diff options
author | Moritz Pflanzer <moritz.pflanzer@arm.com> | 2017-09-01 20:41:12 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | a09de0c8b2ed0f1481502d3b023375609362d9e3 (patch) | |
tree | e34b56d9ca69b025d7d9b943cc4df59cd458f6cb /tests/datasets/system_tests | |
parent | 5280071b336d53aff94ca3a6c70ebbe6bf03f4c3 (diff) | |
download | ComputeLibrary-a09de0c8b2ed0f1481502d3b023375609362d9e3.tar.gz |
COMPMID-415: Rename and move tests
The boost validation is now "standalone" in validation_old and builds as
arm_compute_validation_old. The new validation builds now as
arm_compute_validation.
Change-Id: Ib93ba848a25680ac60afb92b461d574a0757150d
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/86187
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/datasets/system_tests')
31 files changed, 2469 insertions, 0 deletions
diff --git a/tests/datasets/system_tests/alexnet/AlexNetActivationLayerDataset.h b/tests/datasets/system_tests/alexnet/AlexNetActivationLayerDataset.h new file mode 100644 index 0000000000..4030e97436 --- /dev/null +++ b/tests/datasets/system_tests/alexnet/AlexNetActivationLayerDataset.h @@ -0,0 +1,58 @@ +/* + * 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_ALEXNET_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_ALEXNET_ACTIVATION_LAYER_DATASET + +#include "tests/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::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +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; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ALEXNET_ACTIVATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h b/tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h new file mode 100644 index 0000000000..d0b901a9a1 --- /dev/null +++ b/tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h @@ -0,0 +1,66 @@ +/* + * 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_ALEXNET_CONVOLUTION_LAYER_DATASET +#define ARM_COMPUTE_TEST_ALEXNET_CONVOLUTION_LAYER_DATASET + +#include "tests/datasets/ConvolutionLayerDataset.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 AlexNetConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + AlexNetConvolutionLayerDataset() + { + add_config(TensorShape(227U, 227U, 3U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U), PadStrideInfo(4, 4, 0, 0)); + add_config(TensorShape(27U, 27U, 96U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U), PadStrideInfo(1, 1, 2, 2)); + add_config(TensorShape(13U, 13U, 256U), TensorShape(3U, 3U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U), PadStrideInfo(1, 1, 1, 1)); + } +}; + +class AlexNetDirectConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + AlexNetDirectConvolutionLayerDataset() + { + add_config(TensorShape(13U, 13U, 256U), TensorShape(3U, 3U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1)); + add_config(TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U), PadStrideInfo(1, 1, 1, 1)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ALEXNET_CONVOLUTION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/alexnet/AlexNetFullyConnectedLayerDataset.h b/tests/datasets/system_tests/alexnet/AlexNetFullyConnectedLayerDataset.h new file mode 100644 index 0000000000..50b0f7d75d --- /dev/null +++ b/tests/datasets/system_tests/alexnet/AlexNetFullyConnectedLayerDataset.h @@ -0,0 +1,53 @@ +/* + * 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_ALEXNET_FULLYCONNECTED_LAYER_DATASET +#define ARM_COMPUTE_TEST_ALEXNET_FULLYCONNECTED_LAYER_DATASET + +#include "tests/datasets/FullyConnectedLayerDataset.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 AlexNetFullyConnectedLayerDataset final : public FullyConnectedLayerDataset +{ +public: + AlexNetFullyConnectedLayerDataset() + { + add_config(TensorShape(6U, 6U, 256U), TensorShape(9216U, 4096U), TensorShape(4096U), TensorShape(4096U)); + add_config(TensorShape(4096U), TensorShape(4096U, 4096U), TensorShape(4096U), TensorShape(4096U)); + add_config(TensorShape(4096U), TensorShape(4096U, 1000U), TensorShape(1000U), TensorShape(1000U)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ALEXNET_FULLYCONNECTED_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/alexnet/AlexNetNormalizationLayerDataset.h b/tests/datasets/system_tests/alexnet/AlexNetNormalizationLayerDataset.h new file mode 100644 index 0000000000..33b7423442 --- /dev/null +++ b/tests/datasets/system_tests/alexnet/AlexNetNormalizationLayerDataset.h @@ -0,0 +1,58 @@ +/* + * 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_ALEXNET_NORMALIZATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_ALEXNET_NORMALIZATION_LAYER_DATASET + +#include "tests/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 AlexNetNormalizationLayerDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<NormalizationLayerInfo>> +{ +public: + AlexNetNormalizationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { TensorShape(55U, 55U, 96U), TensorShape(27U, 27U, 256U) }), + framework::dataset::make("Info", NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)) + } + { + } + AlexNetNormalizationLayerDataset(AlexNetNormalizationLayerDataset &&) = default; + ~AlexNetNormalizationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ALEXNET_NORMALIZATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/alexnet/AlexNetPoolingLayerDataset.h b/tests/datasets/system_tests/alexnet/AlexNetPoolingLayerDataset.h new file mode 100644 index 0000000000..ab2749b36e --- /dev/null +++ b/tests/datasets/system_tests/alexnet/AlexNetPoolingLayerDataset.h @@ -0,0 +1,53 @@ +/* + * 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_ALEXNET_POOLING_LAYER_DATASET +#define ARM_COMPUTE_TEST_ALEXNET_POOLING_LAYER_DATASET + +#include "tests/datasets/PoolingLayerDataset.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 AlexNetPoolingLayerDataset final : public PoolingLayerDataset +{ +public: + AlexNetPoolingLayerDataset() + { + add_config(TensorShape(55U, 55U, 96U), TensorShape(27U, 27U, 96U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))); + add_config(TensorShape(27U, 27U, 256U), TensorShape(13U, 13U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))); + add_config(TensorShape(13U, 13U, 256U), TensorShape(6U, 6U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ALEXNET_POOLING_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ActivationLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ActivationLayerDataset.h new file mode 100644 index 0000000000..dc4ffe4e4e --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ActivationLayerDataset.h @@ -0,0 +1,123 @@ +/* + * 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_GOOGLENETINCEPTIONV1_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_ACTIVATION_LAYER_DATASET + +#include "tests/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 GoogLeNetInceptionV1ActivationLayerDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +public: + GoogLeNetInceptionV1ActivationLayerDataset() + : 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)) + } + { + } + GoogLeNetInceptionV1ActivationLayerDataset(GoogLeNetInceptionV1ActivationLayerDataset &&) = default; + ~GoogLeNetInceptionV1ActivationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_ACTIVATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h new file mode 100644 index 0000000000..a4002d124d --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h @@ -0,0 +1,237 @@ +/* + * 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_GOOGLENETINCEPTIONV1_CONVOLUTION_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_CONVOLUTION_LAYER_DATASET + +#include "tests/datasets/ConvolutionLayerDataset.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 GoogLeNetInceptionV1ConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + // GoogLeNetInceptionV1 inception v1 dataset + GoogLeNetInceptionV1ConvolutionLayerDataset() + { + // conv1/7x7_s2 + add_config(TensorShape(224U, 224U, 3U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U), PadStrideInfo(2, 2, 3, 3)); + // conv2/3x3_reduce + add_config(TensorShape(56U, 56U, 64U), TensorShape(1U, 1U, 64U, 64U), TensorShape(64U), TensorShape(56U, 56U, 64U), PadStrideInfo(1, 1, 0, 0)); + // conv2/3x3 + add_config(TensorShape(56U, 56U, 64U), TensorShape(3U, 3U, 64U, 192U), TensorShape(192U), TensorShape(56U, 56U, 192U), PadStrideInfo(1, 1, 1, 1)); + // inception_3a/1x1 + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_3a/3x3_reduce + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 96U), TensorShape(96U), TensorShape(28U, 28U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_3a/3x3 + add_config(TensorShape(28U, 28U, 96U), TensorShape(3U, 3U, 96U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 1, 1)); + // inception_3a/5x5_reduce + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 16U), TensorShape(16U), TensorShape(28U, 28U, 16U), PadStrideInfo(1, 1, 0, 0)); + // inception_3a/5x5 + add_config(TensorShape(28U, 28U, 16U), TensorShape(5U, 5U, 16U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 2, 2)); + // inception_3a/pool_proj + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_3b/1x1, inception_3b/3x3_reduce + add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_3b/3x3 + add_config(TensorShape(28U, 28U, 128U), TensorShape(3U, 3U, 128U, 192U), TensorShape(192U), TensorShape(28U, 28U, 192U), PadStrideInfo(1, 1, 1, 1)); + // inception_3b/5x5_reduce + add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_3b/5x5 + add_config(TensorShape(28U, 28U, 32U), TensorShape(5U, 5U, 32U, 96U), TensorShape(96U), TensorShape(28U, 28U, 96U), PadStrideInfo(1, 1, 2, 2)); + // inception_3b/pool_proj + add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_4a/1x1 + add_config(TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 192U), TensorShape(192U), TensorShape(14U, 14U, 192U), PadStrideInfo(1, 1, 0, 0)); + // inception_4a/3x3_reduce + add_config(TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 96U), TensorShape(96U), TensorShape(14U, 14U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_4a/3x3 + add_config(TensorShape(14U, 14U, 96U), TensorShape(3U, 3U, 96U, 208U), TensorShape(208U), TensorShape(14U, 14U, 208U), PadStrideInfo(1, 1, 1, 1)); + // inception_4a/5x5_reduce + add_config(TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 16U), TensorShape(16U), TensorShape(14U, 14U, 16U), PadStrideInfo(1, 1, 0, 0)); + // inception_4a/5x5 + add_config(TensorShape(14U, 14U, 16U), TensorShape(5U, 5U, 16U, 48U), TensorShape(48U), TensorShape(14U, 14U, 48U), PadStrideInfo(1, 1, 2, 2)); + // inception_4a/pool_proj + add_config(TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/1x1 + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 160U), TensorShape(160U), TensorShape(14U, 14U, 160U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/3x3_reduce, inception_4d/1x1 + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 112U), TensorShape(112U), TensorShape(14U, 14U, 112U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/3x3 + add_config(TensorShape(14U, 14U, 112U), TensorShape(3U, 3U, 112U, 224U), TensorShape(224U), TensorShape(14U, 14U, 224U), PadStrideInfo(1, 1, 1, 1)); + // inception_4b/5x5_reduce, inception_4c/5x5_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 24U), TensorShape(24U), TensorShape(14U, 14U, 24U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/5x5, inception_4c/5x5 + add_config(TensorShape(14U, 14U, 24U), TensorShape(5U, 5U, 24U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 2, 2)); + // inception_4b/pool_proj, inception_4c/pool_proj, inception_4d/pool_proj + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_4c/1x1, inception_4c/3x3_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_4c/3x3 + add_config(TensorShape(14U, 14U, 128U), TensorShape(3U, 3U, 128U, 256U), TensorShape(256U), TensorShape(14U, 14U, 256U), PadStrideInfo(1, 1, 1, 1)); + // inception_4d/3x3_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 144U), TensorShape(144U), TensorShape(14U, 14U, 144U), PadStrideInfo(1, 1, 0, 0)); + // inception_4d/3x3 + add_config(TensorShape(14U, 14U, 144U), TensorShape(3U, 3U, 144U, 288U), TensorShape(288U), TensorShape(14U, 14U, 288U), PadStrideInfo(1, 1, 1, 1)); + // inception_4d/5x5_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 32U), TensorShape(32U), TensorShape(14U, 14U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_4d/5x5 + add_config(TensorShape(14U, 14U, 32U), TensorShape(5U, 5U, 32U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 2, 2)); + // inception_4e/1x1 + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 256U), TensorShape(256U), TensorShape(14U, 14U, 256U), PadStrideInfo(1, 1, 0, 0)); + // inception_4e/3x3_reduce + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 160U), TensorShape(160U), TensorShape(14U, 14U, 160U), PadStrideInfo(1, 1, 0, 0)); + // inception_4e/3x3 + add_config(TensorShape(14U, 14U, 160U), TensorShape(3U, 3U, 160U, 320U), TensorShape(320U), TensorShape(14U, 14U, 320U), PadStrideInfo(1, 1, 1, 1)); + // inception_4e/5x5_reduce + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 32U), TensorShape(32U), TensorShape(14U, 14U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_4e/5x5 + add_config(TensorShape(14U, 14U, 32U), TensorShape(5U, 5U, 32U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 2, 2)); + // inception_4e/pool_proj + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/1x1 + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 256U), TensorShape(256U), TensorShape(7U, 7U, 256U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/3x3_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 160U), TensorShape(160U), TensorShape(7U, 7U, 160U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/3x3 + add_config(TensorShape(7U, 7U, 160U), TensorShape(3U, 3U, 160U, 320U), TensorShape(320U), TensorShape(7U, 7U, 320U), PadStrideInfo(1, 1, 1, 1)); + // inception_5a/5x5_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 32U), TensorShape(32U), TensorShape(7U, 7U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/5x5 + add_config(TensorShape(7U, 7U, 32U), TensorShape(5U, 5U, 32U, 128U), TensorShape(128U), TensorShape(7U, 7U, 128U), PadStrideInfo(1, 1, 2, 2)); + // inception_5a/pool_proj, inception_5b/pool_proj + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 128U), TensorShape(128U), TensorShape(7U, 7U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_5b/1x1 + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 384U), TensorShape(384U), TensorShape(7U, 7U, 384U), PadStrideInfo(1, 1, 0, 0)); + // inception_5b/3x3_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 192U), TensorShape(192U), TensorShape(7U, 7U, 192U), PadStrideInfo(1, 1, 0, 0)); + // inception_5b/3x3 + add_config(TensorShape(7U, 7U, 192U), TensorShape(3U, 3U, 192U, 384U), TensorShape(384U), TensorShape(7U, 7U, 384U), PadStrideInfo(1, 1, 1, 1)); + // inception_5b/5x5_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 48U), TensorShape(48U), TensorShape(7U, 7U, 48U), PadStrideInfo(1, 1, 0, 0)); + // inception_5b/5x5 + add_config(TensorShape(7U, 7U, 48U), TensorShape(5U, 5U, 48U, 128U), TensorShape(128U), TensorShape(7U, 7U, 128U), PadStrideInfo(1, 1, 2, 2)); + } +}; + +class GoogLeNetInceptionV1DirectConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + // subset of GoogLeNetInceptionV1 inception v1 dataset + GoogLeNetInceptionV1DirectConvolutionLayerDataset() + { + // conv2/3x3_reduce + add_config(TensorShape(56U, 56U, 64U), TensorShape(1U, 1U, 64U, 64U), TensorShape(64U), TensorShape(56U, 56U, 64U), PadStrideInfo(1, 1, 0, 0)); + // conv2/3x3 + add_config(TensorShape(56U, 56U, 64U), TensorShape(3U, 3U, 64U, 192U), TensorShape(192U), TensorShape(56U, 56U, 192U), PadStrideInfo(1, 1, 1, 1)); + // inception_3a/1x1 + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_3a/3x3_reduce + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 96U), TensorShape(96U), TensorShape(28U, 28U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_3a/3x3 + add_config(TensorShape(28U, 28U, 96U), TensorShape(3U, 3U, 96U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 1, 1)); + // inception_3a/5x5_reduce + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 16U), TensorShape(16U), TensorShape(28U, 28U, 16U), PadStrideInfo(1, 1, 0, 0)); + // inception_3a/pool_proj + add_config(TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_3b/1x1, inception_3b/3x3_reduce + add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_3b/3x3 + add_config(TensorShape(28U, 28U, 128U), TensorShape(3U, 3U, 128U, 192U), TensorShape(192U), TensorShape(28U, 28U, 192U), PadStrideInfo(1, 1, 1, 1)); + // inception_3b/5x5_reduce + add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_3b/pool_proj + add_config(TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_4a/1x1 + add_config(TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 192U), TensorShape(192U), TensorShape(14U, 14U, 192U), PadStrideInfo(1, 1, 0, 0)); + // inception_4a/3x3_reduce + add_config(TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 96U), TensorShape(96U), TensorShape(14U, 14U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_4a/3x3 + add_config(TensorShape(14U, 14U, 96U), TensorShape(3U, 3U, 96U, 208U), TensorShape(208U), TensorShape(14U, 14U, 208U), PadStrideInfo(1, 1, 1, 1)); + // inception_4a/pool_proj + add_config(TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/1x1 + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 160U), TensorShape(160U), TensorShape(14U, 14U, 160U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/3x3_reduce, inception_4d/1x1 + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 112U), TensorShape(112U), TensorShape(14U, 14U, 112U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/3x3 + add_config(TensorShape(14U, 14U, 112U), TensorShape(3U, 3U, 112U, 224U), TensorShape(224U), TensorShape(14U, 14U, 224U), PadStrideInfo(1, 1, 1, 1)); + // inception_4b/5x5_reduce, inception_4c/5x5_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 24U), TensorShape(24U), TensorShape(14U, 14U, 24U), PadStrideInfo(1, 1, 0, 0)); + // inception_4b/pool_proj, inception_4c/pool_proj, inception_4d/pool_proj + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_4c/1x1, inception_4c/3x3_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_4c/3x3 + add_config(TensorShape(14U, 14U, 128U), TensorShape(3U, 3U, 128U, 256U), TensorShape(256U), TensorShape(14U, 14U, 256U), PadStrideInfo(1, 1, 1, 1)); + // inception_4d/3x3_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 144U), TensorShape(144U), TensorShape(14U, 14U, 144U), PadStrideInfo(1, 1, 0, 0)); + // inception_4d/3x3 + add_config(TensorShape(14U, 14U, 144U), TensorShape(3U, 3U, 144U, 288U), TensorShape(288U), TensorShape(14U, 14U, 288U), PadStrideInfo(1, 1, 1, 1)); + // inception_4d/5x5_reduce + add_config(TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 32U), TensorShape(32U), TensorShape(14U, 14U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_4e/1x1 + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 256U), TensorShape(256U), TensorShape(14U, 14U, 256U), PadStrideInfo(1, 1, 0, 0)); + // inception_4e/3x3_reduce + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 160U), TensorShape(160U), TensorShape(14U, 14U, 160U), PadStrideInfo(1, 1, 0, 0)); + // inception_4e/3x3 + add_config(TensorShape(14U, 14U, 160U), TensorShape(3U, 3U, 160U, 320U), TensorShape(320U), TensorShape(14U, 14U, 320U), PadStrideInfo(1, 1, 1, 1)); + // inception_4e/5x5_reduce + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 32U), TensorShape(32U), TensorShape(14U, 14U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_4e/pool_proj + add_config(TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/1x1 + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 256U), TensorShape(256U), TensorShape(7U, 7U, 256U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/3x3_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 160U), TensorShape(160U), TensorShape(7U, 7U, 160U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/3x3 + add_config(TensorShape(7U, 7U, 160U), TensorShape(3U, 3U, 160U, 320U), TensorShape(320U), TensorShape(7U, 7U, 320U), PadStrideInfo(1, 1, 1, 1)); + // inception_5a/5x5_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 32U), TensorShape(32U), TensorShape(7U, 7U, 32U), PadStrideInfo(1, 1, 0, 0)); + // inception_5a/pool_proj, inception_5b/pool_proj + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 128U), TensorShape(128U), TensorShape(7U, 7U, 128U), PadStrideInfo(1, 1, 0, 0)); + // inception_5b/1x1 + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 384U), TensorShape(384U), TensorShape(7U, 7U, 384U), PadStrideInfo(1, 1, 0, 0)); + // inception_5b/3x3_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 192U), TensorShape(192U), TensorShape(7U, 7U, 192U), PadStrideInfo(1, 1, 0, 0)); + // inception_5b/3x3 + add_config(TensorShape(7U, 7U, 192U), TensorShape(3U, 3U, 192U, 384U), TensorShape(384U), TensorShape(7U, 7U, 384U), PadStrideInfo(1, 1, 1, 1)); + // inception_5b/5x5_reduce + add_config(TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 48U), TensorShape(48U), TensorShape(7U, 7U, 48U), PadStrideInfo(1, 1, 0, 0)); + } +}; + +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_CONVOLUTION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1FullyConnectedLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1FullyConnectedLayerDataset.h new file mode 100644 index 0000000000..80a3473bc7 --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1FullyConnectedLayerDataset.h @@ -0,0 +1,51 @@ +/* + * 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_GOOGLENETINCEPTIONV1_FULLYCONNECTED_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_FULLYCONNECTED_LAYER_DATASET + +#include "tests/datasets/FullyConnectedLayerDataset.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 GoogLeNetInceptionV1FullyConnectedLayerDataset final : public FullyConnectedLayerDataset +{ +public: + GoogLeNetInceptionV1FullyConnectedLayerDataset() + { + add_config(TensorShape(1024U), TensorShape(1024U, 1000U), TensorShape(1000U), TensorShape(1000U)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_FULLYCONNECTED_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1GEMMDataset.h b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1GEMMDataset.h new file mode 100644 index 0000000000..806ca9378a --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1GEMMDataset.h @@ -0,0 +1,113 @@ +/* + * 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_GOOGLENETINCEPTIONV1_GEMM_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_GEMM_DATASET + +#include "tests/datasets/GEMMDataset.h" + +#include "tests/TypePrinter.h" + +#include "arm_compute/core/TensorShape.h" + +namespace arm_compute +{ +namespace test +{ +namespace datasets +{ +class GoogLeNetInceptionV1GEMMDataset final : public GEMMDataset +{ +public: + GoogLeNetInceptionV1GEMMDataset() + { + add_config(TensorShape(147U, 12544U), TensorShape(64U, 147U), TensorShape(64U, 12544U), TensorShape(64U, 12544U), 1.0f, 0.0f); + add_config(TensorShape(64U, 3136U), TensorShape(64U, 64U), TensorShape(64U, 3136U), TensorShape(64U, 3136U), 1.0f, 0.0f); + add_config(TensorShape(576U, 3136U), TensorShape(192U, 576U), TensorShape(192U, 3136U), TensorShape(192U, 3136U), 1.0f, 0.0f); + add_config(TensorShape(192U, 784U), TensorShape(64U, 192U), TensorShape(64U, 784U), TensorShape(64U, 784U), 1.0f, 0.0f); + add_config(TensorShape(192U, 784U), TensorShape(96U, 192U), TensorShape(96U, 784U), TensorShape(96U, 784U), 1.0f, 0.0f); + add_config(TensorShape(864U, 784U), TensorShape(128U, 864U), TensorShape(128U, 784U), TensorShape(128U, 784U), 1.0f, 0.0f); + add_config(TensorShape(192U, 784U), TensorShape(16U, 192U), TensorShape(16U, 784U), TensorShape(16U, 784U), 1.0f, 0.0f); + add_config(TensorShape(400U, 784U), TensorShape(32U, 400U), TensorShape(32U, 784U), TensorShape(32U, 784U), 1.0f, 0.0f); + add_config(TensorShape(192U, 784U), TensorShape(32U, 192U), TensorShape(32U, 784U), TensorShape(32U, 784U), 1.0f, 0.0f); + add_config(TensorShape(256U, 784U), TensorShape(128U, 256U), TensorShape(128U, 784U), TensorShape(128U, 784U), 1.0f, 0.0f); + add_config(TensorShape(256U, 784U), TensorShape(128U, 256U), TensorShape(128U, 784U), TensorShape(128U, 784U), 1.0f, 0.0f); + add_config(TensorShape(1152U, 784U), TensorShape(192U, 1152U), TensorShape(192U, 784U), TensorShape(192U, 784U), 1.0f, 0.0f); + add_config(TensorShape(256U, 784U), TensorShape(32U, 256U), TensorShape(32U, 784U), TensorShape(32U, 784U), 1.0f, 0.0f); + add_config(TensorShape(800U, 784U), TensorShape(96U, 800U), TensorShape(96U, 784U), TensorShape(96U, 784U), 1.0f, 0.0f); + add_config(TensorShape(256U, 784U), TensorShape(64U, 256U), TensorShape(64U, 784U), TensorShape(64U, 784U), 1.0f, 0.0f); + add_config(TensorShape(480U, 196U), TensorShape(192U, 480U), TensorShape(192U, 196U), TensorShape(192U, 196U), 1.0f, 0.0f); + add_config(TensorShape(480U, 196U), TensorShape(96U, 480U), TensorShape(96U, 196U), TensorShape(96U, 196U), 1.0f, 0.0f); + add_config(TensorShape(864U, 196U), TensorShape(204U, 864U), TensorShape(204U, 196U), TensorShape(204U, 196U), 1.0f, 0.0f); + add_config(TensorShape(480U, 196U), TensorShape(16U, 480U), TensorShape(16U, 196U), TensorShape(16U, 196U), 1.0f, 0.0f); + add_config(TensorShape(400U, 196U), TensorShape(48U, 400U), TensorShape(48U, 196U), TensorShape(48U, 196U), 1.0f, 0.0f); + add_config(TensorShape(480U, 196U), TensorShape(64U, 480U), TensorShape(64U, 196U), TensorShape(64U, 196U), 1.0f, 0.0f); + add_config(TensorShape(508U, 196U), TensorShape(160U, 508U), TensorShape(160U, 196U), TensorShape(160U, 196U), 1.0f, 0.0f); + add_config(TensorShape(508U, 196U), TensorShape(112U, 508U), TensorShape(112U, 196U), TensorShape(112U, 196U), 1.0f, 0.0f); + add_config(TensorShape(1008U, 196U), TensorShape(224U, 1008U), TensorShape(224U, 196U), TensorShape(224U, 196U), 1.0f, 0.0f); + add_config(TensorShape(508U, 196U), TensorShape(24U, 508U), TensorShape(24U, 196U), TensorShape(24U, 196U), 1.0f, 0.0f); + add_config(TensorShape(600U, 196U), TensorShape(64U, 600U), TensorShape(64U, 196U), TensorShape(64U, 196U), 1.0f, 0.0f); + add_config(TensorShape(508U, 196U), TensorShape(64U, 508U), TensorShape(64U, 196U), TensorShape(64U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(128U, 512U), TensorShape(128U, 196U), TensorShape(128U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(128U, 512U), TensorShape(128U, 196U), TensorShape(128U, 196U), 1.0f, 0.0f); + add_config(TensorShape(1152U, 196U), TensorShape(256U, 1152U), TensorShape(256U, 196U), TensorShape(256U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(24U, 512U), TensorShape(24U, 196U), TensorShape(24U, 196U), 1.0f, 0.0f); + add_config(TensorShape(600U, 196U), TensorShape(64U, 600U), TensorShape(64U, 196U), TensorShape(64U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(64U, 512U), TensorShape(64U, 196U), TensorShape(64U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(112U, 512U), TensorShape(112U, 196U), TensorShape(112U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(144U, 512U), TensorShape(144U, 196U), TensorShape(144U, 196U), 1.0f, 0.0f); + add_config(TensorShape(1296U, 196U), TensorShape(288U, 1296U), TensorShape(288U, 196U), TensorShape(288U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(32U, 512U), TensorShape(32U, 196U), TensorShape(32U, 196U), 1.0f, 0.0f); + add_config(TensorShape(800U, 196U), TensorShape(64U, 800U), TensorShape(64U, 196U), TensorShape(64U, 196U), 1.0f, 0.0f); + add_config(TensorShape(512U, 196U), TensorShape(64U, 512U), TensorShape(64U, 196U), TensorShape(64U, 196U), 1.0f, 0.0f); + add_config(TensorShape(528U, 196U), TensorShape(256U, 528U), TensorShape(256U, 196U), TensorShape(256U, 196U), 1.0f, 0.0f); + add_config(TensorShape(528U, 196U), TensorShape(160U, 528U), TensorShape(160U, 196U), TensorShape(160U, 196U), 1.0f, 0.0f); + add_config(TensorShape(1440U, 196U), TensorShape(320U, 1440U), TensorShape(320U, 196U), TensorShape(320U, 196U), 1.0f, 0.0f); + add_config(TensorShape(528U, 196U), TensorShape(32U, 528U), TensorShape(32U, 196U), TensorShape(32U, 196U), 1.0f, 0.0f); + add_config(TensorShape(800U, 196U), TensorShape(128U, 800U), TensorShape(128U, 196U), TensorShape(128U, 196U), 1.0f, 0.0f); + add_config(TensorShape(528U, 196U), TensorShape(128U, 528U), TensorShape(128U, 196U), TensorShape(128U, 196U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(256U, 832U), TensorShape(256U, 49U), TensorShape(256U, 49U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(160U, 832U), TensorShape(160U, 49U), TensorShape(160U, 49U), 1.0f, 0.0f); + add_config(TensorShape(1440U, 49U), TensorShape(320U, 1440U), TensorShape(320U, 49U), TensorShape(320U, 49U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(48U, 832U), TensorShape(48U, 49U), TensorShape(48U, 49U), 1.0f, 0.0f); + add_config(TensorShape(1200U, 49U), TensorShape(128U, 1200U), TensorShape(128U, 49U), TensorShape(128U, 49U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(128U, 832U), TensorShape(128U, 49U), TensorShape(128U, 49U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(384U, 832U), TensorShape(384U, 49U), TensorShape(384U, 49U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(192U, 832U), TensorShape(192U, 49U), TensorShape(192U, 49U), 1.0f, 0.0f); + add_config(TensorShape(1728U, 49U), TensorShape(384U, 1728U), TensorShape(384U, 49U), TensorShape(384U, 49U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(48U, 832U), TensorShape(48U, 49U), TensorShape(48U, 49U), 1.0f, 0.0f); + add_config(TensorShape(1200U, 49U), TensorShape(128U, 1200U), TensorShape(128U, 49U), TensorShape(128U, 49U), 1.0f, 0.0f); + add_config(TensorShape(832U, 49U), TensorShape(128U, 832U), TensorShape(128U, 49U), TensorShape(128U, 49U), 1.0f, 0.0f); + add_config(TensorShape(508U, 16U), TensorShape(128U, 508U), TensorShape(128U, 16U), TensorShape(128U, 16U), 1.0f, 0.0f); + add_config(TensorShape(2048U, 1U), TensorShape(1024U, 2048U), TensorShape(1024U, 1U), TensorShape(1024U, 1U), 1.0f, 0.0f); + add_config(TensorShape(1024U, 1U), TensorShape(1008U, 1024U), TensorShape(1008U, 1U), TensorShape(1008U, 1U), 1.0f, 0.0f); + add_config(TensorShape(528U, 16U), TensorShape(128U, 528U), TensorShape(128U, 16U), TensorShape(128U, 16U), 1.0f, 0.0f); + add_config(TensorShape(2048U, 1U), TensorShape(1024U, 2048U), TensorShape(1024U, 1U), TensorShape(1024U, 1U), 1.0f, 0.0f); + add_config(TensorShape(1024U, 1U), TensorShape(1008U, 1024U), TensorShape(1008U, 1U), TensorShape(1008U, 1U), 1.0f, 0.0f); + add_config(TensorShape(1024U, 1U), TensorShape(1008U, 1024U), TensorShape(1008U, 1U), TensorShape(1008U, 1U), 1.0f, 0.0f); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_GEMM_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1NormalizationLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1NormalizationLayerDataset.h new file mode 100644 index 0000000000..d8fd061b66 --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1NormalizationLayerDataset.h @@ -0,0 +1,61 @@ +/* + * 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_GOOGLENETINCEPTIONV1_NORMALIZATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_NORMALIZATION_LAYER_DATASET + +#include "tests/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 GoogLeNetInceptionV1NormalizationLayerDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<NormalizationLayerInfo>> +{ +public: + GoogLeNetInceptionV1NormalizationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { // conv2/norm2 + TensorShape(56U, 56U, 192U), + // pool1/norm1 + TensorShape(56U, 56U, 64U) }), + framework::dataset::make("Info", NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)) + } + { + } + GoogLeNetInceptionV1NormalizationLayerDataset(GoogLeNetInceptionV1NormalizationLayerDataset &&) = default; + ~GoogLeNetInceptionV1NormalizationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_NORMALIZATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1PoolingLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1PoolingLayerDataset.h new file mode 100644 index 0000000000..6164bbacea --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1PoolingLayerDataset.h @@ -0,0 +1,71 @@ +/* + * 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_GOOGLENETINCEPTIONV1_POOLING_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_POOLING_LAYER_DATASET + +#include "tests/datasets/PoolingLayerDataset.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 GoogLeNetInceptionV1PoolingLayerDataset final : public PoolingLayerDataset +{ +public: + GoogLeNetInceptionV1PoolingLayerDataset() + { + // FIXME: Add support for 7x7 pooling layer pool5/7x7_s1 + // pool1/3x3_s2 + add_config(TensorShape(112U, 112U, 64U), TensorShape(56U, 56U, 64U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool2/3x3_s2 + add_config(TensorShape(56U, 56U, 192U), TensorShape(28U, 28U, 192U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // inception_3a/pool + add_config(TensorShape(28U, 28U, 192U), TensorShape(28U, 28U, 192U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + // inception_3b/pool + add_config(TensorShape(28U, 28U, 256U), TensorShape(28U, 28U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + // pool3/3x3_s2 + add_config(TensorShape(28U, 28U, 480U), TensorShape(14U, 14U, 480U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // inception_4a/pool + add_config(TensorShape(14U, 14U, 480U), TensorShape(14U, 14U, 480U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + // inception_4b/pool, inception_4c/pool, inception_4d/pool + add_config(TensorShape(14U, 14U, 512U), TensorShape(14U, 14U, 512U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + // inception_4e/pool + add_config(TensorShape(14U, 14U, 528U), TensorShape(14U, 14U, 528U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + // pool4/3x3_s2 + add_config(TensorShape(14U, 14U, 832U), TensorShape(7U, 7U, 832U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // inception_5a/pool, inception_5b/pool + add_config(TensorShape(7U, 7U, 832U), TensorShape(7U, 7U, 832U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV1_POOLING_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ActivationLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ActivationLayerDataset.h new file mode 100644 index 0000000000..2d586390ec --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ActivationLayerDataset.h @@ -0,0 +1,101 @@ +/* + * 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_GOOGLENETINCEPTIONV4_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_ACTIVATION_LAYER_DATASET + +#include "tests/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 GoogLeNetInceptionV4ActivationLayerDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +public: + GoogLeNetInceptionV4ActivationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { // conv1_3x3_s2_relu + TensorShape(149U, 149U, 32U), + // conv2_3x3_s1_relu + TensorShape(147U, 147U, 32U), + // conv3_3x3_s1_relu + TensorShape(147U, 147U, 64U), + // inception_stem1_3x3_s2_relu + TensorShape(73U, 73U, 96U), + // inception_stem2_3x3_reduce_relu, inception_stem2_1x7_reduce_relu, inception_stem2_1x7_relu, inception_stem2_7x1_relu + TensorShape(73U, 73U, 64U), + // inception_stem2_3x3_relu, inception_stem2_3x3_2_relu + TensorShape(71U, 71U, 96U), + // inception_stem3_3x3_s2_relu, reduction_a_3x3_2_reduce_relu + TensorShape(35U, 35U, 192U), + // inception_a1_1x1_2_relu, inception_a1_3x3_relu, inception_a1_3x3_2_relu, inception_a1_3x3_3_relu, inception_a1_1x1_relu, inception_a2_1x1_2_relu, inception_a2_3x3_relu, inception_a2_3x3_2_relu, inception_a2_3x3_3_relu, inception_a2_1x1_relu, inception_a3_1x1_2_relu, inception_a3_3x3_relu, inception_a3_3x3_2_relu, inception_a3_3x3_3_relu, inception_a3_1x1_relu, inception_a4_1x1_2_relu, inception_a4_3x3_relu, inception_a4_3x3_2_relu, inception_a4_3x3_3_relu, inception_a4_1x1_relu + TensorShape(35U, 35U, 96U), + // inception_a1_3x3_reduce_relu, inception_a1_3x3_2_reduce_relu, inception_a2_3x3_reduce_relu, inception_a2_3x3_2_reduce_relu, inception_a3_3x3_reduce_relu, inception_a3_3x3_2_reduce_relu, inception_a4_3x3_reduce_relu, inception_a4_3x3_2_reduce_relu + TensorShape(35U, 35U, 64U), + // reduction_a_3x3_relu, inception_b1_1x1_2_relu, inception_b2_1x1_2_relu, inception_b3_1x1_2_relu, inception_b4_1x1_2_relu, inception_b5_1x1_2_relu, inception_b6_1x1_2_relu, inception_b7_1x1_2_relu + TensorShape(17U, 17U, 384U), + // reduction_a_3x3_2_relu + TensorShape(35U, 35U, 224U), + // reduction_a_3x3_3_relu, inception_b1_7x1_relu, inception_b1_1x7_3_relu, inception_b2_7x1_relu, inception_b2_1x7_3_relu, inception_b3_7x1_relu, inception_b3_1x7_3_relu, inception_b4_7x1_relu, inception_b4_1x7_3_relu, inception_b5_7x1_relu, inception_b5_1x7_3_relu, inception_b6_7x1_relu, inception_b6_1x7_3_relu, inception_b7_7x1_relu, inception_b7_1x7_3_relu, reduction_b_1x7_reduce_relu, reduction_b_1x7_relu + TensorShape(17U, 17U, 256U), + // inception_b1_1x7_reduce_relu, inception_b1_7x1_2_reduce_relu, inception_b1_7x1_2_relu, inception_b2_1x7_reduce_relu, inception_b2_7x1_2_reduce_relu, inception_b2_7x1_2_relu, inception_b3_1x7_reduce_relu, inception_b3_7x1_2_reduce_relu, inception_b3_7x1_2_relu, inception_b4_1x7_reduce_relu, inception_b4_7x1_2_reduce_relu, inception_b4_7x1_2_relu, inception_b5_1x7_reduce_relu, inception_b5_7x1_2_reduce_relu, inception_b5_7x1_2_relu, inception_b6_1x7_reduce_relu, inception_b6_7x1_2_reduce_relu, inception_b6_7x1_2_relu, inception_b7_1x7_reduce_relu, inception_b7_7x1_2_reduce_relu, inception_b7_7x1_2_relu, reduction_b_3x3_reduce_relu + TensorShape(17U, 17U, 192U), + // inception_b1_1x7_relu, inception_b1_1x7_2_relu, inception_b1_7x1_3_relu, inception_b2_1x7_relu, inception_b2_1x7_2_relu, inception_b2_7x1_3_relu, inception_b3_1x7_relu, inception_b3_1x7_2_relu, inception_b3_7x1_3_relu, inception_b4_1x7_relu, inception_b4_1x7_2_relu, inception_b4_7x1_3_relu, inception_b5_1x7_relu, inception_b5_1x7_2_relu, inception_b5_7x1_3_relu, inception_b6_1x7_relu, inception_b6_1x7_2_relu, inception_b6_7x1_3_relu, inception_b7_1x7_relu, inception_b7_1x7_2_relu, inception_b7_7x1_3_relu + TensorShape(17U, 17U, 224U), + // inception_b1_1x1_relu, inception_b2_1x1_relu, inception_b3_1x1_relu, inception_b4_1x1_relu, inception_b5_1x1_relu, inception_b6_1x1_relu, inception_b7_1x1_relu + TensorShape(17U, 17U, 128U), + // reduction_b_3x3_relu + TensorShape(8U, 8U, 192U), + // reduction_b_7x1_relu + TensorShape(17U, 17U, 320U), + // reduction_b_3x3_2_relu + TensorShape(8U, 8U, 320U), + // inception_c1_1x1_2_relu, inception_c1_1x3_relu, inception_c1_3x1_relu, inception_c1_1x3_3_relu, inception_c1_3x1_3_relu, inception_c1_1x1_relu, inception_c2_1x1_2_relu, inception_c2_1x3_relu, inception_c2_3x1_relu, inception_c2_1x3_3_relu, inception_c2_3x1_3_relu, inception_c2_1x1_relu, inception_c3_1x1_2_relu, inception_c3_1x3_relu, inception_c3_3x1_relu, inception_c3_1x3_3_relu, inception_c3_3x1_3_relu, inception_c3_1x1_relu + TensorShape(8U, 8U, 256U), + // inception_c1_1x1_3_relu, inception_c1_1x1_4_relu, inception_c2_1x1_3_relu, inception_c2_1x1_4_relu, inception_c3_1x1_3_relu, inception_c3_1x1_4_relu + TensorShape(8U, 8U, 384U), + // inception_c1_3x1_2_relu, inception_c2_3x1_2_relu, inception_c3_3x1_2_relu + TensorShape(8U, 8U, 448U), + // inception_c1_1x3_2_relu, inception_c2_1x3_2_relu, inception_c3_1x3_2_relu + TensorShape(8U, 8U, 512U) }), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + GoogLeNetInceptionV4ActivationLayerDataset(GoogLeNetInceptionV4ActivationLayerDataset &&) = default; + ~GoogLeNetInceptionV4ActivationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_ACTIVATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h new file mode 100644 index 0000000000..d96410f9eb --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h @@ -0,0 +1,94 @@ +/* + * 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_GOOGLENETINCEPTIONV4_BATCHNORMALIZATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_BATCHNORMALIZATION_LAYER_DATASET + +#include "tests/datasets/BatchNormalizationLayerDataset.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 GoogLeNetInceptionV4BatchNormalizationLayerDataset final : public BatchNormalizationLayerDataset +{ +public: + GoogLeNetInceptionV4BatchNormalizationLayerDataset() + { + // conv1_3x3_s2_bn + add_config(TensorShape(149U, 149U, 32U), TensorShape(32U), 0.000010f); + // conv2_3x3_s1_bn + add_config(TensorShape(147U, 147U, 32U), TensorShape(32U), 0.000010f); + // conv3_3x3_s1_bn + add_config(TensorShape(147U, 147U, 64U), TensorShape(64U), 0.000010f); + // inception_stem1_3x3_s2_bn + add_config(TensorShape(73U, 73U, 96U), TensorShape(96U), 0.000010f); + // inception_stem2_3x3_reduce_bn, inception_stem2_1x7_reduce_bn, inception_stem2_1x7_bn, inception_stem2_7x1_bn + add_config(TensorShape(73U, 73U, 64U), TensorShape(64U), 0.000010f); + // inception_stem2_3x3_bn, inception_stem2_3x3_2_bn + add_config(TensorShape(71U, 71U, 96U), TensorShape(96U), 0.000010f); + // inception_stem3_3x3_s2_bn, reduction_a_3x3_2_reduce_bn + add_config(TensorShape(35U, 35U, 192U), TensorShape(192U), 0.000010f); + // inception_a1_1x1_2_bn, inception_a1_3x3_bn, inception_a1_3x3_2_bn, inception_a1_3x3_3_bn, inception_a1_1x1_bn, inception_a2_1x1_2_bn, inception_a2_3x3_bn, inception_a2_3x3_2_bn, inception_a2_3x3_3_bn, inception_a2_1x1_bn, inception_a3_1x1_2_bn, inception_a3_3x3_bn, inception_a3_3x3_2_bn, inception_a3_3x3_3_bn, inception_a3_1x1_bn, inception_a4_1x1_2_bn, inception_a4_3x3_bn, inception_a4_3x3_2_bn, inception_a4_3x3_3_bn, inception_a4_1x1_bn + add_config(TensorShape(35U, 35U, 96U), TensorShape(96U), 0.000010f); + // inception_a1_3x3_reduce_bn, inception_a1_3x3_2_reduce_bn, inception_a2_3x3_reduce_bn, inception_a2_3x3_2_reduce_bn, inception_a3_3x3_reduce_bn, inception_a3_3x3_2_reduce_bn, inception_a4_3x3_reduce_bn, inception_a4_3x3_2_reduce_bn + add_config(TensorShape(35U, 35U, 64U), TensorShape(64U), 0.000010f); + // reduction_a_3x3_bn, inception_b1_1x1_2_bn, inception_b2_1x1_2_bn, inception_b3_1x1_2_bn, inception_b4_1x1_2_bn, inception_b5_1x1_2_bn, inception_b6_1x1_2_bn, inception_b7_1x1_2_bn + add_config(TensorShape(17U, 17U, 384U), TensorShape(384U), 0.000010f); + // reduction_a_3x3_2_bn + add_config(TensorShape(35U, 35U, 224U), TensorShape(224U), 0.000010f); + // reduction_a_3x3_3_bn, inception_b1_7x1_bn, inception_b1_1x7_3_bn, inception_b2_7x1_bn, inception_b2_1x7_3_bn, inception_b3_7x1_bn, inception_b3_1x7_3_bn, inception_b4_7x1_bn, inception_b4_1x7_3_bn, inception_b5_7x1_bn, inception_b5_1x7_3_bn, inception_b6_7x1_bn, inception_b6_1x7_3_bn, inception_b7_7x1_bn, inception_b7_1x7_3_bn, reduction_b_1x7_reduce_bn, reduction_b_1x7_bn + add_config(TensorShape(17U, 17U, 256U), TensorShape(256U), 0.000010f); + // inception_b1_1x7_reduce_bn, inception_b1_7x1_2_reduce_bn, inception_b1_7x1_2_bn, inception_b2_1x7_reduce_bn, inception_b2_7x1_2_reduce_bn, inception_b2_7x1_2_bn, inception_b3_1x7_reduce_bn, inception_b3_7x1_2_reduce_bn, inception_b3_7x1_2_bn, inception_b4_1x7_reduce_bn, inception_b4_7x1_2_reduce_bn, inception_b4_7x1_2_bn, inception_b5_1x7_reduce_bn, inception_b5_7x1_2_reduce_bn, inception_b5_7x1_2_bn, inception_b6_1x7_reduce_bn, inception_b6_7x1_2_reduce_bn, inception_b6_7x1_2_bn, inception_b7_1x7_reduce_bn, inception_b7_7x1_2_reduce_bn, inception_b7_7x1_2_bn, reduction_b_3x3_reduce_bn + add_config(TensorShape(17U, 17U, 192U), TensorShape(192U), 0.000010f); + // inception_b1_1x7_bn, inception_b1_1x7_2_bn, inception_b1_7x1_3_bn, inception_b2_1x7_bn, inception_b2_1x7_2_bn, inception_b2_7x1_3_bn, inception_b3_1x7_bn, inception_b3_1x7_2_bn, inception_b3_7x1_3_bn, inception_b4_1x7_bn, inception_b4_1x7_2_bn, inception_b4_7x1_3_bn, inception_b5_1x7_bn, inception_b5_1x7_2_bn, inception_b5_7x1_3_bn, inception_b6_1x7_bn, inception_b6_1x7_2_bn, inception_b6_7x1_3_bn, inception_b7_1x7_bn, inception_b7_1x7_2_bn, inception_b7_7x1_3_bn + add_config(TensorShape(17U, 17U, 224U), TensorShape(224U), 0.000010f); + // inception_b1_1x1_bn, inception_b2_1x1_bn, inception_b3_1x1_bn, inception_b4_1x1_bn, inception_b5_1x1_bn, inception_b6_1x1_bn, inception_b7_1x1_bn + add_config(TensorShape(17U, 17U, 128U), TensorShape(128U), 0.000010f); + // reduction_b_3x3_bn + add_config(TensorShape(8U, 8U, 192U), TensorShape(192U), 0.000010f); + // reduction_b_7x1_bn + add_config(TensorShape(17U, 17U, 320U), TensorShape(320U), 0.000010f); + // reduction_b_3x3_2_bn + add_config(TensorShape(8U, 8U, 320U), TensorShape(320U), 0.000010f); + // inception_c1_1x1_2_bn, inception_c1_1x3_bn, inception_c1_3x1_bn, inception_c1_1x3_3_bn, inception_c1_3x1_3_bn, inception_c1_1x1_bn, inception_c2_1x1_2_bn, inception_c2_1x3_bn, inception_c2_3x1_bn, inception_c2_1x3_3_bn, inception_c2_3x1_3_bn, inception_c2_1x1_bn, inception_c3_1x1_2_bn, inception_c3_1x3_bn, inception_c3_3x1_bn, inception_c3_1x3_3_bn, inception_c3_3x1_3_bn, inception_c3_1x1_bn + add_config(TensorShape(8U, 8U, 256U), TensorShape(256U), 0.000010f); + // inception_c1_1x1_3_bn, inception_c1_1x1_4_bn, inception_c2_1x1_3_bn, inception_c2_1x1_4_bn, inception_c3_1x1_3_bn, inception_c3_1x1_4_bn + add_config(TensorShape(8U, 8U, 384U), TensorShape(384U), 0.000010f); + // inception_c1_3x1_2_bn, inception_c2_3x1_2_bn, inception_c3_3x1_2_bn + add_config(TensorShape(8U, 8U, 448U), TensorShape(448U), 0.000010f); + // inception_c1_1x3_2_bn, inception_c2_1x3_2_bn, inception_c3_1x3_2_bn + add_config(TensorShape(8U, 8U, 512U), TensorShape(512U), 0.000010f); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_BATCHNORMALIZATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h new file mode 100644 index 0000000000..a050d3da74 --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h @@ -0,0 +1,184 @@ +/* + * 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_GOOGLENETINCEPTIONV4_CONVOLUTION_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_CONVOLUTION_LAYER_DATASET + +#include "tests/datasets/ConvolutionLayerDataset.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 GoogLeNetInceptionV4ConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + // GoogLeNetInceptionV4 inception v1 dataset + GoogLeNetInceptionV4ConvolutionLayerDataset() + { + // conv1_3x3_s2 + add_config(TensorShape(299U, 299U, 3U), TensorShape(3U, 3U, 3U, 32U), TensorShape(32U), TensorShape(149U, 149U, 32U), PadStrideInfo(2, 2, 0, 0)); + // conv2_3x3_s1 + add_config(TensorShape(149U, 149U, 32U), TensorShape(3U, 3U, 32U, 32U), TensorShape(32U), TensorShape(147U, 147U, 32U), PadStrideInfo(1, 1, 0, 0)); + // conv3_3x3_s1 + add_config(TensorShape(147U, 147U, 32U), TensorShape(3U, 3U, 32U, 64U), TensorShape(64U), TensorShape(147U, 147U, 64U), PadStrideInfo(1, 1, 1, 1)); + // inception_stem1_3x3_s2 + add_config(TensorShape(147U, 147U, 64U), TensorShape(3U, 3U, 64U, 96U), TensorShape(96U), TensorShape(73U, 73U, 96U), PadStrideInfo(2, 2, 0, 0)); + // inception_stem2_3x3_reduce, inception_stem2_1x7_reduce + add_config(TensorShape(73U, 73U, 160U), TensorShape(1U, 1U, 160U, 64U), TensorShape(64U), TensorShape(73U, 73U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_stem2_3x3, inception_stem2_3x3_2 + add_config(TensorShape(73U, 73U, 64U), TensorShape(3U, 3U, 64U, 96U), TensorShape(96U), TensorShape(71U, 71U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_stem2_1x7 + add_config(TensorShape(73U, 73U, 64U), TensorShape(7U, 1U, 64U, 64U), TensorShape(64U), TensorShape(73U, 73U, 64U), PadStrideInfo(1, 1, 3, 0)); + // inception_stem2_7x1 + add_config(TensorShape(73U, 73U, 64U), TensorShape(1U, 7U, 64U, 64U), TensorShape(64U), TensorShape(73U, 73U, 64U), PadStrideInfo(1, 1, 0, 3)); + // inception_stem3_3x3_s2 + add_config(TensorShape(71U, 71U, 192U), TensorShape(3U, 3U, 192U, 192U), TensorShape(192U), TensorShape(35U, 35U, 192U), PadStrideInfo(2, 2, 0, 0)); + // inception_a1_1x1_2, inception_a1_1x1, inception_a2_1x1_2, inception_a2_1x1, inception_a3_1x1_2, inception_a3_1x1, inception_a4_1x1_2, inception_a4_1x1 + add_config(TensorShape(35U, 35U, 384U), TensorShape(1U, 1U, 384U, 96U), TensorShape(96U), TensorShape(35U, 35U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_a1_3x3_reduce, inception_a1_3x3_2_reduce, inception_a2_3x3_reduce, inception_a2_3x3_2_reduce, inception_a3_3x3_reduce, inception_a3_3x3_2_reduce, inception_a4_3x3_reduce, inception_a4_3x3_2_reduce + add_config(TensorShape(35U, 35U, 384U), TensorShape(1U, 1U, 384U, 64U), TensorShape(64U), TensorShape(35U, 35U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_a1_3x3, inception_a1_3x3_2, inception_a2_3x3, inception_a2_3x3_2, inception_a3_3x3, inception_a3_3x3_2, inception_a4_3x3, inception_a4_3x3_2 + add_config(TensorShape(35U, 35U, 64U), TensorShape(3U, 3U, 64U, 96U), TensorShape(96U), TensorShape(35U, 35U, 96U), PadStrideInfo(1, 1, 1, 1)); + // inception_a1_3x3_3, inception_a2_3x3_3, inception_a3_3x3_3, inception_a4_3x3_3 + add_config(TensorShape(35U, 35U, 96U), TensorShape(3U, 3U, 96U, 96U), TensorShape(96U), TensorShape(35U, 35U, 96U), PadStrideInfo(1, 1, 1, 1)); + // reduction_a_3x3 + add_config(TensorShape(35U, 35U, 384U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(17U, 17U, 384U), PadStrideInfo(2, 2, 0, 0)); + // reduction_a_3x3_2_reduce + add_config(TensorShape(35U, 35U, 384U), TensorShape(1U, 1U, 384U, 192U), TensorShape(192U), TensorShape(35U, 35U, 192U), PadStrideInfo(1, 1, 0, 0)); + // reduction_a_3x3_2 + add_config(TensorShape(35U, 35U, 192U), TensorShape(3U, 3U, 192U, 224U), TensorShape(224U), TensorShape(35U, 35U, 224U), PadStrideInfo(1, 1, 1, 1)); + // reduction_a_3x3_3 + add_config(TensorShape(35U, 35U, 224U), TensorShape(3U, 3U, 224U, 256U), TensorShape(256U), TensorShape(17U, 17U, 256U), PadStrideInfo(2, 2, 0, 0)); + // inception_b1_1x1_2, inception_b2_1x1_2, inception_b3_1x1_2, inception_b4_1x1_2, inception_b5_1x1_2, inception_b6_1x1_2, inception_b7_1x1_2 + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 384U), TensorShape(384U), TensorShape(17U, 17U, 384U), PadStrideInfo(1, 1, 0, 0)); + // inception_b1_1x7_reduce, inception_b1_7x1_2_reduce, inception_b2_1x7_reduce, inception_b2_7x1_2_reduce, inception_b3_1x7_reduce, inception_b3_7x1_2_reduce, inception_b4_1x7_reduce, inception_b4_7x1_2_reduce, inception_b5_1x7_reduce, inception_b5_7x1_2_reduce, inception_b6_1x7_reduce, inception_b6_7x1_2_reduce, inception_b7_1x7_reduce, inception_b7_7x1_2_reduce, reduction_b_3x3_reduce + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 192U), TensorShape(192U), TensorShape(17U, 17U, 192U), PadStrideInfo(1, 1, 0, 0)); + // inception_b1_1x7, inception_b1_1x7_2, inception_b2_1x7, inception_b2_1x7_2, inception_b3_1x7, inception_b3_1x7_2, inception_b4_1x7, inception_b4_1x7_2, inception_b5_1x7, inception_b5_1x7_2, inception_b6_1x7, inception_b6_1x7_2, inception_b7_1x7, inception_b7_1x7_2 + add_config(TensorShape(17U, 17U, 192U), TensorShape(7U, 1U, 192U, 224U), TensorShape(224U), TensorShape(17U, 17U, 224U), PadStrideInfo(1, 1, 3, 0)); + // inception_b1_7x1, inception_b2_7x1, inception_b3_7x1, inception_b4_7x1, inception_b5_7x1, inception_b6_7x1, inception_b7_7x1 + add_config(TensorShape(17U, 17U, 224U), TensorShape(1U, 7U, 224U, 256U), TensorShape(256U), TensorShape(17U, 17U, 256U), PadStrideInfo(1, 1, 0, 3)); + // inception_b1_7x1_2, inception_b2_7x1_2, inception_b3_7x1_2, inception_b4_7x1_2, inception_b5_7x1_2, inception_b6_7x1_2, inception_b7_7x1_2 + add_config(TensorShape(17U, 17U, 192U), TensorShape(1U, 7U, 192U, 192U), TensorShape(192U), TensorShape(17U, 17U, 192U), PadStrideInfo(1, 1, 0, 3)); + // inception_b1_7x1_3, inception_b2_7x1_3, inception_b3_7x1_3, inception_b4_7x1_3, inception_b5_7x1_3, inception_b6_7x1_3, inception_b7_7x1_3 + add_config(TensorShape(17U, 17U, 224U), TensorShape(1U, 7U, 224U, 224U), TensorShape(224U), TensorShape(17U, 17U, 224U), PadStrideInfo(1, 1, 0, 3)); + // inception_b1_1x7_3, inception_b2_1x7_3, inception_b3_1x7_3, inception_b4_1x7_3, inception_b5_1x7_3, inception_b6_1x7_3, inception_b7_1x7_3 + add_config(TensorShape(17U, 17U, 224U), TensorShape(7U, 1U, 224U, 256U), TensorShape(256U), TensorShape(17U, 17U, 256U), PadStrideInfo(1, 1, 3, 0)); + // inception_b1_1x1, inception_b2_1x1, inception_b3_1x1, inception_b4_1x1, inception_b5_1x1, inception_b6_1x1, inception_b7_1x1 + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 128U), TensorShape(128U), TensorShape(17U, 17U, 128U), PadStrideInfo(1, 1, 0, 0)); + // reduction_b_3x3 + add_config(TensorShape(17U, 17U, 192U), TensorShape(3U, 3U, 192U, 192U), TensorShape(192U), TensorShape(8U, 8U, 192U), PadStrideInfo(2, 2, 0, 0)); + // reduction_b_1x7_reduce + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 256U), TensorShape(256U), TensorShape(17U, 17U, 256U), PadStrideInfo(1, 1, 0, 0)); + // reduction_b_1x7 + add_config(TensorShape(17U, 17U, 256U), TensorShape(7U, 1U, 256U, 256U), TensorShape(256U), TensorShape(17U, 17U, 256U), PadStrideInfo(1, 1, 3, 0)); + // reduction_b_7x1 + add_config(TensorShape(17U, 17U, 256U), TensorShape(1U, 7U, 256U, 320U), TensorShape(320U), TensorShape(17U, 17U, 320U), PadStrideInfo(1, 1, 0, 3)); + // reduction_b_3x3_2 + add_config(TensorShape(17U, 17U, 320U), TensorShape(3U, 3U, 320U, 320U), TensorShape(320U), TensorShape(8U, 8U, 320U), PadStrideInfo(2, 2, 0, 0)); + // inception_c1_1x1_2, inception_c1_1x1, inception_c2_1x1_2, inception_c2_1x1, inception_c3_1x1_2, inception_c3_1x1 + add_config(TensorShape(8U, 8U, 1536U), TensorShape(1U, 1U, 1536U, 256U), TensorShape(256U), TensorShape(8U, 8U, 256U), PadStrideInfo(1, 1, 0, 0)); + // inception_c1_1x1_3, inception_c1_1x1_4, inception_c2_1x1_3, inception_c2_1x1_4, inception_c3_1x1_3, inception_c3_1x1_4 + add_config(TensorShape(8U, 8U, 1536U), TensorShape(1U, 1U, 1536U, 384U), TensorShape(384U), TensorShape(8U, 8U, 384U), PadStrideInfo(1, 1, 0, 0)); + // inception_c1_1x3, inception_c2_1x3, inception_c3_1x3 + add_config(TensorShape(8U, 8U, 384U), TensorShape(3U, 1U, 384U, 256U), TensorShape(256U), TensorShape(8U, 8U, 256U), PadStrideInfo(1, 1, 1, 0)); + // inception_c1_3x1, inception_c2_3x1, inception_c3_3x1 + add_config(TensorShape(8U, 8U, 384U), TensorShape(1U, 3U, 384U, 256U), TensorShape(256U), TensorShape(8U, 8U, 256U), PadStrideInfo(1, 1, 0, 1)); + // inception_c1_3x1_2, inception_c2_3x1_2, inception_c3_3x1_2 + add_config(TensorShape(8U, 8U, 384U), TensorShape(1U, 3U, 384U, 448U), TensorShape(448U), TensorShape(8U, 8U, 448U), PadStrideInfo(1, 1, 0, 1)); + // inception_c1_1x3_2, inception_c2_1x3_2, inception_c3_1x3_2 + add_config(TensorShape(8U, 8U, 448U), TensorShape(3U, 1U, 448U, 512U), TensorShape(512U), TensorShape(8U, 8U, 512U), PadStrideInfo(1, 1, 1, 0)); + // inception_c1_1x3_3, inception_c2_1x3_3, inception_c3_1x3_3 + add_config(TensorShape(8U, 8U, 512U), TensorShape(3U, 1U, 512U, 256U), TensorShape(256U), TensorShape(8U, 8U, 256U), PadStrideInfo(1, 1, 1, 0)); + // inception_c1_3x1_3, inception_c2_3x1_3, inception_c3_3x1_3 + add_config(TensorShape(8U, 8U, 512U), TensorShape(1U, 3U, 512U, 256U), TensorShape(256U), TensorShape(8U, 8U, 256U), PadStrideInfo(1, 1, 0, 1)); + } +}; + +/** A subset of GoogLeNetInceptionV4 convolution layers with filter dimensions supported by DirectConvolution kernel */ +class GoogLeNetInceptionV4DirectConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + // subset of GoogLeNetInceptionV4 inception v1 dataset + GoogLeNetInceptionV4DirectConvolutionLayerDataset() + { + // conv1_3x3_s2 + add_config(TensorShape(299U, 299U, 3U), TensorShape(3U, 3U, 3U, 32U), TensorShape(32U), TensorShape(149U, 149U, 32U), PadStrideInfo(2, 2, 0, 0)); + // conv2_3x3_s1 + add_config(TensorShape(149U, 149U, 32U), TensorShape(3U, 3U, 32U, 32U), TensorShape(32U), TensorShape(147U, 147U, 32U), PadStrideInfo(1, 1, 0, 0)); + // conv3_3x3_s1 + add_config(TensorShape(147U, 147U, 32U), TensorShape(3U, 3U, 32U, 64U), TensorShape(64U), TensorShape(147U, 147U, 64U), PadStrideInfo(1, 1, 1, 1)); + // inception_stem1_3x3_s2 + add_config(TensorShape(147U, 147U, 64U), TensorShape(3U, 3U, 64U, 96U), TensorShape(96U), TensorShape(73U, 73U, 96U), PadStrideInfo(2, 2, 0, 0)); + // inception_stem2_3x3_reduce, inception_stem2_1x7_reduce + add_config(TensorShape(73U, 73U, 160U), TensorShape(1U, 1U, 160U, 64U), TensorShape(64U), TensorShape(73U, 73U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_stem2_3x3, inception_stem2_3x3_2 + add_config(TensorShape(73U, 73U, 64U), TensorShape(3U, 3U, 64U, 96U), TensorShape(96U), TensorShape(71U, 71U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_stem3_3x3_s2 + add_config(TensorShape(71U, 71U, 192U), TensorShape(3U, 3U, 192U, 192U), TensorShape(192U), TensorShape(35U, 35U, 192U), PadStrideInfo(2, 2, 0, 0)); + // inception_a1_1x1_2, inception_a1_1x1, inception_a2_1x1_2, inception_a2_1x1, inception_a3_1x1_2, inception_a3_1x1, inception_a4_1x1_2, inception_a4_1x1 + add_config(TensorShape(35U, 35U, 384U), TensorShape(1U, 1U, 384U, 96U), TensorShape(96U), TensorShape(35U, 35U, 96U), PadStrideInfo(1, 1, 0, 0)); + // inception_a1_3x3_reduce, inception_a1_3x3_2_reduce, inception_a2_3x3_reduce, inception_a2_3x3_2_reduce, inception_a3_3x3_reduce, inception_a3_3x3_2_reduce, inception_a4_3x3_reduce, inception_a4_3x3_2_reduce + add_config(TensorShape(35U, 35U, 384U), TensorShape(1U, 1U, 384U, 64U), TensorShape(64U), TensorShape(35U, 35U, 64U), PadStrideInfo(1, 1, 0, 0)); + // inception_a1_3x3, inception_a1_3x3_2, inception_a2_3x3, inception_a2_3x3_2, inception_a3_3x3, inception_a3_3x3_2, inception_a4_3x3, inception_a4_3x3_2 + add_config(TensorShape(35U, 35U, 64U), TensorShape(3U, 3U, 64U, 96U), TensorShape(96U), TensorShape(35U, 35U, 96U), PadStrideInfo(1, 1, 1, 1)); + // inception_a1_3x3_3, inception_a2_3x3_3, inception_a3_3x3_3, inception_a4_3x3_3 + add_config(TensorShape(35U, 35U, 96U), TensorShape(3U, 3U, 96U, 96U), TensorShape(96U), TensorShape(35U, 35U, 96U), PadStrideInfo(1, 1, 1, 1)); + // reduction_a_3x3 + add_config(TensorShape(35U, 35U, 384U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(17U, 17U, 384U), PadStrideInfo(2, 2, 0, 0)); + // reduction_a_3x3_2_reduce + add_config(TensorShape(35U, 35U, 384U), TensorShape(1U, 1U, 384U, 192U), TensorShape(192U), TensorShape(35U, 35U, 192U), PadStrideInfo(1, 1, 0, 0)); + // reduction_a_3x3_2 + add_config(TensorShape(35U, 35U, 192U), TensorShape(3U, 3U, 192U, 224U), TensorShape(224U), TensorShape(35U, 35U, 224U), PadStrideInfo(1, 1, 1, 1)); + // reduction_a_3x3_3 + add_config(TensorShape(35U, 35U, 224U), TensorShape(3U, 3U, 224U, 256U), TensorShape(256U), TensorShape(17U, 17U, 256U), PadStrideInfo(2, 2, 0, 0)); + // inception_b1_1x1_2, inception_b2_1x1_2, inception_b3_1x1_2, inception_b4_1x1_2, inception_b5_1x1_2, inception_b6_1x1_2, inception_b7_1x1_2 + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 384U), TensorShape(384U), TensorShape(17U, 17U, 384U), PadStrideInfo(1, 1, 0, 0)); + // inception_b1_1x7_reduce, inception_b1_7x1_2_reduce, inception_b2_1x7_reduce, inception_b2_7x1_2_reduce, inception_b3_1x7_reduce, inception_b3_7x1_2_reduce, inception_b4_1x7_reduce, inception_b4_7x1_2_reduce, inception_b5_1x7_reduce, inception_b5_7x1_2_reduce, inception_b6_1x7_reduce, inception_b6_7x1_2_reduce, inception_b7_1x7_reduce, inception_b7_7x1_2_reduce, reduction_b_3x3_reduce + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 192U), TensorShape(192U), TensorShape(17U, 17U, 192U), PadStrideInfo(1, 1, 0, 0)); + // inception_b1_1x1, inception_b2_1x1, inception_b3_1x1, inception_b4_1x1, inception_b5_1x1, inception_b6_1x1, inception_b7_1x1 + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 128U), TensorShape(128U), TensorShape(17U, 17U, 128U), PadStrideInfo(1, 1, 0, 0)); + // reduction_b_3x3 + add_config(TensorShape(17U, 17U, 192U), TensorShape(3U, 3U, 192U, 192U), TensorShape(192U), TensorShape(8U, 8U, 192U), PadStrideInfo(2, 2, 0, 0)); + // reduction_b_1x7_reduce + add_config(TensorShape(17U, 17U, 1024U), TensorShape(1U, 1U, 1024U, 256U), TensorShape(256U), TensorShape(17U, 17U, 256U), PadStrideInfo(1, 1, 0, 0)); + // reduction_b_3x3_2 + add_config(TensorShape(17U, 17U, 320U), TensorShape(3U, 3U, 320U, 320U), TensorShape(320U), TensorShape(8U, 8U, 320U), PadStrideInfo(2, 2, 0, 0)); + // inception_c1_1x1_2, inception_c1_1x1, inception_c2_1x1_2, inception_c2_1x1, inception_c3_1x1_2, inception_c3_1x1 + add_config(TensorShape(8U, 8U, 1536U), TensorShape(1U, 1U, 1536U, 256U), TensorShape(256U), TensorShape(8U, 8U, 256U), PadStrideInfo(1, 1, 0, 0)); + // inception_c1_1x1_3, inception_c1_1x1_4, inception_c2_1x1_3, inception_c2_1x1_4, inception_c3_1x1_3, inception_c3_1x1_4 + add_config(TensorShape(8U, 8U, 1536U), TensorShape(1U, 1U, 1536U, 384U), TensorShape(384U), TensorShape(8U, 8U, 384U), PadStrideInfo(1, 1, 0, 0)); + } +}; + +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_CONVOLUTION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4FullyConnectedLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4FullyConnectedLayerDataset.h new file mode 100644 index 0000000000..8cf59e8207 --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4FullyConnectedLayerDataset.h @@ -0,0 +1,51 @@ +/* + * 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_GOOGLENETINCEPTIONV4_FULLYCONNECTED_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_FULLYCONNECTED_LAYER_DATASET + +#include "tests/datasets/FullyConnectedLayerDataset.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 GoogLeNetInceptionV4FullyConnectedLayerDataset final : public FullyConnectedLayerDataset +{ +public: + GoogLeNetInceptionV4FullyConnectedLayerDataset() + { + add_config(TensorShape(1536U), TensorShape(1536U, 1000U), TensorShape(1000U), TensorShape(1000U)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_FULLYCONNECTED_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4PoolingLayerDataset.h b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4PoolingLayerDataset.h new file mode 100644 index 0000000000..3b1ee8dcb4 --- /dev/null +++ b/tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4PoolingLayerDataset.h @@ -0,0 +1,65 @@ +/* + * 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_GOOGLENETINCEPTIONV4_POOLING_LAYER_DATASET +#define ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_POOLING_LAYER_DATASET + +#include "tests/datasets/PoolingLayerDataset.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 GoogLeNetInceptionV4PoolingLayerDataset final : public PoolingLayerDataset +{ +public: + GoogLeNetInceptionV4PoolingLayerDataset() + { + // FIXME: Add support for global pooling layer pool_8x8_s1 + // inception_stem1_pool + add_config(TensorShape(147U, 147U, 64U), TensorShape(73U, 73U, 64U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // inception_stem3_pool + add_config(TensorShape(71U, 71U, 192U), TensorShape(35U, 35U, 192U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // inception_a1_pool_ave, inception_a2_pool_ave, inception_a3_pool_ave, inception_a4_pool_ave + add_config(TensorShape(35U, 35U, 384U), TensorShape(35U, 35U, 384U), PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + // reduction_a_pool + add_config(TensorShape(35U, 35U, 384U), TensorShape(17U, 17U, 384U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // inception_b1_pool_ave, inception_b2_pool_ave, inception_b3_pool_ave, inception_b4_pool_ave, inception_b5_pool_ave, inception_b6_pool_ave, inception_b7_pool_ave + add_config(TensorShape(17U, 17U, 1024U), TensorShape(17U, 17U, 1024U), PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + // reduction_b_pool + add_config(TensorShape(17U, 17U, 1024U), TensorShape(8U, 8U, 1024U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // inception_c1_pool_ave, inception_c2_pool_ave, inception_c3_pool_ave + add_config(TensorShape(8U, 8U, 1536U), TensorShape(8U, 8U, 1536U), PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL))); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_GOOGLENETINCEPTIONV4_POOLING_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/lenet5/LeNet5ActivationLayerDataset.h b/tests/datasets/system_tests/lenet5/LeNet5ActivationLayerDataset.h new file mode 100644 index 0000000000..4c88cde58d --- /dev/null +++ b/tests/datasets/system_tests/lenet5/LeNet5ActivationLayerDataset.h @@ -0,0 +1,58 @@ +/* + * 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_LENET5_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_LENET5_ACTIVATION_LAYER_DATASET + +#include "tests/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 LeNet5ActivationLayerDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::SingletonDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +public: + LeNet5ActivationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", TensorShape(500U)), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + LeNet5ActivationLayerDataset(LeNet5ActivationLayerDataset &&) = default; + ~LeNet5ActivationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_LENET5_ACTIVATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/lenet5/LeNet5ConvolutionLayerDataset.h b/tests/datasets/system_tests/lenet5/LeNet5ConvolutionLayerDataset.h new file mode 100644 index 0000000000..e1d3ead65b --- /dev/null +++ b/tests/datasets/system_tests/lenet5/LeNet5ConvolutionLayerDataset.h @@ -0,0 +1,52 @@ +/* + * 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_LENET5_CONVOLUTION_LAYER_DATASET +#define ARM_COMPUTE_TEST_LENET5_CONVOLUTION_LAYER_DATASET + +#include "tests/datasets/ConvolutionLayerDataset.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 LeNet5ConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + LeNet5ConvolutionLayerDataset() + { + add_config(TensorShape(28U, 28U, 1U), TensorShape(5U, 5U, 1U, 20U), TensorShape(20U), TensorShape(24U, 24U, 20U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(12U, 12U, 20U), TensorShape(5U, 5U, 20U, 50U), TensorShape(50U), TensorShape(8U, 8U, 50U), PadStrideInfo(1, 1, 0, 0)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_LENET5_CONVOLUTION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/lenet5/LeNet5FullyConnectedLayerDataset.h b/tests/datasets/system_tests/lenet5/LeNet5FullyConnectedLayerDataset.h new file mode 100644 index 0000000000..343ecc0190 --- /dev/null +++ b/tests/datasets/system_tests/lenet5/LeNet5FullyConnectedLayerDataset.h @@ -0,0 +1,54 @@ +/* + * 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_LENET5_FULLYCONNECTED_LAYER_DATASET +#define ARM_COMPUTE_TEST_LENET5_FULLYCONNECTED_LAYER_DATASET + +#include "tests/datasets/FullyConnectedLayerDataset.h" + +#include "tests/TypePrinter.h" + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" + +using namespace arm_compute; + +namespace arm_compute +{ +namespace test +{ +namespace datasets +{ +class LeNet5FullyConnectedLayerDataset final : public FullyConnectedLayerDataset +{ +public: + LeNet5FullyConnectedLayerDataset() + { + add_config(TensorShape(4U, 4U, 50U), TensorShape(800U, 500U), TensorShape(500U), TensorShape(500U)); + add_config(TensorShape(500U), TensorShape(500U, 10U), TensorShape(10U), TensorShape(10U)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_LENET5_FULLYCONNECTED_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/lenet5/LeNet5PoolingLayerDataset.h b/tests/datasets/system_tests/lenet5/LeNet5PoolingLayerDataset.h new file mode 100644 index 0000000000..bc2de7b235 --- /dev/null +++ b/tests/datasets/system_tests/lenet5/LeNet5PoolingLayerDataset.h @@ -0,0 +1,52 @@ +/* + * 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_LENET5_POOLING_LAYER_DATASET +#define ARM_COMPUTE_TEST_LENET5_POOLING_LAYER_DATASET + +#include "tests/datasets/PoolingLayerDataset.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 LeNet5PoolingLayerDataset final : public PoolingLayerDataset +{ +public: + LeNet5PoolingLayerDataset() + { + add_config(TensorShape(24U, 24U, 20U), TensorShape(12U, 12U, 20U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))); + add_config(TensorShape(8U, 8U, 50U), TensorShape(4U, 4U, 50U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_LENET5_POOLING_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/squeezenet/SqueezeNetActivationLayerDataset.h b/tests/datasets/system_tests/squeezenet/SqueezeNetActivationLayerDataset.h new file mode 100644 index 0000000000..7644387384 --- /dev/null +++ b/tests/datasets/system_tests/squeezenet/SqueezeNetActivationLayerDataset.h @@ -0,0 +1,77 @@ +/* + * 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_SQUEEZENET_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_SQUEEZENET_ACTIVATION_LAYER_DATASET + +#include "tests/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 SqueezeNetActivationLayerDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +public: + SqueezeNetActivationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { // relu_conv1 + TensorShape(111U, 111U, 64U), + // fire2/relu_squeeze1x1, fire3/relu_squeeze1x1 + TensorShape(55U, 55U, 16U), + // fire2/relu_expand1x1, fire2/relu_expand3x3, fire3/relu_expand1x1, fire3/relu_expand3x3 + TensorShape(55U, 55U, 64U), + // fire4/relu_squeeze1x1, fire5/relu_squeeze1x1 + TensorShape(27U, 27U, 32U), + // fire4/relu_expand1x1, fire4/relu_expand3x3, fire5/relu_expand1x1, fire5/relu_expand3x3 + TensorShape(27U, 27U, 128U), + // fire6/relu_squeeze1x1, fire7/relu_squeeze1x1 + TensorShape(13U, 13U, 48U), + // fire6/relu_expand1x1, fire6/relu_expand3x3, fire7/relu_expand1x1, fire7/relu_expand3x3 + TensorShape(13U, 13U, 192U), + // fire8/relu_squeeze1x1, fire9/relu_squeeze1x1 + TensorShape(13U, 13U, 64U), + // fire8/relu_expand1x1, fire8/relu_expand3x3, fire9/relu_expand1x1, fire9/relu_expand3x3 + TensorShape(13U, 13U, 256U), + // relu_conv10 + TensorShape(13U, 13U, 1000U) }), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + SqueezeNetActivationLayerDataset(SqueezeNetActivationLayerDataset &&) = default; + ~SqueezeNetActivationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_SQUEEZENET_ACTIVATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h b/tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h new file mode 100644 index 0000000000..2d447b0156 --- /dev/null +++ b/tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h @@ -0,0 +1,86 @@ +/* + * 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_SQUEEZENET_CONVOLUTION_LAYER_DATASET +#define ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET + +#include "tests/datasets/ConvolutionLayerDataset.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 SqueezeNetConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + SqueezeNetConvolutionLayerDataset() + { + // conv1 + add_config(TensorShape(224U, 224U, 3U), TensorShape(3U, 3U, 3U, 64U), TensorShape(64U), TensorShape(111U, 111U, 64U), PadStrideInfo(2, 2, 0, 0)); + // fire2/squeeze1x1 + add_config(TensorShape(55U, 55U, 64U), TensorShape(1U, 1U, 64U, 16U), TensorShape(16U), TensorShape(55U, 55U, 16U), PadStrideInfo(1, 1, 0, 0)); + // fire2/expand1x1, fire3/expand1x1 + add_config(TensorShape(55U, 55U, 16U), TensorShape(1U, 1U, 16U, 64U), TensorShape(64U), TensorShape(55U, 55U, 64U), PadStrideInfo(1, 1, 0, 0)); + // fire2/expand3x3, fire3/expand3x3 + add_config(TensorShape(55U, 55U, 16U), TensorShape(3U, 3U, 16U, 64U), TensorShape(64U), TensorShape(55U, 55U, 64U), PadStrideInfo(1, 1, 1, 1)); + // fire3/squeeze1x1 + add_config(TensorShape(55U, 55U, 128U), TensorShape(1U, 1U, 128U, 16U), TensorShape(16U), TensorShape(55U, 55U, 16U), PadStrideInfo(1, 1, 0, 0)); + // fire4/squeeze1x1 + add_config(TensorShape(27U, 27U, 128U), TensorShape(1U, 1U, 128U, 32U), TensorShape(32U), TensorShape(27U, 27U, 32U), PadStrideInfo(1, 1, 0, 0)); + // fire4/expand1x1, fire5/expand1x1 + add_config(TensorShape(27U, 27U, 32U), TensorShape(1U, 1U, 32U, 128U), TensorShape(128U), TensorShape(27U, 27U, 128U), PadStrideInfo(1, 1, 0, 0)); + // fire4/expand3x3, fire5/expand3x3 + add_config(TensorShape(27U, 27U, 32U), TensorShape(3U, 3U, 32U, 128U), TensorShape(128U), TensorShape(27U, 27U, 128U), PadStrideInfo(1, 1, 1, 1)); + // fire5/squeeze1x1 + add_config(TensorShape(27U, 27U, 256U), TensorShape(1U, 1U, 256U, 32U), TensorShape(32U), TensorShape(27U, 27U, 32U), PadStrideInfo(1, 1, 0, 0)); + // fire6/squeeze1x1 + add_config(TensorShape(13U, 13U, 256U), TensorShape(1U, 1U, 256U, 48U), TensorShape(48U), TensorShape(13U, 13U, 48U), PadStrideInfo(1, 1, 0, 0)); + // fire6/expand1x1, fire7/expand1x1 + add_config(TensorShape(13U, 13U, 48U), TensorShape(1U, 1U, 48U, 192U), TensorShape(192U), TensorShape(13U, 13U, 192U), PadStrideInfo(1, 1, 0, 0)); + // fire6/expand3x3, fire7/expand3x3 + add_config(TensorShape(13U, 13U, 48U), TensorShape(3U, 3U, 48U, 192U), TensorShape(192U), TensorShape(13U, 13U, 192U), PadStrideInfo(1, 1, 1, 1)); + // fire7/squeeze1x1 + add_config(TensorShape(13U, 13U, 384U), TensorShape(1U, 1U, 384U, 48U), TensorShape(48U), TensorShape(13U, 13U, 48U), PadStrideInfo(1, 1, 0, 0)); + // fire8/squeeze1x1 + add_config(TensorShape(13U, 13U, 384U), TensorShape(1U, 1U, 384U, 64U), TensorShape(64U), TensorShape(13U, 13U, 64U), PadStrideInfo(1, 1, 0, 0)); + // fire8/expand1x1, fire9/expand1x1 + add_config(TensorShape(13U, 13U, 64U), TensorShape(1U, 1U, 64U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U), PadStrideInfo(1, 1, 0, 0)); + // fire8/expand3x3, fire9/expand3x3 + add_config(TensorShape(13U, 13U, 64U), TensorShape(3U, 3U, 64U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U), PadStrideInfo(1, 1, 1, 1)); + // fire9/squeeze1x1 + add_config(TensorShape(13U, 13U, 512U), TensorShape(1U, 1U, 512U, 64U), TensorShape(64U), TensorShape(13U, 13U, 64U), PadStrideInfo(1, 1, 0, 0)); + // conv10 + add_config(TensorShape(13U, 13U, 512U), TensorShape(1U, 1U, 512U, 1000U), TensorShape(1000U), TensorShape(13U, 13U, 1000U), PadStrideInfo(1, 1, 0, 0)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_SQUEEZENET_CONVOLUTION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/squeezenet/SqueezeNetPoolingLayerDataset.h b/tests/datasets/system_tests/squeezenet/SqueezeNetPoolingLayerDataset.h new file mode 100644 index 0000000000..69d04db7e1 --- /dev/null +++ b/tests/datasets/system_tests/squeezenet/SqueezeNetPoolingLayerDataset.h @@ -0,0 +1,57 @@ +/* + * 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_SQUEEZENET_POOLING_LAYER_DATASET +#define ARM_COMPUTE_TEST_SQUEEZENET_POOLING_LAYER_DATASET + +#include "tests/datasets/PoolingLayerDataset.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 SqueezeNetPoolingLayerDataset final : public PoolingLayerDataset +{ +public: + SqueezeNetPoolingLayerDataset() + { + // pool1 + add_config(TensorShape(111U, 111U, 64U), TensorShape(55U, 55U, 64U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool3 + add_config(TensorShape(55U, 55U, 128U), TensorShape(27U, 27U, 128U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool5 + add_config(TensorShape(27U, 27U, 256U), TensorShape(13U, 13U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + //FIXME: Add support for global pooling. + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_SQUEEZENET_POOLING_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/vgg/vgg16/VGG16ActivationLayerDataset.h b/tests/datasets/system_tests/vgg/vgg16/VGG16ActivationLayerDataset.h new file mode 100644 index 0000000000..66301ddf08 --- /dev/null +++ b/tests/datasets/system_tests/vgg/vgg16/VGG16ActivationLayerDataset.h @@ -0,0 +1,69 @@ +/* + * 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_VGG16_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_VGG16_ACTIVATION_LAYER_DATASET + +#include "tests/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 VGG16ActivationLayerDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +public: + VGG16ActivationLayerDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { // relu1_1, relu1_2 + TensorShape(224U, 224U, 64U), + // relu2_1, relu2_2 + TensorShape(112U, 112U, 128U), + // relu3_1, relu3_2, relu3_3 + TensorShape(56U, 56U, 256U), + // relu4_1, relu4_2, relu4_3 + TensorShape(28U, 28U, 512U), + // relu5_1, relu5_2, relu5_3 + TensorShape(14U, 14U, 512U), + // relu6, relu7 + TensorShape(4096U) }), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + VGG16ActivationLayerDataset(VGG16ActivationLayerDataset &&) = default; + ~VGG16ActivationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_VGG16_ACTIVATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h b/tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h new file mode 100644 index 0000000000..36cb5d93aa --- /dev/null +++ b/tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h @@ -0,0 +1,94 @@ +/* + * 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_VGG16_CONVOLUTION_LAYER_DATASET +#define ARM_COMPUTE_TEST_VGG16_CONVOLUTION_LAYER_DATASET + +#include "tests/datasets/ConvolutionLayerDataset.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 VGG16ConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + VGG16ConvolutionLayerDataset() + { + // conv1_1 + add_config(TensorShape(224U, 224U, 3U), TensorShape(3U, 3U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U), PadStrideInfo(1, 1, 1, 1)); + // conv1_2 + add_config(TensorShape(224U, 224U, 64U), TensorShape(3U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U), PadStrideInfo(1, 1, 1, 1)); + // conv2_1 + add_config(TensorShape(112U, 112U, 64U), TensorShape(3U, 3U, 64U, 128U), TensorShape(128U), TensorShape(112U, 112U, 128U), PadStrideInfo(1, 1, 1, 1)); + // conv2_2 + add_config(TensorShape(112U, 112U, 128U), TensorShape(3U, 3U, 128U, 128U), TensorShape(128U), TensorShape(112U, 112U, 128U), PadStrideInfo(1, 1, 1, 1)); + // conv3_1 + add_config(TensorShape(56U, 56U, 128U), TensorShape(3U, 3U, 128U, 256U), TensorShape(256U), TensorShape(56U, 56U, 256U), PadStrideInfo(1, 1, 1, 1)); + // conv3_2, conv3_3 + add_config(TensorShape(56U, 56U, 256U), TensorShape(3U, 3U, 256U, 256U), TensorShape(256U), TensorShape(56U, 56U, 256U), PadStrideInfo(1, 1, 1, 1)); + // conv4_1 + add_config(TensorShape(28U, 28U, 256U), TensorShape(3U, 3U, 256U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 1)); + // conv4_2, conv4_3 + add_config(TensorShape(28U, 28U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 1)); + // conv5_1, conv5_2, conv5_3 + add_config(TensorShape(14U, 14U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(14U, 14U, 512U), PadStrideInfo(1, 1, 1, 1)); + } +}; + +class VGG16DirectConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + VGG16DirectConvolutionLayerDataset() + { + // conv1_1 + add_config(TensorShape(224U, 224U, 3U), TensorShape(3U, 3U, 3U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U), PadStrideInfo(1, 1, 1, 1)); + // conv1_2 + add_config(TensorShape(224U, 224U, 64U), TensorShape(3U, 3U, 64U, 64U), TensorShape(64U), TensorShape(224U, 224U, 64U), PadStrideInfo(1, 1, 1, 1)); + // conv2_1 + add_config(TensorShape(112U, 112U, 64U), TensorShape(3U, 3U, 64U, 128U), TensorShape(128U), TensorShape(112U, 112U, 128U), PadStrideInfo(1, 1, 1, 1)); + // conv2_2 + add_config(TensorShape(112U, 112U, 128U), TensorShape(3U, 3U, 128U, 128U), TensorShape(128U), TensorShape(112U, 112U, 128U), PadStrideInfo(1, 1, 1, 1)); + // conv3_1 + add_config(TensorShape(56U, 56U, 128U), TensorShape(3U, 3U, 128U, 256U), TensorShape(256U), TensorShape(56U, 56U, 256U), PadStrideInfo(1, 1, 1, 1)); + // conv3_2, conv3_3 + add_config(TensorShape(56U, 56U, 256U), TensorShape(3U, 3U, 256U, 256U), TensorShape(256U), TensorShape(56U, 56U, 256U), PadStrideInfo(1, 1, 1, 1)); + // conv4_1 + add_config(TensorShape(28U, 28U, 256U), TensorShape(3U, 3U, 256U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 1)); + // conv4_2, conv4_3 + add_config(TensorShape(28U, 28U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(28U, 28U, 512U), PadStrideInfo(1, 1, 1, 1)); + // conv5_1, conv5_2, conv5_3 + add_config(TensorShape(14U, 14U, 512U), TensorShape(3U, 3U, 512U, 512U), TensorShape(512U), TensorShape(14U, 14U, 512U), PadStrideInfo(1, 1, 1, 1)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_VGG16_CONVOLUTION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/vgg/vgg16/VGG16FullyConnectedLayerDataset.h b/tests/datasets/system_tests/vgg/vgg16/VGG16FullyConnectedLayerDataset.h new file mode 100644 index 0000000000..d34dc3f87e --- /dev/null +++ b/tests/datasets/system_tests/vgg/vgg16/VGG16FullyConnectedLayerDataset.h @@ -0,0 +1,56 @@ +/* + * 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_VGG16_FULLYCONNECTED_LAYER_DATASET +#define ARM_COMPUTE_TEST_VGG16_FULLYCONNECTED_LAYER_DATASET + +#include "tests/datasets/FullyConnectedLayerDataset.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 VGG16FullyConnectedLayerDataset final : public FullyConnectedLayerDataset +{ +public: + VGG16FullyConnectedLayerDataset() + { + // fc6 + add_config(TensorShape(7U, 7U, 512U), TensorShape(25088U, 4096U), TensorShape(4096U), TensorShape(4096U)); + // fc7 + add_config(TensorShape(4096U), TensorShape(4096U, 4096U), TensorShape(4096U), TensorShape(4096U)); + // fc8 + add_config(TensorShape(4096U), TensorShape(4096U, 1000U), TensorShape(1000U), TensorShape(1000U)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_VGG16_FULLYCONNECTED_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/vgg/vgg16/VGG16PoolingLayerDataset.h b/tests/datasets/system_tests/vgg/vgg16/VGG16PoolingLayerDataset.h new file mode 100644 index 0000000000..4db20870f2 --- /dev/null +++ b/tests/datasets/system_tests/vgg/vgg16/VGG16PoolingLayerDataset.h @@ -0,0 +1,60 @@ +/* + * 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_VGG16_POOLING_LAYER_DATASET +#define ARM_COMPUTE_TEST_VGG16_POOLING_LAYER_DATASET + +#include "tests/datasets/PoolingLayerDataset.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 VGG16PoolingLayerDataset final : public PoolingLayerDataset +{ +public: + VGG16PoolingLayerDataset() + { + // pool1 + add_config(TensorShape(224U, 224U, 64U), TensorShape(112U, 112U, 64U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool2 + add_config(TensorShape(112U, 112U, 128U), TensorShape(56U, 56U, 128U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool3 + add_config(TensorShape(56U, 56U, 256U), TensorShape(28U, 28U, 256U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool4 + add_config(TensorShape(28U, 28U, 512U), TensorShape(14U, 14U, 512U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool5 + add_config(TensorShape(14U, 14U, 512U), TensorShape(7U, 7U, 512U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_VGG16_POOLING_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/yolo/v2/YOLOV2ActivationLayerDataset.h b/tests/datasets/system_tests/yolo/v2/YOLOV2ActivationLayerDataset.h new file mode 100644 index 0000000000..8a2cd1665e --- /dev/null +++ b/tests/datasets/system_tests/yolo/v2/YOLOV2ActivationLayerDataset.h @@ -0,0 +1,109 @@ +/* + * 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_YOLOV2_ACTIVATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_YOLOV2_ACTIVATION_LAYER_DATASET + +#include "tests/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 YOLOV2ActivationLayerRELUDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +public: + YOLOV2ActivationLayerRELUDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { // relu1 + TensorShape(416U, 416U, 32U), + // relu2 + TensorShape(208U, 208U, 64U), + // relu3, relu5 + TensorShape(104U, 104U, 128U), + // relu4 + TensorShape(104U, 104U, 64U), + // relu6, relu8 + TensorShape(52U, 52U, 256U), + // relu7 + TensorShape(52U, 52U, 128U), + // relu9, relu11, relu13 + TensorShape(26U, 26U, 512U), + // relu10, relu12 + TensorShape(26U, 26U, 256U), + // relu14, relu16, relu18, relu19, relu20, relu21 + TensorShape(13U, 13U, 1024U), + // relu15, relu17 + TensorShape(13U, 13U, 512U) }), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + } + { + } + YOLOV2ActivationLayerRELUDataset(YOLOV2ActivationLayerRELUDataset &&) = default; + ~YOLOV2ActivationLayerRELUDataset() = default; +}; + +class YOLOV2ActivationLayerLINEARDataset final : public + framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>> +{ +public: + YOLOV2ActivationLayerLINEARDataset() + : CartesianProductDataset + { + framework::dataset::make("Shape", { // linear22 + TensorShape(15U, 15U, 425U) }), + framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR)) + } + { + } + YOLOV2ActivationLayerLINEARDataset(YOLOV2ActivationLayerLINEARDataset &&) = default; + ~YOLOV2ActivationLayerLINEARDataset() = default; +}; + +class YOLOV2ActivationLayerDataset final : public framework::dataset::JoinDataset<YOLOV2ActivationLayerRELUDataset, YOLOV2ActivationLayerLINEARDataset> +{ +public: + YOLOV2ActivationLayerDataset() + : JoinDataset + { + YOLOV2ActivationLayerRELUDataset(), + YOLOV2ActivationLayerLINEARDataset() + } + { + } + YOLOV2ActivationLayerDataset(YOLOV2ActivationLayerDataset &&) = default; + ~YOLOV2ActivationLayerDataset() = default; +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_YOLOV2_ACTIVATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h b/tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h new file mode 100644 index 0000000000..cc6a6dcccc --- /dev/null +++ b/tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h @@ -0,0 +1,70 @@ +/* + * 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_YOLOV2_BATCHNORMALIZATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_YOLOV2_BATCHNORMALIZATION_LAYER_DATASET + +#include "tests/datasets/BatchNormalizationLayerDataset.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 YOLOV2BatchNormalizationLayerDataset final : public BatchNormalizationLayerDataset +{ +public: + YOLOV2BatchNormalizationLayerDataset() + { + // conv1_bn + add_config(TensorShape(416U, 416U, 32U), TensorShape(32U), 0.00001f); + // conv2_bn + add_config(TensorShape(208U, 208U, 64U), TensorShape(64U), 0.00001f); + // conv3_bn, conv5_bn + add_config(TensorShape(104U, 104U, 128U), TensorShape(128U), 0.00001f); + // conv4_bn + add_config(TensorShape(104U, 104U, 64U), TensorShape(64U), 0.00001f); + // conv6_bn, conv8_bn + add_config(TensorShape(52U, 52U, 256U), TensorShape(256U), 0.00001f); + // conv7_bn + add_config(TensorShape(52U, 52U, 128U), TensorShape(128U), 0.00001f); + // conv9_bn, conv11_bn, conv13_bn + add_config(TensorShape(26U, 26U, 512U), TensorShape(512U), 0.00001f); + // conv10_bn, conv12_bn + add_config(TensorShape(26U, 26U, 256U), TensorShape(256U), 0.00001f); + // conv14_bn, conv16_bn, conv18_bn, conv19_bn, conv20_bn, conv21_bn + add_config(TensorShape(13U, 13U, 1024U), TensorShape(1024U), 0.00001f); + // conv15_bn, conv17_bn + add_config(TensorShape(13U, 13U, 512U), TensorShape(512U), 0.00001f); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_YOLOV2_BATCHNORMALIZATION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h b/tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h new file mode 100644 index 0000000000..41f48b0958 --- /dev/null +++ b/tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h @@ -0,0 +1,76 @@ +/* + * 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_YOLOV2_CONVOLUTION_LAYER_DATASET +#define ARM_COMPUTE_TEST_YOLOV2_CONVOLUTION_LAYER_DATASET + +#include "tests/datasets/ConvolutionLayerDataset.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 YOLOV2ConvolutionLayerDataset final : public ConvolutionLayerDataset +{ +public: + YOLOV2ConvolutionLayerDataset() + { + // conv1 + add_config(TensorShape(416U, 416U, 3U), TensorShape(3U, 3U, 3U, 32U), TensorShape(32U), TensorShape(416U, 416U, 32U), PadStrideInfo(1, 1, 1, 1)); + // conv2 + add_config(TensorShape(208U, 208U, 32U), TensorShape(3U, 3U, 32U, 64U), TensorShape(64U), TensorShape(208U, 208U, 64U), PadStrideInfo(1, 1, 1, 1)); + // conv3, conv5 + add_config(TensorShape(104U, 104U, 64U), TensorShape(3U, 3U, 64U, 128U), TensorShape(128U), TensorShape(104U, 104U, 128U), PadStrideInfo(1, 1, 1, 1)); + // conv4 + add_config(TensorShape(104U, 104U, 128U), TensorShape(1U, 1U, 128U, 64U), TensorShape(64U), TensorShape(104U, 104U, 64U), PadStrideInfo(1, 1, 0, 0)); + // conv6, conv8 + add_config(TensorShape(52U, 52U, 128U), TensorShape(3U, 3U, 128U, 256U), TensorShape(256U), TensorShape(52U, 52U, 256U), PadStrideInfo(1, 1, 1, 1)); + // conv7 + add_config(TensorShape(52U, 52U, 256U), TensorShape(1U, 1U, 256U, 128U), TensorShape(128U), TensorShape(52U, 52U, 128U), PadStrideInfo(1, 1, 0, 0)); + // conv9, conv11, conv13 + add_config(TensorShape(26U, 26U, 256U), TensorShape(3U, 3U, 256U, 512U), TensorShape(512U), TensorShape(26U, 26U, 512U), PadStrideInfo(1, 1, 1, 1)); + // conv10, conv12 + add_config(TensorShape(26U, 26U, 512U), TensorShape(1U, 1U, 512U, 256U), TensorShape(256U), TensorShape(26U, 26U, 256U), PadStrideInfo(1, 1, 0, 0)); + // conv14, conv16, conv18 + add_config(TensorShape(13U, 13U, 512U), TensorShape(3U, 3U, 512U, 1024U), TensorShape(1024U), TensorShape(13U, 13U, 1024U), PadStrideInfo(1, 1, 1, 1)); + // conv15, conv17 + add_config(TensorShape(13U, 13U, 1024U), TensorShape(1U, 1U, 1024U, 512U), TensorShape(512U), TensorShape(13U, 13U, 512U), PadStrideInfo(1, 1, 0, 0)); + // conv19, conv20 + add_config(TensorShape(13U, 13U, 1024U), TensorShape(3U, 3U, 1024U, 1024U), TensorShape(1024U), TensorShape(13U, 13U, 1024U), PadStrideInfo(1, 1, 1, 1)); + // conv21 + add_config(TensorShape(13U, 13U, 3072U), TensorShape(3U, 3U, 3072U, 1024U), TensorShape(1024U), TensorShape(13U, 13U, 1024U), PadStrideInfo(1, 1, 1, 1)); + // conv22 + add_config(TensorShape(13U, 13U, 1024U), TensorShape(1U, 1U, 1024U, 425U), TensorShape(425U), TensorShape(15U, 15U, 425U), PadStrideInfo(1, 1, 1, 1)); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_YOLOV2_CONVOLUTION_LAYER_DATASET */ diff --git a/tests/datasets/system_tests/yolo/v2/YOLOV2PoolingLayerDataset.h b/tests/datasets/system_tests/yolo/v2/YOLOV2PoolingLayerDataset.h new file mode 100644 index 0000000000..3763d63588 --- /dev/null +++ b/tests/datasets/system_tests/yolo/v2/YOLOV2PoolingLayerDataset.h @@ -0,0 +1,60 @@ +/* + * 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_YOLOV2_POOLING_LAYER_DATASET +#define ARM_COMPUTE_TEST_YOLOV2_POOLING_LAYER_DATASET + +#include "tests/datasets/PoolingLayerDataset.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 YOLOV2PoolingLayerDataset final : public PoolingLayerDataset +{ +public: + YOLOV2PoolingLayerDataset() + { + // pool1 + add_config(TensorShape(416U, 416U, 32U), TensorShape(208U, 208U, 32U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool2 + add_config(TensorShape(208U, 208U, 64U), TensorShape(104U, 104U, 64U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool5 + add_config(TensorShape(104U, 104U, 128U), TensorShape(52U, 52U, 128U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool8 + add_config(TensorShape(52U, 52U, 256U), TensorShape(26U, 26U, 256U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + // pool13 + add_config(TensorShape(26U, 26U, 512U), TensorShape(13U, 13U, 512U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_YOLOV2_POOLING_LAYER_DATASET */ |