Fix nightly failures in MatMulLowpNativeKernel when using bounded activation functions
- Added checks for supported activation functions in MatMulLowpKernel validate
- Replaced incorrect float activation macro with quantized implementation in mat_mul_quantized
Resolves: [COMPMID-6339]
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: I15661f14877f1d3305644e6473feb5482a67e773
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/532858
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9855
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/MatMul.cpp b/tests/validation/CL/MatMul.cpp
index 5a262a8..844597f 100644
--- a/tests/validation/CL/MatMul.cpp
+++ b/tests/validation/CL/MatMul.cpp
@@ -69,30 +69,27 @@
template <typename T>
using CLQuantizedMatMulActivationFixture = QuantizedMatMulValidationWithActivationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>;
-/* The main act functions matmul is expected to support */
+/* The main act functions matmul (float) is expected to support */
const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
{
ActivationLayerInfo(),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.75f, 0.25f),
- ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH)
});
+/* (Float datatype only) Larger activation functions dataset, used during some nightly tests. */
+const auto AllActivationsDataset = combine(datasets::ActivationFunctions(), framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
+
+// Alpha beta values should be integer values
+// This is for testing purposes with quantized datatypes and is not a limitation of the kernel.
+// To properly remove this restriction, dst_qinfo should be auto-initialised with consideration for alpha beta values
+// The main act functions quantized matmul kernels are expected to support
const auto ActivationFunctionsQuantizedDataset = concat(concat(concat(
framework::dataset::make("ActivationInfo", ActivationLayerInfo()),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f))),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.75f, 0.25f)));
-
-/* Larger activation functions dataset, used during some nightly tests. */
-const auto AllActivationsDataset = combine(datasets::ActivationFunctions(), framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
-
-const auto AllQuantizedActivationsDataset = combine(concat(datasets::ActivationFunctionsQuantized(),
- framework::dataset::make("ActivationFunction", { ActivationLayerInfo::ActivationFunction::HARD_SWISH,
- ActivationLayerInfo::ActivationFunction::LEAKY_RELU
- })),
- framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 1.f))),
+ framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 1.f)));
TEST_SUITE(CL)
TEST_SUITE(MatMul)
@@ -218,22 +215,7 @@
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);
-}
-
-FIXTURE_DATA_TEST_CASE(RunAllActivations, CLQuantizedMatMulActivationFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(combine(combine(
- datasets::LargeMatMulDataset(),
- framework::dataset::make("TransposeA", { false })),
- framework::dataset::make("TransposeB", { true })),
- framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
- AllQuantizedActivationsDataset),
- 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) })))
+ framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 50) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_quant);