Stephen Li | e855c23 | 2018-01-04 14:13:22 +0800 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2017-2018 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/core/TensorShape.h" |
| 25 | #include "arm_compute/core/Types.h" |
| 26 | #include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h" |
| 27 | #include "arm_compute/runtime/GLES_COMPUTE/GCTensorAllocator.h" |
| 28 | #include "arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h" |
| 29 | #include "tests/GLES_COMPUTE/GCAccessor.h" |
| 30 | #include "tests/benchmark/fixtures/ConvolutionLayerFixture.h" |
| 31 | #include "tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h" |
| 32 | #include "tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h" |
| 33 | #include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h" |
| 34 | #include "tests/datasets/system_tests/lenet5/LeNet5ConvolutionLayerDataset.h" |
| 35 | #include "tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h" |
| 36 | #include "tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h" |
| 37 | #include "tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h" |
| 38 | #include "tests/framework/Macros.h" |
| 39 | #include "tests/framework/datasets/Datasets.h" |
| 40 | #include "utils/TypePrinter.h" |
| 41 | |
| 42 | namespace arm_compute |
| 43 | { |
| 44 | namespace test |
| 45 | { |
| 46 | namespace |
| 47 | { |
| 48 | const auto data_types = framework::dataset::make("DataType", { DataType::F16 }); |
| 49 | } // namespace |
| 50 | |
| 51 | using GCConvolutionLayerFixture = ConvolutionLayerFixture<GCTensor, GCConvolutionLayer, GCAccessor>; |
| 52 | |
| 53 | TEST_SUITE(GC) |
| 54 | |
| 55 | REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, |
| 56 | framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), |
| 57 | data_types), |
| 58 | framework::dataset::make("Batches", 1))); |
| 59 | |
| 60 | REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, |
| 61 | framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), |
| 62 | data_types), |
| 63 | framework::dataset::make("Batches", 1))); |
| 64 | |
| 65 | REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, |
| 66 | framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), |
| 67 | data_types), |
| 68 | framework::dataset::make("Batches", 1))); |
| 69 | |
| 70 | REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, |
| 71 | framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), |
| 72 | data_types), |
| 73 | framework::dataset::make("Batches", 1))); |
| 74 | |
| 75 | REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, |
| 76 | framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), |
| 77 | data_types), |
| 78 | framework::dataset::make("Batches", 1))); |
| 79 | |
| 80 | TEST_SUITE(NIGHTLY) |
| 81 | REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| 82 | framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), |
| 83 | data_types), |
| 84 | framework::dataset::make("Batches", { 4, 8 }))); |
| 85 | |
| 86 | REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| 87 | framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), |
| 88 | data_types), |
| 89 | framework::dataset::make("Batches", { 4, 8 }))); |
| 90 | |
| 91 | REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| 92 | framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), |
| 93 | data_types), |
| 94 | framework::dataset::make("Batches", { 4, 8 }))); |
| 95 | |
| 96 | REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| 97 | framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), |
| 98 | data_types), |
| 99 | framework::dataset::make("Batches", { 4, 8 }))); |
| 100 | |
| 101 | REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| 102 | framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), |
| 103 | data_types), |
| 104 | framework::dataset::make("Batches", { 4, 8 }))); |
| 105 | |
| 106 | // 8 batches use about 1.8GB of memory which is too much for most devices! |
| 107 | REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| 108 | framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), |
| 109 | data_types), |
| 110 | framework::dataset::make("Batches", { 1, 4 }))); |
| 111 | |
| 112 | REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| 113 | framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), |
| 114 | data_types), |
| 115 | framework::dataset::make("Batches", { 1, 4, 8 }))); |
| 116 | TEST_SUITE_END() |
| 117 | TEST_SUITE_END() |
| 118 | } // namespace test |
| 119 | } // namespace arm_compute |