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>

1 files changed, 325 insertions, 0 deletions

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