| /* |
| * Copyright (c) 2019-2020 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/runtime/RuntimeContext.h" |
| |
| #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" |
| #include "arm_compute/runtime/SchedulerFactory.h" |
| #include "arm_compute/runtime/Tensor.h" |
| #include "tests/Globals.h" |
| #include "tests/NEON/Accessor.h" |
| #include "tests/Utils.h" |
| #include "tests/framework/Asserts.h" |
| #include "tests/framework/Macros.h" |
| #include "tests/validation/Validation.h" |
| #include "tests/validation/reference/ActivationLayer.h" |
| |
| #include <memory> |
| #include <random> |
| #if !defined(BARE_METAL) |
| #include <thread> |
| #endif // !defined(BARE_METAL) |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| TEST_SUITE(NEON) |
| TEST_SUITE(UNIT) |
| TEST_SUITE(RuntimeContext) |
| |
| TEST_CASE(Scheduler, framework::DatasetMode::ALL) |
| { |
| using namespace arm_compute; |
| // Create a runtime context object |
| RuntimeContext ctx; |
| |
| // Check if it's been initialised properly |
| ARM_COMPUTE_EXPECT(ctx.scheduler() != nullptr, framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(ctx.asset_manager() == nullptr, framework::LogLevel::ERRORS); |
| |
| // Create a Scheduler |
| auto scheduler = SchedulerFactory::create(); |
| ctx.set_scheduler(scheduler.get()); |
| // Check if the scheduler has been properly setup |
| ARM_COMPUTE_EXPECT(ctx.scheduler() != nullptr, framework::LogLevel::ERRORS); |
| |
| // Create a new activation function |
| NEActivationLayer act_layer(&ctx); |
| |
| Tensor src = create_tensor<Tensor>(TensorShape(32, 32), DataType::F32, 1); |
| Tensor dst = create_tensor<Tensor>(TensorShape(32, 32), DataType::F32, 1); |
| |
| act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR)); |
| |
| 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); |
| |
| float min_bound = 0; |
| float max_bound = 0; |
| std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(ActivationLayerInfo::ActivationFunction::LINEAR, DataType::F32); |
| std::uniform_real_distribution<> distribution(min_bound, max_bound); |
| library->fill(Accessor(src), distribution, 0); |
| |
| // Compute function |
| act_layer.run(); |
| } |
| |
| #if !defined(BARE_METAL) |
| // This test tries scheduling work concurrently from two independent threads |
| TEST_CASE(MultipleThreadedScheduller, framework::DatasetMode::ALL) |
| { |
| // Create a runtime context object for thread 1 |
| RuntimeContext ctx1; |
| |
| // Create a runtime context object for thread 2 |
| RuntimeContext ctx2; |
| |
| // Create a new activation function |
| NEActivationLayer act_layer_thread0(&ctx1); |
| NEActivationLayer act_layer_thread1(&ctx2); |
| |
| const TensorShape tensor_shape(128, 128); |
| Tensor src_t0 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| Tensor dst_t0 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| Tensor src_t1 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| Tensor dst_t1 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| ActivationLayerInfo activation_info(ActivationLayerInfo::ActivationFunction::LINEAR); |
| |
| act_layer_thread0.configure(&src_t0, &dst_t0, activation_info); |
| act_layer_thread1.configure(&src_t1, &dst_t1, activation_info); |
| |
| ARM_COMPUTE_EXPECT(src_t0.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst_t0.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(src_t1.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst_t1.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Allocate tensors |
| src_t0.allocator()->allocate(); |
| dst_t0.allocator()->allocate(); |
| src_t1.allocator()->allocate(); |
| dst_t1.allocator()->allocate(); |
| |
| ARM_COMPUTE_EXPECT(!src_t0.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(!src_t1.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| float min_bound = 0; |
| float max_bound = 0; |
| std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(ActivationLayerInfo::ActivationFunction::LINEAR, DataType::F32); |
| std::uniform_real_distribution<> distribution(min_bound, max_bound); |
| library->fill(Accessor(src_t0), distribution, 0); |
| library->fill(Accessor(src_t1), distribution, 0); |
| |
| std::thread neon_thread1([&] { act_layer_thread0.run(); }); |
| std::thread neon_thread2([&] { act_layer_thread1.run(); }); |
| |
| neon_thread1.join(); |
| neon_thread2.join(); |
| |
| Window window; |
| window.use_tensor_dimensions(dst_t0.info()->tensor_shape()); |
| Iterator t0_it(&dst_t0, window); |
| Iterator t1_it(&dst_t1, window); |
| execute_window_loop(window, [&](const Coordinates &) |
| { |
| const bool match = (*reinterpret_cast<float *>(t0_it.ptr()) == *reinterpret_cast<float *>(t1_it.ptr())); |
| ARM_COMPUTE_EXPECT(match, framework::LogLevel::ERRORS); |
| }, |
| t0_it, t1_it); |
| } |
| #endif // !defined(BARE_METAL) |
| |
| TEST_SUITE_END() // RuntimeContext |
| TEST_SUITE_END() // UNIT |
| TEST_SUITE_END() // NEON |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |