/* * Copyright (c) 2018-2020 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 "src/core/CL/kernels/CLCol2ImKernel.h" #include "tests/CL/CLAccessor.h" #include "tests/CL/Helper.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/Col2ImFixture.h" namespace arm_compute { namespace test { namespace validation { TEST_SUITE(CL) TEST_SUITE(Col2Im) using CLCol2Im = CLSynthetizeFunction; /** Negative tests * * A series of validation tests on configurations which according to the API specification * the function should fail against. * * Checks performed in order: * - Pass unsupported data type for input * - Pass NHWC as output data layout * - Pass an invalid output shape */ TEST_CASE(Negative, framework::DatasetMode::ALL) { // Unsupported data type { const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::SIZET); const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32); const auto conv_size = Size2D(3, 4); const auto status = CLCol2ImKernel::validate(&input, &output, conv_size); ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS); } // NHWC as output data layout { const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32); const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32, DataLayout::NHWC); const auto conv_size = Size2D(3, 4); const auto status = CLCol2ImKernel::validate(&input, &output, conv_size); ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS); } // Invalid output size { const auto input = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32); const auto output = TensorInfo(TensorShape(3U, 4U, 10U, 2U, 2U), 1, DataType::F32); const auto conv_size = Size2D(3, 4); const auto status = CLCol2ImKernel::validate(&input, &output, conv_size); ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS); } } template using CLCol2ImFixture = Col2ImValidationFixture; /** Test kernel for single-precision floating point * * @note 8 elements processed per iteration * * Three main tests will be run: * - Channels are multiple of elements processed * - Channels larger and non multiple of elements used * - Channels smaller and not multiple of elements used * * The above will be repeated with a different group size * * Kernel tested col2im */ FIXTURE_DATA_TEST_CASE(FP32, CLCol2ImFixture, framework::DatasetMode::ALL, combine(combine(combine(combine( framework::dataset::make("InputShape", { TensorShape(8U, 16U, 3U, 1U), TensorShape(17U, 16U, 3U, 1U), TensorShape(7U, 16U, 3U, 1U) }), framework::dataset::make("ConvolvedWidth", 4)), framework::dataset::make("ConvolvedHeight", 4)), framework::dataset::make("Groups", { 1, 3 })), framework::dataset::make("DataType", DataType::F32))) { // Validate output validate(CLAccessor(_target), _reference); } /** Test kernel for half-precision floating point * * @note 8 elements processed per iteration * * One main tests will be run: * - Channels larger and non multiple of elements used * * We just need to test the difference in the data type size. * Any other issues can be identified by the main FP32 tests * * Kernel tested col2im */ FIXTURE_DATA_TEST_CASE(F16, CLCol2ImFixture, framework::DatasetMode::ALL, combine(combine(combine(combine( framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)), framework::dataset::make("ConvolvedWidth", 4)), framework::dataset::make("ConvolvedHeight", 4)), framework::dataset::make("Groups", 3)), framework::dataset::make("DataType", DataType::F16))) { // Validate output validate(CLAccessor(_target), _reference); } /** Test kernel for unsigned asymmetric quantized type * * @note 8 elements processed per iteration * * One main tests will be run: * - Channels larger and non multiple of elements used * * We just need to test the difference in the data type size. * Any other issues can be identified by the main FP32 tests * * Kernel tested col2im */ FIXTURE_DATA_TEST_CASE(QASYMM8, CLCol2ImFixture, framework::DatasetMode::ALL, combine(combine(combine(combine( framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)), framework::dataset::make("ConvolvedWidth", 4)), framework::dataset::make("ConvolvedHeight", 4)), framework::dataset::make("Groups", 3)), framework::dataset::make("DataType", DataType::QASYMM8))) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() // CL TEST_SUITE_END() // Col2Im } // namespace validation } // namespace test } // namespace arm_compute