COMPMID-661: Add avgpool-uint8 support. Optimize avgpool-fp32 for Bifrost. (#13)
Change-Id: I32ba6afbac6694ffa053dd16f03a1b3d14627a19
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/94857
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/tests/validation/CL/PoolingLayer.cpp b/tests/validation/CL/PoolingLayer.cpp
index 7038f2c..b3d5612 100644
--- a/tests/validation/CL/PoolingLayer.cpp
+++ b/tests/validation/CL/PoolingLayer.cpp
@@ -43,19 +43,26 @@
{
namespace
{
-/** Input data set for float data types */
+/** Input data set for floating-point data types */
const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 4, 7, 9 })),
framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
framework::dataset::make("ExcludePadding", { true, false }));
-/** Input data set for quantized data types */
+/** Input data set for fixed-point data types */
const auto PoolingLayerDatasetQS = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })),
framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
framework::dataset::make("ExcludePadding", { true, false }));
-constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for float types */
-constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for float types */
-constexpr AbsoluteTolerance<float> tolerance_qs8(3); /**< Tolerance value for comparing reference's output against implementation's output for quantized input */
-constexpr AbsoluteTolerance<float> tolerance_qs16(6); /**< Tolerance value for comparing reference's output against implementation's output for quantized input */
+
+/** Input data set for asymmetric data type */
+const auto PoolingLayerDatasetQASYMM8 = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })),
+ framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
+ framework::dataset::make("ExcludePadding", { true, false }));
+
+constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for 32-bit floating-point type */
+constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */
+constexpr AbsoluteTolerance<float> tolerance_qs16(6); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit fixed-point type */
+constexpr AbsoluteTolerance<float> tolerance_qs8(3); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit fixed-point type */
+constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit asymmetric type */
} // namespace
TEST_SUITE(CL)
@@ -64,12 +71,13 @@
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 4),
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 4), // Mismatching fixed point position
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS16, 11),
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid pad/size combination
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid pad/size combination
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8, 0), // Invalid parameters
}),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16, 0),
TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0),
@@ -77,6 +85,7 @@
TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::QS16, 11),
TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32, 0),
TensorInfo(TensorShape(25U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8, 0),
})),
framework::dataset::make("PoolInfo", { PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 0, 0)),
PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 0, 0)),
@@ -84,8 +93,9 @@
PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 0, 0)),
PoolingLayerInfo(PoolingType::AVG, 2, PadStrideInfo(1, 1, 2, 0)),
PoolingLayerInfo(PoolingType::AVG, 2, PadStrideInfo(1, 1, 0, 2)),
+ PoolingLayerInfo(PoolingType::L2, 3, PadStrideInfo(1, 1, 0, 0)),
})),
- framework::dataset::make("Expected", { true, false, true, false, true, true})),
+ framework::dataset::make("Expected", { true, false, true, false, true, true, true })),
input_info, output_info, pool_info, expected)
{
ARM_COMPUTE_EXPECT(bool(CLPoolingLayer::validate(&input_info, &output_info, pool_info)) == expected, framework::LogLevel::ERRORS);
@@ -131,7 +141,7 @@
template <typename T>
using CLPoolingLayerFixedPointFixture = PoolingLayerValidationFixedPointFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
-TEST_SUITE(Quantized)
+TEST_SUITE(FixedPoint)
TEST_SUITE(QS8)
FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQS,
framework::dataset::make("DataType", DataType::QS8))),
@@ -167,6 +177,31 @@
TEST_SUITE_END()
TEST_SUITE_END()
+TEST_SUITE(Quantized)
+
+template <typename T>
+using CLPoolingLayerQuantizedFixture = PoolingLayerValidationQuantizedFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
+
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQASYMM8,
+ framework::dataset::make("DataType", DataType::QASYMM8))),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127),
+ QuantizationInfo(7.f / 255, 123)
+ })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLPoolingLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), combine(PoolingLayerDatasetQASYMM8,
+ framework::dataset::make("DataType", DataType::QASYMM8))),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255, 0) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/CPP/PoolingLayer.cpp b/tests/validation/CPP/PoolingLayer.cpp
index 4f755ce..90a48e0 100644
--- a/tests/validation/CPP/PoolingLayer.cpp
+++ b/tests/validation/CPP/PoolingLayer.cpp
@@ -25,6 +25,7 @@
#include "arm_compute/core/Types.h"
#include "tests/validation/FixedPoint.h"
+#include "tests/validation/Helpers.h"
namespace arm_compute
{
@@ -277,6 +278,15 @@
return dst;
}
+template <>
+SimpleTensor<uint8_t> pooling_layer<uint8_t>(const SimpleTensor<uint8_t> &src, PoolingLayerInfo info)
+{
+ SimpleTensor<float> src_tmp = convert_from_asymmetric(src);
+ SimpleTensor<float> dst_tmp = pooling_layer<float>(src_tmp, info);
+ SimpleTensor<uint8_t> dst = convert_to_asymmetric(dst_tmp, src.quantization_info());
+ return dst;
+}
+
template SimpleTensor<float> pooling_layer(const SimpleTensor<float> &src, PoolingLayerInfo info);
template SimpleTensor<half> pooling_layer(const SimpleTensor<half> &src, PoolingLayerInfo info);
template SimpleTensor<qint8_t> pooling_layer(const SimpleTensor<qint8_t> &src, PoolingLayerInfo info);
diff --git a/tests/validation/Helpers.cpp b/tests/validation/Helpers.cpp
index 23ad62a..3ef5fc1 100644
--- a/tests/validation/Helpers.cpp
+++ b/tests/validation/Helpers.cpp
@@ -112,6 +112,27 @@
return params;
}
+
+SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint8_t> &src)
+{
+ const QuantizationInfo &quantization_info = src.quantization_info();
+ SimpleTensor<float> dst{ src.shape(), DataType::F32, 1, 0 };
+ for(int i = 0; i < src.num_elements(); ++i)
+ {
+ dst[i] = quantization_info.dequantize(src[i]);
+ }
+ return dst;
+}
+
+SimpleTensor<uint8_t> convert_to_asymmetric(const SimpleTensor<float> &src, const QuantizationInfo &quantization_info)
+{
+ SimpleTensor<uint8_t> dst{ src.shape(), DataType::QASYMM8, 1, 0, quantization_info };
+ for(int i = 0; i < src.num_elements(); ++i)
+ {
+ dst[i] = quantization_info.quantize(src[i]);
+ }
+ return dst;
+}
} // namespace validation
} // namespace test
} // namespace arm_compute
diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h
index eecf976..6b1c4b9 100644
--- a/tests/validation/Helpers.h
+++ b/tests/validation/Helpers.h
@@ -201,6 +201,23 @@
return bounds;
}
+
+/** Convert quantized simple tensor into float using tensor quantization information.
+ *
+ * @param[in] src Quantized tensor.
+ *
+ * @return Float tensor.
+*/
+SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint8_t> &src);
+
+/** Convert float simple tensor into quantized using specified quantization information.
+ *
+ * @param[in] src Float tensor.
+ * @param[in] quantization_info Quantification information.
+ *
+ * @return Quantized tensor.
+*/
+SimpleTensor<uint8_t> convert_to_asymmetric(const SimpleTensor<float> &src, const QuantizationInfo &quantization_info);
} // namespace validation
} // namespace test
} // namespace arm_compute
diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h
index 09b9e0e..d6190e2 100644
--- a/tests/validation/fixtures/PoolingLayerFixture.h
+++ b/tests/validation/fixtures/PoolingLayerFixture.h
@@ -43,28 +43,34 @@
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class PoolingLayerValidationFixedPointFixture : public framework::Fixture
+class PoolingLayerValidationGenericFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, int fractional_bits)
+ void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding,
+ DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
{
- _fractional_bits = fractional_bits;
+ _fractional_bits = fractional_bits;
+ _quantization_info = quantization_info;
PoolingLayerInfo info(pool_type, pool_size, pad_stride_info, exclude_padding);
- _target = compute_target(shape, info, data_type, fractional_bits);
- _reference = compute_reference(shape, info, data_type, fractional_bits);
+ _target = compute_target(shape, info, data_type, fractional_bits, quantization_info);
+ _reference = compute_reference(shape, info, data_type, fractional_bits, quantization_info);
}
protected:
template <typename U>
void fill(U &&tensor)
{
- if(_fractional_bits == 0)
+ if(!is_data_type_quantized(tensor.data_type()))
{
std::uniform_real_distribution<> distribution(-1.f, 1.f);
library->fill(tensor, distribution, 0);
}
+ else if(is_data_type_quantized_asymmetric(tensor.data_type()))
+ {
+ library->fill_tensor_uniform(tensor, 0);
+ }
else
{
const int one_fixed = 1 << _fractional_bits;
@@ -73,10 +79,11 @@
}
}
- TensorType compute_target(const TensorShape &shape, PoolingLayerInfo info, DataType data_type, int fixed_point_position = 0)
+ TensorType compute_target(const TensorShape &shape, PoolingLayerInfo info,
+ DataType data_type, int fixed_point_position, QuantizationInfo quantization_info)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
+ TensorType src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, quantization_info);
TensorType dst;
// Create and configure function
@@ -102,10 +109,11 @@
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, PoolingLayerInfo info, DataType data_type, int fixed_point_position = 0)
+ SimpleTensor<T> compute_reference(const TensorShape &shape, PoolingLayerInfo info,
+ DataType data_type, int fixed_point_position, QuantizationInfo quantization_info)
{
// Create reference
- SimpleTensor<T> src{ shape, data_type, 1, fixed_point_position };
+ SimpleTensor<T> src{ shape, data_type, 1, fixed_point_position, quantization_info };
// Fill reference
fill(src);
@@ -113,30 +121,56 @@
return reference::pooling_layer<T>(src, info);
}
- TensorType _target{};
- SimpleTensor<T> _reference{};
- int _fractional_bits{};
+ TensorType _target{};
+ SimpleTensor<T> _reference{};
+ int _fractional_bits{};
+ QuantizationInfo _quantization_info{};
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class PoolingLayerValidationFixture : public PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+class PoolingLayerValidationFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
template <typename...>
void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type)
{
- PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, exclude_padding, data_type, 0);
+ PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, exclude_padding,
+ data_type, 0, QuantizationInfo());
}
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class GlobalPoolingLayerValidationFixture : public PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+class PoolingLayerValidationFixedPointFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, int fractional_bits)
+ {
+ PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, exclude_padding,
+ data_type, fractional_bits, QuantizationInfo());
+ }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class PoolingLayerValidationQuantizedFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, QuantizationInfo quantization_info)
+ {
+ PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, exclude_padding,
+ data_type, 0, quantization_info);
+ }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class GlobalPoolingLayerValidationFixture : public PoolingLayerValidationFixture<TensorType, AccessorType, FunctionType, T>
{
public:
template <typename...>
void setup(TensorShape shape, PoolingType pool_type, DataType data_type)
{
- PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, shape.x(), PadStrideInfo(1, 1, 0, 0), true, data_type, 0);
+ PoolingLayerValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, shape.x(), PadStrideInfo(1, 1, 0, 0), true, data_type);
}
};
} // namespace validation