/* * Copyright (c) 2017-2020 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. */ #ifndef ARM_COMPUTE_TEST_SCALELAYERFIXTURE #define ARM_COMPUTE_TEST_SCALELAYERFIXTURE #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" #include "tests/Globals.h" #include "tests/Utils.h" #include "tests/framework/Asserts.h" #include "tests/framework/Fixture.h" namespace arm_compute { namespace test { /** Fixture that can be used for NEON, CL and OpenGL ES */ template class ScaleLayerFixture : public framework::Fixture { public: template void setup(TensorShape shape, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy, float sx, float sy, DataType data_type) { constexpr float max_width = 8192.0f; constexpr float max_height = 6384.0f; std::mt19937 generator(library->seed()); float scale_x = ((shape.x() * sx) > max_width) ? (max_width / shape.x()) : sx; float scale_y = ((shape.y() * sy) > max_height) ? (max_height / shape.y()) : sy; std::uniform_int_distribution distribution_u8(0, 255); T constant_border_value = static_cast(distribution_u8(generator)); // Create tensors src = create_tensor(shape, data_type); TensorShape shape_scaled(shape); shape_scaled.set(0, shape[0] * scale_x); shape_scaled.set(1, shape[1] * scale_y); dst = create_tensor(shape_scaled, data_type); scale_layer.configure(&src, &dst, ScaleKernelInfo{ policy, border_mode, constant_border_value, sampling_policy }); 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(); } void run() { scale_layer.run(); } void sync() { sync_if_necessary(); sync_tensor_if_necessary(dst); } void teardown() { src.allocator()->free(); dst.allocator()->free(); } private: TensorType src{}; TensorType dst{}; Function scale_layer{}; }; } // namespace test } // namespace arm_compute #endif /* ARM_COMPUTE_TEST_SCALELAYERFIXTURE */