COMPMID-1765: CPP: Implement TopKV

Change-Id: Ib113f19e3e9ad1f2a3084df25eae38c0131df02d
Reviewed-on: https://review.mlplatform.org/439
Reviewed-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

7 files changed, 544 insertions, 2 deletions

diff --git a/arm_compute/core/CPP/CPPKernels.h b/arm_compute/core/CPP/CPPKernels.h
index 39b77cde45..70d858220f 100644
--- a/arm_compute/core/CPP/CPPKernels.h
+++ b/arm_compute/core/CPP/CPPKernels.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -31,6 +31,7 @@
 #include "arm_compute/core/CPP/kernels/CPPFlipWeightsKernel.h"
 #include "arm_compute/core/CPP/kernels/CPPPermuteKernel.h"
 #include "arm_compute/core/CPP/kernels/CPPSortEuclideanDistanceKernel.h"
+#include "arm_compute/core/CPP/kernels/CPPTopKVKernel.h"
 #include "arm_compute/core/CPP/kernels/CPPUpsampleKernel.h"
 
 #endif /* __ARM_COMPUTE_CPPKERNELS_H__ */
diff --git a/arm_compute/core/CPP/kernels/CPPTopKVKernel.h b/arm_compute/core/CPP/kernels/CPPTopKVKernel.h
new file mode 100644
index 0000000000..8d2456f30f
--- /dev/null
+++ b/arm_compute/core/CPP/kernels/CPPTopKVKernel.h
@@ -0,0 +1,92 @@
+/*
+ * Copyright (c) 2019 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_CPPTOPKVERNEL_H__
+#define __ARM_COMPUTE_CPPTOPKVERNEL_H__
+
+#include "arm_compute/core/CPP/ICPPKernel.h"
+
+namespace arm_compute
+{
+class ITensor;
+
+/** CPP kernel to perform tensor TopKV operation. */
+class CPPTopKVKernel : public ICPPKernel
+{
+public:
+    const char *name() const override
+    {
+        return "CPPTopKVKernel";
+    }
+    /** Default constructor */
+    CPPTopKVKernel();
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    CPPTopKVKernel(const CPPTopKVKernel &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    CPPTopKVKernel &operator=(const CPPTopKVKernel &) = delete;
+    /** Allow instances of this class to be moved */
+    CPPTopKVKernel(CPPTopKVKernel &&) = default;
+    /** Allow instances of this class to be moved */
+    CPPTopKVKernel &operator=(CPPTopKVKernel &&) = default;
+    /** Default destructor */
+    ~CPPTopKVKernel() = default;
+
+    /** Set the input and output of the kernel.
+     *
+     * @param[in]  predictions A batch_size x classes tensor. Data types supported: F16/S32/F32/QASYMM8
+     * @param[in]  targets     A batch_size 1D tensor of class ids. Data types supported: S32
+     * @param[out] output      Computed precision at @p k as a bool 1D tensor. Data types supported: U8
+     * @param[in]  k           Number of top elements to look at for computing precision.
+     */
+    void configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k);
+
+    /** Static function to check if given info will lead to a valid configuration of @ref CPPTopKVKernel
+     *
+     * @param[in] predictions A batch_size x classes tensor info. Data types supported: F16/S32/F32/QASYMM8
+     * @param[in] targets     A batch_size 1D tensor info of class ids. Data types supported: S32
+     * @param[in] output      Computed precision at @p k as a bool 1D tensor info. Data types supported: U8
+     * @param[in] k           Number of top elements to look at for computing precision.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k);
+
+    // Inherited methods overridden:
+    void run(const Window &window, const ThreadInfo &info) override;
+    bool is_parallelisable() const override;
+
+private:
+    /** Template function to run the topKV operation. */
+    template <typename T>
+    void run_topkv();
+
+    const ITensor *_predictions;
+    const ITensor *_targets;
+    ITensor       *_output;
+
+    unsigned int _k;
+    unsigned int _batch_size;
+    unsigned int _num_classes;
+};
+} // namespace arm_compute
+#endif /*__ARM_COMPUTE_CPPTOPKVKERNEL_H__ */
diff --git a/arm_compute/runtime/CPP/CPPFunctions.h b/arm_compute/runtime/CPP/CPPFunctions.h
index 63df437d11..4bb668fc83 100644
--- a/arm_compute/runtime/CPP/CPPFunctions.h
+++ b/arm_compute/runtime/CPP/CPPFunctions.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -28,6 +28,7 @@
 #include "arm_compute/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.h"
 #include "arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h"
 #include "arm_compute/runtime/CPP/functions/CPPPermute.h"
+#include "arm_compute/runtime/CPP/functions/CPPTopKV.h"
 #include "arm_compute/runtime/CPP/functions/CPPUpsample.h"
 
 #endif /* __ARM_COMPUTE_CPPFUNCTIONS_H__ */
diff --git a/arm_compute/runtime/CPP/functions/CPPTopKV.h b/arm_compute/runtime/CPP/functions/CPPTopKV.h
new file mode 100644
index 0000000000..10917be97c
--- /dev/null
+++ b/arm_compute/runtime/CPP/functions/CPPTopKV.h
@@ -0,0 +1,60 @@
+/*
+ * Copyright (c) 2019 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_CPPTOPKV_H__
+#define __ARM_COMPUTE_CPPTOPKV_H__
+
+#include "arm_compute/runtime/CPP/ICPPSimpleFunction.h"
+
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+class ITensor;
+
+/** Basic function to run @ref CPPTopKVKernel */
+class CPPTopKV : public ICPPSimpleFunction
+{
+public:
+    /** Set the input and output of the kernel.
+     *
+     * @param[in]  predictions A batch_size x classes tensor. Data types supported: F16/S32/F32/QASYMM8
+     * @param[in]  targets     A batch_size 1D tensor of class ids. Data types supported: S32
+     * @param[out] output      Computed precision at @p k as a bool 1D tensor. Data types supported: U8
+     * @param[in]  k           Number of top elements to look at for computing precision.
+     */
+    void configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k);
+
+    /** Static function to check if given info will lead to a valid configuration of @ref CPPTopKVKernel
+     *
+     * @param[in] predictions A batch_size x classes tensor info. Data types supported: F16/S32/F32/QASYMM8
+     * @param[in] targets     A batch_size 1D tensor info of class ids. Data types supported: S32
+     * @param[in] output      Computed precision at @p k as a bool 1D tensor info. Data types supported: U8
+     * @param[in] k           Number of top elements to look at for computing precision.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k);
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_CPPTOPKV_H__ */
diff --git a/src/core/CPP/kernels/CPPTopKVKernel.cpp b/src/core/CPP/kernels/CPPTopKVKernel.cpp
new file mode 100644
index 0000000000..533543a988
--- /dev/null
+++ b/src/core/CPP/kernels/CPPTopKVKernel.cpp
@@ -0,0 +1,152 @@
+/*
+ * Copyright (c) 2019 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/CPP/kernels/CPPTopKVKernel.h"
+#include "arm_compute/core/Coordinates.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+
+namespace arm_compute
+{
+namespace
+{
+template <typename T,
+          typename std::enable_if<utils::traits::is_floating_point<T>::value, int>::type = 0>
+inline bool greater_than(T a, T b)
+{
+    const T epsilon = std::numeric_limits<T>::epsilon();
+    return (a - b > epsilon);
+}
+
+template < typename T,
+           typename std::enable_if < !utils::traits::is_floating_point<T>::value, int >::type = 0 >
+inline bool greater_than(T a, T b)
+{
+    return (a > b);
+}
+
+Status validate_arguments(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k)
+{
+    ARM_COMPUTE_UNUSED(k);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(predictions, 1, DataType::QASYMM8, DataType::S32, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(targets, 1, DataType::U32);
+
+    ARM_COMPUTE_RETURN_ERROR_ON(predictions->num_dimensions() > 2);
+    ARM_COMPUTE_RETURN_ERROR_ON(targets->num_dimensions() > 1);
+    ARM_COMPUTE_RETURN_ERROR_ON(targets->dimension(0) != predictions->dimension(1));
+    // Validate configured output
+    if(output->total_size() != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), targets->tensor_shape());
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
+    }
+
+    return Status{};
+}
+} // namespace
+
+template <typename T>
+void CPPTopKVKernel::run_topkv()
+{
+    for(unsigned int i = 0; i < _batch_size; ++i)
+    {
+        const auto target_class_id = *reinterpret_cast<uint32_t *>(_targets->ptr_to_element(Coordinates{ i }));
+        const auto predicted_value = *reinterpret_cast<T *>(_predictions->ptr_to_element(Coordinates{ target_class_id, i }));
+
+        // The variable rank indicates how many values there are before the target_class_id
+        unsigned int rank = 0;
+        for(unsigned int j = 0; (j < _num_classes) && (rank < _k); ++j)
+        {
+            const auto current_prediction = *reinterpret_cast<T *>(_predictions->ptr_to_element(Coordinates{ j, i }));
+            if(greater_than(current_prediction, predicted_value))
+            {
+                rank++;
+            }
+        }
+        *(_output->ptr_to_element(Coordinates{ i })) = static_cast<uint8_t>(rank < _k);
+    }
+}
+
+CPPTopKVKernel::CPPTopKVKernel()
+    : _predictions(nullptr), _targets(nullptr), _output(nullptr), _k(), _batch_size(), _num_classes()
+{
+}
+
+void CPPTopKVKernel::configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(predictions, targets, output);
+
+    // Perform validation step
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(predictions->info(), targets->info(), output->info(), k));
+    auto_init_if_empty(*output->info(), targets->info()->tensor_shape(), 1, DataType::U8);
+
+    _predictions = predictions;
+    _targets     = targets;
+    _output      = output;
+
+    _k           = k;
+    _batch_size  = predictions->info()->dimension(1);
+    _num_classes = predictions->info()->dimension(0);
+
+    ICPPKernel::configure(Window()); // Default 1 iteration window
+}
+
+Status CPPTopKVKernel::validate(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(predictions, targets, output, k));
+    return Status{};
+}
+
+bool CPPTopKVKernel::is_parallelisable() const
+{
+    return false;
+}
+
+void CPPTopKVKernel::run(const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(window, info);
+    switch(_predictions->info()->data_type())
+    {
+        case DataType::F32:
+            run_topkv<float>();
+            break;
+        case DataType::F16:
+            run_topkv<half>();
+            break;
+        case DataType::S32:
+            run_topkv<int>();
+            break;
+        case DataType::QASYMM8:
+            run_topkv<uint8_t>();
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Not supported");
+    }
+}
+} // namespace arm_compute
diff --git a/src/runtime/CPP/functions/CPPTopKV.cpp b/src/runtime/CPP/functions/CPPTopKV.cpp
new file mode 100644
index 0000000000..c4e1eab16a
--- /dev/null
+++ b/src/runtime/CPP/functions/CPPTopKV.cpp
@@ -0,0 +1,42 @@
+/*
+ * Copyright (c) 2019 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/runtime/CPP/functions/CPPTopKV.h"
+
+#include "arm_compute/core/CPP/kernels/CPPTopKVKernel.h"
+#include "support/ToolchainSupport.h"
+
+namespace arm_compute
+{
+void CPPTopKV::configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k)
+{
+    auto kernel = arm_compute::support::cpp14::make_unique<CPPTopKVKernel>();
+    kernel->configure(predictions, targets, output, k);
+    _kernel = std::move(kernel);
+}
+
+Status CPPTopKV::validate(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k)
+{
+    return CPPTopKVKernel::validate(predictions, targets, output, k);
+}
+} // namespace arm_compute
diff --git a/tests/validation/CPP/TopKV.cpp b/tests/validation/CPP/TopKV.cpp
new file mode 100644
index 0000000000..ee11cbc54c
--- /dev/null
+++ b/tests/validation/CPP/TopKV.cpp
@@ -0,0 +1,194 @@
+/*
+ * Copyright (c) 2019 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/CPP/functions/CPPTopKV.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/PaddingCalculator.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/PermuteFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+template <typename U, typename T>
+inline void fill_tensor(U &&tensor, const std::vector<T> &v)
+{
+    std::memcpy(tensor.data(), v.data(), sizeof(T) * v.size());
+}
+} // namespace
+
+TEST_SUITE(CPP)
+TEST_SUITE(TopKV)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
+        framework::dataset::make("PredictionsInfo", { TensorInfo(TensorShape(20, 10), 1, DataType::F32),
+                                                TensorInfo(TensorShape(10, 20), 1, DataType::F16),  // Mismatching batch_size
+                                                TensorInfo(TensorShape(20, 10), 1, DataType::S8), // Unsupported data type
+                                                TensorInfo(TensorShape(10, 10, 10), 1, DataType::F32), // Wrong predictions dimensions
+                                                TensorInfo(TensorShape(20, 10), 1, DataType::F32)}), // Wrong output dimension
+        framework::dataset::make("TargetsInfo",{ TensorInfo(TensorShape(10), 1, DataType::U32),
+                                                TensorInfo(TensorShape(10), 1, DataType::U32),
+                                                TensorInfo(TensorShape(10), 1, DataType::U32),
+                                                TensorInfo(TensorShape(10), 1, DataType::U32),
+                                                TensorInfo(TensorShape(10), 1, DataType::U32)})),
+        framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(10), 1, DataType::U8),
+                                                TensorInfo(TensorShape(10), 1, DataType::U8),
+                                                TensorInfo(TensorShape(10), 1, DataType::U8),
+                                                TensorInfo(TensorShape(10), 1, DataType::U8),
+                                                TensorInfo(TensorShape(1), 1, DataType::U8)})),
+
+        framework::dataset::make("k",{ 0, 1, 2, 3, 4 })),
+        framework::dataset::make("Expected", {true, false, false, false, false })),
+        prediction_info, targets_info, output_info, k, expected)
+{
+    const Status status = CPPTopKV::validate(&prediction_info.clone()->set_is_resizable(false),&targets_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), k);
+    ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+TEST_CASE(Float, framework::DatasetMode::ALL)
+{
+    const unsigned int k = 5;
+
+    Tensor predictions = create_tensor<Tensor>(TensorShape(10, 20), DataType::F32);
+    Tensor targets     = create_tensor<Tensor>(TensorShape(20), DataType::U32);
+
+    predictions.allocator()->allocate();
+    targets.allocator()->allocate();
+
+    // Fill the tensors with random pre-generated values
+    fill_tensor(Accessor(predictions), std::vector<float>
+    {
+        0.8147, 0.6557, 0.4387, 0.7513, 0.3517, 0.1622, 0.1067, 0.8530, 0.7803, 0.5470,
+        0.9058, 0.0357, 0.3816, 0.2551, 0.8308, 0.7943, 0.9619, 0.6221, 0.3897, 0.2963,
+        0.1270, 0.8491, 0.7655, 0.5060, 0.5853, 0.3112, 0.0046, 0.3510, 0.2417, 0.7447,
+        0.9134, 0.9340, 0.7952, 0.6991, 0.5497, 0.5285, 0.7749, 0.5132, 0.4039, 0.1890,
+        0.6324, 0.6787, 0.1869, 0.8909, 0.9172, 0.1656, 0.8173, 0.4018, 0.0965, 0.6868,
+        0.0975, 0.7577, 0.4898, 0.9593, 0.2858, 0.6020, 0.8687, 0.0760, 0.1320, 0.1835,
+        0.2785, 0.7431, 0.4456, 0.5472, 0.7572, 0.2630, 0.0844, 0.2399, 0.9421, 0.3685,
+        0.5469, 0.3922, 0.6463, 0.1386, 0.7537, 0.6541, 0.3998, 0.1233, 0.9561, 0.6256,
+        0.9575, 0.6555, 0.7094, 0.1493, 0.3804, 0.6892, 0.2599, 0.1839, 0.5752, 0.7802,
+        0.9649, 0.1712, 0.7547, 0.2575, 0.5678, 0.7482, 0.8001, 0.2400, 0.0598, 0.0811,
+        0.1576, 0.7060, 0.2760, 0.8407, 0.0759, 0.4505, 0.4314, 0.4173, 0.2348, 0.9294,
+        0.9706, 0.0318, 0.6797, 0.2543, 0.0540, 0.0838, 0.9106, 0.0497, 0.3532, 0.7757,
+        0.9572, 0.2769, 0.6551, 0.8143, 0.5308, 0.2290, 0.1818, 0.9027, 0.8212, 0.4868,
+        0.4854, 0.0462, 0.1626, 0.2435, 0.7792, 0.9133, 0.2638, 0.9448, 0.0154, 0.4359,
+        0.8003, 0.0971, 0.1190, 0.9293, 0.9340, 0.1524, 0.1455, 0.4909, 0.0430, 0.4468,
+        0.1419, 0.8235, 0.4984, 0.3500, 0.1299, 0.8258, 0.1361, 0.4893, 0.1690, 0.3063,
+        0.4218, 0.6948, 0.9597, 0.1966, 0.5688, 0.5383, 0.8693, 0.3377, 0.6491, 0.5085,
+        0.9157, 0.3171, 0.3404, 0.2511, 0.4694, 0.9961, 0.5797, 0.9001, 0.7317, 0.5108,
+        0.7922, 0.9502, 0.5853, 0.6160, 0.0119, 0.0782, 0.5499, 0.3692, 0.6477, 0.8176,
+        0.9595, 0.0344, 0.2238, 0.4733, 0.3371, 0.4427, 0.1450, 0.1112, 0.4509, 0.7948
+    });
+
+    fill_tensor(Accessor(targets), std::vector<int> { 1, 5, 7, 2, 8, 1, 2, 1, 2, 4, 3, 9, 4, 1, 9, 9, 4, 1, 2, 4 });
+
+    // Determine the output through the CPP kernel
+    Tensor   output;
+    CPPTopKV topkv;
+    topkv.configure(&predictions, &targets, &output, k);
+
+    output.allocator()->allocate();
+
+    // Run the kernel
+    topkv.run();
+
+    // Validate against the expected values
+    SimpleTensor<float> expected_output(TensorShape(20), DataType::U8);
+    fill_tensor(expected_output, std::vector<uint8_t> { 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1 });
+    validate(Accessor(output), expected_output);
+}
+
+TEST_CASE(Quantized, framework::DatasetMode::ALL)
+{
+    const unsigned int k = 5;
+
+    Tensor predictions = create_tensor<Tensor>(TensorShape(10, 20), DataType::F32);
+    Tensor targets     = create_tensor<Tensor>(TensorShape(20), DataType::U32);
+
+    predictions.allocator()->allocate();
+    targets.allocator()->allocate();
+
+    // Fill the tensors with random pre-generated values
+    fill_tensor(Accessor(predictions), std::vector<uint8_t>
+    {
+        133, 235, 69, 118, 140, 179, 189, 203, 137, 157,
+        242, 1, 196, 170, 166, 25, 102, 244, 24, 254,
+        164, 119, 49, 198, 140, 135, 175, 84, 29, 136,
+        246, 109, 74, 90, 185, 136, 181, 172, 35, 123,
+        62, 118, 24, 170, 134, 221, 114, 113, 174, 206,
+        174, 198, 148, 107, 255, 125, 6, 214, 127, 59,
+        75, 83, 175, 216, 56, 101, 85, 197, 49, 128,
+        172, 201, 140, 214, 28, 172, 109, 43, 127, 231,
+        178, 121, 109, 66, 29, 190, 70, 221, 38, 148,
+        18, 10, 165, 158, 17, 134, 51, 254, 15, 217,
+        66, 46, 166, 150, 104, 90, 211, 132, 218, 190,
+        58, 185, 174, 139, 115, 39, 111, 227, 144, 151,
+        171, 122, 163, 223, 94, 151, 228, 151, 238, 64,
+        217, 40, 242, 68, 196, 68, 101, 40, 179, 171,
+        89, 88, 54, 82, 161, 12, 197, 52, 150, 22,
+        200, 156, 182, 31, 198, 194, 102, 105, 209, 161,
+        173, 50, 61, 241, 239, 63, 207, 192, 226, 170,
+        2, 190, 31, 166, 250, 114, 194, 212, 254, 187,
+        155, 63, 156, 123, 50, 177, 97, 203, 1, 229,
+        100, 235, 116, 164, 36, 92, 56, 82, 222, 252
+    });
+
+    fill_tensor(Accessor(targets), std::vector<int> { 1, 5, 7, 2, 8, 1, 2, 1, 2, 4, 3, 9, 4, 1, 9, 9, 4, 1, 2, 4 });
+
+    // Determine the output through the CPP kernel
+    Tensor   output;
+    CPPTopKV topkv;
+    topkv.configure(&predictions, &targets, &output, k);
+
+    output.allocator()->allocate();
+
+    // Run the kernel
+    topkv.run();
+
+    // Validate against the expected values
+    SimpleTensor<float> expected_output(TensorShape(20), DataType::U8);
+    fill_tensor(expected_output, std::vector<uint8_t> { 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0 });
+    validate(Accessor(output), expected_output);
+}
+
+TEST_SUITE_END() // TopKV
+TEST_SUITE_END() // CPP
+} // namespace validation
+} // namespace test
+} // namespace arm_compute