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-rw-r--r--tests/validation/CL/GEMMLowp.cpp29
-rw-r--r--tests/validation/NEON/GEMMLowp.cpp6
-rw-r--r--tests/validation/fixtures/GEMMLowpFixture.h59
-rw-r--r--tests/validation/reference/GEMMLowp.cpp43
-rw-r--r--tests/validation/reference/GEMMLowp.h18
5 files changed, 90 insertions, 65 deletions
diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp
index 2890eb161b..eb42c4c659 100644
--- a/tests/validation/CL/GEMMLowp.cpp
+++ b/tests/validation/CL/GEMMLowp.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -44,11 +44,14 @@ namespace test
{
namespace validation
{
+namespace
+{
+constexpr AbsoluteTolerance<float> tolerance_quant(1); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
+}
TEST_SUITE(CL)
TEST_SUITE(GEMMLowp)
TEST_SUITE(MatrixMultiplyCore)
-
using CLGEMMLowpMatrixMultiplyCoreFixture = GEMMLowpMatrixMultiplyCoreValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, datasets::SmallGEMMLowpDataset(),
@@ -84,21 +87,33 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFixture, framework:
validate(CLAccessor(_target), _reference);
}
-using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;
TEST_SUITE(FusedOffsetOutput)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::ALL, combine(datasets::SmallGEMMLowpFusedOffsetOutputDataset(),
+TEST_SUITE(QASYMM8)
+using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture, framework::DatasetMode::ALL, combine(datasets::SmallGEMMLowpFusedOffsetOutputUint8Dataset(),
framework::dataset::make("DataType", { DataType::QASYMM8 })))
{
// Validate output
- validate(CLAccessor(_target), _reference);
+ validate(CLAccessor(_target), _reference, tolerance_quant);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGEMMLowpFusedOffsetOutputDataset(),
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGEMMLowpFusedOffsetOutputUint8Dataset(),
framework::dataset::make("DataType", { DataType::QASYMM8 })))
{
// Validate output
- validate(CLAccessor(_target), _reference);
+ validate(CLAccessor(_target), _reference, tolerance_quant);
+}
+TEST_SUITE_END() // QASYMM8
+TEST_SUITE(QASYMM8_SIGNED)
+using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputInt8Fixture =
+ GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore, false, false, int8_t, int8_t>;
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputInt8Fixture, framework::DatasetMode::ALL, combine(datasets::SmallGEMMLowpFusedOffsetOutputInt8Dataset(),
+ framework::dataset::make("DataType", { DataType::QASYMM8_SIGNED })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_quant);
}
+TEST_SUITE_END() // QASYMM8_SIGNED
TEST_SUITE_END() // FusedOffsetOutput
TEST_SUITE(Output3D)
diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp
index 78fbc5845f..10f2284914 100644
--- a/tests/validation/NEON/GEMMLowp.cpp
+++ b/tests/validation/NEON/GEMMLowp.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -147,14 +147,14 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpMatrixMultiplyCoreFixture, framework:
using NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture<Tensor, Accessor, NEGEMMLowpMatrixMultiplyCore>;
TEST_SUITE(FusedOffsetOutput)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::ALL, combine(datasets::SmallGEMMLowpFusedOffsetOutputDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::ALL, combine(datasets::SmallGEMMLowpFusedOffsetOutputUint8Dataset(),
framework::dataset::make("DataType", { DataType::QASYMM8 })))
{
// Validate output
validate(Accessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGEMMLowpFusedOffsetOutputDataset(),
+FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpMatrixMultiplyCoreFusedOffsetOutputFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGEMMLowpFusedOffsetOutputUint8Dataset(),
framework::dataset::make("DataType", { DataType::QASYMM8 })))
{
// Validate output
diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index b93a6447d7..1154d6c8de 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -91,12 +91,15 @@ void fill(U &&tensor, int i)
template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d, bool reinterpret_output_as_3d, typename OutputType, bool is_fused = false>
TensorType compute_gemmlowp_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
- GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo(), DataType data_type_b = DataType::QASYMM8, QuantizationInfo b_qinfo = QuantizationInfo())
+ GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo(), DataType data_type_a = DataType::QASYMM8, DataType data_type_b = DataType::QASYMM8,
+ QuantizationInfo b_qinfo = QuantizationInfo())
{
// Create tensors
- TensorType a = create_tensor<TensorType>(shape_a, DataType::QASYMM8, 1);
+ DataType data_type_output = output_stage.type == GEMMLowpOutputStageType::NONE ? DataType::S32 : data_type_a;
+
+ TensorType a = create_tensor<TensorType>(shape_a, data_type_a, 1);
TensorType b = create_tensor<TensorType>(shape_b, data_type_b, 1); // gemm output before output stage mismatch if i pass data_layout_output here. to be investigated
- TensorType output = create_tensor<TensorType>(shape_output, output_stage.type == GEMMLowpOutputStageType::NONE ? DataType::S32 : DataType::QASYMM8, 1);
+ TensorType output = create_tensor<TensorType>(shape_output, data_type_output, 1);
a.info()->set_quantization_info(QuantizationInfo(1.0f / 255, a_offset));
@@ -150,9 +153,9 @@ TensorType compute_gemmlowp_target(const TensorShape &shape_a, const TensorShape
return output;
}
-template <bool reinterpret_input_as_3d, typename TW = uint8_t>
+template <bool reinterpret_input_as_3d, typename TI = uint8_t, typename TW = uint8_t>
SimpleTensor<int32_t> compute_gemmlowp_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
- DataType data_type_b = DataType::QASYMM8, QuantizationInfo b_qinfo = QuantizationInfo())
+ DataType data_type_a = DataType::QASYMM8, DataType data_type_b = DataType::QASYMM8, QuantizationInfo b_qinfo = QuantizationInfo())
{
TensorShape shape_a_to_use = shape_a;
if(reinterpret_input_as_3d)
@@ -162,13 +165,13 @@ SimpleTensor<int32_t> compute_gemmlowp_reference(const TensorShape &shape_a, con
}
// Create reference
- SimpleTensor<uint8_t> a{ shape_a_to_use, DataType::QASYMM8, 1 };
- SimpleTensor<TW> b{ shape_b, data_type_b, 1, data_type_b == DataType::QSYMM8_PER_CHANNEL ? b_qinfo : QuantizationInfo(1.0f / 255, b_offset) };
+ SimpleTensor<TI> a{ shape_a_to_use, data_type_a, 1 };
+ SimpleTensor<TW> b{ shape_b, data_type_b, 1, data_type_b == DataType::QSYMM8_PER_CHANNEL ? b_qinfo : QuantizationInfo(1.0f / 255, b_offset) };
// Fill reference
fill(a, 0);
fill(b, 1);
- return reference::gemmlowp_matrix_multiply_core<int32_t, uint8_t, TW>(a, b, shape_output, a_offset, b_offset);
+ return reference::gemmlowp_matrix_multiply_core<int32_t, TI, TW>(a, b, shape_output, a_offset, b_offset);
}
}
@@ -198,7 +201,7 @@ protected:
SimpleTensor<int32_t> _reference{};
};
-template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d = false, bool reinterpret_output_as_3d = false, typename TW = uint8_t>
+template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d = false, bool reinterpret_output_as_3d = false, typename TI = uint8_t, typename TW = uint8_t>
class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture : public framework::Fixture
{
public:
@@ -206,6 +209,8 @@ public:
void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage, DataType data_type_b)
{
ARM_COMPUTE_EXPECT(output_stage.type != GEMMLowpOutputStageType::NONE, framework::LogLevel::ERRORS);
+ DataType data_type_a = data_type_b == DataType::QASYMM8_SIGNED ? DataType::QASYMM8_SIGNED : DataType::QASYMM8;
+
if(data_type_b == DataType::QSYMM8_PER_CHANNEL)
{
output_stage.is_quantized_per_channel = true;
@@ -220,28 +225,28 @@ public:
quantization::calculate_quantized_multiplier(scales[i], &output_stage.gemmlowp_multipliers[i], &output_stage.gemmlowp_shifts[i]);
}
- _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_b, QuantizationInfo(scales));
- _target = compute_target(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_b, QuantizationInfo(scales));
+ _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales));
+ _target = compute_target(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales));
}
else
{
- _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_b, QuantizationInfo());
- _target = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_b, QuantizationInfo());
+ _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo());
+ _target = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo());
}
}
protected:
TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage,
- DataType data_type_b, QuantizationInfo b_qinfo)
+ DataType data_type_a, DataType data_type_b, QuantizationInfo b_qinfo)
{
return compute_gemmlowp_target<TensorType, AccessorType, FunctionType, reinterpret_input_as_3d, reinterpret_output_as_3d, qasymm8_t, true>(shape_a, shape_b, shape_output, a_offset, b_offset,
- output_stage, data_type_b, b_qinfo);
+ output_stage, data_type_a, data_type_b, b_qinfo);
}
- SimpleTensor<qasymm8_t> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
- GEMMLowpOutputStageInfo output_stage, DataType data_type_b, QuantizationInfo b_qinfo)
+ SimpleTensor<TI> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
+ GEMMLowpOutputStageInfo output_stage, DataType data_type_a, DataType data_type_b, QuantizationInfo b_qinfo)
{
- SimpleTensor<int32_t> output = compute_gemmlowp_reference<reinterpret_input_as_3d, TW>(shape_a, shape_b, shape_output, a_offset, b_offset, data_type_b, b_qinfo);
+ SimpleTensor<int32_t> output = compute_gemmlowp_reference<reinterpret_input_as_3d, TI, TW>(shape_a, shape_b, shape_output, a_offset, b_offset, data_type_a, data_type_b, b_qinfo);
TensorShape bias_shape(shape_b[0]);
SimpleTensor<int32_t> bias{ bias_shape, DataType::S32, 1 };
@@ -250,20 +255,20 @@ protected:
switch(output_stage.type)
{
case GEMMLowpOutputStageType::QUANTIZE_DOWN:
- return reference::gemmlowp_quantize_down_int32_to_uint8_scale<int32_t>(output, bias,
- output_stage.gemmlowp_offset, output_stage.gemmlowp_multipliers, output_stage.gemmlowp_shifts, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound);
+ return reference::gemmlowp_quantize_down_scale<int32_t, TW>(output, bias,
+ output_stage.gemmlowp_offset, output_stage.gemmlowp_multipliers, output_stage.gemmlowp_shifts, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound);
break;
case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT:
- return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, uint8_t>(output, bias,
- output_stage.gemmlowp_multipliers, output_stage.gemmlowp_shifts, output_stage.gemmlowp_offset, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound);
+ return reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, TW>(output, bias,
+ output_stage.gemmlowp_multipliers, output_stage.gemmlowp_shifts, output_stage.gemmlowp_offset, output_stage.gemmlowp_min_bound, output_stage.gemmlowp_max_bound);
break;
default:
ARM_COMPUTE_ERROR("Not Supported!");
}
}
- TensorType _target{};
- SimpleTensor<qasymm8_t> _reference{};
+ TensorType _target{};
+ SimpleTensor<TI> _reference{};
};
template <typename TensorType, typename AccessorType, typename FunctionType>
@@ -348,11 +353,11 @@ protected:
// Fill bias
fill(b, 1);
- return reference::gemmlowp_quantize_down_int32_to_uint8_scale<int32_t>(a, b, result_offset, result_mult_int_vec, result_shift_vec, min, max);
+ return reference::gemmlowp_quantize_down_scale<int32_t, uint8_t>(a, b, result_offset, result_mult_int_vec, result_shift_vec, min, max);
}
else
{
- return reference::gemmlowp_quantize_down_int32_to_uint8_scale<int32_t>(a, result_offset, result_mult_int_vec, result_shift_vec, min, max);
+ return reference::gemmlowp_quantize_down_scale<int32_t, uint8_t>(a, result_offset, result_mult_int_vec, result_shift_vec, min, max);
}
}
diff --git a/tests/validation/reference/GEMMLowp.cpp b/tests/validation/reference/GEMMLowp.cpp
index 4529b91a48..99d08e34f1 100644
--- a/tests/validation/reference/GEMMLowp.cpp
+++ b/tests/validation/reference/GEMMLowp.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -60,9 +60,9 @@ struct DataTypeExtractor
}
};
-template <typename T>
-void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_offset, std::vector<int32_t> result_mult_int,
- std::vector<int32_t> result_shift, int32_t min, int32_t max)
+template <typename TIn, typename TOut>
+void quantize_down_scale(const SimpleTensor<TIn> *in, const SimpleTensor<TIn> *bias, SimpleTensor<TOut> *dst, int32_t result_offset, std::vector<int32_t> result_mult_int,
+ std::vector<int32_t> result_shift, int32_t min, int32_t max)
{
const int cols_in = in->shape().x();
const bool is_per_channel = result_mult_int.size() > 1;
@@ -86,7 +86,8 @@ void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleT
result = std::max(min, std::min(max, result));
}
- (*dst)[i] = static_cast<uint8_t>(std::max(0, std::min(255, result)));
+ (*dst)[i] = static_cast<TOut>(std::max<TIn>(std::numeric_limits<TOut>::lowest(),
+ std::min<TIn>(std::numeric_limits<TOut>::max(), result)));
}
}
@@ -192,24 +193,24 @@ SimpleTensor<T1> gemmlowp(const SimpleTensor<T2> &a, const SimpleTensor<T3> &b,
return gemmlowp_matrix_multiply_core<T1, T2, T3>(a, b, shape_c, 0, 0);
}
-template <typename T>
-SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<int32_t> result_shift,
- int32_t min, int32_t max)
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale(const SimpleTensor<TIn> &in, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<int32_t> result_shift,
+ int32_t min, int32_t max)
{
- SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8);
+ SimpleTensor<TOut> dst(in.shape(), DataTypeExtractor<TOut>::data_type());
- quantize_down_int32_to_uint8_scale<T>(&in, nullptr, &dst, result_offset, result_mult_int, result_shift, min, max);
+ quantize_down_scale<TIn, TOut>(&in, nullptr, &dst, result_offset, result_mult_int, result_shift, min, max);
return dst;
}
-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, std::vector<int32_t> result_mult_int,
- std::vector<int32_t> result_shift, int32_t min, int32_t max)
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale(const SimpleTensor<TIn> &in, const SimpleTensor<TIn> &bias, int32_t result_offset, std::vector<int32_t> result_mult_int,
+ std::vector<int32_t> result_shift, int32_t min, int32_t max)
{
- SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8);
+ SimpleTensor<TOut> dst(in.shape(), DataTypeExtractor<TOut>::data_type());
- quantize_down_int32_to_uint8_scale<T>(&in, &bias, &dst, result_offset, result_mult_int, result_shift, min, max);
+ quantize_down_scale<TIn, TOut>(&in, &bias, &dst, result_offset, result_mult_int, result_shift, min, max);
return dst;
}
@@ -251,10 +252,14 @@ template SimpleTensor<int16_t> gemmlowp_quantize_down_scale_by_fixedpoint(const
template SimpleTensor<int16_t> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b,
std::vector<int32_t> result_fixedpoint_multiplier,
std::vector<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, std::vector<int32_t> result_mult_int,
- std::vector<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, std::vector<int32_t> result_mult_int,
- std::vector<int32_t> result_shift, int32_t min, int32_t max);
+template SimpleTensor<uint8_t> gemmlowp_quantize_down_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, std::vector<int32_t> result_mult_int,
+ std::vector<int32_t> result_shift, int32_t min, int32_t max);
+template SimpleTensor<uint8_t> gemmlowp_quantize_down_scale(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_offset, std::vector<int32_t> result_mult_int,
+ std::vector<int32_t> result_shift, int32_t min, int32_t max);
+template SimpleTensor<int8_t> gemmlowp_quantize_down_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, std::vector<int32_t> result_mult_int,
+ std::vector<int32_t> result_shift, int32_t min, int32_t max);
+template SimpleTensor<int8_t> gemmlowp_quantize_down_scale(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_offset, std::vector<int32_t> result_mult_int,
+ std::vector<int32_t> result_shift, int32_t min, int32_t max);
template SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b, TensorShape shape_c, int32_t a_offset, int32_t b_offset);
template SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<uint8_t> &a, const SimpleTensor<uint8_t> &b, TensorShape shape_c, int32_t a_offset, int32_t b_offset);
template SimpleTensor<int32_t> gemmlowp<int32_t, int8_t, int8_t>(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b, TensorShape shape_c);
diff --git a/tests/validation/reference/GEMMLowp.h b/tests/validation/reference/GEMMLowp.h
index 7b4b1c5c71..7d711263e8 100644
--- a/tests/validation/reference/GEMMLowp.h
+++ b/tests/validation/reference/GEMMLowp.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -41,16 +41,16 @@ SimpleTensor<T1> gemmlowp_matrix_multiply_core(const SimpleTensor<T2> &a, const
template <typename T1, typename T2, typename T3 = T2>
SimpleTensor<T1> gemmlowp(const SimpleTensor<T2> &a, const SimpleTensor<T3> &b, TensorShape shape_c);
-template <typename T>
-SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<int32_t> result_shift);
+template <typename TIn, typename TOut>
+SimpleTensor<uint8_t> gemmlowp_quantize_down_scale(const SimpleTensor<TIn> &in, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<int32_t> result_shift);
-template <typename T>
-SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<int32_t> result_shift,
- int32_t min = 0, int32_t max = 0);
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale(const SimpleTensor<TIn> &in, int32_t result_offset, std::vector<int32_t> result_mult_int, std::vector<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(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_offset, std::vector<int32_t> result_mult_int,
- std::vector<int32_t> result_shift, int32_t min = 0, int32_t max = 0);
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale(const SimpleTensor<TIn> &in, const SimpleTensor<TIn> &bias, int32_t result_offset, std::vector<int32_t> result_mult_int,
+ std::vector<int32_t> result_shift, int32_t min = 0, int32_t max = 0);
template <typename TIn, typename TOut>
SimpleTensor<TOut> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> &in, std::vector<int32_t> result_fixedpoint_multiplier, std::vector<int32_t> result_shift,
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-16 21:29:11 +0000