/* * Copyright (c) 2017-2019 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_NESOFTMAXLAYER_H__ #define __ARM_COMPUTE_NESOFTMAXLAYER_H__ #include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h" #include "arm_compute/core/NEON/kernels/NEFlattenLayerKernel.h" #include "arm_compute/core/NEON/kernels/NEReshapeLayerKernel.h" #include "arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/MemoryGroup.h" #include "arm_compute/runtime/Tensor.h" namespace arm_compute { class ITensor; /** Basic function to compute a SoftmaxLayer. * * Softmax is calculated by : * @f[ out = \frac{e^{x - max(x)}}{\sum{e^{x - max(x)}}} @f] * * This function runs the following kernels: * -# @ref NEFillBorderKernel * -# @ref NELogits1DMaxKernel * -# @ref NELogits1DSoftmaxKernel */ class NESoftmaxLayer : public IFunction { public: /** Constructor */ NESoftmaxLayer(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ NESoftmaxLayer(const NESoftmaxLayer &) = delete; /** Default move constructor */ NESoftmaxLayer(NESoftmaxLayer &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ NESoftmaxLayer &operator=(const NESoftmaxLayer &) = delete; /** Default move assignment operator */ NESoftmaxLayer &operator=(NESoftmaxLayer &&) = default; /** Set the input and output tensors. * * @param[in,out] input Source tensor. Data types supported: QASYMM8/F16/F32. If the width is not a * multiple of the internal processing block size, @ref NEFillBorderKernel replicates the * last value of each row to the nearest multiple. * @param[out] output Destination tensor. Data types supported: same as @p input. * @param[in] beta (Optional) A scaling factor for the exponent. * @param[in] axis (Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image, * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image. */ void configure(ITensor *input, ITensor *output, float beta = 1.0f, size_t axis = 1); /** Static function to check if given info will lead to a valid configuration of @ref NESoftmaxLayer * * @param[in] input Source tensor info. Data types supported: QASYMM8/F16/F32. * @param[in] output Destination tensor info. Data types supported: same as @p input * @param[in] beta (Optional) A scaling factor for the exponent. * @param[in] axis (Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image, * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image. * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, size_t axis = 1); // Inherited methods overridden: void run() override; private: /** Utility method to configure the kernels needed to flatten the input * tensor. * * @note This function changes the internal state of this class. In particular, * it initializes the kernel @p _flatten_kernel and the tensors @p _input_flat and * @p _output_flat * * @param[in] input Original source tensor. * @param[in] output Original destination tensor. * @param[in] axis (Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image, * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image. */ void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, size_t axis); MemoryGroup _memory_group; NELogits1DMaxKernel _max_kernel; NELogits1DSoftmaxKernel _softmax_kernel; std::unique_ptr _flat_or_reshape_kernel_ptr; NEFillBorderKernel _fill_border_kernel; NEReshapeLayerKernel _reshape_kernel; Tensor _max; Tensor _tmp; Tensor _input_flattened; Tensor _output_flattened; bool _needs_flattening; }; } // namespace arm_compute #endif /* __ARM_COMPUTE_NESOFTMAXLAYER_H__ */