Georgios Pinitas | 12833d0 | 2019-07-25 13:31:10 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2019 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "arm_compute/runtime/RuntimeContext.h" |
| 25 | |
| 26 | #include "arm_compute/runtime/CPP/CPPScheduler.h" |
| 27 | #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" |
| 28 | #include "arm_compute/runtime/Tensor.h" |
| 29 | #include "support/ToolchainSupport.h" |
| 30 | #include "tests/Globals.h" |
| 31 | #include "tests/NEON/Accessor.h" |
| 32 | #include "tests/Utils.h" |
| 33 | #include "tests/framework/Asserts.h" |
| 34 | #include "tests/framework/Macros.h" |
| 35 | #include "tests/validation/Validation.h" |
| 36 | #include "tests/validation/reference/ActivationLayer.h" |
| 37 | |
| 38 | #include <memory> |
| 39 | #include <random> |
| 40 | #if !defined(BARE_METAL) |
| 41 | #include <thread> |
| 42 | #endif // !defined(BARE_METAL) |
| 43 | |
| 44 | namespace arm_compute |
| 45 | { |
| 46 | namespace test |
| 47 | { |
| 48 | namespace validation |
| 49 | { |
| 50 | TEST_SUITE(NEON) |
| 51 | TEST_SUITE(UNIT) |
| 52 | TEST_SUITE(RuntimeContext) |
| 53 | |
| 54 | TEST_CASE(Scheduler, framework::DatasetMode::ALL) |
| 55 | { |
| 56 | using namespace arm_compute; |
| 57 | // Create a runtime context object |
| 58 | RuntimeContext ctx; |
| 59 | |
| 60 | // Check if it's been initialised properly |
| 61 | ARM_COMPUTE_EXPECT(ctx.scheduler() != nullptr, framework::LogLevel::ERRORS); |
| 62 | ARM_COMPUTE_EXPECT(ctx.asset_manager() == nullptr, framework::LogLevel::ERRORS); |
| 63 | |
| 64 | // Create a CPPScheduler |
| 65 | CPPScheduler scheduler; |
| 66 | ctx.set_scheduler(&scheduler); |
| 67 | // Check if the scheduler has been properly setup |
| 68 | ARM_COMPUTE_EXPECT(ctx.scheduler() != nullptr, framework::LogLevel::ERRORS); |
| 69 | |
| 70 | // Create a new activation function |
| 71 | NEActivationLayer act_layer(&ctx); |
| 72 | |
| 73 | Tensor src = create_tensor<Tensor>(TensorShape(32, 32), DataType::F32, 1); |
| 74 | Tensor dst = create_tensor<Tensor>(TensorShape(32, 32), DataType::F32, 1); |
| 75 | |
| 76 | act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR)); |
| 77 | |
| 78 | ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 79 | ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 80 | |
| 81 | // Allocate tensors |
| 82 | src.allocator()->allocate(); |
| 83 | dst.allocator()->allocate(); |
| 84 | |
| 85 | ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 86 | |
| 87 | float min_bound = 0; |
| 88 | float max_bound = 0; |
| 89 | std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(ActivationLayerInfo::ActivationFunction::LINEAR, DataType::F32); |
| 90 | std::uniform_real_distribution<> distribution(min_bound, max_bound); |
| 91 | library->fill(Accessor(src), distribution, 0); |
| 92 | |
| 93 | // Compute function |
| 94 | act_layer.run(); |
| 95 | } |
| 96 | |
| 97 | #if !defined(BARE_METAL) |
| 98 | // This test tries scheduling work concurrently from two independent threads |
| 99 | TEST_CASE(MultipleThreadedScheduller, framework::DatasetMode::ALL) |
| 100 | { |
| 101 | // Create a runtime context object for thread 1 |
| 102 | RuntimeContext ctx1; |
| 103 | |
| 104 | // Create a runtime context object for thread 2 |
| 105 | RuntimeContext ctx2; |
| 106 | |
| 107 | // Create a new activation function |
| 108 | NEActivationLayer act_layer_thread0(&ctx1); |
| 109 | NEActivationLayer act_layer_thread1(&ctx2); |
| 110 | |
| 111 | const TensorShape tensor_shape(128, 128); |
| 112 | Tensor src_t0 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| 113 | Tensor dst_t0 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| 114 | Tensor src_t1 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| 115 | Tensor dst_t1 = create_tensor<Tensor>(tensor_shape, DataType::F32, 1); |
| 116 | ActivationLayerInfo activation_info(ActivationLayerInfo::ActivationFunction::LINEAR); |
| 117 | |
| 118 | act_layer_thread0.configure(&src_t0, &dst_t0, activation_info); |
| 119 | act_layer_thread1.configure(&src_t1, &dst_t1, activation_info); |
| 120 | |
| 121 | ARM_COMPUTE_EXPECT(src_t0.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 122 | ARM_COMPUTE_EXPECT(dst_t0.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 123 | ARM_COMPUTE_EXPECT(src_t1.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 124 | ARM_COMPUTE_EXPECT(dst_t1.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 125 | |
| 126 | // Allocate tensors |
| 127 | src_t0.allocator()->allocate(); |
| 128 | dst_t0.allocator()->allocate(); |
| 129 | src_t1.allocator()->allocate(); |
| 130 | dst_t1.allocator()->allocate(); |
| 131 | |
| 132 | ARM_COMPUTE_EXPECT(!src_t0.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 133 | ARM_COMPUTE_EXPECT(!src_t1.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 134 | |
| 135 | float min_bound = 0; |
| 136 | float max_bound = 0; |
| 137 | std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(ActivationLayerInfo::ActivationFunction::LINEAR, DataType::F32); |
| 138 | std::uniform_real_distribution<> distribution(min_bound, max_bound); |
| 139 | library->fill(Accessor(src_t0), distribution, 0); |
| 140 | library->fill(Accessor(src_t1), distribution, 0); |
| 141 | |
| 142 | std::thread neon_thread1([&] { act_layer_thread0.run(); }); |
| 143 | std::thread neon_thread2([&] { act_layer_thread1.run(); }); |
| 144 | |
| 145 | neon_thread1.join(); |
| 146 | neon_thread2.join(); |
| 147 | |
| 148 | Window window; |
| 149 | window.use_tensor_dimensions(dst_t0.info()->tensor_shape()); |
| 150 | Iterator t0_it(&dst_t0, window); |
| 151 | Iterator t1_it(&dst_t1, window); |
| 152 | execute_window_loop(window, [&](const Coordinates &) |
| 153 | { |
| 154 | const bool match = (*reinterpret_cast<float *>(t0_it.ptr()) == *reinterpret_cast<float *>(t1_it.ptr())); |
| 155 | ARM_COMPUTE_EXPECT(match, framework::LogLevel::ERRORS); |
| 156 | }, |
| 157 | t0_it, t1_it); |
| 158 | } |
| 159 | #endif // !defined(BARE_METAL) |
| 160 | |
| 161 | TEST_SUITE_END() // RuntimeContext |
| 162 | TEST_SUITE_END() // UNIT |
| 163 | TEST_SUITE_END() // NEON |
| 164 | } // namespace validation |
| 165 | } // namespace test |
| 166 | } // namespace arm_compute |