diff options
Diffstat (limited to 'fw/hid-dials/Drivers/CMSIS/NN/Source/ConvolutionFunctions/arm_depthwise_separable_conv_HWC_q7.c')
| -rw-r--r-- | fw/hid-dials/Drivers/CMSIS/NN/Source/ConvolutionFunctions/arm_depthwise_separable_conv_HWC_q7.c | 418 |
1 files changed, 418 insertions, 0 deletions
diff --git a/fw/hid-dials/Drivers/CMSIS/NN/Source/ConvolutionFunctions/arm_depthwise_separable_conv_HWC_q7.c b/fw/hid-dials/Drivers/CMSIS/NN/Source/ConvolutionFunctions/arm_depthwise_separable_conv_HWC_q7.c new file mode 100644 index 0000000..705fa6a --- /dev/null +++ b/fw/hid-dials/Drivers/CMSIS/NN/Source/ConvolutionFunctions/arm_depthwise_separable_conv_HWC_q7.c @@ -0,0 +1,418 @@ +/*
+ * 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_depthwise_separable_conv_HWC_q7.c
+ * Description: Q7 depthwise separable convolution 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 NNConv
+ * @{
+ */
+
+/**
+ * @brief Q7 depthwise separable convolution function
+ * @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 ch_im_out
+ *
+ * Implementation:
+ * There are 3 nested loop here:
+ * Inner loop: calculate each output value with MAC instruction over an accumulator
+ * Mid loop: loop over different output channel
+ * Outer loop: loop over different output (x, y)
+ */
+
+arm_status arm_depthwise_separable_conv_HWC_q7(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;
+ int16_t i_ker_y, i_ker_x;
+ q7_t *colBuffer = (q7_t *) bufferA;
+ q7_t *pBuffer = colBuffer;
+ const q7_t *pBias = bias;
+ q7_t *pOut = Im_out;
+ uint16_t rowCnt;
+ uint16_t row_shift;
+
+ /* do some checking here, basically ch_im_in == ch_im_out */
+ if (ch_im_in != ch_im_out)
+ {
+ return ARM_MATH_SIZE_MISMATCH;
+ }
+
+ 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++)
+ {
+ /* we first do im2col here */
+ 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)
+ {
+ /* arm_fill_q7(0, pBuffer, ch_im_in); */
+ memset(pBuffer, 0, ch_im_in);
+ } else
+ {
+ /* arm_copy_q7((q7_t *) Im_in + (i_ker_y * dim_im_in + i_ker_x) * ch_im_in, pBuffer, ch_im_in); */
+ memcpy(pBuffer, (q7_t *) Im_in + (i_ker_y * dim_im_in + i_ker_x) * ch_im_in, ch_im_in);
+ }
+ pBuffer += ch_im_in;
+ }
+ }
+
+ /* we will do the computation here for each channel */
+ rowCnt = ch_im_out >> 2;
+ row_shift = 0;
+ 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_kernel * dim_kernel) >> 1;
+ q7_t *pB = colBuffer + row_shift;
+ const q7_t *pA = wt + row_shift;
+ row_shift += 4;
+
+#ifdef USE_INTRINSIC
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+ while (colCnt)
+ {
+ q31_t inA1, inA2, inB1, inB2, opA, opB;
+
+ inB1 = *__SIMD32(pB);
+ pB += ch_im_in;
+ opB = *__SIMD32(pB);
+ pB += ch_im_in;
+ inB2 = __PKHTB(opB, inB1, 16);
+ inB1 = __PKHBT(inB1, opB, 16);
+ inA1 = *__SIMD32(pA);
+ pA += ch_im_in;
+ opB = *__SIMD32(pA);
+ pA += ch_im_in;
+ inA2 = __PKHTB(opB, inA1, 16);
+ inA1 = __PKHBT(inA1, opB, 16);
+ opA = __SXTB16(inA1);
+ opB = __SXTB16(inB1);
+ sum = __SMLAD(opA, opB, sum);
+ opA = __SXTB16(__ROR(inA1, 8));
+ opB = __SXTB16(__ROR(inB1, 8));
+ sum2 = __SMLAD(opA, opB, sum2);
+ opA = __SXTB16(inA2);
+ opB = __SXTB16(inB2);
+ sum3 = __SMLAD(opA, opB, sum3);
+ opA = __SXTB16(__ROR(inA2, 8));
+ opB = __SXTB16(__ROR(inB2, 8));
+ sum4 = __SMLAD(opA, opB, sum4);
+ colCnt--;
+ }
+#else
+
+ while (colCnt)
+ {
+ q31_t inA1, inA2, inB1, inB2, opA, opB;
+
+ inB1 = *__SIMD32(pB);
+ pB += ch_im_in;
+ opB = *__SIMD32(pB);
+ pB += ch_im_in;
+ inB2 = __PKHBT(opB, inB1, 16);
+ inB1 = __PKHTB(inB1, opB, 16);
+ inA1 = *__SIMD32(pA);
+ pA += ch_im_in;
+ opB = *__SIMD32(pA);
+ pA += ch_im_in;
+ inA2 = __PKHBT(opB, inA1, 16);
+ inA1 = __PKHTB(inA1, opB, 16);
+ opA = __SXTB16(inA1);
+ opB = __SXTB16(inB1);
+ sum2 = __SMLAD(opA, opB, sum2);
+ opA = __SXTB16(__ROR(inA1, 8));
+ opB = __SXTB16(__ROR(inB1, 8));
+ sum = __SMLAD(opA, opB, sum);
+ opA = __SXTB16(inA2);
+ opB = __SXTB16(inB2);
+ sum4 = __SMLAD(opA, opB, sum4);
+ opA = __SXTB16(__ROR(inA2, 8));
+ opB = __SXTB16(__ROR(inB2, 8));
+ sum3 = __SMLAD(opA, opB, sum3);
+ colCnt--;
+ }
+
+#endif /* ARM_MATH_BIG_ENDIAN */
+
+#else
+
+#ifndef ARM_MATH_BIG_ENDIAN
+ /*
+ * r0 r1 r2 r3 r4 r5
+ * inA1, inA2, inB1, inB2, opA, opB
+ */
+
+ asm volatile ("COL_LOOP_%=:\n"
+ "ldr.w r2, [%[pB], #0]\n"
+ "add.w %[pB], %[pB], %[ch_im_in]\n"
+ "ldr.w r5, [%[pB], #0]\n"
+ "add.w %[pB], %[pB], %[ch_im_in]\n"
+ "pkhtb r3, r5, r2, ASR #16\n"
+ "pkhbt r2, r2, r5, LSL #16\n"
+ "ldr.w r0, [%[pA], #0]\n"
+ "add.w %[pA], %[pA], %[ch_im_in]\n"
+ "ldr.w r5, [%[pA], #0]\n"
+ "add.w %[pA], %[pA], %[ch_im_in]\n"
+ "pkhtb r1, r5, r0, ASR #16\n"
+ "pkhbt r0, r0, r5, LSL #16\n"
+ "sxtb16 r4, r0\n"
+ "sxtb16 r5, r2\n"
+ "smlad %[sum], r4, r5, %[sum]\n"
+ "mov.w r4, r0, ror #8\n"
+ "mov.w r5, r2, ror #8\n"
+ "sxtb16 r4, r4\n"
+ "sxtb16 r5, r5\n"
+ "smlad %[sum2], r4, r5, %[sum2]\n"
+ "sxtb16 r4, r1\n"
+ "sxtb16 r5, r3\n"
+ "smlad %[sum3], r4, r5, %[sum3]\n"
+ "mov.w r4, r1, ror #8\n"
+ "mov.w r5, r3, ror #8\n"
+ "sxtb16 r4, r4\n"
+ "sxtb16 r5, r5\n"
+ "smlad %[sum4], r4, r5, %[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),[ch_im_in] "r"(ch_im_in):"r0", "r1", "r2", "r3", "r4", "r5");
+#else
+ /*
+ * r0 r1 r2 r3 r4 r5
+ * inA1, inA2, inB1, inB2, opA, opB
+ */
+ asm volatile ("COL_LOOP_%=:\n"
+ "ldr.w r2, [%[pB], #0]\n"
+ "add.w %[pB], %[pB], %[ch_im_in]\n"
+ "ldr.w r5, [%[pB], #0]\n"
+ "add.w %[pB], %[pB], %[ch_im_in]\n"
+ "pkhbt r3, r5, r2, LSL #16\n"
+ "pkhtb r2, r2, r5, ASR #16\n"
+ "ldr.w r0, [%[pA], #0]\n"
+ "add.w %[pA], %[pA], %[ch_im_in]\n"
+ "ldr.w r5, [%[pA], #0]\n"
+ "add.w %[pA], %[pA], %[ch_im_in]\n"
+ "pkhbt r1, r5, r0, LSL #16\n"
+ "pkhtb r0, r0, r5, ASR #16\n"
+ "sxtb16 r4, r0\n"
+ "sxtb16 r5, r2\n"
+ "smlad %[sum2], r4, r5, %[sum2]\n"
+ "mov.w r4, r0, ror #8\n"
+ "mov.w r5, r2, ror #8\n"
+ "sxtb16 r4, r4\n"
+ "sxtb16 r5, r5\n"
+ "smlad %[sum], r4, r5, %[sum]\n"
+ "sxtb16 r4, r1\n"
+ "sxtb16 r5, r3\n"
+ "smlad %[sum4], r4, r5, %[sum4]\n"
+ "mov.w r4, r1, ror #8\n"
+ "mov.w r5, r3, ror #8\n"
+ "sxtb16 r4, r4\n"
+ "sxtb16 r5, r5\n"
+ "smlad %[sum3], r4, r5, %[sum3]\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),[ch_im_in] "r"(ch_im_in):"r0", "r1", "r2", "r3", "r4", "r5");
+
+#endif /* ARM_MATH_BIG_ENDIAN */
+
+#endif /* USE_INTRINSIC */
+
+ colCnt = (dim_kernel * dim_kernel) & 0x1;
+ while (colCnt)
+ {
+ union arm_nnword inA, inB;
+ inA.word = *__SIMD32(pA);
+ pA += ch_im_in;
+ inB.word = *__SIMD32(pB);
+ pB += ch_im_in;
+ sum += inA.bytes[0] * inB.bytes[0];
+ sum2 += inA.bytes[1] * inB.bytes[1];
+ sum3 += inA.bytes[2] * inB.bytes[2];
+ sum4 += inA.bytes[3] * inB.bytes[3];
+ colCnt--;
+ }
+
+ *pOut++ = (q7_t) __SSAT((sum >> out_shift), 8);
+ *pOut++ = (q7_t) __SSAT((sum2 >> out_shift), 8);
+ *pOut++ = (q7_t) __SSAT((sum3 >> out_shift), 8);
+ *pOut++ = (q7_t) __SSAT((sum4 >> out_shift), 8);
+
+ rowCnt--;
+ }
+
+ rowCnt = ch_im_out & 0x3;
+ while (rowCnt)
+ {
+ q7_t *pB = colBuffer + row_shift;
+ const q7_t *pA = wt + row_shift;
+ q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+ uint16_t colCnt = (dim_kernel * dim_kernel);
+
+ row_shift += 1;
+
+ while (colCnt)
+ {
+ q7_t A1 = *pA;
+ q7_t B1 = *pB;
+ pA += ch_im_in;
+ pB += ch_im_in;
+ sum += A1 * B1;
+
+ colCnt--;
+ }
+ *pOut++ = (q7_t) __SSAT((sum >> out_shift), 8);
+ rowCnt--;
+ }
+
+ /* clear counter and pointers */
+ pBuffer = colBuffer;
+ }
+ }
+
+#else
+ /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+ int i_out_y, i_out_x, i_ch_out, i_ker_x, i_ker_y;
+ int conv_out;
+
+ /* do some checking here, basically ch_im_in == ch_im_out */
+ if (ch_im_in != ch_im_out)
+ {
+ return ARM_MATH_SIZE_MISMATCH;
+ }
+
+ 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_ch_out = 0; i_ch_out < ch_im_out; i_ch_out++)
+ {
+ // for each output
+ conv_out = ((q31_t)(bias[i_ch_out]) << bias_shift) + NN_ROUND(out_shift);
+ for (i_ker_y = 0; i_ker_y < dim_kernel; i_ker_y++)
+ {
+ for (i_ker_x = 0; i_ker_x < dim_kernel; i_ker_x++)
+ {
+ int in_row = stride * i_out_y + i_ker_y - padding;
+ int in_col = stride * i_out_x + i_ker_x - padding;
+ if (in_row >= 0 && in_col >= 0 && in_row < dim_im_in && in_col < dim_im_in)
+ {
+ conv_out +=
+ Im_in[(in_row *
+ dim_im_in +
+ in_col) *
+ ch_im_in +
+ i_ch_out] * wt[(i_ker_y * dim_kernel + i_ker_x) * ch_im_out + i_ch_out];
+ }
+ }
+ }
+ Im_out[(i_out_y * dim_im_out +
+ i_out_x) * ch_im_out + i_ch_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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