/* * Copyright (c) 2018-2019 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_NECONVERTFULLYCONNECTEDWEIGHTS_H #define ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTS_H #include "arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/ITransformWeights.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "arm_compute/runtime/Tensor.h" namespace arm_compute { // Forward declarations class ITensor; /** Basic function to run @ref NEConvertFullyConnectedWeightsKernel. */ class NEConvertFullyConnectedWeights : public IFunction { public: /** Default constructor */ NEConvertFullyConnectedWeights(); /** Initialize the function. * * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: All. * @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input. * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). * @param[in] data_layout The data layout the weights have been trained in. */ void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout); /** Static function to check if given info will lead to a valid configuration of @ref NEConvertFullyConnectedWeights * * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All. * @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input. * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). * @param[in] data_layout The data layout the weights have been trained in. * * @return A Status */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout); // Inherited methods overriden: void run() override; private: NEConvertFullyConnectedWeightsKernel _kernel; }; namespace weights_transformations { /** Basic function to run @ref NEConvertFullyConnectedWeightsKernel. */ class NEConvertFullyConnectedWeightsManaged : public ITransformWeights { public: void run() override { _output.allocator()->allocate(); _func.run(); _reshape_run = true; } void release() override { _output.allocator()->free(); } ITensor *get_weights() override { return &_output; } uint32_t uid() override { return _uid; } void configure(const ITensor *input, const TensorShape &original_input_shape, DataLayout data_layout) { _func.configure(input, &_output, original_input_shape, data_layout); } private: static constexpr uint32_t _uid = 0x4; Tensor _output{}; NEConvertFullyConnectedWeights _func{}; }; } // namespace weights_transformations } // namespace arm_compute #endif /* ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTS_H */