[ONCPUML-1451] Add matmul kernel to enable bf16 to bf16 operations via PyTorch® autocast() function
The full range of tests must be added with [MLINFSW-482] epic due to the lack of reordering kernels implemented in Acl.
Co-Authored-By: David Mansell <David.Mansell@arm.com>
Change-Id: I820d316295a1ec94fdc89c37e4144a268f914c36
Signed-off-by: Renato Arantes <renato.arantes@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11169
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/NEON/MatMul.cpp b/tests/validation/NEON/MatMul.cpp
index f91dea1..02f0bfd 100644
--- a/tests/validation/NEON/MatMul.cpp
+++ b/tests/validation/NEON/MatMul.cpp
@@ -24,15 +24,14 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEMatMul.h"
-#include "tests/NEON/Accessor.h"
-#include "tests/framework/Asserts.h"
-#include "tests/framework/Macros.h"
-#include "tests/framework/datasets/Datasets.h"
-#include "tests/validation/Validation.h"
-
#include "tests/datasets/LargeMatMulDataset.h"
#include "tests/datasets/SmallMatMulDataset.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/framework/Macros.h"
+#include "tests/NEON/Accessor.h"
#include "tests/validation/fixtures/MatMulFixture.h"
+#include "tests/validation/Validation.h"
namespace arm_compute
{
@@ -45,8 +44,9 @@
TEST_SUITE(NEON)
TEST_SUITE(MatMul)
-constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for FP32 data types */
-const AbsoluteTolerance<half> tolerance_fp16(half(0.1f));
+constexpr AbsoluteTolerance<float> tolerance_fp32(
+ 0.001f); /**< Tolerance value for comparing reference's output against implementation's output for FP32 data types */
+const AbsoluteTolerance<half> tolerance_fp16(half(0.1f));
#ifdef __aarch64__
constexpr AbsoluteTolerance<int32_t> tolerance_qasymm8(1);
constexpr AbsoluteTolerance<int32_t> tolerance_qasymm8_signed(1);
@@ -120,55 +120,79 @@
using NEMatMulFastMathFixture = MatMulGenericValidationFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>;
template <typename T>
-using NEMatMulDynamicTensorsFixture = MatMulValidationWithDynamicTensorsFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>;
+using NEMatMulFixedFormatFixture = MatMulFixedFormatFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>;
+
+template <typename T>
+using NEMatMulDynamicTensorsFixture =
+ MatMulValidationWithDynamicTensorsFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>;
template <typename T>
using NEQuantizedMatMulFixture = QuantizedMatMulValidationFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>;
TEST_SUITE(Float)
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEMatMulFixture<float>, framework::DatasetMode::PRECOMMIT,
- combine(
- datasets::SmallMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F32),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })))
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NEMatMulFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F32),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_fp32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEMatMulFixture<float>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::LargeMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F32),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })))
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ NEMatMulFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::LargeMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F32),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_fp32);
}
-FIXTURE_DATA_TEST_CASE(RunHighDimensions, NEMatMulFixture<float>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::HighDimensionalMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F32),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })))
+FIXTURE_DATA_TEST_CASE(RunHighDimensions,
+ NEMatMulFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::HighDimensionalMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F32),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_fp32);
}
-FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors, NEMatMulDynamicTensorsFixture<float>, framework::DatasetMode::PRECOMMIT,
- combine(
- datasets::SmallMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F32),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }),
- make("NumberOfRuns", 5)))
+FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors,
+ NEMatMulDynamicTensorsFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F32),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+}),
+make("NumberOfRuns", 5)))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_fp32);
@@ -179,37 +203,58 @@
/* Note : MatMul BF16 is enabled by specifying FP32 datatype and enabling the fast math setting */
constexpr AbsoluteTolerance<float> tolerance_bf16(0.02f);
TEST_SUITE(BF16)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEMatMulFastMathFixture<float>, framework::DatasetMode::PRECOMMIT,
- combine(
- datasets::SmallMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F32),
- make("ActivationInfo", { ActivationLayerInfo() }),
- make("RunTimes", { 0 }),
- make("Settings", { CpuMatMulSettings().fast_math(true) }),
- make("LhsQInfo", { QuantizationInfo() }),
- make("RhsQInfo", { QuantizationInfo() }),
- make("OutQInfo", { QuantizationInfo() }))
-)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NEMatMulFastMathFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F32),
+ make("ActivationInfo", {ActivationLayerInfo()}),
+ make("RunTimes", {0}),
+ make("Settings", {CpuMatMulSettings().fast_math(true)}),
+ make("LhsQInfo", {QuantizationInfo()}),
+ make("RhsQInfo", {QuantizationInfo()}),
+ make("OutQInfo", {QuantizationInfo()})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_bf16);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEMatMulFastMathFixture<float>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::LargeMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F32),
- make("ActivationInfo", { ActivationLayerInfo() }),
- make("RunTimes", { 0 }),
- make("Settings", { CpuMatMulSettings().fast_math(true) }),
- make("LhsQInfo", { QuantizationInfo() }),
- make("RhsQInfo", { QuantizationInfo() }),
- make("OutQInfo", { QuantizationInfo() }))
-)
+FIXTURE_DATA_TEST_CASE(RunTinyFixedFormat,
+ NEMatMulFixedFormatFixture<bfloat16>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::TinyMatMulDataset(),
+ make("TransposeA", {false}),
+ make("TransposeB", {false}),
+ make("DataType", DataType::BFLOAT16),
+ make("ActivationInfo", {ActivationLayerInfo()}),
+ make("RunTimes", {0}),
+ make("Settings", {CpuMatMulSettings().fast_math(true).fixed_format(true)}),
+ make("LhsQInfo", {QuantizationInfo()}),
+ make("RhsQInfo", {QuantizationInfo()}),
+ make("OutQInfo", {QuantizationInfo()})))
+{
+ if (CPUInfo::get().has_bf16())
+ {
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_bf16);
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ NEMatMulFastMathFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::LargeMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F32),
+ make("ActivationInfo", {ActivationLayerInfo()}),
+ make("RunTimes", {0}),
+ make("Settings", {CpuMatMulSettings().fast_math(true)}),
+ make("LhsQInfo", {QuantizationInfo()}),
+ make("RhsQInfo", {QuantizationInfo()}),
+ make("OutQInfo", {QuantizationInfo()})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_bf16, 0.01 /* tolerance_num */);
@@ -219,36 +264,51 @@
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEMatMulFixture<half>, framework::DatasetMode::PRECOMMIT,
- combine(
- datasets::SmallMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F16),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })))
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NEMatMulFixture<half>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F16),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_fp16);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEMatMulFixture<half>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::LargeMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F16),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })))
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ NEMatMulFixture<half>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::LargeMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F16),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_fp16);
}
-FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors, NEMatMulDynamicTensorsFixture<half>, framework::DatasetMode::PRECOMMIT,
- combine(
- datasets::SmallMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::F16),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }),
- make("NumberOfRuns", 5)))
+FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors,
+ NEMatMulDynamicTensorsFixture<half>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::F16),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+}),
+make("NumberOfRuns", 5)))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_fp16);
@@ -263,52 +323,64 @@
TEST_SUITE(QASYMM8)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEQuantizedMatMulFixture<uint8_t>, framework::DatasetMode::PRECOMMIT,
- combine(
- datasets::SmallMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::QASYMM8),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }),
- make("NumberOfExtraRuns", { 0, 1 }),
- make("LhsQInfo", { QuantizationInfo(1.f / 50, 1) }),
- make("RhsQInfo", { QuantizationInfo(1.f / 30, -1) }),
- make("OutQInfo", { QuantizationInfo(1.f, 2) }))
-)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NEQuantizedMatMulFixture<uint8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::QASYMM8),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+}),
+make("NumberOfExtraRuns", {0, 1}),
+make("LhsQInfo", {QuantizationInfo(1.f / 50, 1)}),
+make("RhsQInfo", {QuantizationInfo(1.f / 30, -1)}),
+make("OutQInfo", {QuantizationInfo(1.f, 2)})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8);
}
-FIXTURE_DATA_TEST_CASE(RunSmallExtraActivation, NEQuantizedMatMulFixture<uint8_t>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::SmallerMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::QASYMM8),
- make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) }),
- make("NumberOfExtraRuns", { 0, 1 }),
- make("LhsQInfo", { QuantizationInfo(1.f / 50, 1) }),
- make("RhsQInfo", { QuantizationInfo(1.f / 30, -1) }),
- make("OutQInfo", { QuantizationInfo(1.f, 2) }))
-)
+FIXTURE_DATA_TEST_CASE(RunSmallExtraActivation,
+ NEQuantizedMatMulFixture<uint8_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::SmallerMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::QASYMM8),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU)
+}),
+make("NumberOfExtraRuns", {0, 1}),
+make("LhsQInfo", {QuantizationInfo(1.f / 50, 1)}),
+make("RhsQInfo", {QuantizationInfo(1.f / 30, -1)}),
+make("OutQInfo", {QuantizationInfo(1.f, 2)})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEQuantizedMatMulFixture<uint8_t>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::LargeMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::QASYMM8),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }),
- make("NumberOfExtraRuns", { 0, 1 }),
- make("LhsQInfo", { QuantizationInfo(1.f / 100, 1) }),
- make("RhsQInfo", { QuantizationInfo(1.f / 200, -1) }),
- make("OutQInfo", { QuantizationInfo(1.f, 2) }))
-)
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ NEQuantizedMatMulFixture<uint8_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::LargeMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::QASYMM8),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+}),
+make("NumberOfExtraRuns", {0, 1}),
+make("LhsQInfo", {QuantizationInfo(1.f / 100, 1)}),
+make("RhsQInfo", {QuantizationInfo(1.f / 200, -1)}),
+make("OutQInfo", {QuantizationInfo(1.f, 2)})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8);
@@ -318,52 +390,64 @@
TEST_SUITE(QASYMM8_SIGNED)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEQuantizedMatMulFixture<int8_t>, framework::DatasetMode::PRECOMMIT,
- combine(
- datasets::SmallMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::QASYMM8_SIGNED),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }),
- make("NumberOfExtraRuns", { 0, 1 }),
- make("LhsQInfo", { QuantizationInfo(1.f / 40, -2) }),
- make("RhsQInfo", { QuantizationInfo(1.f / 50, 1) }),
- make("OutQInfo", { QuantizationInfo(1.f, 1) }))
-)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ NEQuantizedMatMulFixture<int8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(datasets::SmallMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::QASYMM8_SIGNED),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+}),
+make("NumberOfExtraRuns", {0, 1}),
+make("LhsQInfo", {QuantizationInfo(1.f / 40, -2)}),
+make("RhsQInfo", {QuantizationInfo(1.f / 50, 1)}),
+make("OutQInfo", {QuantizationInfo(1.f, 1)})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
}
-FIXTURE_DATA_TEST_CASE(RunSmallExtraActivation, NEQuantizedMatMulFixture<int8_t>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::SmallerMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::QASYMM8_SIGNED),
- make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) }),
- make("NumberOfExtraRuns", { 0, 1 }),
- make("LhsQInfo", { QuantizationInfo(1.f / 40, -2) }),
- make("RhsQInfo", { QuantizationInfo(1.f / 50, 1) }),
- make("OutQInfo", { QuantizationInfo(1.f, 1) }))
-)
+FIXTURE_DATA_TEST_CASE(RunSmallExtraActivation,
+ NEQuantizedMatMulFixture<int8_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::SmallerMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::QASYMM8_SIGNED),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU)
+}),
+make("NumberOfExtraRuns", {0, 1}),
+make("LhsQInfo", {QuantizationInfo(1.f / 40, -2)}),
+make("RhsQInfo", {QuantizationInfo(1.f / 50, 1)}),
+make("OutQInfo", {QuantizationInfo(1.f, 1)})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEQuantizedMatMulFixture<int8_t>, framework::DatasetMode::NIGHTLY,
- combine(
- datasets::LargeMatMulDataset(),
- make("TransposeA", { false, true }),
- make("TransposeB", { false, true }),
- make("DataType", DataType::QASYMM8_SIGNED),
- make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }),
- make("NumberOfExtraRuns", { 0, 1 }),
- make("LhsQInfo", { QuantizationInfo(1.f / 150, -2) }),
- make("RhsQInfo", { QuantizationInfo(1.f / 250, 1) }),
- make("OutQInfo", { QuantizationInfo(1.f, 1) }))
-)
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ NEQuantizedMatMulFixture<int8_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(datasets::LargeMatMulDataset(),
+ make("TransposeA", {false, true}),
+ make("TransposeB", {false, true}),
+ make("DataType", DataType::QASYMM8_SIGNED),
+ make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+}),
+make("NumberOfExtraRuns", {0, 1}),
+make("LhsQInfo", {QuantizationInfo(1.f / 150, -2)}),
+make("RhsQInfo", {QuantizationInfo(1.f / 250, 1)}),
+make("OutQInfo", {QuantizationInfo(1.f, 1)})))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
@@ -372,7 +456,7 @@
TEST_SUITE_END() // QASYMM8_SIGNED
TEST_SUITE_END() // Quantized
-#endif // __aarch64__
+#endif // __aarch64__
TEST_SUITE_END() // MatMul
TEST_SUITE_END() // NEON