::testing::Values(beta),
::testing::Values(bias),
::testing::Values(size),
- ::testing::Values(std::vector<size_t>({1})),
+ ::testing::Values(std::vector<int64_t>({1})),
::testing::ValuesIn(netPrecisions),
::testing::Values(std::vector<size_t>({10, 10, 3, 2})),
::testing::Values(CommonTestUtils::DEVICE_CPU)),
::testing::Values(beta),
::testing::Values(bias),
::testing::Values(size),
- ::testing::Values(std::vector<size_t>({1})),
+ ::testing::Values(std::vector<int64_t>({1})),
::testing::ValuesIn(netPrecisions),
::testing::Values(std::vector<size_t>({10, 10, 3, 2})),
::testing::Values(CommonTestUtils::DEVICE_GPU)),
double, // Beta
double, // Bias
size_t, // Size
- std::vector<size_t>, // Reduction axes
+ std::vector<int64_t>, // Reduction axes
InferenceEngine::Precision, // Network precision
InferenceEngine::SizeVector, // Input shapes
std::string // Device name
std::string LrnLayerTest::getTestCaseName(testing::TestParamInfo<lrnLayerTestParamsSet> obj) {
double alpha, beta, bias;
size_t size;
- std::vector<size_t> axes;
+ std::vector<int64_t> axes;
InferenceEngine::Precision netPrecision;
std::vector<size_t> inputShapes;
std::string targetDevice;
auto netPrecision = InferenceEngine::Precision::UNSPECIFIED;
double alpha, beta, bias;
size_t size;
- std::vector<size_t> axes;
+ std::vector<int64_t> axes;
std::tie(alpha, beta, bias, size, axes, netPrecision, inputShapes, targetDevice) = GetParam();
auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision);