/* * 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_CLDEQUANTIZATIONLAYER_H__ #define __ARM_COMPUTE_CLDEQUANTIZATIONLAYER_H__ #include "arm_compute/runtime/IFunction.h" #include "arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/core/Types.h" namespace arm_compute { class ICLTensor; /** Basic function to simulate a dequantization layer. This function calls the following CL kernels: * * -# @ref CLDequantizationLayerKernel * */ class CLDequantizationLayer : public IFunction { public: /** Default constructor */ CLDequantizationLayer(); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDequantizationLayer(const CLDequantizationLayer &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDequantizationLayer &operator=(const CLDequantizationLayer &) = delete; /** Set the input and output tensors. * * @param[in] input Source tensor with at least 3 dimensions. The dimensions over the third will be interpreted as batches. Data types supported: U8. * @param[out] output Destination tensor with the same dimensions of input. Data type supported: F32. * @param[in] min_max Pointer to the tensor with shape [2, batches] which stores the minimum and maximum value for each 3D input tensor. * The dimensions over the second must match the batched dimensions of the input tensor. Data type supported: F32. */ void configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *min_max); /** Static function to check if given info will lead to a valid configuration of @ref CLDequantizationLayer * * @param[in] input Input tensor info. Data types supported: U8. * @param[in] output Output tensor info. Data type supported: F32. * @param[in] min_max Info for the tensor with shape [2, batches] which stores the minimum and maximum value for each 3D input tensor. * The dimensions over the second must match the batched dimensions of the input tensor. Data type supported: F32. * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *min_max); // Inherited methods overridden: void run() override; private: CLDequantizationLayerKernel _dequantize_kernel; }; } #endif /* __ARM_COMPUTE_CLDEQUANTIZATIONLAYER_H__ */