ret = PrepareTensorBuffers(engine.get(), inputs, outputs);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -369,7 +351,7 @@ TEST_P(InferenceEngineCaffeTest, Inference)
 	}
 
 	tensor_t result;
-	FillOutputResult(engine, outputs, result);
+	FillOutputResult(engine.get(), outputs, result);
 
 	switch (test_type) {
 	case TEST_IMAGE_CLASSIFICATION:
@@ -402,8 +384,6 @@ TEST_P(InferenceEngineCaffeTest, Inference)
 
 	engine->UnbindBackend();
 	models.clear();
-
-	delete engine;
 }
 
 TEST_P(InferenceEngineDldtTest, Inference)
@@ -453,7 +433,7 @@ TEST_P(InferenceEngineDldtTest, Inference)
 		.target_devices = target_devices
 	};
 
-	InferenceEngineCommon *engine = new InferenceEngineCommon();
+	auto engine = std::make_unique<InferenceEngineCommon>();
 	if (engine == nullptr) {
 		ASSERT_TRUE(engine);
 		return;
@@ -461,21 +441,18 @@ TEST_P(InferenceEngineDldtTest, Inference)
 
 	int ret = engine->EnableProfiler(true);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->DumpProfileToFile("profile_data_" + backend_name + "_dldt_model.txt");
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->BindBackend(&config);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -490,7 +467,6 @@ TEST_P(InferenceEngineDldtTest, Inference)
 	std::vector <std::string> models;
 	int model_type = GetModelInfo(model_paths, models);
 	if (model_type == -1) {
-		delete engine;
 		ASSERT_NE(model_type, -1);
 		return;
 	}
@@ -512,7 +488,6 @@ TEST_P(InferenceEngineDldtTest, Inference)
 
 	ret = engine->SetInputLayerProperty(input_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -525,22 +500,19 @@ TEST_P(InferenceEngineDldtTest, Inference)
 
 	ret = engine->SetOutputLayerProperty(output_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->Load(models, (inference_model_format_e)model_type);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	std::vector<inference_engine_tensor_buffer> inputs, outputs;
-	ret = PrepareTensorBuffers(engine, inputs, outputs);
+	ret = PrepareTensorBuffers(engine.get(), inputs, outputs);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -556,7 +528,7 @@ TEST_P(InferenceEngineDldtTest, Inference)
 	}
 
 	tensor_t result;
-	FillOutputResult(engine, outputs, result);
+	FillOutputResult(engine.get(), outputs, result);
 
 	switch (test_type) {
 	case TEST_IMAGE_CLASSIFICATION:
@@ -589,8 +561,6 @@ TEST_P(InferenceEngineDldtTest, Inference)
 
 	engine->UnbindBackend();
 	models.clear();
-
-	delete engine;
 }
 
 INSTANTIATE_TEST_CASE_P(Prefix, InferenceEngineTfliteTest,
diff --git a/test/src/inference_engine_tc.cpp b/test/src/inference_engine_tc.cpp
index 27c5004..2c1441e 100644
--- a/test/src/inference_engine_tc.cpp
+++ b/test/src/inference_engine_tc.cpp
@@ -50,12 +50,11 @@ TEST_P(InferenceEngineTestCase_G1, Bind_P)
 		.target_devices = target_devices
 	};
 
-	InferenceEngineCommon *engine = new InferenceEngineCommon();
+	auto engine = std::make_unique<InferenceEngineCommon>();
 	ASSERT_TRUE(engine);
 
 	int ret = engine->BindBackend(&config);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -65,8 +64,6 @@ TEST_P(InferenceEngineTestCase_G1, Bind_P)
 	EXPECT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 
 	engine->UnbindBackend();
-
-	delete engine;
 }
 
 TEST_P(InferenceEngineTestCase_G2, Load_P)
@@ -84,12 +81,11 @@ TEST_P(InferenceEngineTestCase_G2, Load_P)
 		.target_devices = target_devices
 	};
 
-	InferenceEngineCommon *engine = new InferenceEngineCommon();
+	auto engine = std::make_unique<InferenceEngineCommon>();
 	ASSERT_TRUE(engine);
 
 	int ret = engine->BindBackend(&config);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -104,7 +100,6 @@ TEST_P(InferenceEngineTestCase_G2, Load_P)
 	std::vector <std::string> models;
 	int model_type = GetModelInfo(model_paths, models);
 	if (model_type == -1) {
-		delete engine;
 		ASSERT_NE(model_type, -1);
 		return;
 	}
@@ -113,8 +108,6 @@ TEST_P(InferenceEngineTestCase_G2, Load_P)
 	EXPECT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 
 	engine->UnbindBackend();
-
-	delete engine;
 }
 
 TEST_P(InferenceEngineTestCase_G3, Inference)
@@ -154,7 +147,7 @@ TEST_P(InferenceEngineTestCase_G3, Inference)
 		.target_devices = target_devices
 	};
 
-	InferenceEngineCommon *engine = new InferenceEngineCommon();
+	auto engine = std::make_unique<InferenceEngineCommon>();
 	if (engine == nullptr) {
 		ASSERT_TRUE(engine);
 		return;
@@ -162,7 +155,6 @@ TEST_P(InferenceEngineTestCase_G3, Inference)
 
 	int ret = engine->BindBackend(&config);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -177,7 +169,6 @@ TEST_P(InferenceEngineTestCase_G3, Inference)
 	std::vector <std::string> models;
 	int model_type = GetModelInfo(model_paths, models);
 	if (model_type == -1) {
-		delete engine;
 		ASSERT_NE(model_type, -1);
 		return;
 	}
@@ -199,7 +190,6 @@ TEST_P(InferenceEngineTestCase_G3, Inference)
 
 	ret = engine->SetInputLayerProperty(input_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -212,22 +202,19 @@ TEST_P(InferenceEngineTestCase_G3, Inference)
 
 	ret = engine->SetOutputLayerProperty(output_property);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	ret = engine->Load(models, (inference_model_format_e)model_type);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
 
 	std::vector<inference_engine_tensor_buffer> inputs, outputs;
-	ret = PrepareTensorBuffers(engine, inputs, outputs);
+	ret = PrepareTensorBuffers(engine.get(), inputs, outputs);
 	if (ret != INFERENCE_ENGINE_ERROR_NONE) {
-		delete engine;
 		ASSERT_EQ(ret, INFERENCE_ENGINE_ERROR_NONE);
 		return;
 	}
@@ -243,7 +230,7 @@ TEST_P(InferenceEngineTestCase_G3, Inference)
 	}
 
 	tensor_t result;
-	FillOutputResult(engine, outputs, result);
+	FillOutputResult(engine.get(), outputs, result);
 
 	ret = VerifyImageClassificationResults(result, answers[0]);
 	EXPECT_EQ(ret, 1);
@@ -252,8 +239,6 @@ TEST_P(InferenceEngineTestCase_G3, Inference)
 
 	engine->UnbindBackend();
 	models.clear();
-
-	delete engine;
 }
 
 INSTANTIATE_TEST_CASE_P(Prefix, InferenceEngineTestCase_G1,