COMPMID-1539 Implement YOLOLayer on CL

Change-Id: I332c0703e1399fca0c5b724529b54a28f49c88da
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/146842
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

9 files changed, 515 insertions, 50 deletions

diff --git a/tests/datasets/ActivationFunctionsDataset.h b/tests/datasets/ActivationFunctionsDataset.h
index 31323dc8be..147c5ae51b 100644
--- a/tests/datasets/ActivationFunctionsDataset.h
+++ b/tests/datasets/ActivationFunctionsDataset.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -56,6 +56,21 @@ public:
     {
     }
 };
+
+class ActivationFunctionsQuantized final : public framework::dataset::ContainerDataset<std::vector<ActivationLayerInfo::ActivationFunction>>
+{
+public:
+    ActivationFunctionsQuantized()
+        : ContainerDataset("ActivationFunctionQuantized",
+    {
+        ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
+                            ActivationLayerInfo::ActivationFunction::RELU,
+                            ActivationLayerInfo::ActivationFunction::LOGISTIC,
+                            ActivationLayerInfo::ActivationFunction::BOUNDED_RELU
+    })
+    {
+    }
+};
 } // namespace datasets
 } // namespace test
 } // namespace arm_compute
diff --git a/tests/datasets/ShapeDatasets.h b/tests/datasets/ShapeDatasets.h
index c7955bc8c5..551e7ffa8c 100644
--- a/tests/datasets/ShapeDatasets.h
+++ b/tests/datasets/ShapeDatasets.h
@@ -846,6 +846,38 @@ public:
     {
     }
 };
+
+/** Data set containing small YOLO tensor shapes. */
+class SmallYOLOShapes final : public ShapeDataset
+{
+public:
+    SmallYOLOShapes()
+        : ShapeDataset("Shape",
+    {
+        // Batch size 1
+        TensorShape{ 11U, 11U, 270U },
+                     TensorShape{ 27U, 13U, 90U },
+                     TensorShape{ 128U, 64U, 45U, 2U },
+                     TensorShape{ 11U, 11U, 45U, 3U }
+    })
+    {
+    }
+};
+
+/** Data set containing large YOLO tensor shapes. */
+class LargeYOLOShapes final : public ShapeDataset
+{
+public:
+    LargeYOLOShapes()
+        : ShapeDataset("Shape",
+    {
+        TensorShape{ 24U, 23U, 270U },
+                     TensorShape{ 51U, 63U, 90U, 2U },
+                     TensorShape{ 76U, 91U, 45U, 3U }
+    })
+    {
+    }
+};
 } // namespace datasets
 } // namespace test
 } // namespace arm_compute
diff --git a/tests/validation/CL/ActivationLayer.cpp b/tests/validation/CL/ActivationLayer.cpp
index d91f7082b4..8a6d5ad88a 100644
--- a/tests/validation/CL/ActivationLayer.cpp
+++ b/tests/validation/CL/ActivationLayer.cpp
@@ -202,14 +202,7 @@ TEST_SUITE_END()
 template <typename T>
 using CLActivationLayerQuantizedFixture = ActivationValidationQuantizedFixture<CLTensor, CLAccessor, CLActivationLayer, T>;
 
-/** Input data sets. */
-const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationFunction", { ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
-                                                                                                  ActivationLayerInfo::ActivationFunction::RELU,
-                                                                                                  ActivationLayerInfo::ActivationFunction::LOGISTIC,
-                                                                                                  ActivationLayerInfo::ActivationFunction::BOUNDED_RELU
-                                                                                                });
-
-const auto QuantizedActivationDataset = combine(combine(framework::dataset::make("InPlace", { false, true }), QuantizedActivationFunctionsDataset),
+const auto QuantizedActivationDataset = combine(combine(framework::dataset::make("InPlace", { false, true }), datasets::ActivationFunctionsQuantized()),
                                                 framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
 
 TEST_SUITE(Quantized)
diff --git a/tests/validation/CL/YOLOLayer.cpp b/tests/validation/CL/YOLOLayer.cpp
new file mode 100644
index 0000000000..d8e6e54246
--- /dev/null
+++ b/tests/validation/CL/YOLOLayer.cpp
@@ -0,0 +1,127 @@
+/*
+ * 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/CLYOLOLayer.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets/ActivationFunctionsDataset.h"
+#include "tests/datasets/ShapeDatasets.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/YOLOLayerFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+/** Define tolerance of the yolo layer.
+ *
+ * @param[in] activation The activation function used.
+ * @param[in] data_type  Data type.
+ *
+ * @return Tolerance depending on the activation function.
+ */
+AbsoluteTolerance<float> tolerance(ActivationLayerInfo::ActivationFunction activation, DataType data_type)
+{
+    constexpr float epsilon = 1e-6f;
+
+    switch(activation)
+    {
+        case ActivationLayerInfo::ActivationFunction::LINEAR:
+            return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.2f : epsilon);
+        case ActivationLayerInfo::ActivationFunction::SQUARE:
+            return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.1f : epsilon);
+        case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+            return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.001f : epsilon);
+        case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
+            return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.00001f : epsilon);
+        case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+        case ActivationLayerInfo::ActivationFunction::SQRT:
+            return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.01f : 0.00001f);
+        case ActivationLayerInfo::ActivationFunction::TANH:
+            return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.001f : 0.00001f);
+        default:
+            return AbsoluteTolerance<float>(epsilon);
+    }
+}
+
+/** Floating point data sets. */
+const auto YOLODataset = combine(combine(combine(combine(framework::dataset::make("InPlace", { false, true }), datasets::ActivationFunctions()),
+                                                 framework::dataset::make("AlphaBeta", { 0.5f, 1.f })),
+                                         framework::dataset::make("Classes", 40)),
+                                 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }));
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(YOLOLayer)
+
+template <typename T>
+using CLYOLOLayerFixture = YOLOValidationFixture<CLTensor, CLAccessor, CLYOLOLayer, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLYOLOLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallYOLOShapes(), YOLODataset), framework::dataset::make("DataType",
+                                                                                                       DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLYOLOLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeYOLOShapes(), YOLODataset), framework::dataset::make("DataType",
+                                                                                                     DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLYOLOLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallYOLOShapes(), YOLODataset), framework::dataset::make("DataType",
+                                                                                                      DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLYOLOLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeYOLOShapes(), YOLODataset), framework::dataset::make("DataType",
+                                                                                                    DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+TEST_SUITE_END() // FP16
+TEST_SUITE_END() // Float
+
+TEST_SUITE_END() // YOLOLayer
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/YOLOLayerFixture.h b/tests/validation/fixtures/YOLOLayerFixture.h
new file mode 100644
index 0000000000..a3842e1e8a
--- /dev/null
+++ b/tests/validation/fixtures/YOLOLayerFixture.h
@@ -0,0 +1,162 @@
+/*
+ * 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_YOLO_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_YOLO_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.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/Helpers.h"
+#include "tests/validation/reference/YOLOLayer.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class YOLOValidationGenericFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, int32_t num_classes, DataLayout data_layout, DataType data_type,
+               QuantizationInfo quantization_info)
+    {
+        _data_type = data_type;
+        _function  = function;
+
+        ActivationLayerInfo info(function, alpha_beta, alpha_beta);
+
+        _target    = compute_target(shape, in_place, info, num_classes, data_layout, data_type, quantization_info);
+        _reference = compute_reference(shape, info, num_classes, data_type, quantization_info);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        float min_bound = 0;
+        float max_bound = 0;
+        std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<T>(_function, _data_type);
+        std::uniform_real_distribution<> distribution(min_bound, max_bound);
+        library->fill(tensor, distribution, 0);
+    }
+
+    TensorType compute_target(TensorShape shape, bool in_place, const ActivationLayerInfo &info, int32_t num_classes, DataLayout data_layout, DataType data_type, QuantizationInfo quantization_info)
+    {
+        if(data_layout == DataLayout::NHWC)
+        {
+            permute(shape, PermutationVector(2U, 0U, 1U));
+        }
+
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type, 1, quantization_info, data_layout);
+        TensorType dst = create_tensor<TensorType>(shape, data_type, 1, quantization_info, data_layout);
+
+        // Create and configure function
+        FunctionType yolo_layer;
+
+        TensorType *dst_ptr = in_place ? &src : &dst;
+
+        yolo_layer.configure(&src, dst_ptr, info, num_classes);
+
+        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();
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        if(!in_place)
+        {
+            dst.allocator()->allocate();
+            ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+        }
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        yolo_layer.run();
+
+        if(in_place)
+        {
+            return src;
+        }
+        else
+        {
+            return dst;
+        }
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, const ActivationLayerInfo &info, int32_t num_classes, DataType data_type, QuantizationInfo quantization_info)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type, 1, quantization_info };
+
+        // Fill reference
+        fill(src);
+
+        return reference::yolo_layer<T>(src, info, num_classes);
+    }
+
+    TensorType                              _target{};
+    SimpleTensor<T>                         _reference{};
+    DataType                                _data_type{};
+    ActivationLayerInfo::ActivationFunction _function{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class YOLOValidationFixture : public YOLOValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, int32_t num_classes, DataLayout data_layout, DataType data_type)
+    {
+        YOLOValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, num_classes, data_layout, data_type, QuantizationInfo());
+    }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class YOLOValidationQuantizedFixture : public YOLOValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, int32_t num_classes, DataLayout data_layout, DataType data_type,
+               QuantizationInfo quantization_info)
+    {
+        YOLOValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, num_classes, data_layout, data_type, quantization_info);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif // ARM_COMPUTE_TEST_YOLO_LAYER_FIXTURE
diff --git a/tests/validation/reference/ActivationLayer.cpp b/tests/validation/reference/ActivationLayer.cpp
index 9455effd72..9750ea95a6 100644
--- a/tests/validation/reference/ActivationLayer.cpp
+++ b/tests/validation/reference/ActivationLayer.cpp
@@ -46,46 +46,7 @@ SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo
 
     for(int i = 0; i < src.num_elements(); ++i)
     {
-        T x = src[i];
-
-        switch(info.activation())
-        {
-            case ActivationLayerInfo::ActivationFunction::ABS:
-                dst[i] = std::abs(x);
-                break;
-            case ActivationLayerInfo::ActivationFunction::LINEAR:
-                dst[i] = a * x + b;
-                break;
-            case ActivationLayerInfo::ActivationFunction::LOGISTIC:
-                dst[i] = static_cast<T>(1) / (static_cast<T>(1) + std::exp(-x));
-                break;
-            case ActivationLayerInfo::ActivationFunction::RELU:
-                dst[i] = std::max<T>(static_cast<T>(0), x);
-                break;
-            case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
-                dst[i] = std::min<T>(a, std::max(static_cast<T>(0), x));
-                break;
-            case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
-                dst[i] = std::min<T>(a, std::max<T>(b, x));
-                break;
-            case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
-                dst[i] = (x > 0) ? x : a * x;
-                break;
-            case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
-                dst[i] = std::log(static_cast<T>(1) + std::exp(x));
-                break;
-            case ActivationLayerInfo::ActivationFunction::SQRT:
-                dst[i] = std::sqrt(x);
-                break;
-            case ActivationLayerInfo::ActivationFunction::SQUARE:
-                dst[i] = x * x;
-                break;
-            case ActivationLayerInfo::ActivationFunction::TANH:
-                dst[i] = a * std::tanh(b * x);
-                break;
-            default:
-                ARM_COMPUTE_ERROR("Unsupported activation function");
-        }
+        dst[i] = activate_float<T>(src[i], a, b, info.activation());
     }
 
     return dst;
diff --git a/tests/validation/reference/ActivationLayer.h b/tests/validation/reference/ActivationLayer.h
index 09f602ffa1..c752e74733 100644
--- a/tests/validation/reference/ActivationLayer.h
+++ b/tests/validation/reference/ActivationLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -35,6 +35,54 @@ namespace validation
 {
 namespace reference
 {
+template <typename T>
+inline T activate_float(T x, T a, T b, ActivationLayerInfo::ActivationFunction activation)
+{
+    T ret;
+
+    switch(activation)
+    {
+        case ActivationLayerInfo::ActivationFunction::ABS:
+            ret = std::abs(x);
+            break;
+        case ActivationLayerInfo::ActivationFunction::LINEAR:
+            ret = a * x + b;
+            break;
+        case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+            ret = static_cast<T>(1) / (static_cast<T>(1) + std::exp(-x));
+            break;
+        case ActivationLayerInfo::ActivationFunction::RELU:
+            ret = std::max<T>(static_cast<T>(0), x);
+            break;
+        case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
+            ret = std::min<T>(a, std::max(static_cast<T>(0), x));
+            break;
+        case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
+            ret = std::min<T>(a, std::max<T>(b, x));
+            break;
+        case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
+            ret = (x > 0) ? x : a * x;
+            break;
+        case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+            ret = std::log(static_cast<T>(1) + std::exp(x));
+            break;
+        case ActivationLayerInfo::ActivationFunction::SQRT:
+            ret = std::sqrt(x);
+            break;
+        case ActivationLayerInfo::ActivationFunction::SQUARE:
+            ret = x * x;
+            break;
+        case ActivationLayerInfo::ActivationFunction::TANH:
+            ret = a * std::tanh(b * x);
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Unsupported activation function");
+            break;
+    }
+
+    return ret;
+}
+
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type = 0>
 SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info);
 
diff --git a/tests/validation/reference/YOLOLayer.cpp b/tests/validation/reference/YOLOLayer.cpp
new file mode 100644
index 0000000000..a12f411680
--- /dev/null
+++ b/tests/validation/reference/YOLOLayer.cpp
@@ -0,0 +1,80 @@
+/*
+ * 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 "YOLOLayer.h"
+
+#include "ActivationLayer.h"
+
+#include "arm_compute/core/Types.h"
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
+SimpleTensor<T> yolo_layer(const SimpleTensor<T> &src, const ActivationLayerInfo &info, int32_t num_classes)
+{
+    // Create reference
+    SimpleTensor<T> dst{ src.shape(), src.data_type() };
+
+    // Compute reference
+    const T a(info.a());
+    const T b(info.b());
+
+    for(int i = 0; i < src.num_elements(); ++i)
+    {
+        const size_t z = index2coord(dst.shape(), i).z() % (num_classes + 5);
+
+        if(z != 2 && z != 3)
+        {
+            dst[i] = activate_float<T>(src[i], a, b, info.activation());
+        }
+        else
+        {
+            dst[i] = src[i];
+        }
+    }
+
+    return dst;
+}
+
+template <>
+SimpleTensor<uint8_t> yolo_layer<uint8_t>(const SimpleTensor<uint8_t> &src, const ActivationLayerInfo &info, int32_t num_classes)
+{
+    SimpleTensor<float>   src_tmp = convert_from_asymmetric(src);
+    SimpleTensor<float>   dst_tmp = yolo_layer<float>(src_tmp, info, num_classes);
+    SimpleTensor<uint8_t> dst     = convert_to_asymmetric(dst_tmp, src.quantization_info());
+    return dst;
+}
+
+template SimpleTensor<float> yolo_layer(const SimpleTensor<float> &src, const ActivationLayerInfo &info, int32_t num_classes);
+template SimpleTensor<half> yolo_layer(const SimpleTensor<half> &src, const ActivationLayerInfo &info, int32_t num_classes);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/reference/YOLOLayer.h b/tests/validation/reference/YOLOLayer.h
new file mode 100644
index 0000000000..659f1dd2d9
--- /dev/null
+++ b/tests/validation/reference/YOLOLayer.h
@@ -0,0 +1,47 @@
+/*
+ * 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_YOLO_LAYER_H__
+#define __ARM_COMPUTE_TEST_YOLO_LAYER_H__
+
+#include "tests/SimpleTensor.h"
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type = 0>
+SimpleTensor<T> yolo_layer(const SimpleTensor<T> &src, const ActivationLayerInfo &info, int32_t num_classes);
+
+template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type = 0>
+SimpleTensor<T> yolo_layer(const SimpleTensor<T> &src, const ActivationLayerInfo &info, int32_t num_classes);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_YOLO_LAYER_H__ */