From e75a02b60736f37c34388c23c0ccee230f65da59 Mon Sep 17 00:00:00 2001 From: Gian Marco Date: Wed, 8 Nov 2017 12:24:09 +0000 Subject: COMPMID-675 - Reworked NEGEMMLowp interface/function The new interface makes NEGEMMLowp able to work with ASYMM8 data types. Implemented 2 new functions: - NEGEMMLowpMatrixMultiplyCore - NEGEMMLowpOutputStage These functions should make the integration in android NN doable For more information about GEMMLowp: https://github.com/google/gemmlowp/blob/master/doc/low-precision.md Change-Id: Ie2c775f45234f68ca53dba644b3a912b997fd890 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/95504 Tested-by: Kaizen Reviewed-by: Pablo Tello --- tests/validation/NEON/GEMMLowp.cpp | 93 ++++++++++++++++++++++++++++---------- 1 file changed, 69 insertions(+), 24 deletions(-) (limited to 'tests/validation/NEON/GEMMLowp.cpp') diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp index 4924f98ea6..4407eff060 100644 --- a/tests/validation/NEON/GEMMLowp.cpp +++ b/tests/validation/NEON/GEMMLowp.cpp @@ -23,12 +23,15 @@ */ #include "arm_compute/core/NEON/kernels/NEGEMMInterleaveBlockedKernel.h" #include "arm_compute/core/Types.h" -#include "arm_compute/runtime/NEON/functions/NEGEMMLowp.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" #include "tests/NEON/Accessor.h" #include "tests/NEON/Helper.h" +#include "tests/PaddingCalculator.h" #include "tests/datasets/LargeGEMMLowpDataset.h" +#include "tests/datasets/ShapeDatasets.h" #include "tests/datasets/SmallGEMMLowpDataset.h" #include "tests/framework/Asserts.h" #include "tests/framework/Macros.h" @@ -45,16 +48,13 @@ namespace validation { namespace { -const auto data_int_blk = framework::dataset::make("M", 8, 12) * framework::dataset::make("N", 8, 12) * framework::dataset::make("by", 8, 13) * framework::dataset::make("block", 4, 9); -const auto data_int_blk_tr = framework::dataset::make("M", 8, 17) * framework::dataset::make("N", 8, 14) * framework::dataset::make("by", 12) * framework::dataset::make("block", 4); -const auto data_matrix_multiply = framework::dataset::make("M", 12, 20) * framework::dataset::make("N", 12, 20) * framework::dataset::make("K", 16); +const auto data_int_blk = framework::dataset::make("M", 8, 12) * framework::dataset::make("N", 8, 12) * framework::dataset::make("by", 8, 13) * framework::dataset::make("block", 4, 9); +const auto data_int_blk_tr = framework::dataset::make("M", 8, 17) * framework::dataset::make("N", 8, 14) * framework::dataset::make("by", 12) * framework::dataset::make("block", 4); } // namespace TEST_SUITE(NEON) TEST_SUITE(GEMMLowp) -TEST_SUITE(S8) - TEST_SUITE(INTERLEAVE_BLOCKED) using NEInterleaveBlocked = NESynthetizeFunction; @@ -77,50 +77,95 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMInterleaveBlockedTransposedFixture, frame TEST_SUITE_END() -using NEGEMMLowpOffsetFixture = GEMMLowpOffsetValidationFixture; +TEST_SUITE(MatrixMultiplyCore) +using NEGEMMLowpMatrixMultiplyCoreFixture = GEMMLowpMatrixMultiplyCoreValidationFixture; -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallGEMMLowpDataset(), datasets::LargeGEMMLowpDataset()), framework::dataset::make("DataType", - DataType::S8)), - shape_a, shape_b, shape_c, a_offset, b_offset, c_offset, c_mult_int, out_shift, data_type) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallGEMMLowpDataset(), datasets::LargeGEMMLowpDataset()), + shape_a, shape_b, shape_c, a_offset, b_offset) { // Create tensors - Tensor a = create_tensor(shape_a, data_type); - Tensor b = create_tensor(shape_b, data_type); - Tensor c = create_tensor(shape_c, data_type); + Tensor a = create_tensor(shape_a, DataType::QASYMM8); + Tensor b = create_tensor(shape_b, DataType::QASYMM8); + Tensor c = create_tensor(shape_c, DataType::S32); + + a.info()->set_quantization_info(QuantizationInfo(1.0f / 255, a_offset)); + b.info()->set_quantization_info(QuantizationInfo(1.0f / 255, b_offset)); ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function - NEGEMMLowp gemmlowp; - gemmlowp.configure(&a, &b, &c, a_offset, b_offset, c_offset, c_mult_int, out_shift); + NEGEMMLowpMatrixMultiplyCore gemmlowp_mm; + gemmlowp_mm.configure(&a, &b, &c); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpMatrixMultiplyCoreFixture, framework::DatasetMode::ALL, datasets::SmallGEMMLowpDataset()) +{ + // Validate output + validate(Accessor(_target), _reference); } -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpOffsetFixture, framework::DatasetMode::ALL, combine(datasets::SmallGEMMLowpDataset(), framework::dataset::make("DataType", DataType::S8))) +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpMatrixMultiplyCoreFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpDataset()) { // Validate output validate(Accessor(_target), _reference); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpOffsetFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGEMMLowpDataset(), framework::dataset::make("DataType", DataType::S8))) +TEST_SUITE_END() // MatrixMultiplyCore + +TEST_SUITE(OutputStage) + +TEST_SUITE(QuantizeDownInt32ToUint8Scale) + +using NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture; + +const auto quantize_down_int32_to_uint8_scale_cases = framework::dataset::make("result_offset", -4, 4) * framework::dataset::make("result_mult_int", 1, 3) * framework::dataset::make("result_shift", 2, + 4); + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), quantize_down_int32_to_uint8_scale_cases), + shape, result_offset, result_mult_int, result_shift) +{ + // Create tensors + Tensor in = create_tensor(shape, DataType::S32); + Tensor out = create_tensor(shape, DataType::QASYMM8); + + ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Create and configure function + NEGEMMLowpQuantizeDownInt32ToUint8Scale output_stage; + output_stage.configure(&in, &out, result_offset, result_mult_int, result_shift); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(in.info()->valid_region(), valid_region); + validate(out.info()->valid_region(), valid_region); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + validate(in.info()->padding(), padding); + validate(out.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases)) { // Validate output validate(Accessor(_target), _reference); } -TEST_SUITE_END() // U8 -TEST_SUITE(S32) -using NEGEMMLowpMatrixMultiplyFixture = GEMMLowpMatrixMultiplyValidationFixture; -FIXTURE_DATA_TEST_CASE(MatrixMultiply, NEGEMMLowpMatrixMultiplyFixture, framework::DatasetMode::PRECOMMIT, data_matrix_multiply) +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases)) { // Validate output validate(Accessor(_target), _reference); } -TEST_SUITE_END() -TEST_SUITE_END() -TEST_SUITE_END() +TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale + +TEST_SUITE_END() // OutputStage + +TEST_SUITE_END() // GEMMLowp +TEST_SUITE_END() // NEON } // namespace validation } // namespace test } // namespace arm_compute -- cgit v1.2.1