From aa38e5c1f48e31213ee349aa5cd6f06c85bda70d Mon Sep 17 00:00:00 2001
From: android <android@lingyun.com>
Date: Tue, 25 Jun 2024 21:49:39 +0800
Subject: [PATCH] Add GD32F103RCT6 ADC converter board SDK source code
---
mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ConvolutionFunctions/arm_nn_mat_mult_kernel_q7_q15.c | 187 ++++++++++++++++++++++++++++++++++++++++++++++
1 files changed, 187 insertions(+), 0 deletions(-)
diff --git a/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ConvolutionFunctions/arm_nn_mat_mult_kernel_q7_q15.c b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ConvolutionFunctions/arm_nn_mat_mult_kernel_q7_q15.c
new file mode 100644
index 0000000..24ab412
--- /dev/null
+++ b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ConvolutionFunctions/arm_nn_mat_mult_kernel_q7_q15.c
@@ -0,0 +1,187 @@
+/*
+ * 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_nn_mat_mult_kernel_q7_q15.c
+ * Description: Matrix-multiplication function for convolution
+ *
+ * $Date: 17. January 2018
+ * $Revision: V.1.0.0
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+
+#include "arm_math.h"
+#include "arm_nnfunctions.h"
+
+ /**
+ * @brief Matrix-multiplication function for convolution
+ * @param[in] pA pointer to operand A
+ * @param[in] pInBuffer pointer to operand B, always conssists of 2 vectors
+ * @param[in] ch_im_out numRow of A
+ * @param[in] numCol_A numCol of A
+ * @param[in] bias_shift amount of left-shift for bias
+ * @param[in] out_shift amount of right-shift for output
+ * @param[in] bias the bias
+ * @param[in,out] pOut pointer to output
+ * @return The function returns the incremented output pointer
+ *
+ * @details
+ *
+ * This function does the matrix multiplication with weight matrix
+ * and 2 columns from im2col.
+ */
+
+q7_t *arm_nn_mat_mult_kernel_q7_q15(const q7_t * pA,
+ const q15_t * pInBuffer,
+ const uint16_t ch_im_out,
+ const uint16_t numCol_A,
+ const uint16_t bias_shift,
+ const uint16_t out_shift,
+ const q7_t * bias,
+ q7_t * pOut)
+{
+#if defined (ARM_MATH_DSP)
+ /* set up the second output pointers */
+ q7_t *pOut2 = pOut + ch_im_out;
+ const q7_t *pBias = bias;
+
+ uint16_t rowCnt = ch_im_out >> 1;
+ /* this loop over rows in A */
+ while (rowCnt)
+ {
+ /* setup pointers for B */
+ const q15_t *pB = pInBuffer;
+ const q15_t *pB2 = pB + numCol_A;
+
+ /* align the second pointer for A */
+ const q7_t *pA2 = pA + numCol_A;
+
+ /* init the sum with bias */
+ 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 = numCol_A >> 2;
+ /* accumulate over the vector */
+ while (colCnt)
+ {
+ q31_t inA11, inA12, inA21, inA22;
+ q31_t inB1 = *__SIMD32(pB)++;
+ q31_t inB2 = *__SIMD32(pB2)++;
+
+ pA = (q7_t *) read_and_pad((void *)pA, &inA11, &inA12);
+ pA2 = (q7_t *) read_and_pad((void *)pA2, &inA21, &inA22);
+
+ sum = __SMLAD(inA11, inB1, sum);
+ sum2 = __SMLAD(inA11, inB2, sum2);
+ sum3 = __SMLAD(inA21, inB1, sum3);
+ sum4 = __SMLAD(inA21, inB2, sum4);
+
+ inB1 = *__SIMD32(pB)++;
+ inB2 = *__SIMD32(pB2)++;
+
+ sum = __SMLAD(inA12, inB1, sum);
+ sum2 = __SMLAD(inA12, inB2, sum2);
+ sum3 = __SMLAD(inA22, inB1, sum3);
+ sum4 = __SMLAD(inA22, inB2, sum4);
+
+ colCnt--;
+ } /* while over colCnt */
+ colCnt = numCol_A & 0x3;
+ while (colCnt)
+ {
+ q7_t inA1 = *pA++;
+ q15_t inB1 = *pB++;
+ q7_t inA2 = *pA2++;
+ q15_t inB2 = *pB2++;
+
+ sum += inA1 * inB1;
+ sum2 += inA1 * inB2;
+ sum3 += inA2 * inB1;
+ sum4 += inA2 * inB2;
+ colCnt--;
+ } /* while over colCnt */
+ *pOut++ = (q7_t) __SSAT((sum >> out_shift), 8);
+ *pOut++ = (q7_t) __SSAT((sum3 >> out_shift), 8);
+ *pOut2++ = (q7_t) __SSAT((sum2 >> out_shift), 8);
+ *pOut2++ = (q7_t) __SSAT((sum4 >> out_shift), 8);
+
+ /* skip the row computed with A2 */
+ pA += numCol_A;
+ rowCnt--;
+ } /* for over ch_im_out */
+
+ /* compute left-over row if any */
+ if (ch_im_out & 0x1)
+ {
+ /* setup pointers for B */
+ const q15_t *pB = pInBuffer;
+ const q15_t *pB2 = pB + numCol_A;
+
+ /* load the bias */
+ q31_t sum = ((q31_t)(*pBias) << bias_shift) + NN_ROUND(out_shift);
+ q31_t sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+ uint16_t colCnt = numCol_A >> 2;
+ while (colCnt)
+ {
+ q31_t inA11, inA12;
+ q31_t inB1 = *__SIMD32(pB)++;
+ q31_t inB2 = *__SIMD32(pB2)++;
+
+ pA = (q7_t *) read_and_pad((void *)pA, &inA11, &inA12);
+
+ sum = __SMLAD(inA11, inB1, sum);
+ sum2 = __SMLAD(inA11, inB2, sum2);
+
+ inB1 = *__SIMD32(pB)++;
+ inB2 = *__SIMD32(pB2)++;
+ sum = __SMLAD(inA12, inB1, sum);
+ sum2 = __SMLAD(inA12, inB2, sum2);
+
+ colCnt--;
+ }
+ colCnt = numCol_A & 0x3;
+ while (colCnt)
+ {
+ q7_t inA1 = *pA++;
+ q15_t inB1 = *pB++;
+ q15_t inB2 = *pB2++;
+
+ sum += inA1 * inB1;
+ sum2 += inA1 * inB2;
+ colCnt--;
+ }
+
+ *pOut++ = (q7_t) __SSAT((sum >> out_shift), 8);
+ *pOut2++ = (q7_t) __SSAT((sum2 >> out_shift), 8);
+ }
+
+ pOut += ch_im_out;
+
+ /* return the new output pointer with offset */
+ return pOut;
+#else
+ /* To be completed */
+ return NULL;
+#endif /* ARM_MATH_DSP */
+
+}
--
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