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Diffstat (limited to 'tests/dataset/ActivationLayerDataset.h')
| -rw-r--r-- | tests/dataset/ActivationLayerDataset.h | 177 |
1 files changed, 177 insertions, 0 deletions
diff --git a/tests/dataset/ActivationLayerDataset.h b/tests/dataset/ActivationLayerDataset.h new file mode 100644 index 0000000000..9d7cffba14 --- /dev/null +++ b/tests/dataset/ActivationLayerDataset.h @@ -0,0 +1,177 @@ +/* + * 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_DATASET_ACTIVATION_LAYER_DATASET_H__ +#define __ARM_COMPUTE_TEST_DATASET_ACTIVATION_LAYER_DATASET_H__ + +#include "TypePrinter.h" + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "dataset/GenericDataset.h" + +#include <sstream> +#include <type_traits> + +#ifdef BOOST +#include "boost_wrapper.h" +#endif + +namespace arm_compute +{ +namespace test +{ +class ActivationLayerDataObject +{ +public: + operator std::string() const + { + std::stringstream ss; + ss << "ActivationLayer"; + ss << "_I" << shape; + ss << "_F_" << info.activation(); + return ss.str(); + } + +public: + TensorShape shape; + ActivationLayerInfo info; +}; + +template <unsigned int Size> +using ActivationLayerDataset = GenericDataset<ActivationLayerDataObject, Size>; + +class AlexNetActivationLayerDataset final : public ActivationLayerDataset<5> +{ +public: + AlexNetActivationLayerDataset() + : GenericDataset + { + ActivationLayerDataObject{ TensorShape(55U, 55U, 96U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + ActivationLayerDataObject{ TensorShape(27U, 27U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + ActivationLayerDataObject{ TensorShape(13U, 13U, 384U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + ActivationLayerDataObject{ TensorShape(13U, 13U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + ActivationLayerDataObject{ TensorShape(4096U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + } + { + } + + ~AlexNetActivationLayerDataset() = default; +}; + +class LeNet5ActivationLayerDataset final : public ActivationLayerDataset<1> +{ +public: + LeNet5ActivationLayerDataset() + : GenericDataset + { + ActivationLayerDataObject{ TensorShape(500U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + } + { + } + + ~LeNet5ActivationLayerDataset() = default; +}; + +class GoogLeNetActivationLayerDataset final : public ActivationLayerDataset<33> +{ +public: + GoogLeNetActivationLayerDataset() + : GenericDataset + { + // conv1/relu_7x7 + ActivationLayerDataObject{ TensorShape(112U, 112U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // conv2/relu_3x3_reduce + ActivationLayerDataObject{ TensorShape(56U, 56U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // conv2/relu_3x3 + ActivationLayerDataObject{ TensorShape(56U, 56U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_3a/relu_1x1, inception_3b/relu_pool_proj + ActivationLayerDataObject{ TensorShape(28U, 28U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_3a/relu_3x3_reduce, inception_3b/relu_5x5 + ActivationLayerDataObject{ TensorShape(28U, 28U, 96U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_3a/relu_3x3, inception_3b/relu_1x1, inception_3b/relu_3x3_reduce + ActivationLayerDataObject{ TensorShape(28U, 28U, 128U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_3a/relu_5x5_reduce + ActivationLayerDataObject{ TensorShape(28U, 28U, 16U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_3a/relu_5x5, inception_3a/relu_pool_proj, inception_3b/relu_5x5_reduce + ActivationLayerDataObject{ TensorShape(28U, 28U, 32U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_3b/relu_3x3 + ActivationLayerDataObject{ TensorShape(28U, 28U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4a/relu_1x1 + ActivationLayerDataObject{ TensorShape(14U, 14U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4a/relu_3x3_reduce + ActivationLayerDataObject{ TensorShape(14U, 14U, 96U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4a/relu_3x3 + ActivationLayerDataObject{ TensorShape(14U, 14U, 208U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4a/relu_5x5_reduce + ActivationLayerDataObject{ TensorShape(14U, 14U, 16U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4a/relu_5x5 + ActivationLayerDataObject{ TensorShape(14U, 14U, 48U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // 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 + ActivationLayerDataObject{ TensorShape(14U, 14U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4b/relu_1x1, inception_4e/relu_3x3_reduce + ActivationLayerDataObject{ TensorShape(14U, 14U, 160U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4b/relu_3x3_reduce, inception_4d/relu_1x1 + ActivationLayerDataObject{ TensorShape(14U, 14U, 112U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4b/relu_3x3 + ActivationLayerDataObject{ TensorShape(14U, 14U, 224U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4b/relu_5x5_reduce, inception_4c/relu_5x5_reduce + ActivationLayerDataObject{ TensorShape(14U, 14U, 24U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4c/relu_1x1, inception_4c/relu_3x3_reduce, inception_4e/relu_5x5, inception_4e/relu_pool_proj + ActivationLayerDataObject{ TensorShape(14U, 14U, 128U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4c/relu_3x3, inception_4e/relu_1x1 + ActivationLayerDataObject{ TensorShape(14U, 14U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4d/relu_3x3_reduce + ActivationLayerDataObject{ TensorShape(14U, 14U, 144U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4d/relu_3x3 + ActivationLayerDataObject{ TensorShape(14U, 14U, 288U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4d/relu_5x5_reduce, inception_4e/relu_5x5_reduce + ActivationLayerDataObject{ TensorShape(14U, 14U, 32U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_4e/relu_3x3 + ActivationLayerDataObject{ TensorShape(14U, 14U, 320U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5a/relu_1x1 + ActivationLayerDataObject{ TensorShape(7U, 7U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5a/relu_3x3_reduce + ActivationLayerDataObject{ TensorShape(7U, 7U, 160U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5a/relu_3x3 + ActivationLayerDataObject{ TensorShape(7U, 7U, 320U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5a/relu_5x5_reduce + ActivationLayerDataObject{ TensorShape(7U, 7U, 32U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5a/relu_5x5, inception_5a/relu_pool_proj, inception_5b/relu_5x5, inception_5b/relu_pool_proj + ActivationLayerDataObject{ TensorShape(7U, 7U, 128U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5b/relu_1x1, inception_5b/relu_3x3 + ActivationLayerDataObject{ TensorShape(7U, 7U, 384U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5b/relu_3x3_reduce + ActivationLayerDataObject{ TensorShape(7U, 7U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }, + // inception_5b/relu_5x5_reduce + ActivationLayerDataObject{ TensorShape(7U, 7U, 48U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) } + } + { + } + + ~GoogLeNetActivationLayerDataset() = default; +}; + +} // namespace test +} // namespace arm_compute +#endif //__ARM_COMPUTE_TEST_DATASET_ACTIVATION_LAYER_DATASET_H__ |