COMPMID-1574 Implement ReduceMean in OpenCL
Change-Id: Id331199f569f52a37280a9ada5bf84694580b93c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/152843
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
diff --git a/tests/validation/CL/ReduceMean.cpp b/tests/validation/CL/ReduceMean.cpp
new file mode 100644
index 0000000..07e859f
--- /dev/null
+++ b/tests/validation/CL/ReduceMean.cpp
@@ -0,0 +1,172 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/CLTensorAllocator.h"
+#include "arm_compute/runtime/CL/functions/CLReduceMean.h"
+
+#include "tests/CL/CLAccessor.h"
+#include "tests/datasets/ShapeDatasets.h"
+#include "tests/datasets/SplitDataset.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/ReduceMeanFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+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(0.03f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */
+constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit asymmetric quantized type */
+
+const auto axis_keep = combine(framework::dataset::make("Axis", { Coordinates(0), Coordinates(1, 0), Coordinates(1, 2), Coordinates(0, 2), Coordinates(1, 3), Coordinates(0, 1, 2, 3) }),
+ framework::dataset::make("KeepDims", { true }));
+const auto axis_drop = combine(framework::dataset::make("Axis", { Coordinates(0), Coordinates(1), Coordinates(3) }), framework::dataset::make("KeepDims", { false }));
+} // namespace
+TEST_SUITE(CL)
+TEST_SUITE(ReduceMean)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32), // Invalid axis
+ TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32), // Invalid output shape
+ TensorInfo(TensorShape(32U, 16U, 16U, 2U), 1, DataType::F32)
+ }),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(27U, 3U, 1U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(27U, 3U, 1U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 16U, 1U, 2U), 1, DataType::F32)
+ })),
+ framework::dataset::make("Axis", { Coordinates(4), Coordinates(0,2), Coordinates(2) })),
+ framework::dataset::make("Expected", { false, false, true })),
+ input_info, output_info, axis, expected)
+{
+ const Status status = CLReduceMean::validate(&input_info.clone()->set_is_resizable(false), axis, true, &output_info.clone()->set_is_resizable(false));
+ ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+DATA_TEST_CASE(Configuration,
+ framework::DatasetMode::ALL,
+ combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
+ shape, data_type)
+{
+ // Create tensors
+ CLTensor ref_src = create_tensor<CLTensor>(shape, data_type);
+ CLTensor dst;
+
+ Coordinates axis(1);
+
+ // Create and Configure function
+ CLReduceMean reduce_mean;
+ reduce_mean.configure(&ref_src, axis, true, &dst);
+
+ // Validate valid region
+ TensorShape output_shape = shape;
+ output_shape.set(1, 1);
+ const ValidRegion valid_region = shape_to_valid_region(output_shape);
+ validate(dst.info()->valid_region(), valid_region);
+}
+
+template <typename T>
+using CLReduceMeanFixture = ReduceMeanFixture<CLTensor, CLAccessor, CLReduceMean, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ CLReduceMeanFixture<half>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F16)), concat(axis_keep, axis_drop)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ CLReduceMeanFixture<half>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::F16)), concat(axis_keep, axis_drop)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+TEST_SUITE_END() // FP16
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ CLReduceMeanFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F32)), concat(axis_keep, axis_drop)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ CLReduceMeanFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::F32)), concat(axis_keep, axis_drop)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+
+template <typename T>
+using CLReduceMeanQuantizedFixture = ReduceMeanQuantizedFixture<CLTensor, CLAccessor, CLReduceMean, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ CLReduceMeanQuantizedFixture<uint8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255, 0) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ CLReduceMeanQuantizedFixture<uint8_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), concat(axis_keep, axis_drop)), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255, 0) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END() // QASYMM8
+TEST_SUITE_END() // Quantized
+TEST_SUITE_END() // ReduceMean
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/CL/ReductionOperation.cpp b/tests/validation/CL/ReductionOperation.cpp
index ca0988f..794db1a 100644
--- a/tests/validation/CL/ReductionOperation.cpp
+++ b/tests/validation/CL/ReductionOperation.cpp
@@ -45,7 +45,7 @@
{
/** Tolerance for float operations */
RelativeTolerance<float> tolerance_f32(0.00001f);
-RelativeTolerance<float> tolerance_f16(0.1f);
+AbsoluteTolerance<float> tolerance_f16(0.1f);
} // namespace
TEST_SUITE(CL)
@@ -58,7 +58,7 @@
TensorInfo(TensorShape(128U, 64U), 2, DataType::F32), // Number of Input channels != 1
TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != F16/F32
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis >= num_max_dimensions
- TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis > 0
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis > 0 and SUM_SQUARE
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
}),
framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(1U, 64U), 1, DataType::F16),
@@ -87,13 +87,13 @@
TEST_SUITE(Float)
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLReductionOperationFixture<half>, framework::DatasetMode::PRECOMMIT,
- combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0 })), datasets::ReductionOperations()))
+ combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), datasets::ReductionOperations()))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLReductionOperationFixture<half>, framework::DatasetMode::NIGHTLY,
- combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0 })), datasets::ReductionOperations()))
+ combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), datasets::ReductionOperations()))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16);
@@ -101,13 +101,13 @@
TEST_SUITE_END() // F16
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, CLReductionOperationFixture<float>, framework::DatasetMode::PRECOMMIT,
- combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0 })), datasets::ReductionOperations()))
+ combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), datasets::ReductionOperations()))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLReductionOperationFixture<float>, framework::DatasetMode::NIGHTLY,
- combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0 })), datasets::ReductionOperations()))
+ combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), datasets::ReductionOperations()))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
diff --git a/tests/validation/NEON/ReductionOperation.cpp b/tests/validation/NEON/ReductionOperation.cpp
index c2f2909..b0480b0 100644
--- a/tests/validation/NEON/ReductionOperation.cpp
+++ b/tests/validation/NEON/ReductionOperation.cpp
@@ -85,13 +85,13 @@
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, NEReductionOperationFixture<float>, framework::DatasetMode::PRECOMMIT,
- combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0 })), datasets::ReductionOperations()))
+ combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0 })), framework::dataset::make("Op", { ReductionOperation::SUM_SQUARE })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, NEReductionOperationFixture<float>, framework::DatasetMode::NIGHTLY,
- combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0 })), datasets::ReductionOperations()))
+ combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0 })), framework::dataset::make("Op", { ReductionOperation::SUM_SQUARE })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
diff --git a/tests/validation/fixtures/ReduceMeanFixture.h b/tests/validation/fixtures/ReduceMeanFixture.h
new file mode 100644
index 0000000..6debd4a
--- /dev/null
+++ b/tests/validation/fixtures/ReduceMeanFixture.h
@@ -0,0 +1,161 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_TEST_REDUCE_MEAN_FIXTURE
+#define ARM_COMPUTE_TEST_REDUCE_MEAN_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/reference/ReductionOperation.h"
+#include "tests/validation/reference/ReshapeLayer.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ReduceMeanValidationFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info)
+ {
+ _target = compute_target(shape, data_type, axis, keep_dims, quantization_info);
+ _reference = compute_reference(shape, data_type, axis, keep_dims, quantization_info);
+ }
+
+protected:
+ template <typename U>
+ void fill(U &&tensor)
+ {
+ if(!is_data_type_quantized(tensor.data_type()))
+ {
+ std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+ library->fill(tensor, distribution, 0);
+ }
+ else
+ {
+ const QuantizationInfo quant_info = tensor.quantization_info();
+ const int min_bound = quant_info.quantize(-1.f, RoundingPolicy::TO_NEAREST_UP);
+ const int max_bound = quant_info.quantize(1.f, RoundingPolicy::TO_NEAREST_UP);
+ std::uniform_int_distribution<> distribution(min_bound, max_bound);
+
+ library->fill(tensor, distribution, 0);
+ }
+ }
+
+ TensorType compute_target(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info)
+ {
+ // Create tensors
+ TensorType src = create_tensor<TensorType>(src_shape, data_type, 1, quantization_info);
+ TensorType dst;
+
+ // Create and configure function
+ FunctionType reduction_mean;
+ reduction_mean.configure(&src, axis, keep_dims, &dst);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Fill tensors
+ fill(AccessorType(src));
+
+ // Compute function
+ reduction_mean.run();
+
+ return dst;
+ }
+
+ SimpleTensor<T> compute_reference(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info)
+ {
+ // Create reference
+ SimpleTensor<T> src{ src_shape, data_type, 1, quantization_info };
+
+ // Fill reference
+ fill(src);
+
+ SimpleTensor<T> out;
+ for(unsigned int i = 0; i < axis.num_dimensions(); ++i)
+ {
+ TensorShape output_shape = i == 0 ? src_shape : out.shape();
+ output_shape.set(axis[i], 1);
+ out = reference::reduction_operation<T>(i == 0 ? src : out, output_shape, axis[i], ReductionOperation::MEAN_SUM);
+ }
+
+ if(!keep_dims)
+ {
+ TensorShape output_shape = src_shape;
+ for(unsigned int i = 0; i < axis.num_dimensions(); ++i)
+ {
+ output_shape.remove_dimension(axis[i]);
+ }
+
+ out = reference::reshape_layer(out, output_shape);
+ }
+ return out;
+ }
+
+ TensorType _target{};
+ SimpleTensor<T> _reference{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ReduceMeanQuantizedFixture : public ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info = QuantizationInfo())
+ {
+ ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, quantization_info);
+ }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ReduceMeanFixture : public ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims)
+ {
+ ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, QuantizationInfo());
+ }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_REDUCE_MEAN_FIXTURE */
diff --git a/tests/validation/reference/ReductionOperation.cpp b/tests/validation/reference/ReductionOperation.cpp
index 871a761..11947bd 100644
--- a/tests/validation/reference/ReductionOperation.cpp
+++ b/tests/validation/reference/ReductionOperation.cpp
@@ -48,12 +48,24 @@
};
template <typename T>
+struct sum
+{
+ T operator()(const T &lhs, const T &rhs) const
+ {
+ return (lhs + rhs);
+ }
+};
+
+template <typename T>
T reduce_operation(T *ptr, int reduce_elements, ReductionOperation op)
{
switch(op)
{
case ReductionOperation::SUM_SQUARE:
return std::accumulate(ptr, ptr + reduce_elements, static_cast<T>(0), square<T>());
+ case ReductionOperation::SUM:
+ case ReductionOperation::MEAN_SUM:
+ return std::accumulate(ptr, ptr + reduce_elements, static_cast<T>(0), sum<T>());
default:
ARM_COMPUTE_ERROR("Unsupported reduction operation");
}
@@ -64,23 +76,172 @@
SimpleTensor<T> reduction_operation(const SimpleTensor<T> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op)
{
// Create reference
- SimpleTensor<T> dst{ dst_shape, src.data_type() };
+ SimpleTensor<T> dst{ dst_shape, src.data_type() };
+ const unsigned int src_width = src.shape().x();
+ const unsigned int src_height = src.shape().y();
+ const unsigned int src_depth = src.shape().z();
+ const unsigned int src_batch = src.shape()[3];
+ const bool mean = op == ReductionOperation::MEAN_SUM;
- // Compute reference
- const int reduce_elems = src.shape()[axis];
- const int upper_dims = src.shape().total_size_upper(axis + 1);
-
- for(int du = 0; du < upper_dims; ++du)
+ switch(axis)
{
- if(axis == 0)
+ case 0:
{
- const T *src_row_ptr = src.data() + du * reduce_elems;
- dst[du] = reduce_operation(src_row_ptr, reduce_elems, op);
+ const int reduce_elems = src.shape()[axis];
+ const unsigned int upper_dims = src.shape().total_size_upper(1);
+ for(unsigned int du = 0; du < upper_dims; ++du)
+ {
+ if(std::is_integral<T>::value)
+ {
+ uint32_t res = 0;
+ for(unsigned int x = 0; x < src_width; ++x)
+ {
+ res += static_cast<uint32_t>(src[du * src_width + x]);
+ }
+ if(mean && src_width > 0)
+ {
+ res /= src_width;
+ }
+ dst[du] = static_cast<uint8_t>(res);
+ }
+ else
+ {
+ const T *src_row_ptr = src.data() + du * reduce_elems;
+
+ auto res = reduce_operation(src_row_ptr, reduce_elems, op);
+ if(mean && src_width > 0)
+ {
+ res /= src_width;
+ }
+ dst[du] = res;
+ }
+ }
}
- else
+ break;
+ case 1:
{
+ const unsigned int upper_dims = src.shape().total_size_upper(2);
+ for(unsigned int du = 0; du < upper_dims; ++du)
+ {
+ for(unsigned int x = 0; x < src_width; ++x)
+ {
+ if(std::is_integral<T>::value)
+ {
+ uint32_t res = 0;
+ for(unsigned int y = 0; y < src_height; ++y)
+ {
+ res += static_cast<uint32_t>(src[du * src_height * src_width + y * src_width + x]);
+ }
+ if(mean && src_height > 0)
+ {
+ res /= src_height;
+ }
+ dst[du * src_width + x] = static_cast<uint8_t>(res);
+ }
+ else
+ {
+ auto res = T(0);
+ for(unsigned int y = 0; y < src_height; ++y)
+ {
+ res += src[du * src_height * src_width + y * src_width + x];
+ }
+ if(mean && src_height > 0)
+ {
+ res /= src_height;
+ }
+ dst[du * src_width + x] = res;
+ }
+ }
+ }
+ }
+ break;
+ case 2:
+ {
+ const unsigned int upper_dims = src.shape().total_size_upper(3);
+ for(unsigned int du = 0; du < upper_dims; ++du)
+ {
+ for(unsigned int x = 0; x < src_width; ++x)
+ {
+ for(unsigned int y = 0; y < src_height; ++y)
+ {
+ if(std::is_integral<T>::value)
+ {
+ uint32_t res = T(0);
+ for(unsigned int z = 0; z < src_depth; ++z)
+ {
+ res += static_cast<uint32_t>(src[du * src_depth * src_height * src_width + z * src_height * src_width + y * src_width + x]);
+ }
+ if(mean && src_depth > 0)
+ {
+ res /= src_depth;
+ }
+ dst[du * src_width * src_height + y * src_width + x] = static_cast<uint8_t>(res);
+ }
+ else
+ {
+ auto res = T(0);
+ for(unsigned int z = 0; z < src_depth; ++z)
+ {
+ res += src[du * src_depth * src_height * src_width + z * src_height * src_width + y * src_width + x];
+ }
+ if(mean && src_depth > 0)
+ {
+ res /= src_depth;
+ }
+ dst[du * src_width * src_height + y * src_width + x] = res;
+ }
+ }
+ }
+ }
+ }
+ break;
+ case 3:
+ {
+ const unsigned int upper_dims = src.shape().total_size_upper(4);
+ for(unsigned int du = 0; du < upper_dims; ++du)
+ {
+ for(unsigned int z = 0; z < src_depth; ++z)
+ {
+ for(unsigned int y = 0; y < src_height; ++y)
+ {
+ for(unsigned int x = 0; x < src_width; ++x)
+ {
+ if(std::is_integral<T>::value)
+ {
+ uint32_t res = 0;
+ for(unsigned int w = 0; w < src_batch; ++w)
+ {
+ res += static_cast<uint32_t>(src[du * src_batch * src_depth * src_height * src_width + w * src_width * src_height * src_depth + z * src_width * src_height + y * src_width + x]);
+ }
+ if(mean && src_batch > 0)
+ {
+ res /= src_batch;
+ }
+
+ dst[du * src_depth * src_height * src_width + z * src_width * src_height + y * src_width + x] = static_cast<uint8_t>(res);
+ }
+ else
+ {
+ auto res = T(0);
+ for(unsigned int w = 0; w < src_batch; ++w)
+ {
+ res += src[du * src_batch * src_depth * src_height * src_width + w * src_width * src_height * src_depth + z * src_width * src_height + y * src_width + x];
+ }
+ if(mean && src_batch > 0)
+ {
+ res /= src_batch;
+ }
+
+ dst[du * src_depth * src_height * src_width + z * src_width * src_height + y * src_width + x] = res;
+ }
+ }
+ }
+ }
+ }
+ }
+ break;
+ default:
ARM_COMPUTE_ERROR("Unsupported reduction axis");
- }
}
return dst;
@@ -88,6 +249,7 @@
template SimpleTensor<float> reduction_operation(const SimpleTensor<float> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
template SimpleTensor<half> reduction_operation(const SimpleTensor<half> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
+template SimpleTensor<uint8_t> reduction_operation(const SimpleTensor<uint8_t> &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/ReductionOperation.h b/tests/validation/reference/ReductionOperation.h
index 6da6436..859b57a 100644
--- a/tests/validation/reference/ReductionOperation.h
+++ b/tests/validation/reference/ReductionOperation.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*