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author | Jakub Sujak <jakub.sujak@arm.com> | 2023-04-17 12:08:48 +0100 |
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committer | Omar Al Khatib <omar.alkhatib@arm.com> | 2023-05-05 14:48:28 +0000 |
commit | e9b3ee2badebf91188c1cd0e59d6aaa30ed60985 (patch) | |
tree | 750c39df7c0113caf6a893bb6af6e9ef1ecc3756 /tests/validation/CL/MatMul.cpp | |
parent | edafe7f5fdc056fddc395c70420fc869dcb7d9fb (diff) | |
download | ComputeLibrary-e9b3ee2badebf91188c1cd0e59d6aaa30ed60985.tar.gz |
Connect CLMatMul function to quantized kernels and resolve NE BatchMatMul int_8 failures
* Adapt the CLMatMul function and ClMatMul operator to use quantized kernels.
* Add function-level tests.
Resolves: COMPMID-5929 and COMPMID-5811
Change-Id: I5348cdcf07b8074c138e04dfef0a73399377accd
Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>
Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9575
Reviewed-by: Mohmun02 <MohammedSuhail.Munshi@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/validation/CL/MatMul.cpp')
-rw-r--r-- | tests/validation/CL/MatMul.cpp | 143 |
1 files changed, 118 insertions, 25 deletions
diff --git a/tests/validation/CL/MatMul.cpp b/tests/validation/CL/MatMul.cpp index 7c1d16008f..6364b16200 100644 --- a/tests/validation/CL/MatMul.cpp +++ b/tests/validation/CL/MatMul.cpp @@ -21,14 +21,19 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ +#include "arm_compute/core/Types.h" #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/functions/CLMatMul.h" + #include "tests/CL/CLAccessor.h" -#include "tests/datasets/LargeMatMulDataset.h" -#include "tests/datasets/SmallMatMulDataset.h" +#include "tests/framework/DatasetModes.h" #include "tests/framework/Macros.h" +#include "tests/framework/TestCase.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" + +#include "tests/datasets/LargeMatMulDataset.h" +#include "tests/datasets/SmallMatMulDataset.h" #include "tests/validation/fixtures/MatMulFixture.h" namespace arm_compute @@ -39,55 +44,143 @@ namespace validation { namespace { -RelativeTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for fp32 data type */ -constexpr float abs_tolerance_f32( - 0.0001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for fp32 data type in case using relative tolerance fails because of small values */ -constexpr float abs_tolerance_f16( - 0.001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for fp16 data type in case using relative tolerance fails because of small values */ -RelativeTolerance<half_float::half> tolerance_f16(half(0.01)); /**< Tolerance value for comparing reference's output against implementation's output for fp16 data type */ +RelativeTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for fp32 data type */ +constexpr float abs_tolerance_f32(0.0001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for fp32 data type in case using relative tolerance fails because of small values */ +constexpr float abs_tolerance_f16(0.001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for fp16 data type in case using relative tolerance fails because of small values */ +RelativeTolerance<half_float::half> tolerance_f16(half(0.01)); /**< Tolerance value for comparing reference's output against implementation's output for fp16 data type */ +constexpr AbsoluteTolerance<uint8_t> tolerance_quant(1); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ } // namespace template <typename T> -using MatMulFixture = MatMulValidationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; +using CLMatMulFixture = MatMulValidationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; + +template <typename T> +using CLQuantizedMatMulFixture = QuantizedMatMulValidationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; TEST_SUITE(CL) TEST_SUITE(MatMul) + +TEST_SUITE(Float) TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, MatMulFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallMatMulDataset(), - framework::dataset::make("pretransose_A", { false, true })), - framework::dataset::make("pretransose_B", { false, true })), - framework::dataset::make("DataType", DataType::F32))) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F32))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, MatMulFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeMatMulDataset(), - framework::dataset::make("pretransose_A", { false, true })), - framework::dataset::make("pretransose_B", { false, true })), - framework::dataset::make("DataType", DataType::F32))) + +FIXTURE_DATA_TEST_CASE(RunLarge, CLMatMulFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F32))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32); } + TEST_SUITE_END() // FP32 + TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, MatMulFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallMatMulDataset(), - framework::dataset::make("pretransose_A", { false, true })), - framework::dataset::make("pretransose_B", { false, true })), - framework::dataset::make("DataType", DataType::F16))) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F16))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16); } -FIXTURE_DATA_TEST_CASE(RunLarge, MatMulFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeMatMulDataset(), - framework::dataset::make("pretransose_A", { false, true })), - framework::dataset::make("pretransose_B", { false, true })), - framework::dataset::make("DataType", DataType::F16))) + +FIXTURE_DATA_TEST_CASE(RunLarge, CLMatMulFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F16))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16); } + TEST_SUITE_END() // FP16 +TEST_SUITE_END() // Float + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLQuantizedMatMulFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 50, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 30, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 2) })) +) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLQuantizedMatMulFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 100, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 200, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 2) })) +) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +TEST_SUITE_END() // QASYMM8 + +TEST_SUITE(QASYMM8_SIGNED) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLQuantizedMatMulFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), + framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 50, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 30, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 2) })) +) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLQuantizedMatMulFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), + framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 100, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 200, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 2) })) +) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +TEST_SUITE_END() // QASYMM8_SIGNED + +TEST_SUITE_END() // Quantized + TEST_SUITE_END() // MatMul TEST_SUITE_END() // CL } // namespace validation |