COMPMID-706 - Add GEMMLowp output stage for scaling by a fixed point number
DoD:
- Implement NEON kernel for quantizing down the gemmlowp result. The
result should be scaled by a fixedpoint number
- Implement OpenCL kernel for quantizing down the gemmlowp result. The
result should be scaled by a fixedpoint number
- Add test for validating the result
Required for:
- Integration of GEMMLowp in Android NN
- Convolution quantized
- Fully connected quantized
Change-Id: Ia963d25d695471e963961fb49a5600e78374ac4f
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110981
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp
index e3c686b..5148a31 100644
--- a/tests/validation/CL/GEMMLowp.cpp
+++ b/tests/validation/CL/GEMMLowp.cpp
@@ -137,34 +137,120 @@
}
}
-DISABLED_FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-DISABLED_FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
TEST_SUITE(BoundedReLu)
-DISABLED_FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-DISABLED_FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
- quantize_down_int32_to_uint8_scale_relu_cases))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
+ quantize_down_int32_to_uint8_scale_relu_cases))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
TEST_SUITE_END() // BoundedReLu
-
TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale
+
+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)
+ * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });
+
+const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
+ 2)
+ * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 174) * framework::dataset::make("addBias", { false, true });
+
+using CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture =
+ GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture<CLTensor, CLAccessor, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint>;
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_cases),
+ shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias)
+{
+ TensorShape shape_bias(shape[0]);
+
+ // Create tensors
+ CLTensor in = create_tensor<CLTensor>(shape, DataType::S32);
+ CLTensor bias = create_tensor<CLTensor>(shape_bias, DataType::S32);
+ CLTensor out = create_tensor<CLTensor>(shape, DataType::QASYMM8);
+
+ 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);
+
+ // Create and configure function
+ CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint output_stage;
+ output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+
+ // 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);
+
+ // 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);
+ }
+
+ // Validate padding
+ const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding();
+ validate(in.info()->padding(), padding);
+ validate(out.info()->padding(), padding);
+
+ if(add_bias)
+ {
+ validate(bias.info()->padding(), padding);
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+TEST_SUITE(BoundedReLu)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+TEST_SUITE_END() // BoundedReLu
+TEST_SUITE_END() // QuantizeDownInt32ToUint8ScaleByFixedPoint
+
TEST_SUITE_END() // OutputStage
TEST_SUITE_END() // GEMMLowp
TEST_SUITE_END() // CL
diff --git a/tests/validation/CPP/GEMMLowp.cpp b/tests/validation/CPP/GEMMLowp.cpp
index 35b8a64..9287894 100644
--- a/tests/validation/CPP/GEMMLowp.cpp
+++ b/tests/validation/CPP/GEMMLowp.cpp
@@ -24,6 +24,9 @@
#include "GEMMLowp.h"
#include "arm_compute/core/Types.h"
+#include "tests/validation/CPP/UtilsQuantizedAsymm.h"
+
+#include <limits>
namespace arm_compute
{
@@ -43,13 +46,15 @@
for(int i = 0; i < in->num_elements(); ++i)
{
- int32_t result = ((*in)[i] + result_offset) * result_mult_int;
+ int32_t result = ((*in)[i] + result_offset);
if(bias != nullptr)
{
result += (*bias)[i % cols_in];
}
+ result *= result_mult_int;
+
result >>= result_shift;
// Bounded ReLu
@@ -61,6 +66,35 @@
(*dst)[i] = static_cast<uint8_t>(std::max(0, std::min(255, result)));
}
}
+
+template <typename T>
+void quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_fixedpoint_multiplier, int32_t result_shift,
+ int32_t result_offset_after_shift, int32_t min, int32_t max)
+{
+ const int cols_in = in->shape().x();
+
+ for(int i = 0; i < in->num_elements(); ++i)
+ {
+ int32_t result = (*in)[i];
+
+ if(bias != nullptr)
+ {
+ result += (*bias)[i % cols_in];
+ }
+
+ // Fixed point multiplication
+ result = asymm_rounding_divide_by_pow2(asymm_int_mult(result, result_fixedpoint_multiplier), result_shift);
+ result += result_offset_after_shift;
+
+ // Bounded ReLu
+ if(min != max)
+ {
+ result = std::max(min, std::min(max, result));
+ }
+
+ (*dst)[i] = static_cast<uint8_t>(std::max(0, std::min(255, result)));
+ }
+}
} // namespace
template <typename T_out, typename T_in>
@@ -133,6 +167,33 @@
return dst;
}
+template <typename T>
+SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, int32_t result_fixedpoint_multiplier, int32_t result_shift,
+ int32_t result_offset_after_shift, int32_t min,
+ int32_t max)
+{
+ SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8);
+
+ quantize_down_int32_to_uint8_scale_by_fixedpoint<T>(&in, nullptr, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+
+ return dst;
+}
+
+template <typename T>
+SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_fixedpoint_multiplier, int32_t result_shift,
+ int32_t result_offset_after_shift, int32_t min, int32_t max)
+{
+ SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8);
+
+ quantize_down_int32_to_uint8_scale_by_fixedpoint<T>(&in, &bias, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+
+ return dst;
+}
+
+template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, int32_t result_fixedpoint_multiplier, int32_t result_shift,
+ int32_t result_offset_after_shift, int32_t min, int32_t max);
+template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_fixedpoint_multiplier,
+ int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min,
int32_t max);
template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_offset, int32_t result_mult_int,
diff --git a/tests/validation/CPP/GEMMLowp.h b/tests/validation/CPP/GEMMLowp.h
index 6c72b56..a3d0beb 100644
--- a/tests/validation/CPP/GEMMLowp.h
+++ b/tests/validation/CPP/GEMMLowp.h
@@ -49,6 +49,15 @@
template <typename T>
SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_offset, int32_t result_mult_int, int32_t result_shift,
int32_t min = 0, int32_t max = 0);
+
+template <typename T>
+SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, int32_t result_fixedpoint_multiplier, int32_t result_shift,
+ int32_t result_offset_after_shift,
+ int32_t min = 0, int32_t max = 0);
+
+template <typename T>
+SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_fixedpoint_multiplier, int32_t result_shift,
+ int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp
index 6d13fdc..a49ca46 100644
--- a/tests/validation/NEON/GEMMLowp.cpp
+++ b/tests/validation/NEON/GEMMLowp.cpp
@@ -255,6 +255,93 @@
TEST_SUITE_END() // BoundedReLu
TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale
+
+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)
+ * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0) * framework::dataset::make("max", 0) * framework::dataset::make("addBias", { false, true });
+
+const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1,
+ 2)
+ * framework::dataset::make("result_offset_after_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 174) * framework::dataset::make("addBias", { false, true });
+
+using NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture =
+ GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture<Tensor, Accessor, NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint>;
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_cases),
+ shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias)
+{
+ TensorShape shape_bias(shape[0]);
+
+ // Create tensors
+ Tensor in = create_tensor<Tensor>(shape, DataType::S32);
+ Tensor bias = create_tensor<Tensor>(shape_bias, DataType::S32);
+ Tensor out = create_tensor<Tensor>(shape, DataType::QASYMM8);
+
+ 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);
+
+ // Create and configure function
+ NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint output_stage;
+ output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+
+ // 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);
+
+ // 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);
+ }
+
+ // Validate padding
+ const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding();
+ validate(in.info()->padding(), padding);
+ validate(out.info()->padding(), padding);
+
+ if(add_bias)
+ {
+ validate(bias.info()->padding(), padding);
+ }
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+
+TEST_SUITE(BoundedReLu)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(),
+ quantize_down_int32_to_uint8_scale_by_fixedpoint_relu_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // BoundedReLu
+
+TEST_SUITE_END() // QuantizeDownInt32ToUint8ScaleByFixedPoint
TEST_SUITE_END() // OutputStage
TEST_SUITE_END() // GEMMLowp
diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index 60b89bc..d3e2aac 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -207,6 +207,98 @@
TensorType _target{};
SimpleTensor<uint8_t> _reference{};
};
+
+template <typename TensorType, typename AccessorType, typename FunctionType>
+class GEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointValidationFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, int32_t result_fixedpoint_multiplier, int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max, bool add_bias)
+ {
+ _target = compute_target(shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias);
+ _reference = compute_reference(shape, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max, add_bias);
+ }
+
+protected:
+ template <typename U>
+ 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_fixedpoint_multiplier, int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max, bool add_bias)
+ {
+ TensorShape shape_bias(shape[0]);
+
+ // Create tensors
+ TensorType a = create_tensor<TensorType>(shape, DataType::S32, 1);
+ TensorType b = create_tensor<TensorType>(shape_bias, DataType::S32, 1);
+ TensorType c = create_tensor<TensorType>(shape, DataType::QASYMM8, 1);
+
+ // Create and configure function
+ FunctionType output_stage;
+ output_stage.configure(&a, add_bias ? &b : nullptr, &c, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+
+ 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<uint8_t> compute_reference(const TensorShape &shape, int32_t result_fixed_point_multiplier, int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max,
+ bool add_bias)
+ {
+ // Create reference
+ TensorShape shape_bias(shape[0]);
+
+ SimpleTensor<int32_t> a{ shape, DataType::S32, 1 };
+ SimpleTensor<int32_t> b{ shape_bias, DataType::S32, 1 };
+
+ // Fill reference
+ fill(a, 0);
+
+ if(add_bias)
+ {
+ // Fill bias
+ fill(b, 1);
+
+ return reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(a, b, result_fixed_point_multiplier, result_shift, result_offset_after_shift, min, max);
+ }
+ else
+ {
+ return reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(a, result_fixed_point_multiplier, result_shift, result_offset_after_shift, min, max);
+ }
+ }
+
+ TensorType _target{};
+ SimpleTensor<uint8_t> _reference{};
+};
} // namespace validation
} // namespace test
} // namespace arm_compute