/* * Copyright (c) 2017-2018 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_FULLYCONNECTED_LAYER_DATASET #define ARM_COMPUTE_TEST_FULLYCONNECTED_LAYER_DATASET #include "utils/TypePrinter.h" #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" namespace arm_compute { namespace test { namespace datasets { class FullyConnectedLayerDataset { public: using type = std::tuple; struct iterator { iterator(std::vector::const_iterator src_it, std::vector::const_iterator weights_it, std::vector::const_iterator biases_it, std::vector::const_iterator dst_it) : _src_it{ std::move(src_it) }, _weights_it{ std::move(weights_it) }, _biases_it{ std::move(biases_it) }, _dst_it{ std::move(dst_it) } { } std::string description() const { std::stringstream description; description << "In=" << *_src_it << ":"; description << "Weights=" << *_weights_it << ":"; description << "Biases=" << *_biases_it << ":"; description << "Out=" << *_dst_it; return description.str(); } FullyConnectedLayerDataset::type operator*() const { return std::make_tuple(*_src_it, *_weights_it, *_biases_it, *_dst_it); } iterator &operator++() { ++_src_it; ++_weights_it; ++_biases_it; ++_dst_it; return *this; } private: std::vector::const_iterator _src_it; std::vector::const_iterator _weights_it; std::vector::const_iterator _biases_it; std::vector::const_iterator _dst_it; }; iterator begin() const { return iterator(_src_shapes.begin(), _weight_shapes.begin(), _bias_shapes.begin(), _dst_shapes.begin()); } int size() const { return std::min(_src_shapes.size(), std::min(_weight_shapes.size(), std::min(_bias_shapes.size(), _dst_shapes.size()))); } void add_config(TensorShape src, TensorShape weights, TensorShape biases, TensorShape dst) { _src_shapes.emplace_back(std::move(src)); _weight_shapes.emplace_back(std::move(weights)); _bias_shapes.emplace_back(std::move(biases)); _dst_shapes.emplace_back(std::move(dst)); } protected: FullyConnectedLayerDataset() = default; FullyConnectedLayerDataset(FullyConnectedLayerDataset &&) = default; private: std::vector _src_shapes{}; std::vector _weight_shapes{}; std::vector _bias_shapes{}; std::vector _dst_shapes{}; }; class TinyFullyConnectedLayerDataset final : public FullyConnectedLayerDataset { public: TinyFullyConnectedLayerDataset() { // Conv -> FC add_config(TensorShape(8U, 1U, 1U), TensorShape(8U, 16U), TensorShape(16U), TensorShape(16U)); // Conv -> FC add_config(TensorShape(1U, 1U, 1U, 3U), TensorShape(1U, 10U), TensorShape(10U), TensorShape(10U, 3U)); // FC -> FC add_config(TensorShape(1U), TensorShape(1U, 10U), TensorShape(10U), TensorShape(10U)); // FC -> FC (batched) add_config(TensorShape(1U, 3U), TensorShape(1U, 10U), TensorShape(10U), TensorShape(10U, 3U)); } }; class SmallFullyConnectedLayerDataset final : public FullyConnectedLayerDataset { public: SmallFullyConnectedLayerDataset() { // Conv -> FC add_config(TensorShape(8U, 1U, 1U), TensorShape(8U, 16U), TensorShape(16U), TensorShape(16U)); // Conv -> FC add_config(TensorShape(1U, 1U, 1U, 3U), TensorShape(1U, 10U), TensorShape(10U), TensorShape(10U, 3U)); // Conv -> FC add_config(TensorShape(9U, 5U, 7U), TensorShape(315U, 271U), TensorShape(271U), TensorShape(271U)); // Conv -> FC (batched) add_config(TensorShape(9U, 5U, 7U, 3U), TensorShape(315U, 271U), TensorShape(271U), TensorShape(271U, 3U)); // FC -> FC add_config(TensorShape(1U), TensorShape(1U, 10U), TensorShape(10U), TensorShape(10U)); // FC -> FC (batched) add_config(TensorShape(1U, 3U), TensorShape(1U, 10U), TensorShape(10U), TensorShape(10U, 3U)); // FC -> FC add_config(TensorShape(201U), TensorShape(201U, 529U), TensorShape(529U), TensorShape(529U)); // FC -> FC (batched) add_config(TensorShape(201U, 3U), TensorShape(201U, 529U), TensorShape(529U), TensorShape(529U, 3U)); add_config(TensorShape(9U, 5U, 7U, 3U, 2U), TensorShape(315U, 271U), TensorShape(271U), TensorShape(271U, 3U, 2U)); } }; class LargeFullyConnectedLayerDataset final : public FullyConnectedLayerDataset { public: LargeFullyConnectedLayerDataset() { add_config(TensorShape(9U, 5U, 257U), TensorShape(11565U, 2123U), TensorShape(2123U), TensorShape(2123U)); add_config(TensorShape(9U, 5U, 257U, 2U), TensorShape(11565U, 2123U), TensorShape(2123U), TensorShape(2123U, 2U)); add_config(TensorShape(3127U), TensorShape(3127U, 989U), TensorShape(989U), TensorShape(989U)); add_config(TensorShape(3127U, 2U), TensorShape(3127U, 989U), TensorShape(989U), TensorShape(989U, 2U)); add_config(TensorShape(9U, 5U, 257U, 2U, 3U), TensorShape(11565U, 2123U), TensorShape(2123U), TensorShape(2123U, 2U, 3U)); } }; } // namespace datasets } // namespace test } // namespace arm_compute #endif /* ARM_COMPUTE_TEST_FULLYCONNECTED_LAYER_DATASET */