diff options
Diffstat (limited to 'tests/validation/NEON/DirectConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/NEON/DirectConvolutionLayer.cpp | 42 |
1 files changed, 33 insertions, 9 deletions
diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp index 57e030c349..b6f9f62ff0 100644 --- a/tests/validation/NEON/DirectConvolutionLayer.cpp +++ b/tests/validation/NEON/DirectConvolutionLayer.cpp @@ -86,6 +86,14 @@ const auto data_qs16 = combine(datasets::TinyDirectConvolutionShapes(), combine(framework::dataset::make("PadY", 0), combine(framework::dataset::make("KernelSize", 1), framework::dataset::make("NumKernels", { 1, 4, 8, 16 }))))))); +/** Activation function Dataset*/ +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) +}); } // namespace TEST_SUITE(NEON) @@ -93,7 +101,7 @@ TEST_SUITE(DirectConvolutionLayer) // *INDENT-OFF* // clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type input/weights TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching input feature maps TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Unsupported kernel width @@ -144,10 +152,15 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 1, 0, 0), })), + framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +})), framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false })), - input_info, weights_info, biases_info, output_info, conv_info, expected) + input_info, weights_info, biases_info, output_info, conv_info, act_info, expected) { - bool is_valid = bool(NEDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info)); + bool is_valid = bool(NEDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info)); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } // clang-format on @@ -161,7 +174,8 @@ using NEDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<Tenso TEST_SUITE(Float) #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(data_f32, framework::dataset::make("DataType", DataType::F16))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(data_f32, framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_fp16); @@ -170,7 +184,8 @@ TEST_SUITE_END() #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(data_f32, framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(data_f32, framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_fp32); @@ -181,11 +196,19 @@ TEST_SUITE_END() template <typename T> using NEDirectConvolutionLayerFixedPointFixture = DirectConvolutionValidationFixedPointFixture<Tensor, Accessor, NEDirectConvolutionLayer, T>; +const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) +}); + TEST_SUITE(Quantized) TEST_SUITE(QS8) // We test for fixed point precision [4,6] -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(data_qs8, framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(data_qs8, framework::dataset::make("DataType", DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7)), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qs); @@ -194,8 +217,9 @@ TEST_SUITE_END() TEST_SUITE(QS16) // We test for fixed point precision [4,13] -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(data_qs16, framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 4, 14))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(combine(data_qs16, framework::dataset::make("DataType", DataType::QS16)), + framework::dataset::make("FractionalBits", 4, 14)), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qs); |