| /* |
| * 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<IMemoryManager> 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<INEKernel> _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__ */ |