COMPMID-2966 Add support for QASYMM8_SIGNED in NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel
Signed-off-by: Luca Foschiani <luca.foschiani@arm.com>
Change-Id: Ia8692f8fda16fa3b73f343e4b5b1b55e14403225
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2750
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp
index 8aa81d0..41a441c 100644
--- a/tests/validation/CL/GEMMLowp.cpp
+++ b/tests/validation/CL/GEMMLowp.cpp
@@ -147,6 +147,65 @@
TEST_SUITE(OutputStage)
+TEST_SUITE(QuantizeDownInt32Scale)
+
+TEST_SUITE(QASYMM8)
+
+const auto quantize_down_int32_to_uint8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_shift", 2,
+ 3)
+ * framework::dataset::make("min", 0) * framework::dataset::make("max", 255) * framework::dataset::make("addBias", { false, true });
+
+const auto quantize_down_int32_to_uint8_scale_relu_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1,
+ 2)
+ * framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 173) * framework::dataset::make("addBias", { false, true });
+
+using CLGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture<CLTensor, CLAccessor, CLGEMMLowpOutputStage>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+TEST_SUITE(BoundedReLu)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+TEST_SUITE_END() // BoundedReLu
+TEST_SUITE_END() // QASYMM8
+
+TEST_SUITE(QASYMM8_SIGNED)
+
+const auto quantize_down_int32_to_int8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_shift", 2,
+ 3)
+ * framework::dataset::make("min", -128) * framework::dataset::make("max", 127) * framework::dataset::make("addBias", { false, true });
+
+const auto quantize_down_int32_to_int8_scale_relu_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1,
+ 2)
+ * framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", -100, -98) * framework::dataset::make("max", 71, 73) * framework::dataset::make("addBias", { false, true });
+
+using CLGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToInt8ScaleValidationFixture<CLTensor, CLAccessor, CLGEMMLowpOutputStage>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+TEST_SUITE(BoundedReLu)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_relu_cases))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference);
+}
+
+TEST_SUITE_END() // BoundedReLu
+TEST_SUITE_END() // QASYMM8_SIGNED
+TEST_SUITE_END() // QuantizeDownInt32Scale
+
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)
diff --git a/tests/validation/NEON/GEMMLowp.cpp b/tests/validation/NEON/GEMMLowp.cpp
index de30bd5..c3747dd 100644
--- a/tests/validation/NEON/GEMMLowp.cpp
+++ b/tests/validation/NEON/GEMMLowp.cpp
@@ -165,7 +165,9 @@
TEST_SUITE(OutputStage)
-TEST_SUITE(QuantizeDownInt32ToUint8Scale)
+TEST_SUITE(QuantizeDownInt32Scale)
+
+TEST_SUITE(QASYMM8)
const auto quantize_down_int32_to_uint8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_shift", 2,
3)
@@ -175,7 +177,7 @@
2)
* framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 174) * framework::dataset::make("addBias", { false, true });
-using NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture<Tensor, Accessor, NEGEMMLowpQuantizeDownInt32ToUint8Scale>;
+using NEGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture<Tensor, Accessor, NEGEMMLowpOutputStage>;
// *INDENT-OFF*
// clang-format off
@@ -198,85 +200,112 @@
framework::dataset::make("Expected", { true, false })),
a_info, b_info, output_info, min, max, expected)
{
+
+ GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo();
+ output_stage.type = GEMMLowpOutputStageType::QUANTIZE_DOWN;
+ output_stage.gemmlowp_min_bound = min;
+ output_stage.gemmlowp_max_bound = max;
+ output_stage.output_data_type = DataType::QASYMM8;
+
// Lock tensors
- Status status = NEGEMMLowpQuantizeDownInt32ToUint8Scale::validate(&a_info.clone()->set_is_resizable(false),
+ Status status = NEGEMMLowpOutputStage::validate(&a_info.clone()->set_is_resizable(false),
&b_info.clone()->set_is_resizable(false),
&output_info.clone()->set_is_resizable(false),
- min,
- max);
+ output_stage);
ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases),
- shape, result_offset, result_mult_int, result_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
- NEGEMMLowpQuantizeDownInt32ToUint8Scale output_stage;
- output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_offset, result_mult_int, result_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(0);
- validate(in.info()->padding(), padding);
- validate(out.info()->padding(), padding);
-
- if(add_bias)
- {
- validate(bias.info()->padding(), padding);
- }
-}
-
-FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases))
-{
- // Validate output
- validate(Accessor(_target), _reference);
-}
-
-FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases))
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases))
{
// Validate output
validate(Accessor(_target), _reference);
}
TEST_SUITE(BoundedReLu)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
{
// Validate output
validate(Accessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_relu_cases))
-{
- // Validate output
- validate(Accessor(_target), _reference);
-}
TEST_SUITE_END() // BoundedReLu
-TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale
+TEST_SUITE_END() // QASYMM8
+
+TEST_SUITE(QASYMM8_SIGNED)
+
+const auto quantize_down_int32_to_int8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_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_int8_scale_relu_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1,
+ 2)
+ * framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", -100, -98) * framework::dataset::make("max", 71, 74) * framework::dataset::make("addBias", { false, true });
+
+using NEGEMMLowpQuantizeDownInt32ScaleFixture = GEMMLowpQuantizeDownInt32ToInt8ScaleValidationFixture<Tensor, Accessor, NEGEMMLowpOutputStage>;
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
+ framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Input not a multiple of 16
+ TensorInfo(TensorShape(21U, 13U), 1, DataType::S32), // Invalid min and max
+ TensorInfo(TensorShape(20U, 13U), 1, DataType::S32), // Wrong output data type
+ }),
+ framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(21U), 1, DataType::S32),
+ TensorInfo(TensorShape(21U), 1, DataType::S32),
+ TensorInfo(TensorShape(20U), 1, DataType::S32),
+ })),
+ framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8_SIGNED),
+ TensorInfo(TensorShape(21U, 13U), 1, DataType::QASYMM8_SIGNED),
+ TensorInfo(TensorShape(20U, 13U), 1, DataType::S32),
+ })),
+ framework::dataset::make("Min",{ -10,
+ -200,
+ -113,
+ })),
+ framework::dataset::make("Max",{ 105,
+ 300,
+ -18,
+ })),
+ framework::dataset::make("Expected", { true, false, false })),
+ a_info, b_info, output_info, min, max, expected)
+{
+ GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo();
+ output_stage.type = GEMMLowpOutputStageType::QUANTIZE_DOWN;
+ output_stage.gemmlowp_min_bound = min;
+ output_stage.gemmlowp_max_bound = max;
+ output_stage.output_data_type = DataType::QASYMM8_SIGNED;
+
+ // Lock tensors
+ Status status = NEGEMMLowpOutputStage::validate(&a_info.clone()->set_is_resizable(false),
+ &b_info.clone()->set_is_resizable(false),
+ &output_info.clone()->set_is_resizable(false),
+ output_stage);
+ ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+
+TEST_SUITE(BoundedReLu)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMLowpQuantizeDownInt32ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_int8_scale_relu_cases))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+
+TEST_SUITE_END() // BoundedReLu
+
+TEST_SUITE_END() // QASYMM8_SIGNED
+
+TEST_SUITE_END() // QuantizeDownInt32Scale
TEST_SUITE(QuantizeDownInt32ToUint8ScaleByFixedPoint)
diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index be9ce96..e3dc738 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -301,8 +301,16 @@
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_offset, result_mult_int, result_shift, min, max);
+ FunctionType output_stage;
+ GEMMLowpOutputStageInfo output_stage_info = GEMMLowpOutputStageInfo();
+ output_stage_info.type = GEMMLowpOutputStageType::QUANTIZE_DOWN;
+ output_stage_info.gemmlowp_offset = result_offset;
+ output_stage_info.gemmlowp_multiplier = result_mult_int;
+ output_stage_info.gemmlowp_shift = result_shift;
+ output_stage_info.gemmlowp_min_bound = min;
+ output_stage_info.gemmlowp_max_bound = max;
+ output_stage_info.output_data_type = DataType::QASYMM8;
+ output_stage.configure(&a, add_bias ? &b : nullptr, &c, output_stage_info);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -367,6 +375,108 @@
};
template <typename TensorType, typename AccessorType, typename FunctionType>
+class GEMMLowpQuantizeDownInt32ToInt8ScaleValidationFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, int32_t min, int32_t max, bool add_bias)
+ {
+ _target = compute_target(shape, result_offset, result_mult_int, result_shift, min, max, add_bias);
+ _reference = compute_reference(shape, result_offset, result_mult_int, result_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_offset, int32_t result_mult_int, int32_t result_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_SIGNED, 1);
+
+ // Create and configure function
+ FunctionType output_stage;
+ GEMMLowpOutputStageInfo output_stage_info = GEMMLowpOutputStageInfo();
+ output_stage_info.type = GEMMLowpOutputStageType::QUANTIZE_DOWN;
+ output_stage_info.gemmlowp_offset = result_offset;
+ output_stage_info.gemmlowp_multiplier = result_mult_int;
+ output_stage_info.gemmlowp_shift = result_shift;
+ output_stage_info.gemmlowp_min_bound = min;
+ output_stage_info.gemmlowp_max_bound = max;
+ output_stage_info.output_data_type = DataType::QASYMM8_SIGNED;
+ output_stage.configure(&a, add_bias ? &b : nullptr, &c, output_stage_info);
+
+ 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<int8_t> compute_reference(const TensorShape &shape, int32_t result_offset, int32_t result_mult_int, int32_t result_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);
+
+ const std::vector<int32_t> result_mult_int_vec = { result_mult_int };
+ const std::vector<int32_t> result_shift_vec = { result_shift };
+
+ if(add_bias)
+ {
+ // Fill bias
+ fill(b, 1);
+
+ return reference::gemmlowp_quantize_down_scale<int32_t, int8_t>(a, b, result_offset, result_mult_int_vec, result_shift_vec, min, max);
+ }
+ else
+ {
+ return reference::gemmlowp_quantize_down_scale<int32_t, int8_t>(a, result_offset, result_mult_int_vec, result_shift_vec, min, max);
+ }
+ }
+
+ TensorType _target{};
+ SimpleTensor<int8_t> _reference{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType>
class GEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointValidationFixture : public framework::Fixture
{
public: