COMPMID-563 - Implement reference and CL/NEON validation for Custom_Convolution (Output U8)

Change-Id: I57a6db857474929322206ee7440e088bc0bbbbe2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111080
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>

6 files changed, 932 insertions, 4 deletions

diff --git a/src/core/NEON/kernels/NEConvolutionKernel.cpp b/src/core/NEON/kernels/NEConvolutionKernel.cpp
index 263fbe058a..3a4884eb21 100644
--- a/src/core/NEON/kernels/NEConvolutionKernel.cpp
+++ b/src/core/NEON/kernels/NEConvolutionKernel.cpp
@@ -627,16 +627,17 @@ void NEConvolutionKernel<matrix_size>::run(const Window &window, const ThreadInf
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
 
-    switch(_output->info()->format())
+    switch(_output->info()->data_type())
     {
-        case Format::U8:
+        case DataType::U8:
             convolution<uint8_t>(window);
             break;
-        case Format::S16:
+        case DataType::S16:
             convolution<int16_t>(window);
             break;
         default:
-            ARM_COMPUTE_ERROR("Not supported");
+            ARM_COMPUTE_ERROR("Not supported Data type!");
+            break;
     }
 }
 
diff --git a/tests/validation/CL/Convolution.cpp b/tests/validation/CL/Convolution.cpp
new file mode 100644
index 0000000000..c836edabb8
--- /dev/null
+++ b/tests/validation/CL/Convolution.cpp
@@ -0,0 +1,325 @@
+/*
+ * Copyright (c) 2017 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/functions/CLConvolution.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets/BorderModeDataset.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/ConvolutionFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+/* Convolution3x3 */
+constexpr unsigned int filter_size_3x3 = 3;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_3x3(filter_size_3x3 / 2); /* Border size of the kernel/filter around its central element. */
+
+/* Convolution5x5 */
+constexpr unsigned int filter_size_5x5 = 5;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_5x5(filter_size_5x5 / 2); /* Border size of the kernel/filter around its central element. */
+
+/* Convolution7x7 */
+constexpr unsigned int filter_size_7x7 = 7;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_7x7(filter_size_7x7 / 2); /* Border size of the kernel/filter around its central element. */
+
+/* Convolution9x9 */
+constexpr unsigned int filter_size_9x9 = 9;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_9x9(filter_size_9x9 / 2); /* Border size of the kernel/filter around its central element. */
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(CustomConvolution)
+TEST_SUITE(CustomConvolution3x3)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    CLTensor src = create_tensor<CLTensor>(shape, data_type);
+    CLTensor dst = create_tensor<CLTensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[9];
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    const uint32_t                         scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    CLConvolution3x3 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_3x3);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(1);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-1);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution3x3, T, filter_size_3x3>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3));
+}
+TEST_SUITE_END() /* Custom_Convolution 3x3 */
+
+TEST_SUITE(CustomConvolution5x5)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    CLTensor src = create_tensor<CLTensor>(shape, data_type);
+    CLTensor dst = create_tensor<CLTensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[25];
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    const uint32_t                         scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    CLConvolution5x5 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_5x5);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(2);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-2);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution5x5, T, filter_size_5x5>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5));
+}
+TEST_SUITE_END() /* Custom Convolution 5x5 */
+
+TEST_SUITE(CustomConvolution7x7)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    CLTensor src = create_tensor<CLTensor>(shape, data_type);
+    CLTensor dst = create_tensor<CLTensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[49];
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    const uint32_t                         scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    CLConvolution7x7 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_7x7);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(3);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-3);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution7x7, T, filter_size_7x7>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7));
+}
+TEST_SUITE_END() /* Custom Convolution 7x7 */
+
+TEST_SUITE(CustomConvolution9x9)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    CLTensor src = create_tensor<CLTensor>(shape, data_type);
+    CLTensor dst = create_tensor<CLTensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[81];
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    const uint32_t                         scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    CLConvolution9x9 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_9x9);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(4);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-4);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution9x9, T, filter_size_9x9>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9));
+}
+TEST_SUITE_END() /* Custom Convolution 9x9 */
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/CPP/Convolution.cpp b/tests/validation/CPP/Convolution.cpp
new file mode 100644
index 0000000000..84be858cfc
--- /dev/null
+++ b/tests/validation/CPP/Convolution.cpp
@@ -0,0 +1,70 @@
+/*
+ * Copyright (c) 2017 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/Helpers.h"
+
+#include "Convolution.h"
+#include "Utils.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, T constant_border_value, const unsigned int filter_size)
+{
+    SimpleTensor<T>       dst(src.shape(), src.data_type());
+    SimpleTensor<int32_t> sum(src.shape(), src.data_type());
+
+    for(int element_idx = 0; element_idx < src.num_elements(); ++element_idx)
+    {
+        const Coordinates id = index2coord(src.shape(), element_idx);
+        apply_2d_spatial_filter(id, src, sum, TensorShape(filter_size, filter_size), conv, 1, border_mode, constant_border_value);
+
+        if(tensor_elem_at<int32_t>(sum, id, border_mode, constant_border_value) < 0)
+        {
+            dst[element_idx] = 0;
+        }
+        else if((tensor_elem_at<int32_t>(sum, id, border_mode, constant_border_value) / scale) > 255)
+        {
+            dst[element_idx] = 255;
+        }
+        else
+        {
+            dst[element_idx] = tensor_elem_at<int32_t>(sum, id, border_mode, constant_border_value) / scale;
+        }
+    }
+
+    return dst;
+}
+
+template SimpleTensor<uint8_t> convolution(const SimpleTensor<uint8_t> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value,
+                                           const unsigned int filter_size);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/CPP/Convolution.h b/tests/validation/CPP/Convolution.h
new file mode 100644
index 0000000000..bdaac28ae6
--- /dev/null
+++ b/tests/validation/CPP/Convolution.h
@@ -0,0 +1,43 @@
+/*
+ * Copyright (c) 2017 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_CONVOLUTION_H__
+#define __ARM_COMPUTE_TEST_CONVOLUTION_H__
+
+#include "tests/SimpleTensor.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, T constant_border_value, const unsigned int filter_size);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_CONVOLUTION_H__ */
diff --git a/tests/validation/NEON/Convolution.cpp b/tests/validation/NEON/Convolution.cpp
new file mode 100644
index 0000000000..b820491e18
--- /dev/null
+++ b/tests/validation/NEON/Convolution.cpp
@@ -0,0 +1,345 @@
+/*
+ * Copyright (c) 2017 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/NEON/functions/NEConvolution.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/BorderModeDataset.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/ConvolutionFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+/* Convolution3x3 */
+constexpr unsigned int filter_size_3x3 = 3;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_3x3(filter_size_3x3 / 2); /* Border size of the kernel/filter around its central element. */
+
+/* Convolution5x5 */
+constexpr unsigned int filter_size_5x5 = 5;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_5x5(filter_size_5x5 / 2); /* Border size of the kernel/filter around its central element. */
+
+/* Convolution7x7 */
+constexpr unsigned int filter_size_7x7 = 7;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_7x7(filter_size_7x7 / 2); /* Border size of the kernel/filter around its central element. */
+
+/* Convolutionx */
+constexpr unsigned int filter_size_9x9 = 9;                  /* Size of the kernel/filter in number of elements. */
+constexpr BorderSize   border_size_9x9(filter_size_9x9 / 2); /* Border size of the kernel/filter around its central element. */
+
+/** Create conv matrix with filter size, and fill them with random value
+ *
+ * @param[in/out] conv        Convolution matrix to be filled with random int16_t
+ * @param[in]     filter_size Filter Size.
+ */
+void create_conv(int16_t *conv, const unsigned int filter_size)
+{
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<int16_t> distribution_int16(-32768, 32767);
+
+    for(unsigned int i = 0; i < filter_size * filter_size; ++i)
+    {
+        conv[i] = distribution_int16(gen);
+    }
+}
+} // namespace
+
+TEST_SUITE(NEON)
+TEST_SUITE(CustomConvolution)
+TEST_SUITE(CustomConvolution3x3)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    Tensor src = create_tensor<Tensor>(shape, data_type);
+    Tensor dst = create_tensor<Tensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[9];
+    create_conv(conv, filter_size_3x3);
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    uint32_t                               scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NEConvolution3x3 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_3x3);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(1);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-1);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution3x3, T, filter_size_3x3>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3));
+}
+TEST_SUITE_END() /* Custom Convolution3x3 */
+
+TEST_SUITE(CustomConvolution5x5)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    Tensor src = create_tensor<Tensor>(shape, data_type);
+    Tensor dst = create_tensor<Tensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[25];
+    create_conv(conv, filter_size_5x5);
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    uint32_t                               scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NEConvolution5x5 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_5x5);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(2);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-2);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution5x5, T, filter_size_5x5>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5));
+}
+TEST_SUITE_END() /* Custom Convolution 5x5 */
+
+TEST_SUITE(CustomConvolution7x7)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    Tensor src = create_tensor<Tensor>(shape, data_type);
+    Tensor dst = create_tensor<Tensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[49];
+    create_conv(conv, filter_size_7x7);
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    uint32_t                               scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NEConvolution7x7 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_7x7);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(3);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-3);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution7x7, T, filter_size_7x7>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7));
+}
+TEST_SUITE_END() /* Custom Convolution 7x7 */
+
+TEST_SUITE(CustomConvolution9x9)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)),
+                                                                   datasets::BorderModes()),
+               shape, data_type, border_mode)
+{
+    // Create tensors
+    Tensor src = create_tensor<Tensor>(shape, data_type);
+    Tensor dst = create_tensor<Tensor>(shape, data_type);
+
+    // Create conv matrix
+    int16_t conv[81];
+    create_conv(conv, filter_size_9x9);
+
+    // Generate random scale value between 0 and 255.
+    std::mt19937                           gen(library->seed());
+    std::uniform_int_distribution<uint8_t> distribution(0, 255);
+    uint32_t                               scale = distribution(gen);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NEConvolution9x9 convolution;
+    convolution.configure(&src, &dst, conv, scale, border_mode);
+
+    // Validate valid region
+    const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_9x9);
+    validate(dst.info()->valid_region(), dst_valid_region);
+
+    // Validate padding
+    PaddingCalculator calculator(shape.x(), 8);
+    calculator.set_border_size(4);
+    calculator.set_border_mode(border_mode);
+
+    const PaddingSize dst_padding = calculator.required_padding();
+
+    calculator.set_accessed_elements(16);
+    calculator.set_access_offset(-4);
+
+    const PaddingSize src_padding = calculator.required_padding();
+
+    validate(src.info()->padding(), src_padding);
+    validate(dst.info()->padding(), dst_padding);
+}
+
+template <typename T>
+using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution9x9, T, filter_size_9x9>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::U8)),
+                                                                                                           datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9));
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::U8)),
+                                                                                                         datasets::BorderModes()))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9));
+}
+TEST_SUITE_END() /* Custom Convolution 9x9 */
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/ConvolutionFixture.h b/tests/validation/fixtures/ConvolutionFixture.h
new file mode 100644
index 0000000000..3e881a2e99
--- /dev/null
+++ b/tests/validation/fixtures/ConvolutionFixture.h
@@ -0,0 +1,144 @@
+/*
+ * Copyright (c) 2017 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_CONVOLUTION_FIXTURE
+#define ARM_COMPUTE_TEST_CONVOLUTION_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/CPP/Convolution.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, const unsigned int filter_size>
+class ConvolutionValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, BorderMode border_mode)
+    {
+        std::mt19937                           gen(library->seed());
+        std::uniform_int_distribution<uint8_t> distribution(0, 255);
+        const uint8_t                          constant_border_value = distribution(gen);
+
+        // Generate random scale value between 0 and 255.
+        const uint32_t scale = distribution(gen);
+
+        switch(filter_size)
+        {
+            case 3:
+            case 5:
+            case 7:
+            case 9:
+                int16_t conv[filter_size * filter_size];
+                create_conv(conv);
+
+                _target    = compute_target(shape, data_type, conv, scale, border_mode, constant_border_value);
+                _reference = compute_reference(shape, data_type, conv, scale, border_mode, constant_border_value);
+                break;
+            default:
+                ARM_COMPUTE_ERROR("Filter Size Not Supported");
+        }
+    }
+
+protected:
+    void create_conv(int16_t *conv)
+    {
+        std::mt19937                           gen(library->seed());
+        std::uniform_int_distribution<int16_t> distribution_int16(-32768, 32767);
+
+        for(unsigned int i = 0; i < filter_size * filter_size; ++i)
+        {
+            conv[i] = distribution_int16(gen);
+        }
+    }
+
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        library->fill_tensor_uniform(tensor, i);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+        TensorType dst = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType convolution;
+        convolution.configure(&src, &dst, conv, scale, border_mode, constant_border_value);
+
+        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), 0);
+        fill(AccessorType(dst), 1);
+
+        // Compute function
+        convolution.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
+    {
+        ARM_COMPUTE_ERROR_ON(data_type != DataType::U8);
+
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src, 0);
+
+        // Compute reference
+        return reference::convolution<T>(src, conv, scale, border_mode, constant_border_value, filter_size);
+    }
+
+    BorderMode      _border_mode{};
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE */