From 4b869532f8b2aa7f02aa55c4f4813e994ea2df68 Mon Sep 17 00:00:00 2001 From: Luca Foschiani Date: Thu, 13 Feb 2020 15:07:36 +0000 Subject: COMPMID-2966 Add support for QASYMM8_SIGNED in NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel Signed-off-by: Luca Foschiani Change-Id: Ia8692f8fda16fa3b73f343e4b5b1b55e14403225 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2750 Reviewed-by: Michele Di Giorgio Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins --- tests/validation/CL/GEMMLowp.cpp | 59 +++++++++++++ tests/validation/NEON/GEMMLowp.cpp | 125 +++++++++++++++++----------- tests/validation/fixtures/GEMMLowpFixture.h | 114 ++++++++++++++++++++++++- 3 files changed, 248 insertions(+), 50 deletions(-) (limited to 'tests') diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp index 8aa81d0962..41a441c3d2 100644 --- a/tests/validation/CL/GEMMLowp.cpp +++ b/tests/validation/CL/GEMMLowp.cpp @@ -147,6 +147,65 @@ TEST_SUITE_END() // MatrixMultiplyCore TEST_SUITE(OutputStage) +TEST_SUITE(QuantizeDownInt32Scale) + +TEST_SUITE(QASYMM8) + +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", 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) + * framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 173) * framework::dataset::make("addBias", { false, true }); + +using CLGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +TEST_SUITE(BoundedReLu) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +TEST_SUITE_END() // BoundedReLu +TEST_SUITE_END() // QASYMM8 + +TEST_SUITE(QASYMM8_SIGNED) + +const auto quantize_down_int32_to_int8_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", -128) * framework::dataset::make("max", 127) * framework::dataset::make("addBias", { false, true }); + +const auto quantize_down_int32_to_int8_scale_relu_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", -100, -98) * framework::dataset::make("max", 71, 73) * framework::dataset::make("addBias", { false, true }); + +using CLGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToInt8ScaleValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_cases)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +TEST_SUITE(BoundedReLu) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_relu_cases)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +TEST_SUITE_END() // BoundedReLu +TEST_SUITE_END() // QASYMM8_SIGNED +TEST_SUITE_END() // QuantizeDownInt32Scale + 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) diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp index de30bd5451..c3747ddd24 100644 --- a/tests/validation/NEON/GEMMLowp.cpp +++ b/tests/validation/NEON/GEMMLowp.cpp @@ -165,7 +165,9 @@ TEST_SUITE_END() // MatrixMultiplyCore TEST_SUITE(OutputStage) -TEST_SUITE(QuantizeDownInt32ToUint8Scale) +TEST_SUITE(QuantizeDownInt32Scale) + +TEST_SUITE(QASYMM8) 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) @@ -175,7 +177,7 @@ const auto quantize_down_int32_to_uint8_scale_relu_cases = framework::dataset::m 2) * framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 174) * framework::dataset::make("addBias", { false, true }); -using NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture; +using NEGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture; // *INDENT-OFF* // clang-format off @@ -198,85 +200,112 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( framework::dataset::make("Expected", { true, false })), a_info, b_info, output_info, min, max, expected) { + + GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo(); + output_stage.type = GEMMLowpOutputStageType::QUANTIZE_DOWN; + output_stage.gemmlowp_min_bound = min; + output_stage.gemmlowp_max_bound = max; + output_stage.output_data_type = DataType::QASYMM8; + // Lock tensors - Status status = NEGEMMLowpQuantizeDownInt32ToUint8Scale::validate(&a_info.clone()->set_is_resizable(false), + Status status = NEGEMMLowpOutputStage::validate(&a_info.clone()->set_is_resizable(false), &b_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), - min, - max); + output_stage); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases), - shape, result_offset, result_mult_int, result_shift, min, max, add_bias) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases)) { - TensorShape shape_bias(shape[0]); + // Validate output + validate(Accessor(_target), _reference); +} - // Create tensors - Tensor in = create_tensor(shape, DataType::S32); - Tensor bias = create_tensor(shape_bias, DataType::S32); - Tensor out = create_tensor(shape, DataType::QASYMM8); +TEST_SUITE(BoundedReLu) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases)) +{ + // Validate output + validate(Accessor(_target), _reference); +} - ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS); +TEST_SUITE_END() // BoundedReLu - // Create and configure function - NEGEMMLowpQuantizeDownInt32ToUint8Scale output_stage; - output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_offset, result_mult_int, result_shift, min, max); +TEST_SUITE_END() // QASYMM8 - // Validate valid region input and output - const ValidRegion valid_region = shape_to_valid_region(shape); - validate(in.info()->valid_region(), valid_region); - validate(out.info()->valid_region(), valid_region); +TEST_SUITE(QASYMM8_SIGNED) - // Validate valid region bias - if(add_bias) - { - const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias); - validate(bias.info()->valid_region(), valid_region_bias); - } +const auto quantize_down_int32_to_int8_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 }); - // Validate padding - const PaddingSize padding(0); - validate(in.info()->padding(), padding); - validate(out.info()->padding(), padding); +const auto quantize_down_int32_to_int8_scale_relu_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", -100, -98) * framework::dataset::make("max", 71, 74) * framework::dataset::make("addBias", { false, true }); - if(add_bias) - { - validate(bias.info()->padding(), padding); - } -} +using NEGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToInt8ScaleValidationFixture; -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases)) +// *INDENT-OFF* +// 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_SIGNED), + TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8_SIGNED), + TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), + })), + framework::dataset::make("Min",{ -10, + -200, + -113, + })), + framework::dataset::make("Max",{ 105, + 300, + -18, + })), + framework::dataset::make("Expected", { true, false, false })), + a_info, b_info, output_info, min, max, expected) { - // Validate output - validate(Accessor(_target), _reference); + GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo(); + output_stage.type = GEMMLowpOutputStageType::QUANTIZE_DOWN; + output_stage.gemmlowp_min_bound = min; + output_stage.gemmlowp_max_bound = max; + output_stage.output_data_type = DataType::QASYMM8_SIGNED; + + // Lock tensors + Status status = NEGEMMLowpOutputStage::validate(&a_info.clone()->set_is_resizable(false), + &b_info.clone()->set_is_resizable(false), + &output_info.clone()->set_is_resizable(false), + output_stage); + ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } +// clang-format on +// *INDENT-ON* -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_cases)) { // Validate output validate(Accessor(_target), _reference); } TEST_SUITE(BoundedReLu) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_relu_cases)) { // Validate output validate(Accessor(_target), _reference); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_relu_cases)) -{ - // Validate output - validate(Accessor(_target), _reference); -} TEST_SUITE_END() // BoundedReLu -TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale +TEST_SUITE_END() // QASYMM8_SIGNED + +TEST_SUITE_END() // QuantizeDownInt32Scale TEST_SUITE(QuantizeDownInt32ToUint8ScaleByFixedPoint) diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h index be9ce96dcb..e3dc7381fc 100644 --- a/tests/validation/fixtures/GEMMLowpFixture.h +++ b/tests/validation/fixtures/GEMMLowpFixture.h @@ -301,8 +301,16 @@ protected: TensorType c = create_tensor(shape, DataType::QASYMM8, 1); // Create and configure function - FunctionType output_stage; - output_stage.configure(&a, add_bias ? &b : nullptr, &c, result_offset, result_mult_int, result_shift, min, max); + FunctionType output_stage; + GEMMLowpOutputStageInfo output_stage_info = GEMMLowpOutputStageInfo(); + output_stage_info.type = GEMMLowpOutputStageType::QUANTIZE_DOWN; + output_stage_info.gemmlowp_offset = result_offset; + output_stage_info.gemmlowp_multiplier = result_mult_int; + output_stage_info.gemmlowp_shift = result_shift; + output_stage_info.gemmlowp_min_bound = min; + output_stage_info.gemmlowp_max_bound = max; + output_stage_info.output_data_type = DataType::QASYMM8; + output_stage.configure(&a, add_bias ? &b : nullptr, &c, output_stage_info); ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -366,6 +374,108 @@ protected: SimpleTensor _reference{}; }; +template +class GEMMLowpQuantizeDownInt32ToInt8ScaleValidationFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max, bool add_bias) + { + _target = compute_target(shape, result_offset, result_mult_int, result_shift, min, max, add_bias); + _reference = compute_reference(shape, result_offset, result_mult_int, result_shift, min, max, add_bias); + } + +protected: + template + void fill(U &&tensor, int i) + { + std::uniform_int_distribution<> distribution(-6000, 6000); + library->fill(tensor, distribution, i); + } + + TensorType compute_target(const TensorShape &shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max, bool add_bias) + { + TensorShape shape_bias(shape[0]); + + // Create tensors + TensorType a = create_tensor(shape, DataType::S32, 1); + TensorType b = create_tensor(shape_bias, DataType::S32, 1); + TensorType c = create_tensor(shape, DataType::QASYMM8_SIGNED, 1); + + // Create and configure function + FunctionType output_stage; + GEMMLowpOutputStageInfo output_stage_info = GEMMLowpOutputStageInfo(); + output_stage_info.type = GEMMLowpOutputStageType::QUANTIZE_DOWN; + output_stage_info.gemmlowp_offset = result_offset; + output_stage_info.gemmlowp_multiplier = result_mult_int; + output_stage_info.gemmlowp_shift = result_shift; + output_stage_info.gemmlowp_min_bound = min; + output_stage_info.gemmlowp_max_bound = max; + output_stage_info.output_data_type = DataType::QASYMM8_SIGNED; + output_stage.configure(&a, add_bias ? &b : nullptr, &c, output_stage_info); + + ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + a.allocator()->allocate(); + c.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!c.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensor + fill(AccessorType(a), 0); + + if(add_bias) + { + ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate bias tensor + b.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensor + fill(AccessorType(b), 1); + } + + // Compute GEMM function + output_stage.run(); + return c; + } + + SimpleTensor compute_reference(const TensorShape &shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max, bool add_bias) + { + // Create reference + TensorShape shape_bias(shape[0]); + + SimpleTensor a{ shape, DataType::S32, 1 }; + SimpleTensor b{ shape_bias, DataType::S32, 1 }; + + // Fill reference + fill(a, 0); + + const std::vector result_mult_int_vec = { result_mult_int }; + const std::vector result_shift_vec = { result_shift }; + + if(add_bias) + { + // Fill bias + fill(b, 1); + + return reference::gemmlowp_quantize_down_scale(a, b, result_offset, result_mult_int_vec, result_shift_vec, min, max); + } + else + { + return reference::gemmlowp_quantize_down_scale(a, result_offset, result_mult_int_vec, result_shift_vec, min, max); + } + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; + template class GEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointValidationFixture : public framework::Fixture { -- cgit v1.2.1