From 2628932a40d769d8d0180ba6fed1e7b9b2718982 Mon Sep 17 00:00:00 2001 From: jaseg Date: Sun, 3 May 2020 19:53:02 +0200 Subject: minkbd: repo restructure --- .../NN/Source/SoftmaxFunctions/arm_softmax_q15.c | 120 -------------------- .../NN/Source/SoftmaxFunctions/arm_softmax_q7.c | 121 --------------------- 2 files changed, 241 deletions(-) delete mode 100644 Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c delete mode 100644 Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c (limited to 'Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions') diff --git a/Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c b/Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c deleted file mode 100644 index 22fa62b..0000000 --- a/Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c +++ /dev/null @@ -1,120 +0,0 @@ -/* - * 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_softmax_q15.c - * Description: Q15 softmax function - * - * $Date: 20. February 2018 - * $Revision: V.1.0.0 - * - * Target Processor: Cortex-M cores - * - * -------------------------------------------------------------------- */ - -#include "arm_math.h" -#include "arm_nnfunctions.h" - -/** - * @ingroup groupNN - */ - -/** - * @addtogroup Softmax - * @{ - */ - - /** - * @brief Q15 softmax function - * @param[in] vec_in pointer to input vector - * @param[in] dim_vec input vector dimention - * @param[out] p_out pointer to output vector - * @return none. - * - * @details - * - * Here, instead of typical e based softmax, we use - * 2-based softmax, i.e.,: - * - * y_i = 2^(x_i) / sum(2^x_j) - * - * The relative output will be different here. - * But mathematically, the gradient will be the same - * with a log(2) scaling factor. - * - */ - -void arm_softmax_q15(const q15_t * vec_in, const uint16_t dim_vec, q15_t * p_out) -{ - q31_t sum; - int16_t i; - uint8_t shift; - q31_t base; - base = -1 * 0x100000; - for (i = 0; i < dim_vec; i++) - { - if (vec_in[i] > base) - { - base = vec_in[i]; - } - } - - /* we ignore really small values - * anyway, they will be 0 after shrinking - * to q15_t - */ - base = base - 16; - - sum = 0; - - for (i = 0; i < dim_vec; i++) - { - if (vec_in[i] > base) - { - shift = (uint8_t)__USAT(vec_in[i] - base, 5); - sum += 0x1 << shift; - } - } - - /* This is effectively (0x1 << 32) / sum */ - int64_t div_base = 0x100000000LL; - int output_base = (int32_t)(div_base / sum); - - /* Final confidence will be output_base >> ( 17 - (vec_in[i] - base) ) - * so 32768 (0x1<<15) -> 100% confidence when sum = 0x1 << 16, output_base = 0x1 << 16 - * and vec_in[i]-base = 16 - */ - for (i = 0; i < dim_vec; i++) - { - if (vec_in[i] > base) - { - /* Here minimum value of 17+base-vec[i] will be 1 */ - shift = (uint8_t)__USAT(17+base-vec_in[i], 5); - p_out[i] = (q15_t) __SSAT((output_base >> shift), 16); - } else - { - p_out[i] = 0; - } - } - -} - -/** - * @} end of Softmax group - */ diff --git a/Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c b/Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c deleted file mode 100644 index 06a69e1..0000000 --- a/Blink/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c +++ /dev/null @@ -1,121 +0,0 @@ -/* - * 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_softmax_q7.c - * Description: Q7 softmax function - * - * $Date: 20. February 2018 - * $Revision: V.1.0.0 - * - * Target Processor: Cortex-M cores - * - * -------------------------------------------------------------------- */ - -#include "arm_math.h" -#include "arm_nnfunctions.h" - -/** - * @ingroup groupNN - */ - -/** - * @addtogroup Softmax - * @{ - */ - - /** - * @brief Q7 softmax function - * @param[in] vec_in pointer to input vector - * @param[in] dim_vec input vector dimention - * @param[out] p_out pointer to output vector - * @return none. - * - * @details - * - * Here, instead of typical natural logarithm e based softmax, we use - * 2-based softmax here, i.e.,: - * - * y_i = 2^(x_i) / sum(2^x_j) - * - * The relative output will be different here. - * But mathematically, the gradient will be the same - * with a log(2) scaling factor. - * - */ - -void arm_softmax_q7(const q7_t * vec_in, const uint16_t dim_vec, q7_t * p_out) -{ - q31_t sum; - int16_t i; - uint8_t shift; - q15_t base; - base = -257; - - /* We first search for the maximum */ - for (i = 0; i < dim_vec; i++) - { - if (vec_in[i] > base) - { - base = vec_in[i]; - } - } - - /* - * So the base is set to max-8, meaning - * that we ignore really small values. - * anyway, they will be 0 after shrinking to q7_t. - */ - base = base - 8; - - sum = 0; - - for (i = 0; i < dim_vec; i++) - { - if (vec_in[i] > base) - { - shift = (uint8_t)__USAT(vec_in[i] - base, 5); - sum += 0x1 << shift; - } - } - - /* This is effectively (0x1 << 20) / sum */ - int output_base = 0x100000 / sum; - - /* - * Final confidence will be output_base >> ( 13 - (vec_in[i] - base) ) - * so 128 (0x1<<7) -> 100% confidence when sum = 0x1 << 8, output_base = 0x1 << 12 - * and vec_in[i]-base = 8 - */ - for (i = 0; i < dim_vec; i++) - { - if (vec_in[i] > base) - { - /* Here minimum value of 13+base-vec_in[i] will be 5 */ - shift = (uint8_t)__USAT(13+base-vec_in[i], 5); - p_out[i] = (q7_t) __SSAT((output_base >> shift), 8); - } else { - p_out[i] = 0; - } - } -} - -/** - * @} end of Softmax group - */ -- cgit