Imported Upstream version 1.18.0

[platform/core/ml/nnfw.git] / compiler / luci-interpreter / src / kernels / LogSoftmax.test.cpp

diff --git a/compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp b/compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp
index 8a90c1d..50dcd5c 100644 (file)
--- a/compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp
+++ b/compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp
@@ -17,6 +17,7 @@
 
 #include "kernels/LogSoftmax.h"
 #include "kernels/TestUtils.h"
+#include "luci_interpreter/TestMemoryManager.h"
 
 namespace luci_interpreter
 {
@@ -27,18 +28,28 @@ namespace
 
 using namespace testing;
 
-TEST(LogSoftmaxTest, Float)
+class LogSoftmaxTest : public ::testing::Test
+{
+protected:
+  void SetUp() override { _memory_manager = std::make_unique<TestMemoryManager>(); }
+
+  std::unique_ptr<IMemoryManager> _memory_manager;
+};
+
+TEST_F(LogSoftmaxTest, Float)
 {
   Shape input_shape{2, 4};
   std::vector<float> input_data{
     0, -6, 2,  4, //
     3, -2, 10, 1, //
   };
-  Tensor input_tensor = makeInputTensor<DataType::FLOAT32>(input_shape, input_data);
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
   Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
 
   LogSoftmax kernel(&input_tensor, &output_tensor);
   kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
   kernel.execute();
 
   std::vector<float> ref_output_data{
@@ -48,7 +59,7 @@ TEST(LogSoftmaxTest, Float)
   EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
 }
 
-TEST(LogSoftmaxTest, Uint8)
+TEST_F(LogSoftmaxTest, Uint8)
 {
   float kMin = -10;
   float kMax = 10;
@@ -58,12 +69,13 @@ TEST(LogSoftmaxTest, Uint8)
     0, -6, 2,  4, //
     3, -2, 10, 1, //
   };
-  Tensor input_tensor =
-    makeInputTensor<DataType::U8>({2, 4}, quant_param.first, quant_param.second, input_data);
+  Tensor input_tensor = makeInputTensor<DataType::U8>({2, 4}, quant_param.first, quant_param.second,
+                                                      input_data, _memory_manager.get());
   Tensor output_tensor = makeOutputTensor(DataType::U8, 16. / 256, 255);
 
   LogSoftmax kernel(&input_tensor, &output_tensor);
   kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
   kernel.execute();
 
   std::vector<float> ref_output_data{
@@ -78,28 +90,29 @@ TEST(LogSoftmaxTest, Uint8)
               ::testing::ElementsAreArray({189, 93, 221, 253, 142, 63, 255, 111}));
 }
 
-TEST(LogSoftmaxTest, InvalidInputOutputType_NEG)
+TEST_F(LogSoftmaxTest, InvalidInputOutputType_NEG)
 {
   std::vector<float> input_data{
     0, -6, 2,  4, //
     3, -2, 10, 1, //
   };
-  Tensor input_tensor = makeInputTensor<DataType::FLOAT32>({2, 4}, input_data);
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>({2, 4}, input_data, _memory_manager.get());
   Tensor output_tensor = makeOutputTensor(DataType::U8, 16. / 256, 255);
 
   LogSoftmax kernel(&input_tensor, &output_tensor);
   EXPECT_ANY_THROW(kernel.configure());
 }
 
-TEST(LogSoftmaxTest, InvalidOutputQuantParam_NEG)
+TEST_F(LogSoftmaxTest, InvalidOutputQuantParam_NEG)
 {
   std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(-10, 10);
   std::vector<float> input_data{
     0, -6, 2,  4, //
     3, -2, 10, 1, //
   };
-  Tensor input_tensor =
-    makeInputTensor<DataType::U8>({2, 4}, quant_param.first, quant_param.second, input_data);
+  Tensor input_tensor = makeInputTensor<DataType::U8>({2, 4}, quant_param.first, quant_param.second,
+                                                      input_data, _memory_manager.get());
   Tensor output_tensor = makeOutputTensor(DataType::U8, 20. / 256, 255);
 
   LogSoftmax kernel(&input_tensor, &output_tensor);