Implement Quantized Matmul T/T and T/Nt kernels using MMUL extension
Resolves: COMPMID-6476, COMPMID-6477
Change-Id: Ied37c269d5a108ff72f70e3ad932cf372bda5562
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10346
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/MatMulLowpNativeMMULKernel.cpp b/tests/validation/CL/MatMulLowpNativeMMULKernel.cpp
index 561c455..ac46b67 100644
--- a/tests/validation/CL/MatMulLowpNativeMMULKernel.cpp
+++ b/tests/validation/CL/MatMulLowpNativeMMULKernel.cpp
@@ -61,9 +61,10 @@
/** M0 values to test --nightly*/
const auto m0_values_nightly_lhs_nt = framework::dataset::make("M0", { 2, 4, 5, 8 });
+const auto m0_values_nightly_lhs_t = framework::dataset::make("M0", { 2, 4, 8 });
/** N0 values to test --nightly*/
-const auto n0_values_nightly_rhs_nt = framework::dataset::make("N0", { 1, 3, 8, 16 });
+const auto n0_values_nightly = framework::dataset::make("N0", { 1, 3, 8, 16 });
TEST_SUITE(CL)
TEST_SUITE(MatMulLowpNativeMMULKernel)
@@ -80,9 +81,12 @@
{ MatMulKernelInfo(false, true, 3, 5, 4), false }, // N0 not in {1, 2, 3, 4, 8, 16}
{ MatMulKernelInfo(false, false, 3, 6, 4), false }, // N0 not in {1, 2, 3, 4, 8, 16}
{ MatMulKernelInfo(false, false, 3, 3, 8), false }, // K0 not in 4
+ { MatMulKernelInfo(true, false, 5, 3, 4), false }, // M0 not in {1, 2, 3, 4, 8, 16} when Lhs is transposed
{ MatMulKernelInfo(false, false, 9, 1, 4), true },
{ MatMulKernelInfo(false, true, 3, 16, 4), true },
{ MatMulKernelInfo(false, false, 7, 3, 4), true },
+ { MatMulKernelInfo(true, false, 8, 3, 4), true },
+ { MatMulKernelInfo(true, true, 4, 3, 4), true },
{ MatMulKernelInfo(false, false, 7, 3, 4, true), false }, // export to CLImage is unsupported for quantized types
};
@@ -216,7 +220,7 @@
FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulLowpNativeMMULKernelFixture<int8_t>,
framework::DatasetMode::ALL,
combine(datasets::SmallMatMulLowpMMULDataset(),
- make("TransposeA", { false }),
+ make("TransposeA", { false, true }),
make("TransposeB", { false, true }),
m0_values_precommit,
n0_values_precommit,
@@ -234,7 +238,7 @@
FIXTURE_DATA_TEST_CASE(RunWithBias, CLMatMulLowpNativeMMULKernelWithBiasFixture<int8_t>,
framework::DatasetMode::ALL,
combine(datasets::SmallMatMulLowpMMULWithBiasDataset(),
- make("TransposeA", { false }),
+ make("TransposeA", { false, true }),
make("TransposeB", { false, true }),
m0_values_precommit,
n0_values_precommit,
@@ -249,13 +253,31 @@
}
}
-FIXTURE_DATA_TEST_CASE(RunLargeNoTranspose, CLMatMulLowpNativeMMULKernelFixture<int8_t>,
+FIXTURE_DATA_TEST_CASE(RunLargeLhsNotTransposed, CLMatMulLowpNativeMMULKernelFixture<int8_t>,
framework::DatasetMode::NIGHTLY,
combine(datasets::LargeMatMulLowpMMULDataset(),
make("TransposeA", { false }),
make("TransposeB", { false, true }),
m0_values_nightly_lhs_nt,
- n0_values_nightly_rhs_nt,
+ n0_values_nightly,
+ make("K0", { 4 }),
+ make("ExportRhsToCLImage", { false }),
+ make("DataType", DataType::QASYMM8_SIGNED)))
+{
+ if(_device_supports_mmul)
+ {
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_quant);
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunLargeLhsTransposed, CLMatMulLowpNativeMMULKernelFixture<int8_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::LargeMatMulLowpMMULDataset(),
+ make("TransposeA", { true }),
+ make("TransposeB", { false, true }),
+ m0_values_nightly_lhs_t,
+ n0_values_nightly,
make("K0", { 4 }),
make("ExportRhsToCLImage", { false }),
make("DataType", DataType::QASYMM8_SIGNED)))
@@ -272,7 +294,7 @@
FIXTURE_DATA_TEST_CASE(RunHighDimensional, CLMatMulLowpNativeMMULKernelFixture<int8_t>,
framework::DatasetMode::ALL,
combine(datasets::HighDimensionalMatMulLowpMMULDataset(),
- make("TransposeA", { false }),
+ make("TransposeA", { false, true }),
make("TransposeB", { false, true }),
make("M0", { 2 }),
make("N0", { 2 }),
@@ -294,7 +316,7 @@
FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulLowpNativeMMULKernelFixture<uint8_t>,
framework::DatasetMode::ALL,
combine(datasets::SmallMatMulLowpMMULDatasetSubset(),
- make("TransposeA", { false }),
+ make("TransposeA", { false, true }),
make("TransposeB", { false, true }),
m0_values_precommit,
n0_values_precommit,
@@ -312,7 +334,7 @@
FIXTURE_DATA_TEST_CASE(RunWithBias, CLMatMulLowpNativeMMULKernelWithBiasFixture<uint8_t>,
framework::DatasetMode::ALL,
combine(datasets::SmallMatMulLowpMMULWithBiasDataset(),
- make("TransposeA", { false }),
+ make("TransposeA", { false, true }),
make("TransposeB", { false, true }),
m0_values_precommit,
n0_values_precommit,
@@ -327,13 +349,31 @@
}
}
-FIXTURE_DATA_TEST_CASE(RunLargeNoTranspose, CLMatMulLowpNativeMMULKernelFixture<uint8_t>,
+FIXTURE_DATA_TEST_CASE(RunLargeLhsNotTransposed, CLMatMulLowpNativeMMULKernelFixture<uint8_t>,
framework::DatasetMode::NIGHTLY,
combine(datasets::LargeMatMulLowpMMULDataset(),
make("TransposeA", { false }),
make("TransposeB", { false, true }),
m0_values_nightly_lhs_nt,
- n0_values_nightly_rhs_nt,
+ n0_values_nightly,
+ make("K0", { 4 }),
+ make("ExportRhsToCLImage", { false }),
+ make("DataType", DataType::QASYMM8)))
+{
+ if(_device_supports_mmul)
+ {
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_quant);
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunLargeLhsTransposed, CLMatMulLowpNativeMMULKernelFixture<uint8_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::LargeMatMulLowpMMULDataset(),
+ make("TransposeA", { true }),
+ make("TransposeB", { false, true }),
+ m0_values_nightly_lhs_t,
+ n0_values_nightly,
make("K0", { 4 }),
make("ExportRhsToCLImage", { false }),
make("DataType", DataType::QASYMM8)))