From 1856ff7ebb29e04c3549b74d7ced336111cbf05e Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Fri, 7 Feb 2020 13:46:45 +0000 Subject: COMPMID-3097 Fuse activation with fully connected layer CL Change-Id: I447030e69b9e565f2f81529a41af8c5e7ece7ecf Signed-off-by: Giorgio Arena Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2702 Comments-Addressed: Arm Jenkins Reviewed-by: Georgios Pinitas Tested-by: Arm Jenkins --- tests/validation/NEON/FullyConnectedLayer.cpp | 37 ++++++++++++++++---------- tests/validation/NEON/GEMMLowp.cpp | 38 +++++++-------------------- 2 files changed, 32 insertions(+), 43 deletions(-) (limited to 'tests/validation/NEON') diff --git a/tests/validation/NEON/FullyConnectedLayer.cpp b/tests/validation/NEON/FullyConnectedLayer.cpp index fae116aa9f..f66b0ceb8a 100644 --- a/tests/validation/NEON/FullyConnectedLayer.cpp +++ b/tests/validation/NEON/FullyConnectedLayer.cpp @@ -71,6 +71,8 @@ const auto QuantizationData = framework::dataset::make("QuantizationInfo", QuantizationInfo(1.f / 256.f, 10), QuantizationInfo(1.1f, 10), }); + +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", ActivationLayerInfo()); } // namespace TEST_SUITE(NEON) @@ -179,16 +181,18 @@ using NEFullyConnectedLayerFixture = FullyConnectedLayerValidationFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallFullyConnectedLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeFullyConnectedLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); @@ -197,14 +201,16 @@ TEST_SUITE_END() #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), + framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), + framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); @@ -217,31 +223,34 @@ using NEFullyConnectedLayerQuantizedFixture = FullyConnectedLayerValidationQuant TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine( +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine( combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::QASYMM8)), - QuantizationData)) + QuantizationData), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerQuantizedFixture, framework::DatasetMode::NIGHTLY, combine(combine( +FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerQuantizedFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine( combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::QASYMM8)), - QuantizationData)) + QuantizationData), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } TEST_SUITE_END() TEST_SUITE(QASYMM8_SIGNED) -FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine( +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine( combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), - QuantizationData)) + QuantizationData), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8_signed); diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp index 10f2284914..de30bd5451 100644 --- a/tests/validation/NEON/GEMMLowp.cpp +++ b/tests/validation/NEON/GEMMLowp.cpp @@ -169,7 +169,7 @@ TEST_SUITE(QuantizeDownInt32ToUint8Scale) const auto quantize_down_int32_to_uint8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_shift", 2, 3) - * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true }); + * framework::dataset::make("min", 0) * framework::dataset::make("max", 255) * framework::dataset::make("addBias", { false, true }); const auto quantize_down_int32_to_uint8_scale_relu_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) @@ -181,26 +181,21 @@ using NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture = GEMMLowpQuantizeDownInt32 // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Input not a multiple of 16 - TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), // Wrong output data type }), framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32), - TensorInfo(TensorShape(21U), 1, DataType::S32), TensorInfo(TensorShape(20U), 1, DataType::S32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8), - TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8), TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), })), framework::dataset::make("Min",{ 0, - 8, 13, })), framework::dataset::make("Max",{ 205, - 300, 180, })), - framework::dataset::make("Expected", { true, false, false })), + framework::dataset::make("Expected", { true, false })), a_info, b_info, output_info, min, max, expected) { // Lock tensors @@ -287,7 +282,7 @@ TEST_SUITE(QuantizeDownInt32ToUint8ScaleByFixedPoint) const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2) - * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true }); + * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 255) * framework::dataset::make("addBias", { false, true }); const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2) @@ -303,26 +298,21 @@ using NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture = // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Input not a multiple of 16 - TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), // Wrong output data type }), framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32), - TensorInfo(TensorShape(21U), 1, DataType::S32), TensorInfo(TensorShape(20U), 1, DataType::S32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8), - TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8), TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), })), framework::dataset::make("Min",{ 0, - 8, 13, })), framework::dataset::make("Max",{ 205, - 300, 180, })), - framework::dataset::make("Expected", { true, false, false })), + framework::dataset::make("Expected", { true, false })), a_info, b_info, output_info, min, max, expected) { // Lock tensors @@ -414,7 +404,7 @@ TEST_SUITE(QuantizeDownInt32ToInt8ScaleByFixedPoint) const auto quantize_down_int32_to_int8_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2) - * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true }); + * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", -128) * framework::dataset::make("max", 128) * framework::dataset::make("addBias", { false, true }); const auto quantize_down_int32_to_int8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2) @@ -427,31 +417,26 @@ using NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointFixture = // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::F32), // Invalid input data type - TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), // Wrong output data type TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), }), framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32), - TensorInfo(TensorShape(21U), 1, DataType::S32), TensorInfo(TensorShape(20U), 1, DataType::S32), TensorInfo(TensorShape(21U), 1, DataType::S32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8_SIGNED), - TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8_SIGNED), TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8_SIGNED), })), framework::dataset::make("Min",{ -110, - -130, -113, -113, })), framework::dataset::make("Max",{ 87, - 140, 97, 97, })), - framework::dataset::make("Expected", { false, false, false, true })), + framework::dataset::make("Expected", { false, false, true })), a_info, b_info, output_info, min, max, expected) { // Lock tensors @@ -527,7 +512,7 @@ TEST_SUITE(QuantizeDownInt32ToInt16ScaleByFixedPoint) const auto quantize_down_int32_to_int16_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2) - * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true }); + * framework::dataset::make("min", -32768) * framework::dataset::make("max", 32767) * framework::dataset::make("addBias", { false, true }); const auto quantize_down_int32_to_int16_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2) @@ -536,7 +521,7 @@ const auto quantize_down_int32_to_int16_scale_by_fixedpoint_multgreat1_cases = f 1073741825) * framework::dataset::make("result_shift", -3, -2) - * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true }); + * framework::dataset::make("min", -32768) * framework::dataset::make("max", 32767) * framework::dataset::make("addBias", { false, true }); const auto quantize_down_int32_to_int16_scale_by_fixedpoint_multgreat1_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) @@ -551,26 +536,21 @@ using NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointFixture = // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Input not a multiple of 16 - TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), // Wrong output data type }), framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32), - TensorInfo(TensorShape(21U), 1, DataType::S32), TensorInfo(TensorShape(20U), 1, DataType::S32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16), - TensorInfo(TensorShape(21U, 13U), 1, DataType::QSYMM16), TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), })), framework::dataset::make("Min",{ -205, - -60000, -180, })), framework::dataset::make("Max",{ 205, - 60000, 180, })), - framework::dataset::make("Expected", { true, false, false })), + framework::dataset::make("Expected", { true, false })), a_info, b_info, output_info, min, max, expected) { // Lock tensors -- cgit v1.2.1