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/FullyConnectedFunctions/arm_fully_connected_q15.c | 193 ++++++++++++++++++++++++++++++++++++++++++++++++
1 files changed, 193 insertions(+), 0 deletions(-)
diff --git a/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c
new file mode 100644
index 0000000..a4c6bba
--- /dev/null
+++ b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c
@@ -0,0 +1,193 @@
+/*
+ * 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.c
+ * Description: Q15 basic 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
+ *
+ */
+
+arm_status
+arm_fully_connected_q15(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;
+ const q15_t *pB2 = pB + dim_vec;
+ q15_t *pO = pOut;
+ const q15_t *pA;
+ const q15_t *pBias = bias;
+ uint16_t rowCnt = num_of_rows >> 1;
+
+ /* this loop loops over different output */
+ 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);
+
+ uint16_t colCnt = dim_vec >> 2;
+
+ pA = pV;
+ pB2 = pB + dim_vec;
+
+ while (colCnt)
+ {
+ q31_t inV1, inM1, inM2;
+ inV1 = *__SIMD32(pA)++;
+ inM1 = *__SIMD32(pB)++;
+ sum = __SMLAD(inV1, inM1, sum);
+ inM2 = *__SIMD32(pB2)++;
+ sum2 = __SMLAD(inV1, inM2, sum2);
+
+ inV1 = *__SIMD32(pA)++;
+ inM1 = *__SIMD32(pB)++;
+ sum = __SMLAD(inV1, inM1, sum);
+ inM2 = *__SIMD32(pB2)++;
+ sum2 = __SMLAD(inV1, inM2, sum2);
+
+ colCnt--;
+ }
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q15_t inV = *pA++;
+ q15_t inM = *pB++;
+ q15_t inM2 = *pB2++;
+
+ sum += inV * inM;
+ sum2 += inV * inM2;
+ colCnt--;
+ } /* while over colCnt */
+ *pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
+ *pO++ = (q15_t) (__SSAT((sum2>> out_shift), 16));
+
+ /* adjust the pointers and counters */
+ pB = pB + dim_vec;
+ rowCnt --;
+ }
+
+ rowCnt = num_of_rows & 0x1;
+
+ 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, inM1;
+ inV1 = *__SIMD32(pA)++;
+ inM1 = *__SIMD32(pB)++;
+ sum = __SMLAD(inV1, inM1, sum);
+
+ inV1 = *__SIMD32(pA)++;
+ inM1 = *__SIMD32(pB)++;
+ sum = __SMLAD(inV1, inM1, 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
+ int i, j;
+ /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+ for (i = 0; i < num_of_rows; i++)
+ {
+ int ip_out = ((q31_t)(bias[i]) << bias_shift) + NN_ROUND(out_shift);
+ for (j = 0; j < dim_vec; j++)
+ {
+ ip_out += pV[j] * pM[i * dim_vec + j];
+ }
+ pOut[i] = (q15_t) __SSAT((ip_out >> out_shift), 16);
+ }
+
+#endif /* ARM_MATH_DSP */
+
+ /* Return to application */
+ return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
--
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