From ee493ae23b8cd6de5a6c578cea34bccb478d2f64 Mon Sep 17 00:00:00 2001 From: Moritz Pflanzer Date: Wed, 5 Jul 2017 10:52:21 +0100 Subject: COMPMID-415: Port benchmark tests and remove google benchmark Change-Id: I2f17720a4e974b2cc4481f2884d9f351e8f78b5f Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79776 Tested-by: Kaizen Reviewed-by: Anthony Barbier --- tests/datasets_new/ActivationLayerDataset.h | 158 ++++++++++++++++++++++++++++ 1 file changed, 158 insertions(+) create mode 100644 tests/datasets_new/ActivationLayerDataset.h (limited to 'tests/datasets_new/ActivationLayerDataset.h') diff --git a/tests/datasets_new/ActivationLayerDataset.h b/tests/datasets_new/ActivationLayerDataset.h new file mode 100644 index 0000000000..02f58034d2 --- /dev/null +++ b/tests/datasets_new/ActivationLayerDataset.h @@ -0,0 +1,158 @@ +/* + * Copyright (c) 2017 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_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_ACTIVATION_LAYER_DATASET + +#include "framework/datasets/Datasets.h" + +#include "tests/TypePrinter.h" + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" + +namespace arm_compute +{ +namespace test +{ +namespace datasets +{ +class AlexNetActivationLayerDataset final : public + framework::dataset::CartesianProductDataset, framework::dataset::SingletonDataset> +{ +public: + AlexNetActivationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { + TensorShape(55U, 55U, 96U), TensorShape(27U, 27U, 256U), + TensorShape(13U, 13U, 384U), TensorShape(13U, 13U, 256U), + TensorShape(4096U) }), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + AlexNetActivationLayerDataset(AlexNetActivationLayerDataset &&) = default; + ~AlexNetActivationLayerDataset() = default; +}; + +class LeNet5ActivationLayerDataset final : public + framework::dataset::CartesianProductDataset, framework::dataset::SingletonDataset> +{ +public: + LeNet5ActivationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", TensorShape(500U)), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + LeNet5ActivationLayerDataset(LeNet5ActivationLayerDataset &&) = default; + ~LeNet5ActivationLayerDataset() = default; +}; + +class GoogLeNetActivationLayerDataset final : public + framework::dataset::CartesianProductDataset, framework::dataset::SingletonDataset> +{ +public: + GoogLeNetActivationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { // conv1/relu_7x7 + TensorShape(112U, 112U, 64U), + // conv2/relu_3x3_reduce + TensorShape(56U, 56U, 64U), + // conv2/relu_3x3 + TensorShape(56U, 56U, 192U), + // inception_3a/relu_1x1, inception_3b/relu_pool_proj + TensorShape(28U, 28U, 64U), + // inception_3a/relu_3x3_reduce, inception_3b/relu_5x5 + TensorShape(28U, 28U, 96U), + // inception_3a/relu_3x3, inception_3b/relu_1x1, inception_3b/relu_3x3_reduce + TensorShape(28U, 28U, 128U), + // inception_3a/relu_5x5_reduce + TensorShape(28U, 28U, 16U), + // inception_3a/relu_5x5, inception_3a/relu_pool_proj, inception_3b/relu_5x5_reduce + TensorShape(28U, 28U, 32U), + // inception_3b/relu_3x3 + TensorShape(28U, 28U, 192U), + // inception_4a/relu_1x1 + TensorShape(14U, 14U, 192U), + // inception_4a/relu_3x3_reduce + TensorShape(14U, 14U, 96U), + // inception_4a/relu_3x3 + TensorShape(14U, 14U, 208U), + // inception_4a/relu_5x5_reduce + TensorShape(14U, 14U, 16U), + // inception_4a/relu_5x5 + TensorShape(14U, 14U, 48U), + // inception_4a/relu_pool_proj, inception_4b/relu_5x5, inception_4b/relu_pool_proj, inception_4c/relu_5x5, inception_4c/relu_pool_proj, inception_4d/relu_5x5, inception_4d/relu_pool_proj + TensorShape(14U, 14U, 64U), + // inception_4b/relu_1x1, inception_4e/relu_3x3_reduce + TensorShape(14U, 14U, 160U), + // inception_4b/relu_3x3_reduce, inception_4d/relu_1x1 + TensorShape(14U, 14U, 112U), + // inception_4b/relu_3x3 + TensorShape(14U, 14U, 224U), + // inception_4b/relu_5x5_reduce, inception_4c/relu_5x5_reduce + TensorShape(14U, 14U, 24U), + // inception_4c/relu_1x1, inception_4c/relu_3x3_reduce, inception_4e/relu_5x5, inception_4e/relu_pool_proj + TensorShape(14U, 14U, 128U), + // inception_4c/relu_3x3, inception_4e/relu_1x1 + TensorShape(14U, 14U, 256U), + // inception_4d/relu_3x3_reduce + TensorShape(14U, 14U, 144U), + // inception_4d/relu_3x3 + TensorShape(14U, 14U, 288U), + // inception_4d/relu_5x5_reduce, inception_4e/relu_5x5_reduce + TensorShape(14U, 14U, 32U), + // inception_4e/relu_3x3 + TensorShape(14U, 14U, 320U), + // inception_5a/relu_1x1 + TensorShape(7U, 7U, 256U), + // inception_5a/relu_3x3_reduce + TensorShape(7U, 7U, 160U), + // inception_5a/relu_3x3 + TensorShape(7U, 7U, 320U), + // inception_5a/relu_5x5_reduce + TensorShape(7U, 7U, 32U), + // inception_5a/relu_5x5, inception_5a/relu_pool_proj, inception_5b/relu_5x5, inception_5b/relu_pool_proj + TensorShape(7U, 7U, 128U), + // inception_5b/relu_1x1, inception_5b/relu_3x3 + TensorShape(7U, 7U, 384U), + // inception_5b/relu_3x3_reduce + TensorShape(7U, 7U, 192U), + // inception_5b/relu_5x5_reduce + TensorShape(7U, 7U, 48U) }), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + GoogLeNetActivationLayerDataset(GoogLeNetActivationLayerDataset &&) = default; + ~GoogLeNetActivationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ACTIVATION_LAYER_DATASET */ -- cgit v1.2.1