From 2d7e683e79c8ad328d4930c1f82a46827313faf4 Mon Sep 17 00:00:00 2001 From: George Wort Date: Fri, 22 Feb 2019 16:37:41 +0000 Subject: COMPMID-1694: Fuse offset contribution with the output stage when we use NEGEMMLowpMatrixMultiplyCore Change-Id: Ic1a681e4cc03e1eba3bf8485d9cdb17b3e926047 Signed-off-by: giuros01 Reviewed-on: https://review.mlplatform.org/c/561 Reviewed-by: Gian Marco Iodice Tested-by: Arm Jenkins --- tests/datasets/GEMMLowpFusedOffsetOutputDataset.h | 201 ++++++++++++++++++++++ tests/validation/CL/GEMMLowp.cpp | 16 ++ tests/validation/NEON/GEMMLowp.cpp | 15 ++ tests/validation/fixtures/GEMMLowpFixture.h | 194 ++++++++++++++------- 4 files changed, 368 insertions(+), 58 deletions(-) create mode 100644 tests/datasets/GEMMLowpFusedOffsetOutputDataset.h (limited to 'tests') diff --git a/tests/datasets/GEMMLowpFusedOffsetOutputDataset.h b/tests/datasets/GEMMLowpFusedOffsetOutputDataset.h new file mode 100644 index 0000000000..c94019e3d5 --- /dev/null +++ b/tests/datasets/GEMMLowpFusedOffsetOutputDataset.h @@ -0,0 +1,201 @@ +/* + * Copyright (c) 2019 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef ARM_COMPUTE_TEST_GEMMLOWPOUTPUT_DATASET +#define ARM_COMPUTE_TEST_GEMMLOWPOUTPUT_DATASET + +#include "utils/TypePrinter.h" + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Utils.h" + +using namespace arm_compute; + +namespace arm_compute +{ +namespace test +{ +namespace datasets +{ +class GEMMLowpFusedOffsetOutputDataset +{ +public: + using type = std::tuple; + + struct iterator + { + iterator(std::vector::const_iterator a_it, + std::vector::const_iterator b_it, + std::vector::const_iterator c_it, + std::vector::const_iterator a_offset_it, + std::vector::const_iterator b_offset_it, + std::vector::const_iterator output_stage_it) + : _a_it{ std::move(a_it) }, + _b_it{ std::move(b_it) }, + _c_it{ std::move(c_it) }, + _a_offset_it{ std::move(a_offset_it) }, + _b_offset_it{ std::move(b_offset_it) }, + _output_stage_it{ std::move(output_stage_it) } + { + } + + std::string description() const + { + std::stringstream description; + description << "A=" << *_a_it << ":"; + description << "B=" << *_b_it << ":"; + description << "C=" << *_c_it << ":"; + description << "a_offset=" << *_a_offset_it << ":"; + description << "b_offset=" << *_b_offset_it << ":"; + description << "output_type=" << string_from_gemmlowp_output_stage((*_output_stage_it).type) << ":"; + description << "output_offset=" << (*_output_stage_it).gemmlowp_offset << ":"; + description << "output_multiplier=" << (*_output_stage_it).gemmlowp_multiplier << ":"; + description << "output_shift=" << (*_output_stage_it).gemmlowp_shift << ":"; + description << "output_min=" << (*_output_stage_it).gemmlowp_min_bound << ":"; + description << "output_max=" << (*_output_stage_it).gemmlowp_max_bound << ":"; + + return description.str(); + } + + GEMMLowpFusedOffsetOutputDataset::type operator*() const + { + return std::make_tuple(*_a_it, *_b_it, *_c_it, *_a_offset_it, *_b_offset_it, *_output_stage_it); + } + + iterator &operator++() + { + ++_a_it; + ++_b_it; + ++_c_it; + ++_a_offset_it; + ++_b_offset_it; + ++_output_stage_it; + + return *this; + } + + private: + std::vector::const_iterator _a_it; + std::vector::const_iterator _b_it; + std::vector::const_iterator _c_it; + std::vector::const_iterator _a_offset_it; + std::vector::const_iterator _b_offset_it; + std::vector::const_iterator _output_stage_it; + }; + + iterator begin() const + { + return iterator(_a_shapes.begin(), _b_shapes.begin(), _c_shapes.begin(), _a_offset.begin(), _b_offset.begin(), _output_stage.begin()); + } + + int size() const + { + return std::min(_a_shapes.size(), std::min(_b_shapes.size(), std::min(_c_shapes.size(), std::min(_a_offset.size(), std::min(_b_offset.size(), _output_stage.size()))))); + } + + void add_config(TensorShape a, TensorShape b, TensorShape c, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage) + { + _a_shapes.emplace_back(std::move(a)); + _b_shapes.emplace_back(std::move(b)); + _c_shapes.emplace_back(std::move(c)); + _a_offset.emplace_back(std::move(a_offset)); + _b_offset.emplace_back(std::move(b_offset)); + _output_stage.emplace_back(std::move(output_stage)); + } + + GEMMLowpOutputStageInfo OutputStageInfo(GEMMLowpOutputStageType type, int32_t offset, int32_t multiplier, int32_t shift, int32_t min, int32_t max) + { + GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo(); + output_stage.type = type; + output_stage.gemmlowp_offset = offset; + output_stage.gemmlowp_multiplier = multiplier; + output_stage.gemmlowp_shift = shift; + output_stage.gemmlowp_min_bound = min; + output_stage.gemmlowp_max_bound = max; + return output_stage; + } + +protected: + GEMMLowpFusedOffsetOutputDataset() = default; + GEMMLowpFusedOffsetOutputDataset(GEMMLowpFusedOffsetOutputDataset &&) = default; + +private: + std::vector _a_shapes{}; + std::vector _b_shapes{}; + std::vector _c_shapes{}; + std::vector _a_offset{}; + std::vector _b_offset{}; + std::vector _output_stage{}; +}; + +class SmallGEMMLowpFusedOffsetOutputDataset final : public GEMMLowpFusedOffsetOutputDataset +{ +public: + SmallGEMMLowpFusedOffsetOutputDataset() + { + add_config(TensorShape(21U, 1U), TensorShape(43U, 21U), TensorShape(43U, 1U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -200, 2, 13, 10, 210)); + add_config(TensorShape(21U, 13U), TensorShape(33U, 21U), TensorShape(33U, 13U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 13, 10, 210)); + add_config(TensorShape(31U, 3U), TensorShape(72U, 31U), TensorShape(72U, 3U), -2, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 0, 2, 13, 10, 210)); + add_config(TensorShape(52U, 13U), TensorShape(33U, 52U), TensorShape(33U, 13U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 100, 2, 13, 10, 210)); + add_config(TensorShape(52U, 26U), TensorShape(33U, 52U), TensorShape(33U, 26U), -2, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 0, 2, 13, 10, 210)); + add_config(TensorShape(31U, 27U), TensorShape(23U, 31U), TensorShape(23U, 27U), 18, 23, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 200, 2, 13, 10, 210)); + add_config(TensorShape(38U, 43U), TensorShape(21U, 38U), TensorShape(21U, 43U), -3, -2, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -200, 2, 13, 10, 210)); + add_config(TensorShape(32U, 72U), TensorShape(17U, 32U), TensorShape(17U, 72U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 13, 10, 210)); + + add_config(TensorShape(21U, 1U), TensorShape(43U, 21U), TensorShape(43U, 1U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -2, 254601600, 10, 10, 210)); + add_config(TensorShape(21U, 13U), TensorShape(33U, 21U), TensorShape(33U, 13U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -1, 254601600, 10, 10, 210)); + add_config(TensorShape(31U, 3U), TensorShape(72U, 31U), TensorShape(72U, 3U), -2, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 0, 254601600, 10, 10, 210)); + add_config(TensorShape(52U, 26U), TensorShape(33U, 52U), TensorShape(33U, 26U), -2, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 1, 254601600, 10, 10, 210)); + add_config(TensorShape(31U, 27U), TensorShape(23U, 31U), TensorShape(23U, 27U), 5, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 2, 254601602, 10, 10, 210)); + add_config(TensorShape(38U, 43U), TensorShape(21U, 38U), TensorShape(21U, 43U), -3, -2, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -2, 254601602, 10, 10, 210)); + add_config(TensorShape(32U, 72U), TensorShape(17U, 32U), TensorShape(17U, 72U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -1, 254601602, 10, 10, 210)); + } +}; + +class LargeGEMMLowpFusedOffsetOutputDataset final : public GEMMLowpFusedOffsetOutputDataset +{ +public: + LargeGEMMLowpFusedOffsetOutputDataset() + { + add_config(TensorShape(923U, 1U), TensorShape(871U, 923U), TensorShape(871U, 1U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -200, 2, 18, 10, 210)); + add_config(TensorShape(923U, 429U), TensorShape(871U, 923U), TensorShape(871U, 429U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 18, 10, 210)); + add_config(TensorShape(873U, 7U), TensorShape(784U, 873U), TensorShape(784U, 7U), -1, 3, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 0, 2, 18, 10, 210)); + add_config(TensorShape(873U, 513U), TensorShape(784U, 873U), TensorShape(784U, 513U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 100, 2, 18, 10, 210)); + add_config(TensorShape(697U, 872U), TensorShape(563U, 697U), TensorShape(563U, 872U), -2, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 0, 2, 18, 10, 210)); + add_config(TensorShape(1021U, 973U), TensorShape(783U, 1021U), TensorShape(783U, 973U), 5, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 200, 2, 18, 10, 210)); + add_config(TensorShape(681U, 1023U), TensorShape(213U, 681U), TensorShape(213U, 1023U), -3, -2, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -200, 2, 18, 10, 210)); + add_config(TensorShape(941U, 1011U), TensorShape(623U, 941U), TensorShape(623U, 1011U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 18, 10, 210)); + + add_config(TensorShape(923U, 1U), TensorShape(871U, 923U), TensorShape(871U, 1U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -2, 254601600, 15, 10, 210)); + add_config(TensorShape(923U, 429U), TensorShape(871U, 923U), TensorShape(871U, 429U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -1, 254601600, 15, 10, 210)); + add_config(TensorShape(873U, 7U), TensorShape(784U, 873U), TensorShape(784U, 7U), -1, 3, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 0, 254601600, 15, 10, 210)); + add_config(TensorShape(873U, 513U), TensorShape(784U, 873U), TensorShape(784U, 513U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 1, 254601600, 15, 10, 210)); + add_config(TensorShape(697U, 872U), TensorShape(563U, 697U), TensorShape(563U, 872U), -2, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 2, 254601602, 15, 10, 210)); + add_config(TensorShape(1021U, 973U), TensorShape(783U, 1021U), TensorShape(783U, 973U), 5, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -2, 254601602, 15, 10, 210)); + add_config(TensorShape(681U, 1023U), TensorShape(213U, 681U), TensorShape(213U, 1023U), -3, -2, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -1, 254601602, 15, 10, 210)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GEMMLOWPOUTPUT_DATASET */ diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp index 08641dbaa3..efefbd645b 100644 --- a/tests/validation/CL/GEMMLowp.cpp +++ b/tests/validation/CL/GEMMLowp.cpp @@ -28,6 +28,7 @@ #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" +#include "tests/datasets/GEMMLowpFusedOffsetOutputDataset.h" #include "tests/datasets/LargeGEMMLowpDataset.h" #include "tests/datasets/ShapeDatasets.h" #include "tests/datasets/SmallGEMMLowpDataset.h" @@ -83,6 +84,21 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFixture, framework: validate(CLAccessor(_target), _reference); } +using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture; +TEST_SUITE(FusedOffsetOutput) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::ALL, datasets::SmallGEMMLowpFusedOffsetOutputDataset()) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpFusedOffsetOutputDataset()) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() // FusedOffsetOutput + TEST_SUITE(Output3D) using CLGEMMLowpMatrixMultiplyCoreOutput3DFixture = GEMMLowpMatrixMultiplyCoreValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreOutput3DFixture, framework::DatasetMode::PRECOMMIT, datasets::SmallGEMMLowpOutput3DDataset()) diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp index 57067f140f..f0460b4a23 100644 --- a/tests/validation/NEON/GEMMLowp.cpp +++ b/tests/validation/NEON/GEMMLowp.cpp @@ -30,6 +30,7 @@ #include "tests/NEON/Accessor.h" #include "tests/NEON/Helper.h" #include "tests/PaddingCalculator.h" +#include "tests/datasets/GEMMLowpFusedOffsetOutputDataset.h" #include "tests/datasets/LargeGEMMLowpDataset.h" #include "tests/datasets/ShapeDatasets.h" #include "tests/datasets/SmallGEMMLowpDataset.h" @@ -144,6 +145,20 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpMatrixMultiplyCoreFixture, framework: validate(Accessor(_target), _reference); } +using NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture; +TEST_SUITE(FusedOffsetOutput) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::ALL, datasets::SmallGEMMLowpFusedOffsetOutputDataset()) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::NIGHTLY, datasets::LargeGEMMLowpFusedOffsetOutputDataset()) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // FusedOffsetOutput TEST_SUITE_END() // MatrixMultiplyCore TEST_SUITE(OutputStage) diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h index 836f8eddfe..90a4b5cf40 100644 --- a/tests/validation/fixtures/GEMMLowpFixture.h +++ b/tests/validation/fixtures/GEMMLowpFixture.h @@ -42,86 +42,164 @@ namespace test { namespace validation { -template -class GEMMLowpMatrixMultiplyCoreValidationFixture : public framework::Fixture +namespace { -public: - template - void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, int32_t a_offset, int32_t b_offset) +template +void fill(U &&tensor, int i) +{ + // Between 1 and 254 in order to avoid having -128 and 128 for the DOT product path + std::uniform_int_distribution<> distribution(1, 254); + library->fill(tensor, distribution, i); +} + +template +TensorType compute_gemmlowp_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset, + GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo()) +{ + // Create tensors + TensorType a = create_tensor(shape_a, DataType::QASYMM8, 1); + TensorType b = create_tensor(shape_b, DataType::QASYMM8, 1); + TensorType output = create_tensor(shape_output, output_stage.type == GEMMLowpOutputStageType::NONE ? DataType::S32 : DataType::QASYMM8, 1); + + a.info()->set_quantization_info(QuantizationInfo(1.0f / 255, a_offset)); + b.info()->set_quantization_info(QuantizationInfo(1.0f / 255, b_offset)); + + TensorType bias; + if(is_fused) { - _target = compute_target(shape_a, shape_b, shape_c, a_offset, b_offset); - _reference = compute_reference(shape_a, shape_b, shape_c, a_offset, b_offset); + TensorShape bias_shape(shape_b[0]); + bias = create_tensor(bias_shape, DataType::S32, 1); } -protected: - template - void fill(U &&tensor, int i) + // Create and configure function + // The GEMMinfo includes the values of the depth in case of reinterpreted 3d input/output + FunctionType gemmlowp; + // TODO (COMPMID-1672) - Extending the test to validate add bias in offset contribution + gemmlowp.configure(&a, &b, is_fused ? &bias : nullptr, &output, GEMMInfo(false, false, false, (reinterpret_output_as_3d ? shape_output[2] : 0), reinterpret_input_as_3d, false, output_stage)); + + ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(output.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + a.allocator()->allocate(); + b.allocator()->allocate(); + output.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!output.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(a), 0); + fill(AccessorType(b), 1); + + if(is_fused) { - // Between 1 and 254 in order to avoid having -128 and 128 for the DOT product path - std::uniform_int_distribution<> distribution(1, 254); - library->fill(tensor, distribution, i); + ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); + bias.allocator()->allocate(); + ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS); + fill(AccessorType(bias), 2); } - TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, int32_t a_offset, int32_t b_offset) + // Compute GEMM function + gemmlowp.run(); + return output; +} + +template +SimpleTensor compute_gemmlowp_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset) +{ + TensorShape shape_a_to_use = shape_a; + if(reinterpret_input_as_3d) { - // Create tensors - TensorType a = create_tensor(shape_a, DataType::QASYMM8, 1); - TensorType b = create_tensor(shape_b, DataType::QASYMM8, 1); - TensorType c = create_tensor(shape_c, DataType::S32, 1); + // Collapse the second and third dimension if the input is 3D + shape_a_to_use.collapse(2U, 1U); + } - a.info()->set_quantization_info(QuantizationInfo(1.0f / 255, a_offset)); - b.info()->set_quantization_info(QuantizationInfo(1.0f / 255, b_offset)); + // Create reference + SimpleTensor a{ shape_a_to_use, DataType::QASYMM8, 1 }; + SimpleTensor b{ shape_b, DataType::QASYMM8, 1 }; - // Create and configure function - // The GEMMinfo includes the values of the depth in case of reinterpreted 3d input/output - FunctionType gemmlowp; - // TODO (COMPMID-1672) - Extending the test to validate add bias in offset contribution - gemmlowp.configure(&a, &b, nullptr, &c, GEMMInfo(false, false, false, (reinterpret_output_as_3d ? shape_c[2] : 0), reinterpret_input_as_3d)); + // Fill reference + fill(a, 0); + fill(b, 1); - 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); + return reference::gemmlowp_matrix_multiply_core(a, b, shape_output, a_offset, b_offset); +} +} - // Allocate tensors - a.allocator()->allocate(); - b.allocator()->allocate(); - c.allocator()->allocate(); +template +class GEMMLowpMatrixMultiplyCoreValidationFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset) + { + _target = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset); + _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, 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); +protected: + TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset) + { + return compute_gemmlowp_target(shape_a, shape_b, shape_output, a_offset, b_offset); + } - // Fill tensors - fill(AccessorType(a), 0); - fill(AccessorType(b), 1); + SimpleTensor compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset) + { + return compute_gemmlowp_reference(shape_a, shape_b, shape_output, a_offset, b_offset); + } - // Compute GEMM function - gemmlowp.run(); - return c; + TensorType _target{}; + SimpleTensor _reference{}; +}; + +template +class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage) + { + ARM_COMPUTE_EXPECT(output_stage.type != GEMMLowpOutputStageType::NONE, framework::LogLevel::ERRORS); + _target = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage); + _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage); } - SimpleTensor compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, int32_t a_offset, int32_t b_offset) +protected: + TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage) { - TensorShape shape_a_to_use = shape_a; - if(reinterpret_input_as_3d) - { - // Collapse the second and third dimension if the input is 3D - shape_a_to_use.collapse(2U, 1U); - } + return compute_gemmlowp_target(shape_a, shape_b, shape_output, a_offset, b_offset, + output_stage); + } - // Create reference - SimpleTensor a{ shape_a_to_use, DataType::QASYMM8, 1 }; - SimpleTensor b{ shape_b, DataType::QASYMM8, 1 }; + SimpleTensor compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset, + GEMMLowpOutputStageInfo output_stage) + { + SimpleTensor output = compute_gemmlowp_reference(shape_a, shape_b, shape_output, a_offset, b_offset); - // Fill reference - fill(a, 0); - fill(b, 1); + TensorShape bias_shape(shape_b[0]); + SimpleTensor bias{ bias_shape, DataType::S32, 1 }; + fill(bias, 2); - return reference::gemmlowp_matrix_multiply_core(a, b, shape_c, a_offset, b_offset); + switch(output_stage.type) + { + case GEMMLowpOutputStageType::QUANTIZE_DOWN: + return reference::gemmlowp_quantize_down_int32_to_uint8_scale(output, bias, + output_stage.gemmlowp_offset, output_stage.gemmlowp_multiplier, output_stage.gemmlowp_shift, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound); + break; + case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: + return reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(output, bias, + output_stage.gemmlowp_multiplier, output_stage.gemmlowp_shift, output_stage.gemmlowp_offset, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound); + break; + default: + ARM_COMPUTE_ERROR("Not Supported!"); + } } - TensorType _target{}; - SimpleTensor _reference{}; + TensorType _target{}; + SimpleTensor _reference{}; }; template @@ -536,4 +614,4 @@ protected: } // namespace validation } // namespace test } // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_GEMMLOWP_FIXTURE */ \ No newline at end of file +#endif /* ARM_COMPUTE_TEST_GEMMLOWP_FIXTURE */ -- cgit v1.2.1