/*
* Copyright (C) 2010-2018 Arm Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/* ----------------------------------------------------------------------
* Project: CMSIS NN Library
* Title: arm_nnsupportfunctions.h
* Description: Public header file of support functions for CMSIS NN Library
*
* $Date: 13. July 2018
* $Revision: V.1.0.0
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
#ifndef _ARM_NNSUPPORTFUNCTIONS_H_
#define _ARM_NNSUPPORTFUNCTIONS_H_
#include "arm_math.h"
#include "arm_common_tables.h"
//#include <cstring>
#ifdef __cplusplus
extern "C"
{
#endif
/**
* @brief Union for SIMD access of Q31/Q15/Q7 types
*/
union arm_nnword
{
q31_t word;
/**< Q31 type */
q15_t half_words[2];
/**< Q15 type */
q7_t bytes[4];
/**< Q7 type */
};
/**
* @brief Struct for specifying activation function types
*
*/
typedef enum
{
ARM_SIGMOID = 0,
/**< Sigmoid activation function */
ARM_TANH = 1,
/**< Tanh activation function */
} arm_nn_activation_type;
/**
* @defgroup nndata_convert Neural Network Data Conversion Functions
*
* Perform data type conversion in-between neural network operations
*
*/
/**
* @brief Converts the elements of the Q7 vector to Q15 vector without left-shift
* @param[in] *pSrc points to the Q7 input vector
* @param[out] *pDst points to the Q15 output vector
* @param[in] blockSize length of the input vector
* @return none.
*
*/
void arm_q7_to_q15_no_shift(const q7_t * pSrc, q15_t * pDst, uint32_t blockSize);
/**
* @brief Converts the elements of the Q7 vector to reordered Q15 vector without left-shift
* @param[in] *pSrc points to the Q7 input vector
* @param[out] *pDst points to the Q15 output vector
* @param[in] blockSize length of the input vector
* @return none.
*
*/
void arm_q7_to_q15_reordered_no_shift(const q7_t * pSrc, q15_t * pDst, uint32_t blockSize);
#if defined (ARM_MATH_DSP)
/**
* @brief read and expand one Q7 word into two Q15 words
*/
__STATIC_FORCEINLINE void *read_and_pad(void *source, q31_t * out1, q31_t * out2)
{
q31_t inA = *__SIMD32(source)++;
q31_t inAbuf1 = __SXTB16(__ROR(inA, 8));
q31_t inAbuf2 = __SXTB16(inA);
#ifndef ARM_MATH_BIG_ENDIAN
*out2 = __PKHTB(inAbuf1, inAbuf2, 16);
*out1 = __PKHBT(inAbuf2, inAbuf1, 16);
#else
*out1 = __PKHTB(inAbuf1, inAbuf2, 16);
*out2 = __PKHBT(inAbuf2, inAbuf1, 16);
#endif
return source;
}
/**
* @brief read and expand one Q7 word into two Q15 words with reordering
*/
__STATIC_FORCEINLINE void *read_and_pad_reordered(void *source, q31_t * out1, q31_t * out2)
{
q31_t inA = *__SIMD32(source)++;
#ifndef ARM_MATH_BIG_ENDIAN
*out2 = __SXTB16(__ROR(inA, 8));
*out1 = __SXTB16(inA);
#else
*out1 = __SXTB16(__ROR(inA, 8));
*out2 = __SXTB16(inA);
#endif
return source;
}
#endif
/**
* @defgroup NNBasicMath Basic Math Functions for Neural Network Computation
*
* Basic Math Functions for Neural Network Computation
*
*/
/**
* @brief Q7 vector multiplication with variable output shifts
* @param[in] *pSrcA pointer to the first input vector
* @param[in] *pSrcB pointer to the second input vector
* @param[out] *pDst pointer to the output vector
* @param[in] out_shift amount of right-shift for output
* @param[in] blockSize number of samples in each vector
* @return none.
*
* <b>Scaling and Overflow Behavior:</b>
* \par
* The function uses saturating arithmetic.
* Results outside of the allowable Q15 range [0x8000 0x7FFF] will be saturated.
*/
void arm_nn_mult_q15(
q15_t * pSrcA,
q15_t * pSrcB,
q15_t * pDst,
const uint16_t out_shift,
uint32_t blockSize);
/**
* @brief Q7 vector multiplication with variable output shifts
* @param[in] *pSrcA pointer to the first input vector
* @param[in] *pSrcB pointer to the second input vector
* @param[out] *pDst pointer to the output vector
* @param[in] out_shift amount of right-shift for output
* @param[in] blockSize number of samples in each vector
* @return none.
*
* <b>Scaling and Overflow Behavior:</b>
* \par
* The function uses saturating arithmetic.
* Results outside of the allowable Q7 range [0x80 0x7F] will be saturated.
*/
void arm_nn_mult_q7(
q7_t * pSrcA,
q7_t * pSrcB,
q7_t * pDst,
const uint16_t out_shift,
uint32_t blockSize);
/**
* @brief defition to adding rouding offset
*/
#ifndef ARM_NN_TRUNCATE
#define NN_ROUND(out_shift) ( 0x1 << (out_shift - 1) )
#else
#define NN_ROUND(out_shift) 0
#endif
#ifdef __cplusplus
}
#endif
#endif