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| author | JanHenrik <janhenrik@janhenrik.org> | 2020-04-01 00:40:03 +0200 |
|---|---|---|
| committer | JanHenrik <janhenrik@janhenrik.org> | 2020-04-01 00:40:03 +0200 |
| commit | f7de54fc6fa6b40dfa2dfbe4c2a8ee933affa126 (patch) | |
| tree | 78465e38a01011dc9f17eb73416011310532017f /hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions | |
| parent | 3ec13d81e70e52246545c720abe756ccf09fb231 (diff) | |
| download | minikbd-f7de54fc6fa6b40dfa2dfbe4c2a8ee933affa126.tar.gz minikbd-f7de54fc6fa6b40dfa2dfbe4c2a8ee933affa126.tar.bz2 minikbd-f7de54fc6fa6b40dfa2dfbe4c2a8ee933affa126.zip | |
added files
Diffstat (limited to 'hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions')
6 files changed, 1809 insertions, 0 deletions
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15.c b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15.c new file mode 100644 index 0000000..bb9a091 --- /dev/null +++ b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15.c @@ -0,0 +1,199 @@ +/*
+ * 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_mat_q7_vec_q15.c
+ * Description: Mixed Q15-Q7 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 Mixed Q15-Q7 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
+ *
+ * Q7_Q15 version of the fully connected layer
+ *
+ * Weights are in q7_t and Activations are in q15_t
+ *
+ */
+
+arm_status
+arm_fully_connected_mat_q7_vec_q15(const q15_t * pV,
+ const q7_t * pM,
+ const uint16_t dim_vec,
+ const uint16_t num_of_rows,
+ const uint16_t bias_shift,
+ const uint16_t out_shift,
+ const q7_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 q7_t *pB = pM;
+ const q7_t *pB2;
+ q15_t *pO = pOut;
+ const q7_t *pBias = bias;
+ const q15_t *pA = pV;
+
+ uint16_t rowCnt = num_of_rows >> 1;
+
+ 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 inV, inM11, inM12, inM21, inM22;
+ pB = (q7_t *) read_and_pad((void *)pB, &inM11, &inM12);
+ pB2 = (q7_t *) read_and_pad((void *)pB2, &inM21, &inM22);
+
+ inV = *__SIMD32(pA)++;
+
+ sum = __SMLAD(inV, inM11, sum);
+ sum2 = __SMLAD(inV, inM21, sum2);
+
+ inV = *__SIMD32(pA)++;
+
+ sum = __SMLAD(inV, inM12, sum);
+ sum2 = __SMLAD(inV, inM22, sum2);
+
+ colCnt--;
+ }
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q15_t inV = *pA++;
+ q7_t inM = *pB++;
+ q7_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 += dim_vec;
+ rowCnt--;
+ }
+
+ /* left-over part of the rows */
+ 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, inV2, inM11, inM12;
+
+ pB = (q7_t *) read_and_pad((void *)pB, &inM11, &inM12);
+
+ inV1 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV1, inM11, sum);
+
+ inV2 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV2, inM12, sum);
+
+ colCnt--;
+ }
+
+ /* left-over of the vector */
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q15_t inV = *pA++;
+ q7_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 ARM_MATH_SUCCESS */
+ return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15_opt.c b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15_opt.c new file mode 100644 index 0000000..b0c308b --- /dev/null +++ b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15_opt.c @@ -0,0 +1,403 @@ +/*
+ * 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_mat_q7_vec_q15_opt.c
+ * Description: Mixed Q15-Q7 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 Mixed Q15-Q7 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
+ *
+ * Q7_Q15 version of the fully connected layer
+ *
+ * Weights are in q7_t and Activations are in q15_t
+ *
+ * Limitation: x4 version requires weight reordering to work
+ *
+ * Here we use only one pointer to read 4 rows in the weight
+ * matrix. So if the original q7_t matrix looks like this:
+ *
+ * | a11 | a12 | a13 | a14 | a15 | a16 | a17 |
+ *
+ * | a21 | a22 | a23 | a24 | a25 | a26 | a27 |
+ *
+ * | a31 | a32 | a33 | a34 | a35 | a36 | a37 |
+ *
+ * | a41 | a42 | a43 | a44 | a45 | a46 | a47 |
+ *
+ * | a51 | a52 | a53 | a54 | a55 | a56 | a57 |
+ *
+ * | a61 | a62 | a63 | a64 | a65 | a66 | a67 |
+ *
+ * We operates on multiple-of-4 rows, so the first four rows becomes
+ *
+ * | a11 | a21 | a12 | a22 | a31 | a41 | a32 | a42 |
+ *
+ * | a13 | a23 | a14 | a24 | a33 | a43 | a34 | a44 |
+ *
+ * | a15 | a25 | a16 | a26 | a35 | a45 | a36 | a46 |
+ *
+ * The column left over will be in-order.
+ * which is:
+ * | a17 | a27 | a37 | a47 |
+ *
+ * For the left-over rows, we do 1x1 computation, so the data remains
+ * as its original order.
+ *
+ * So the stored weight matrix looks like this:
+ *
+ * | a11 | a21 | a12 | a22 | a31 | a41 |
+ *
+ * | a32 | a42 | a13 | a23 | a14 | a24 |
+ *
+ * | a33 | a43 | a34 | a44 | a15 | a25 |
+ *
+ * | a16 | a26 | a35 | a45 | a36 | a46 |
+ *
+ * | a17 | a27 | a37 | a47 | a51 | a52 |
+ *
+ * | a53 | a54 | a55 | a56 | a57 | a61 |
+ *
+ * | a62 | a63 | a64 | a65 | a66 | a67 |
+ *
+ */
+
+arm_status
+arm_fully_connected_mat_q7_vec_q15_opt(const q15_t * pV,
+ const q7_t * pM,
+ const uint16_t dim_vec,
+ const uint16_t num_of_rows,
+ const uint16_t bias_shift,
+ const uint16_t out_shift, const q7_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 q7_t *pB = pM;
+ q15_t *pO = pOut;
+ const q7_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
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+ while (colCnt)
+ {
+ q31_t inM11, inM12, inM13, inM14;
+ q31_t inV;
+
+ inV = *__SIMD32(pA)++;
+ inM11 = *__SIMD32(pB)++;
+ inM12 = __SXTB16(__ROR(inM11, 8));
+ inM11 = __SXTB16(inM11);
+ sum = __SMLAD(inM11, inV, sum);
+ sum2 = __SMLAD(inM12, inV, sum2);
+ inM13 = *__SIMD32(pB)++;
+ inM14 = __SXTB16(__ROR(inM13, 8));
+ inM13 = __SXTB16(inM13);
+ sum3 = __SMLAD(inM13, inV, sum3);
+ sum4 = __SMLAD(inM14, inV, sum4);
+ colCnt--;
+ }
+
+#else
+
+ while (colCnt)
+ {
+ q31_t inM11, inM12, inM13, inM14;
+ q31_t inV;
+
+ inV = *__SIMD32(pA)++;
+ inM11 = *__SIMD32(pB)++;
+ inM12 = __SXTB16(__ROR(inM11, 8));
+ inM11 = __SXTB16(inM11);
+ sum = __SMLAD(inM12, inV, sum);
+ sum2 = __SMLAD(inM11, inV, sum2);
+ inM13 = *__SIMD32(pB)++;
+ inM14 = __SXTB16(__ROR(inM13, 8));
+ inM13 = __SXTB16(inM13);
+ sum3 = __SMLAD(inM14, inV, sum3);
+ sum4 = __SMLAD(inM13, inV, sum4);
+ colCnt--;
+ }
+
+#endif /* ARM_MATH_BIG_ENDIAN */
+
+#else
+
+ /*
+ * register needed:
+ * loop counter: colCnt
+ * accumulators: sum, sum2, sum3, sum4
+ * pointers: pB, pA
+ * weight data: inM11, inM12, inM13, inM14
+ * activation data: inV
+ */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+ asm volatile ("COL_LOOP_%=:\n"
+ "ldr.w r4, [%[pA]], #4\n"
+ "ldr.w r1, [%[pB]], #8\n"
+ "mov.w r0, r1, ror #8\n"
+ "sxtb16 r0, r0\n"
+ "sxtb16 r1, r1\n"
+ "smlad %[sum], r4, r1, %[sum]\n"
+ "smlad %[sum2], r4, r0, %[sum2]\n"
+ "ldr.w r3, [%[pB], #-4]\n"
+ "mov.w r2, r3, ror #8\n"
+ "sxtb16 r2, r2\n"
+ "sxtb16 r3, r3\n"
+ "smlad %[sum3], r4, r3, %[sum3]\n"
+ "smlad %[sum4], r4, r2, %[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");
+#else
+ asm volatile ("COL_LOOP_%=:\n"
+ "ldr.w r4, [%[pA]], #4\n"
+ "ldr.w r1, [%[pB]], #8\n"
+ "mov.w r0, r1, ror #8\n"
+ "sxtb16 r0, r0\n"
+ "sxtb16 r1, r1\n"
+ "smlad %[sum], r4, r0, %[sum]\n"
+ "smlad %[sum2], r4, r1, %[sum2]\n"
+ "ldr.w r3, [%[pB], #-4]\n"
+ "mov.w r2, r3, ror #8\n"
+ "sxtb16 r2, r2\n"
+ "sxtb16 r3, r3\n"
+ "smlad %[sum3], r4, r2, %[sum3]\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 /* ARM_MATH_BIG_ENDIAN */
+
+#endif /* USE_INTRINSIC */
+
+ colCnt = dim_vec & 0x1;
+ while (colCnt)
+ {
+ q15_t inV = *pA++;
+ q7_t inM = *pB++;
+ q7_t inM2 = *pB++;
+ q7_t inM3 = *pB++;
+ q7_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, inM11, inM12;
+
+ pB = (q7_t *) read_and_pad((void *)pB, &inM11, &inM12);
+
+ inV1 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV1, inM11, sum);
+
+ inV2 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV2, inM12, sum);
+
+ colCnt--;
+ }
+
+ /* left-over of the vector */
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q15_t inV = *pA++;
+ q7_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 q7_t *pB = pM;
+ const q15_t *pA;
+ q15_t *pO = pOut;
+ const q7_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++;
+
+ q7_t inB1 = *pB++;
+ q7_t inB3 = *pB++;
+ q7_t inB2 = *pB++;
+ q7_t inB4 = *pB++;
+
+ sum += inA1 * inB1 + inA2 * inB2;
+ sum2 += inA1 * inB3 + inA2 * inB4;
+
+ inB1 = *pB++;
+ inB3 = *pB++;
+ inB2 = *pB++;
+ inB4 = *pB++;
+
+ sum3 += inA1 * inB1 + inA2 * inB2;
+ sum4 += inA1 * inB3 + inA2 * inB4;
+
+ colCnt--;
+ }
+
+ colCnt = dim_vec & 0x1;
+ while (colCnt)
+ {
+ q15_t inA = *pA++;
+ q7_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++;
+ q7_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
+ */
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15.c new file mode 100644 index 0000000..a4c6bba --- /dev/null +++ b/hid-dials/Drivers/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
+ */
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c new file mode 100644 index 0000000..8f3bbea --- /dev/null +++ b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q15_opt.c @@ -0,0 +1,332 @@ +/*
+ * 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
+ */
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7.c b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7.c new file mode 100644 index 0000000..75e924f --- /dev/null +++ b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7.c @@ -0,0 +1,198 @@ +/*
+ * 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_q7.c
+ * Description: Q7 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 Q7 basic 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: dim_vec
+ *
+ * This basic function is designed to work with regular weight
+ * matrix without interleaving.
+ *
+ */
+
+arm_status
+arm_fully_connected_q7(const q7_t * pV,
+ const q7_t * pM,
+ const uint16_t dim_vec,
+ const uint16_t num_of_rows,
+ const uint16_t bias_shift,
+ const uint16_t out_shift, const q7_t * bias, q7_t * pOut, q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+ /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+ const q7_t *pB = pM;
+ const q7_t *pB2;
+ q7_t *pO = pOut;
+ const q7_t *pBias = bias;
+ q15_t *pA;
+ uint16_t rowCnt = num_of_rows >> 1;
+
+ /* expand the vector into the buffer */
+ arm_q7_to_q15_reordered_no_shift(pV, vec_buffer, dim_vec);
+
+ 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 = vec_buffer;
+ pB2 = pB + dim_vec;
+
+ while (colCnt)
+ {
+ q31_t inV, inM11, inM12, inM21, inM22;
+ pB = (q7_t *) read_and_pad_reordered((void *)pB, &inM11, &inM12);
+ pB2 = (q7_t *) read_and_pad_reordered((void *)pB2, &inM21, &inM22);
+
+ inV = *__SIMD32(pA)++;
+
+ sum = __SMLAD(inV, inM11, sum);
+ sum2 = __SMLAD(inV, inM21, sum2);
+
+ inV = *__SIMD32(pA)++;
+
+ sum = __SMLAD(inV, inM12, sum);
+ sum2 = __SMLAD(inV, inM22, sum2);
+
+ colCnt--;
+ }
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q7_t inV = *pA++;
+ q15_t inM = *pB++;
+ q15_t inM2 = *pB2++;
+
+ sum += inV * inM;
+ sum2 += inV * inM2;
+ colCnt--;
+ } /* while over colCnt */
+ *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+ *pO++ = (q7_t) (__SSAT((sum2 >> out_shift), 8));
+
+ /* adjust the pointers and counters */
+ pB += dim_vec;
+ rowCnt--;
+ }
+
+ /* left-over part of the rows */
+ rowCnt = num_of_rows & 0x1;
+
+ while (rowCnt)
+ {
+ uint16_t colCnt = dim_vec >> 2;
+ q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
+
+ pA = vec_buffer;
+
+ while (colCnt)
+ {
+ q31_t inV1, inV2, inM11, inM12;
+
+ pB = (q7_t *) read_and_pad_reordered((void *)pB, &inM11, &inM12);
+
+ inV1 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV1, inM11, sum);
+
+ inV2 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV2, inM12, sum);
+
+ colCnt--;
+ }
+
+ /* left-over of the vector */
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q7_t inV = *pA++;
+ q15_t inM = *pB++;
+ sum += inV * inM;
+ colCnt--;
+ }
+
+ *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+
+ 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] = (q7_t) __SSAT((ip_out >> out_shift), 8);
+ }
+
+#endif /* ARM_MATH_DSP */
+
+ /* Return to ARM_MATH_SUCCESS */
+ return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7_opt.c b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7_opt.c new file mode 100644 index 0000000..d197adc --- /dev/null +++ b/hid-dials/Drivers/CMSIS/NN/Source/FullyConnectedFunctions/arm_fully_connected_q7_opt.c @@ -0,0 +1,484 @@ +/*
+ * 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_q7_opt.c
+ * Description: Q7 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 Q7 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: dim_vec
+ *
+ * This opt function is designed to work with interleaved weight
+ * matrix. The vector input is assumed in q7_t format, we call
+ * arm_q7_to_q15_no_shift_shuffle function to expand into
+ * q15_t format with certain weight re-ordering, refer to the function
+ * comments for more details.
+ * Here we use only one pointer to read 4 rows in the weight
+ * matrix. So if the original q7_t matrix looks like this:
+ *
+ * | a11 | a12 | a13 | a14 | a15 | a16 | a17 |
+ *
+ * | a21 | a22 | a23 | a24 | a25 | a26 | a27 |
+ *
+ * | a31 | a32 | a33 | a34 | a35 | a36 | a37 |
+ *
+ * | a41 | a42 | a43 | a44 | a45 | a46 | a47 |
+ *
+ * | a51 | a52 | a53 | a54 | a55 | a56 | a57 |
+ *
+ * | a61 | a62 | a63 | a64 | a65 | a66 | a67 |
+ *
+ *
+ * We operates on multiple-of-4 rows, so the first four rows becomes
+ *
+ * | a11 | a21 | a13 | a23 | a31 | a41 | a33 | a43 |
+ *
+ * | a12 | a22 | a14 | a24 | a32 | a42 | a34 | a44 |
+ *
+ * | a15 | a25 | a35 | a45 | a16 | a26 | a36 | a46 |
+ *
+ * So within the kernel, we first read the re-ordered vector in as:
+ *
+ * | b1 | b3 | and | b2 | b4 |
+ *
+ * the four q31_t weights will look like
+ *
+ * | a11 | a13 |, | a21 | a23 |, | a31 | a33 |, | a41 | a43 |
+ *
+ * | a12 | a14 |, | a22 | a24 |, | a32 | a34 |, | a42 | a44 |
+ *
+ * The column left over will be in-order.
+ * which is:
+ *
+ * | a17 | a27 | a37 | a47 |
+ *
+ * For the left-over rows, we do 1x1 computation, so the data remains
+ * as its original order.
+ *
+ * So the stored weight matrix looks like this:
+ *
+ * | a11 | a21 | a13 | a23 | a31 | a41 |
+ *
+ * | a33 | a43 | a12 | a22 | a14 | a24 |
+ *
+ * | a32 | a42 | a34 | a44 | a15 | a25 |
+ *
+ * | a35 | a45 | a16 | a26 | a36 | a46 |
+ *
+ * | a17 | a27 | a37 | a47 | a51 | a52 |
+ *
+ * | a53 | a54 | a55 | a56 | a57 | a61 |
+ *
+ * | a62 | a63 | a64 | a65 | a66 | a67 |
+ *
+ *
+ */
+
+arm_status
+arm_fully_connected_q7_opt(const q7_t * pV,
+ const q7_t * pM,
+ const uint16_t dim_vec,
+ const uint16_t num_of_rows,
+ const uint16_t bias_shift,
+ const uint16_t out_shift,
+ const q7_t * bias,
+ q7_t * pOut,
+ q15_t * vec_buffer)
+{
+
+#if defined (ARM_MATH_DSP)
+ /* Run the following code for Cortex-M4 and Cortex-M7 */
+
+ const q7_t *pB = pM;
+ q7_t *pO = pOut;
+ const q7_t *pBias = bias;
+ q15_t *pA;
+ uint16_t rowCnt = num_of_rows >> 2;
+
+ arm_q7_to_q15_reordered_no_shift(pV, vec_buffer, dim_vec);
+
+ 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 >> 2;
+
+ pA = vec_buffer;
+
+#ifdef USE_INTRINSIC
+
+#ifndef ARM_MATH_BIG_ENDIAN
+ while (colCnt)
+ {
+ q31_t inM11, inM12, inM13, inM14;
+ q31_t inV;
+
+ inV = *__SIMD32(pA)++;
+ inM11 = *__SIMD32(pB)++;
+ inM12 = __SXTB16(__ROR(inM11, 8));
+ inM11 = __SXTB16(inM11);
+ sum = __SMLAD(inM11, inV, sum);
+ sum2 = __SMLAD(inM12, inV, sum2);
+ inM13 = *__SIMD32(pB)++;
+ inM14 = __SXTB16(__ROR(inM13, 8));
+ inM13 = __SXTB16(inM13);
+ sum3 = __SMLAD(inM13, inV, sum3);
+ sum4 = __SMLAD(inM14, inV, sum4);
+
+ inV = *__SIMD32(pA)++;
+ inM11 = *__SIMD32(pB)++;
+ inM12 = __SXTB16(__ROR(inM11, 8));
+ inM11 = __SXTB16(inM11);
+ sum = __SMLAD(inM11, inV, sum);
+ sum2 = __SMLAD(inM12, inV, sum2);
+ inM13 = *__SIMD32(pB)++;
+ inM14 = __SXTB16(__ROR(inM13, 8));
+ inM13 = __SXTB16(inM13);
+ sum3 = __SMLAD(inM13, inV, sum3);
+ sum4 = __SMLAD(inM14, inV, sum4);
+ colCnt--;
+ }
+#else
+ while (colCnt)
+ {
+ q31_t inM11, inM12, inM13, inM14;
+ q31_t inV;
+
+ inV = *__SIMD32(pA)++;
+ inM11 = *__SIMD32(pB)++;
+ inM12 = __SXTB16(__ROR(inM11, 8));
+ inM11 = __SXTB16(inM11);
+ sum = __SMLAD(inM12, inV, sum);
+ sum2 = __SMLAD(inM11, inV, sum2);
+ inM13 = *__SIMD32(pB)++;
+ inM14 = __SXTB16(__ROR(inM13, 8));
+ inM13 = __SXTB16(inM13);
+ sum3 = __SMLAD(inM14, inV, sum3);
+ sum4 = __SMLAD(inM13, inV, sum4);
+
+ inV = *__SIMD32(pA)++;
+ inM11 = *__SIMD32(pB)++;
+ inM12 = __SXTB16(__ROR(inM11, 8));
+ inM11 = __SXTB16(inM11);
+ sum = __SMLAD(inM12, inV, sum);
+ sum2 = __SMLAD(inM11, inV, sum2);
+ inM13 = *__SIMD32(pB)++;
+ inM14 = __SXTB16(__ROR(inM13, 8));
+ inM13 = __SXTB16(inM13);
+ sum3 = __SMLAD(inM14, inV, sum3);
+ sum4 = __SMLAD(inM13, inV, sum4);
+ colCnt--;
+ }
+#endif /* ARM_MATH_BIG_ENDIAN */
+
+#else
+
+ /*
+ * register needed:
+ * loop counter: colCnt
+ * accumulators: sum, sum2, sum3, sum4
+ * pointers: pB, pA
+ * weight data: inM11, inM12, inM13, inM14
+ * activation data: inV
+ */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+ asm volatile ("COL_LOOP_%=:\n"
+ "ldr.w r4, [%[pA]], #8\n"
+ "ldr.w r1, [%[pB]], #16\n"
+ "mov.w r0, r1, ror #8\n"
+ "sxtb16 r0, r0\n"
+ "sxtb16 r1, r1\n"
+ "smlad %[sum], r4, r1, %[sum]\n"
+ "smlad %[sum2], r4, r0, %[sum2]\n"
+ "ldr.w r3, [%[pB], #-12]\n"
+ "mov.w r2, r3, ror #8\n"
+ "sxtb16 r2, r2\n"
+ "sxtb16 r3, r3\n"
+ "smlad %[sum3], r4, r3, %[sum3]\n"
+ "smlad %[sum4], r4, r2, %[sum4]\n"
+ "ldr.w r4, [%[pA], #-4]\n"
+ "ldr.w r1, [%[pB], #-8]\n"
+ "mov.w r0, r1, ror #8\n"
+ "sxtb16 r0, r0\n"
+ "sxtb16 r1, r1\n"
+ "smlad %[sum], r4, r1, %[sum]\n"
+ "smlad %[sum2], r4, r0, %[sum2]\n"
+ "ldr.w r3, [%[pB], #-4]\n"
+ "mov.w r2, r3, ror #8\n"
+ "sxtb16 r2, r2\n"
+ "sxtb16 r3, r3\n"
+ "smlad %[sum3], r4, r3, %[sum3]\n"
+ "smlad %[sum4], r4, r2, %[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");
+#else
+ asm volatile ("COL_LOOP_%=:\n"
+ "ldr.w r4, [%[pA]], #8\n"
+ "ldr.w r1, [%[pB]], #16\n"
+ "mov.w r0, r1, ror #8\n"
+ "sxtb16 r0, r0\n"
+ "sxtb16 r1, r1\n"
+ "smlad %[sum], r4, r0, %[sum]\n"
+ "smlad %[sum2], r4, r1, %[sum2]\n"
+ "ldr.w r3, [%[pB], #-12]\n"
+ "mov.w r2, r3, ror #8\n"
+ "sxtb16 r2, r2\n"
+ "sxtb16 r3, r3\n"
+ "smlad %[sum3], r4, r2, %[sum3]\n"
+ "smlad %[sum4], r4, r3, %[sum4]\n"
+ "ldr.w r4, [%[pA], #-4]\n"
+ "ldr.w r1, [%[pB], #-8]\n"
+ "mov.w r0, r1, ror #8\n"
+ "sxtb16 r0, r0\n"
+ "sxtb16 r1, r1\n"
+ "smlad %[sum], r4, r0, %[sum]\n"
+ "smlad %[sum2], r4, r1, %[sum2]\n"
+ "ldr.w r3, [%[pB], #-4]\n"
+ "mov.w r2, r3, ror #8\n"
+ "sxtb16 r2, r2\n"
+ "sxtb16 r3, r3\n"
+ "smlad %[sum3], r4, r2, %[sum3]\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 /* ARM_MATH_BIG_ENDIAN */
+
+#endif /* USE_INTRINSIC */
+
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q15_t inV = *pA++;
+ q7_t inM = *pB++;
+ q7_t inM2 = *pB++;
+ q7_t inM3 = *pB++;
+ q7_t inM4 = *pB++;
+
+ sum += inV * inM;
+ sum2 += inV * inM2;
+ sum3 += inV * inM3;
+ sum4 += inV * inM4;
+ colCnt--;
+ } /* while over colCnt */
+ *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+ *pO++ = (q7_t) (__SSAT((sum2 >> out_shift), 8));
+ *pO++ = (q7_t) (__SSAT((sum3 >> out_shift), 8));
+ *pO++ = (q7_t) (__SSAT((sum4 >> out_shift), 8));
+
+ /* 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 = vec_buffer;
+
+ while (colCnt)
+ {
+ q31_t inV1, inV2, inM11, inM12;
+
+ pB = (q7_t *) read_and_pad_reordered((void *)pB, &inM11, &inM12);
+
+ inV1 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV1, inM11, sum);
+
+ inV2 = *__SIMD32(pA)++;
+ sum = __SMLAD(inV2, inM12, sum);
+
+ colCnt--;
+ }
+
+ /* left-over of the vector */
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q15_t inV = *pA++;
+ q7_t inM = *pB++;
+ sum += inV * inM;
+ colCnt--;
+ }
+
+ *pO++ = (q7_t) (__SSAT((sum >> out_shift), 8));
+
+ rowCnt--;
+ }
+
+#else
+ /* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
+ uint16_t rowCnt = num_of_rows >> 2;
+ const q7_t *pB = pM;
+ const q7_t *pA;
+ q7_t *pO = pOut;
+ const q7_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 >> 2;
+
+ pA = pV;
+
+ while (colCnt)
+ {
+ q7_t inA1 = *pA++;
+ q7_t inA3 = *pA++;
+ q7_t inA2 = *pA++;
+ q7_t inA4 = *pA++;
+
+ q7_t inB1 = *pB++;
+ q7_t inB3 = *pB++;
+ q7_t inB2 = *pB++;
+ q7_t inB4 = *pB++;
+
+ sum += inA1 * inB1 + inA2 * inB2;
+ sum2 += inA1 * inB3 + inA2 * inB4;
+
+ inB1 = *pB++;
+ inB3 = *pB++;
+ inB2 = *pB++;
+ inB4 = *pB++;
+
+ sum3 += inA1 * inB1 + inA2 * inB2;
+ sum4 += inA1 * inB3 + inA2 * inB4;
+
+ inB1 = *pB++;
+ inB3 = *pB++;
+ inB2 = *pB++;
+ inB4 = *pB++;
+
+ sum += inA3 * inB1 + inA4 * inB2;
+ sum2 += inA3 * inB3 + inA4 * inB4;
+
+ inB1 = *pB++;
+ inB3 = *pB++;
+ inB2 = *pB++;
+ inB4 = *pB++;
+
+ sum3 += inA3 * inB1 + inA4 * inB2;
+ sum4 += inA3 * inB3 + inA4 * inB4;
+
+ colCnt--;
+ }
+ colCnt = dim_vec & 0x3;
+ while (colCnt)
+ {
+ q7_t inA = *pA++;
+ q7_t inB = *pB++;
+ sum += inA * inB;
+ inB = *pB++;
+ sum2 += inA * inB;
+ inB = *pB++;
+ sum3 += inA * inB;
+ inB = *pB++;
+ sum4 += inA * inB;
+
+ colCnt--;
+ }
+ *pO++ = (q7_t) __SSAT((sum >> out_shift), 8);
+ *pO++ = (q7_t) __SSAT((sum2 >> out_shift), 8);
+ *pO++ = (q7_t) __SSAT((sum3 >> out_shift), 8);
+ *pO++ = (q7_t) __SSAT((sum4 >> out_shift), 8);
+
+ 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++)
+ {
+ q7_t inA = *pA++;
+ q7_t inB = *pB++;
+ ip_out += inA * inB;
+ }
+ *pO++ = (q7_t) __SSAT((ip_out >> out_shift), 8);
+
+ rowCnt--;
+ }
+
+#endif /* ARM_MATH_DSP */
+
+ /* Return to ARM_MATH_SUCCESS */
+ return (ARM_MATH_SUCCESS);
+
+}
+
+/**
+ * @} end of FC group
+ */
|