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diff --git a/fw/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c b/fw/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c
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-/*
- * 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_fully_connected_q15_opt.c
- * Description: Q15 opt fully-connected layer function
- *
- * $Date: 17. January 2018
- * $Revision: V.1.0.0
- *
- * Target Processor: Cortex-M cores
- *
- * -------------------------------------------------------------------- */
-
-#include "arm_math.h"
-#include "arm_nnfunctions.h"
-
-/**
- * @ingroup groupNN
- */
-
-/**
- * @addtogroup FC
- * @{
- */
-
- /**
- * @brief Q15 opt fully-connected layer function
- * @param[in] pV pointer to input vector
- * @param[in] pM pointer to matrix weights
- * @param[in] dim_vec length of the vector
- * @param[in] num_of_rows number of rows in weight matrix
- * @param[in] bias_shift amount of left-shift for bias
- * @param[in] out_shift amount of right-shift for output
- * @param[in] bias pointer to bias
- * @param[in,out] pOut pointer to output vector
- * @param[in,out] vec_buffer pointer to buffer space for input
- * @return The function returns <code>ARM_MATH_SUCCESS</code>
- *
- *
- * @details
- *
- * <b>Buffer size:</b>
- *
- * vec_buffer size: 0
- *
- * Here we use only one pointer to read 4 rows in the weight
- * matrix. So if the original matrix looks like this:
- *
- * | a11 | a12 | a13 |
- *
- * | a21 | a22 | a23 |
- *
- * | a31 | a32 | a33 |
- *
- * | a41 | a42 | a43 |
- *
- * | a51 | a52 | a53 |
- *
- * | a61 | a62 | a63 |
- *
- * We operates on multiple-of-4 rows, so the first four rows becomes
- *
- * | a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
- *
- * | a13 | a23 | a33 | a43 |
- *
- * Remaining rows are kept the same original order.
- *
- * So the stored weight matrix looks like this:
- *
- *
- * | a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
- *
- * | a13 | a23 | a33 | a43 | a51 | a52 | a53 | a61 |
- *
- * | a62 | a63 |
- */
-
-arm_status
-arm_fully_connected_q15_opt(const q15_t * pV,
- const q15_t * pM,
- const uint16_t dim_vec,
- const uint16_t num_of_rows,
- const uint16_t bias_shift,
- const uint16_t out_shift,
- const q15_t * bias,
- q15_t * pOut,
- q15_t * vec_buffer)
-{
-
-#if defined (ARM_MATH_DSP)
- /* Run the following code for Cortex-M4 and Cortex-M7 */
-
- const q15_t *pB = pM;
- q15_t *pO = pOut;
- const q15_t *pBias = bias;
- const q15_t *pA = pV;
-
- uint16_t rowCnt = num_of_rows >> 2;
-
- while (rowCnt)
- {
- q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
- q31_t sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
- q31_t sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
- q31_t sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
-
- uint16_t colCnt = dim_vec >> 1;
-
- pA = pV;
-
-#ifdef USE_INTRINSIC
-
- while (colCnt)
- {
- q31_t inM11, inM12, inM13, inM14;
- q31_t inV;
-
- inV = *__SIMD32(pA)++;
- inM11 = *__SIMD32(pB)++;
- sum = __SMLAD(inV, inM11, sum);
- inM12 = *__SIMD32(pB)++;
- sum2 = __SMLAD(inV, inM12, sum2);
- inM13 = *__SIMD32(pB)++;
- sum3 = __SMLAD(inV, inM13, sum3);
- inM14 = *__SIMD32(pB)++;
- sum4 = __SMLAD(inV, inM14, sum4);
- colCnt--;
- }
-
-#else
-
- /*
- * register needed:
- * loop counter: colCnt
- * accumulators: sum, sum2, sum3, sum4
- * pointers: pB, pA
- * weight data: inM11, inM12, inM13, inM14
- * activation data: inV
- */
-
- asm volatile ("COL_LOOP_%=:\n"
- "ldr.w r4, [%[pA]], #4\n"
- "ldr.w r0, [%[pB]], #16\n"
- "smlad %[sum], r4, r0, %[sum]\n"
- "ldr.w r1, [%[pB] , #-12]\n"
- "smlad %[sum2], r4, r1, %[sum2]\n"
- "ldr.w r2, [%[pB] , #-8]\n"
- "smlad %[sum3], r4, r2, %[sum3]\n"
- "ldr.w r3, [%[pB] , #-4]\n"
- "smlad %[sum4], r4, r3, %[sum4]\n"
- "subs %[colCnt], #1\n"
- "bne COL_LOOP_%=\n":[sum] "+r"(sum),
- [sum2] "+r"(sum2),[sum3] "+r"(sum3),
- [sum4] "+r"(sum4),[pB] "+r"(pB),[pA] "+r"(pA):[colCnt] "r"(colCnt):"r0", "r1", "r2", "r3", "r4");
-
-#endif /* USE_INTRINSIC */
-
- colCnt = dim_vec & 0x1;
- while (colCnt)
- {
-
- q15_t inV = *pA++;
- q15_t inM = *pB++;
- q15_t inM2 = *pB++;
- q15_t inM3 = *pB++;
- q15_t inM4 = *pB++;
-
- sum += inV * inM;
- sum2 += inV * inM2;
- sum3 += inV * inM3;
- sum4 += inV * inM4;
- colCnt--;
- } /* while over colCnt */
- *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
- *pO++ = (q15_t) (__SSAT((sum2 >> out_shift), 16));
- *pO++ = (q15_t) (__SSAT((sum3 >> out_shift), 16));
- *pO++ = (q15_t) (__SSAT((sum4 >> out_shift), 16));
-
- /* adjust the pointers and counters */
- rowCnt--;
- }
-
- /* left-over part of the rows */
- rowCnt = num_of_rows & 0x3;
-
- while (rowCnt)
- {
- q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
-
- uint16_t colCnt = dim_vec >> 2;
-
- pA = pV;
-
- while (colCnt)
- {
- q31_t inV1, inV2, inM1, inM2;
-
- inM1 = *__SIMD32(pB)++;
- inV1 = *__SIMD32(pA)++;
- sum = __SMLAD(inV1, inM1, sum);
-
- inM2 = *__SIMD32(pB)++;
- inV2 = *__SIMD32(pA)++;
- sum = __SMLAD(inV2, inM2, sum);
-
- colCnt--;
- }
-
- /* left-over of the vector */
- colCnt = dim_vec & 0x3;
- while (colCnt)
- {
- q15_t inV = *pA++;
- q15_t inM = *pB++;
- sum += inV * inM;
- colCnt--;
- }
-
- *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
-
- rowCnt--;
- }
-
-#else
- /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
- uint16_t rowCnt = num_of_rows >> 2;
- const q15_t *pB = pM;
- const q15_t *pA;
- q15_t *pO = pOut;
- const q15_t *pBias = bias;
-
- while (rowCnt)
- {
- q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
- q31_t sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
- q31_t sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
- q31_t sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
-
- uint16_t colCnt = dim_vec >> 1;
-
- pA = pV;
- while (colCnt)
- {
- q15_t inA1 = *pA++;
- q15_t inA2 = *pA++;
-
- q15_t inB1 = *pB++;
- q15_t inB2 = *pB++;
- sum += inA1 * inB1 + inA2 * inB2;
-
- inB1 = *pB++;
- inB2 = *pB++;
- sum2 += inA1 * inB1 + inA2 * inB2;
-
- inB1 = *pB++;
- inB2 = *pB++;
- sum3 += inA1 * inB1 + inA2 * inB2;
-
- inB1 = *pB++;
- inB2 = *pB++;
- sum4 += inA1 * inB1 + inA2 * inB2;
-
- colCnt--;
- }
- colCnt = dim_vec & 0x1;
- while (colCnt)
- {
- q15_t inA = *pA++;
- q15_t inB = *pB++;
- sum += inA * inB;
- inB = *pB++;
- sum2 += inA * inB;
- inB = *pB++;
- sum3 += inA * inB;
- inB = *pB++;
- sum4 += inA * inB;
- colCnt--;
- }
- *pO++ = (q15_t) __SSAT((sum >> out_shift), 16);
- *pO++ = (q15_t) __SSAT((sum2 >> out_shift), 16);
- *pO++ = (q15_t) __SSAT((sum3 >> out_shift), 16);
- *pO++ = (q15_t) __SSAT((sum4 >> out_shift), 16);
-
- rowCnt--;
- }
- rowCnt = num_of_rows & 0x3;
-
- while (rowCnt)
- {
- int ip_out = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
- int j;
-
- pA = pV;
- for (j = 0; j < dim_vec; j++)
- {
- q15_t inA = *pA++;
- q15_t inB = *pB++;
- ip_out += inA * inB;
- }
- *pO++ = (q15_t) __SSAT((ip_out >> out_shift), 16);
-
- rowCnt--;
- }
-
-#endif /* ARM_MATH_DSP */
-
- /* Return to ARM_MATH_SUCCESS */
- return (ARM_MATH_SUCCESS);
-
-}
-
-/**
- * @} end of FC group
- */