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/*
* Copyright (c) 2021-2022 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_CPU_SOFTMAX_H
#define ARM_COMPUTE_CPU_SOFTMAX_H
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/experimental/Types.h"
#include "src/cpu/ICpuKernel.h"
#include "src/cpu/ICpuOperator.h"
#include "src/cpu/operators/CpuPermute.h"
#include <memory>
namespace arm_compute
{
namespace cpu
{
class CpuLogits1DMaxKernel;
template <bool IS_LOG>
class CpuLogits1DSoftmaxKernel;
/** Basic function to compute a SoftmaxLayer and a Log SoftmaxLayer.
*
* Softmax is calculated by :
* @f[ out = exp((x - max(x)) * beta) / sum(exp((x - max(x)) * beta)) @f]
*
* Log Softmax is calculated by :
* @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f]
*
* This function runs the following function/kernels:
* -# If axis is not 0:
* -# @ref CpuPermute
* -# @ref kernels::CpuLogits1DMaxKernel
* -# @ref kernels::CpuLogits1DSoftmaxKernel
*/
template <bool IS_LOG = false>
class CpuSoftmaxGeneric : public ICpuOperator
{
public:
CpuSoftmaxGeneric();
/** Set the input and output tensors.
*
* @param[in,out] src Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* last value of each row to the nearest multiple.
* @param[out] dst Destination tensor ifo. Data types supported: same as @p input.
* @param[in] beta (Optional) A scaling factor for the exponent.
* @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
* axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
*/
void configure(const ITensorInfo *src, ITensorInfo *dst, float beta = 1.0f, int32_t axis = 0);
/** Static function to check if given info will lead to a valid configuration
*
* Similar to @ref CpuSoftmaxGeneric::configure()
*
* @return a status
*/
static Status validate(const ITensorInfo *src, const ITensorInfo *dst, float beta = 1.0f, int32_t axis = 0);
// Inherited methods overridden:
void run(ITensorPack &tensors) override;
experimental::MemoryRequirements workspace() const override;
private:
enum InternalTensorIdx
{
MAX = 0,
TMP,
PERMUTED_SRC,
PERMUTED_DST,
COUNT
};
CpuPermute _permute_input;
CpuPermute _permute_output;
std::unique_ptr<ICPPKernel> _max_kernel;
std::unique_ptr<ICPPKernel> _softmax_kernel;
TensorInfo _max;
TensorInfo _tmp;
TensorInfo _input_permuted;
TensorInfo _output_permuted;
bool _needs_permute;
experimental::MemoryRequirements _aux_mem{};
};
using CpuSoftmax = CpuSoftmaxGeneric<false>;
using CpuLogSoftmax = CpuSoftmaxGeneric<true>;
} // namespace cpu
} // namespace arm_compute
#endif /* ARM_COMPUTE_CPU_SOFTMAX_H */