#include "kernels/Less.h"
#include "kernels/TestUtils.h"
+#include "luci_interpreter/TestMemoryManager.h"
namespace luci_interpreter
{
using namespace testing;
-TEST(LessTest, FloatSimple)
+class LessTest : public ::testing::Test
+{
+protected:
+ void SetUp() override { _memory_manager = std::make_unique<TestMemoryManager>(); }
+
+ std::unique_ptr<IMemoryManager> _memory_manager;
+};
+
+TEST_F(LessTest, FloatSimple)
{
std::vector<float> x_data{
0.5, 0.7, 0.9, // Row 1
false, false, true, // Row 2
};
- Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({2, 3}, x_data);
- Tensor y_tensor = makeInputTensor<DataType::FLOAT32>({2, 3}, y_data);
+ Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({2, 3}, x_data, _memory_manager.get());
+ Tensor y_tensor = makeInputTensor<DataType::FLOAT32>({2, 3}, y_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::BOOL);
Less kernel(&x_tensor, &y_tensor, &output_tensor);
kernel.configure();
+ _memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorData<bool>(output_tensor), ::testing::ElementsAreArray(ref_output_data));
EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({2, 3}));
}
-TEST(LessTest, FloatBroardcast)
+TEST_F(LessTest, FloatBroardcast)
{
std::vector<float> x_data{
0.5, 0.7, 0.9, // Row 1
true, true, false, // Row 3
};
- Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({3, 3}, x_data);
- Tensor y_tensor = makeInputTensor<DataType::FLOAT32>({1, 3}, y_data);
+ Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({3, 3}, x_data, _memory_manager.get());
+ Tensor y_tensor = makeInputTensor<DataType::FLOAT32>({1, 3}, y_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::BOOL);
Less kernel(&x_tensor, &y_tensor, &output_tensor);
kernel.configure();
+ _memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorData<bool>(output_tensor), ::testing::ElementsAreArray(ref_output_data));
const float F_MIN = -128.0 / 128.0;
const float F_MAX = 127.0 / 128.0;
-TEST(LessTest, Uint8Quantized)
+TEST_F(LessTest, Uint8Quantized)
{
std::vector<float> x_data{
0.5, 0.6, 0.7, 0.9, // Row 1
};
std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(F_MIN, F_MAX);
- Tensor x_tensor =
- makeInputTensor<DataType::U8>({1, 2, 4, 1}, quant_param.first, quant_param.second, x_data);
- Tensor y_tensor =
- makeInputTensor<DataType::U8>({1, 2, 4, 1}, quant_param.first, quant_param.second, y_data);
+ Tensor x_tensor = makeInputTensor<DataType::U8>(
+ {1, 2, 4, 1}, quant_param.first, quant_param.second, x_data, _memory_manager.get());
+ Tensor y_tensor = makeInputTensor<DataType::U8>(
+ {1, 2, 4, 1}, quant_param.first, quant_param.second, y_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::BOOL);
Less kernel(&x_tensor, &y_tensor, &output_tensor);
kernel.configure();
+ _memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 2, 4, 1}));
EXPECT_THAT(extractTensorData<bool>(output_tensor), ::testing::ElementsAreArray(ref_output_data));
}
-TEST(LessTest, Uint8QuantizedRescale)
+TEST_F(LessTest, Uint8QuantizedRescale)
{
std::vector<float> x_data{
0.5, 0.6, 0.7, 0.9, // Row 1
std::pair<float, int32_t> x_quant_param = quantizationParams<uint8_t>(F_MIN, F_MAX);
std::pair<float, int32_t> y_quant_param = quantizationParams<uint8_t>(F_MIN * 1.2, F_MAX * 1.5);
- Tensor x_tensor =
- makeInputTensor<DataType::U8>({1, 2, 4, 1}, x_quant_param.first, x_quant_param.second, x_data);
- Tensor y_tensor =
- makeInputTensor<DataType::U8>({1, 2, 4, 1}, y_quant_param.first, y_quant_param.second, y_data);
+ Tensor x_tensor = makeInputTensor<DataType::U8>(
+ {1, 2, 4, 1}, x_quant_param.first, x_quant_param.second, x_data, _memory_manager.get());
+ Tensor y_tensor = makeInputTensor<DataType::U8>(
+ {1, 2, 4, 1}, y_quant_param.first, y_quant_param.second, y_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::BOOL);
Less kernel(&x_tensor, &y_tensor, &output_tensor);
kernel.configure();
+ _memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 2, 4, 1}));
EXPECT_THAT(extractTensorData<bool>(output_tensor), ::testing::ElementsAreArray(ref_output_data));
}
-TEST(LessTest, Uint8QuantizedBroadcast)
+TEST_F(LessTest, Uint8QuantizedBroadcast)
{
std::vector<float> x_data{
0.4, -0.8, 0.7, 0.3, // Row 1
};
std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(F_MIN, F_MAX);
- Tensor x_tensor =
- makeInputTensor<DataType::U8>({1, 3, 4, 1}, quant_param.first, quant_param.second, x_data);
- Tensor y_tensor =
- makeInputTensor<DataType::U8>({1, 1, 4, 1}, quant_param.first, quant_param.second, y_data);
+ Tensor x_tensor = makeInputTensor<DataType::U8>(
+ {1, 3, 4, 1}, quant_param.first, quant_param.second, x_data, _memory_manager.get());
+ Tensor y_tensor = makeInputTensor<DataType::U8>(
+ {1, 1, 4, 1}, quant_param.first, quant_param.second, y_data, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::BOOL);
Less kernel(&x_tensor, &y_tensor, &output_tensor);
kernel.configure();
+ _memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 3, 4, 1}));
EXPECT_THAT(extractTensorData<bool>(output_tensor), ::testing::ElementsAreArray(ref_output_data));
}
-TEST(LessTest, Input_Type_Mismatch_NEG)
+TEST_F(LessTest, Input_Type_Mismatch_NEG)
{
- Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1.f});
- Tensor y_tensor = makeInputTensor<DataType::U8>({1}, {1});
+ Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1.f}, _memory_manager.get());
+ Tensor y_tensor = makeInputTensor<DataType::U8>({1}, {1}, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::BOOL);
Less kernel(&x_tensor, &y_tensor, &output_tensor);
EXPECT_ANY_THROW(kernel.configure());
}
-TEST(LessTest, Input_Output_Type_NEG)
+TEST_F(LessTest, Input_Output_Type_NEG)
{
- Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1.f});
- Tensor y_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1.f});
+ Tensor x_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1.f}, _memory_manager.get());
+ Tensor y_tensor = makeInputTensor<DataType::FLOAT32>({1}, {1.f}, _memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
Less kernel(&x_tensor, &y_tensor, &output_tensor);