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_convolve_HWC_q7_RGB.c |  279 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 files changed, 279 insertions(+), 0 deletions(-)

diff --git a/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ConvolutionFunctions/arm_convolve_HWC_q7_RGB.c b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ConvolutionFunctions/arm_convolve_HWC_q7_RGB.c
new file mode 100644
index 0000000..e53c6f9
--- /dev/null
+++ b/mcu_sdk/gd32f103/rk_eFire/Board/CMSIS/NN/Source/ConvolutionFunctions/arm_convolve_HWC_q7_RGB.c
@@ -0,0 +1,279 @@
+/*
+ * 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_convolve_HWC_q7_RGB.c
+ * Description:  Q7 version of convolution for RGB image
+ *
+ * $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 NNConv
+ * @{
+ */
+
+  /**
+   * @brief Q7 convolution function for RGB image
+   * @param[in]       Im_in       pointer to input tensor
+   * @param[in]       dim_im_in   input tensor dimention
+   * @param[in]       ch_im_in    number of input tensor channels
+   * @param[in]       wt          pointer to kernel weights
+   * @param[in]       ch_im_out   number of filters, i.e., output tensor channels
+   * @param[in]       dim_kernel  filter kernel size
+   * @param[in]       padding     padding sizes
+   * @param[in]       stride      convolution stride
+   * @param[in]       bias        pointer to bias
+   * @param[in]       bias_shift  amount of left-shift for bias
+   * @param[in]       out_shift   amount of right-shift for output
+   * @param[in,out]   Im_out      pointer to output tensor
+   * @param[in]       dim_im_out  output tensor dimension
+   * @param[in,out]   bufferA     pointer to buffer space for input
+   * @param[in,out]   bufferB     pointer to buffer space for output
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   *
+   * @details
+   *
+   * <b>Buffer size:</b>
+   *
+   * bufferA size: 2*ch_im_in*dim_kernel*dim_kernel
+   *
+   * bufferB size: 0
+   *
+   * <b>Input dimension constraints:</b>
+   *
+   * ch_im_in equals 3
+   *
+   * This kernel is written exclusively for convolution with ch_im_in
+   * equals 3. This applies on the first layer of CNNs which has input
+   * image with RGB format.
+   */
+
+arm_status
+arm_convolve_HWC_q7_RGB(const q7_t * Im_in,
+                        const uint16_t dim_im_in,
+                        const uint16_t ch_im_in,
+                        const q7_t * wt,
+                        const uint16_t ch_im_out,
+                        const uint16_t dim_kernel,
+                        const uint16_t padding,
+                        const uint16_t stride,
+                        const q7_t * bias,
+                        const uint16_t bias_shift,
+                        const uint16_t out_shift,
+                        q7_t * Im_out, const uint16_t dim_im_out, q15_t * bufferA, q7_t * bufferB)
+{
+
+#if defined (ARM_MATH_DSP)
+    /* Run the following code for Cortex-M4 and Cortex-M7 */
+    int16_t   i_out_y, i_out_x, i_ker_y, i_ker_x;
+
+    /*
+     *  Here we use bufferA as q15_t internally as computation are done with q15_t level
+     *  im2col are done to output in q15_t format from q7_t input
+     */
+    q15_t    *pBuffer = bufferA;
+    q7_t     *pOut = Im_out;
+
+    // check if number of input channels is 3
+    if (ch_im_in != 3)
+    {
+        return ARM_MATH_SIZE_MISMATCH;
+    }
+    // This part implements the im2col function
+    for (i_out_y = 0; i_out_y < dim_im_out; i_out_y++)
+    {
+        for (i_out_x = 0; i_out_x < dim_im_out; i_out_x++)
+        {
+            for (i_ker_y = i_out_y * stride - padding; i_ker_y < i_out_y * stride - padding + dim_kernel; i_ker_y++)
+            {
+                for (i_ker_x = i_out_x * stride - padding; i_ker_x < i_out_x * stride - padding + dim_kernel; i_ker_x++)
+                {
+                    if (i_ker_y < 0 || i_ker_y >= dim_im_in || i_ker_x < 0 || i_ker_x >= dim_im_in)
+                    {
+                        /* Equivalent to arm_fill_q15(0, pBuffer, ch_im_in) with assumption: ch_im_in = 3 */
+                        *__SIMD32(pBuffer) = 0x0;
+                        *(pBuffer + 2) = 0;
+                        pBuffer += 3;
+                    } else
+                    {
+                        /* 
+                         * Equivalent to:
+                         *  arm_q7_to_q15_no_shift( (q7_t*)Im_in+(i_ker_y*dim_im_in+i_ker_x)*3, pBuffer, 3);
+                         */
+
+                        const q7_t *pPixel = Im_in + (i_ker_y * dim_im_in + i_ker_x) * 3;
+                        q31_t     buf = *__SIMD32(pPixel);
+
+                        union arm_nnword top;
+                        union arm_nnword bottom;
+
+                        top.word = __SXTB16(buf);
+                        bottom.word = __SXTB16(__ROR(buf, 8));
+
+#ifndef ARM_MATH_BIG_ENDIAN
+                        /*
+                         *  little-endian, | omit | 3rd  | 2nd  | 1st  |
+                         *                MSB                         LSB
+                         *   top | 3rd | 1st |; bottom | omit | 2nd |
+                         *
+                         *  version 1, need to swap 2nd and 3rd weight
+                         * *__SIMD32(pBuffer) = top.word;
+                         * *(pBuffer+2) = bottom.half_words[0];
+                         *
+                         *  version 2, no weight shuffling required
+                         */
+                        *pBuffer++ = top.half_words[0];
+                        *__SIMD32(pBuffer) = __PKHBT(bottom.word, top.word, 0);
+#else
+                        /*
+                         *  big-endian,    | 1st  | 2nd  | 3rd  | omit | 
+                         *                MSB                         LSB
+                         *  top | 2nd | omit |; bottom | 1st | 3rd |
+                         * 
+                         *  version 1, need to swap 2nd and 3rd weight
+                         * *__SIMD32(pBuffer) = bottom.word;
+                         * *(pBuffer+2) = top.half_words[1];
+                         * 
+                         *  version 2, no weight shuffling required
+                         */
+                        *pBuffer++ = bottom.half_words[0];
+                        *__SIMD32(pBuffer) = __PKHTB(top.word, bottom.word, 0);
+#endif
+                        pBuffer += 2;
+                    }
+                }
+            }
+
+            if (pBuffer == bufferA + 2 * 3 * dim_kernel * dim_kernel)
+            {
+                pOut =
+                    arm_nn_mat_mult_kernel_q7_q15(wt, bufferA,
+                                                  ch_im_out,
+                                                  3 * dim_kernel * dim_kernel, bias_shift, out_shift, bias, pOut);
+
+                /* counter reset */
+                pBuffer = bufferA;
+            }
+        }
+    }
+
+    /* left-over because odd number of output pixels */
+    if (pBuffer != bufferA)
+    {
+        const q7_t *pA = wt;
+        int       i;
+
+        for (i = 0; i < ch_im_out; i++)
+        {
+            q31_t     sum = ((q31_t)bias[i] << bias_shift) + NN_ROUND(out_shift);
+            q15_t    *pB = bufferA;
+            /* basically each time it process 4 entries */
+            uint16_t  colCnt = 3 * dim_kernel * dim_kernel >> 2;
+
+            while (colCnt)
+            {
+
+                q31_t     inA1, inA2;
+                q31_t     inB1, inB2;
+
+                pA = (q7_t *) read_and_pad((void *)pA, &inA1, &inA2);
+
+                inB1 = *__SIMD32(pB)++;
+                sum = __SMLAD(inA1, inB1, sum);
+                inB2 = *__SIMD32(pB)++;
+                sum = __SMLAD(inA2, inB2, sum);
+
+                colCnt--;
+            }
+            colCnt = 3 * dim_kernel * dim_kernel & 0x3;
+            while (colCnt)
+            {
+                q7_t      inA1 = *pA++;
+                q15_t     inB1 = *pB++;
+                sum += inA1 * inB1;
+                colCnt--;
+            }
+            *pOut++ = (q7_t) __SSAT((sum >> out_shift), 8);
+        }
+    }
+#else
+    /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+
+    uint16_t  i, j, k, l, m, n;
+    int       conv_out;
+    signed char in_row, in_col;
+
+    // check if number of input channels is 3
+    if (ch_im_in != 3)
+    {
+        return ARM_MATH_SIZE_MISMATCH;
+    }
+
+    for (i = 0; i < ch_im_out; i++)
+    {
+        for (j = 0; j < dim_im_out; j++)
+        {
+            for (k = 0; k < dim_im_out; k++)
+            {
+                conv_out = (bias[i] << bias_shift) + NN_ROUND(out_shift);
+                for (m = 0; m < dim_kernel; m++)
+                {
+                    for (n = 0; n < dim_kernel; n++)
+                    {
+                        /* if-for implementation */
+                        in_row = stride * j + m - padding;
+                        in_col = stride * k + n - padding;
+                        if (in_row >= 0 && in_col >= 0 && in_row < dim_im_in && in_col < dim_im_in)
+                        {
+                            for (l = 0; l < ch_im_in; l++)
+                            {
+                                conv_out +=
+                                    Im_in[(in_row * dim_im_in + in_col) * ch_im_in +
+                                          l] * wt[i * ch_im_in * dim_kernel * dim_kernel + (m * dim_kernel +
+                                                                                            n) * ch_im_in + l];
+                            }
+                        }
+                    }
+                }
+                Im_out[i + (j * dim_im_out + k) * ch_im_out] = (q7_t) __SSAT((conv_out >> out_shift), 8);
+            }
+        }
+    }
+
+#endif                          /* ARM_MATH_DSP */
+
+    /* Return to application */
+    return (ARM_MATH_SUCCESS);
+}
+
+/**
+ * @} end of NNConv group
+ */

--
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