From 86608c6770cf08c138a2bdab5855072f64be09ef Mon Sep 17 00:00:00 2001 From: joshua Date: Sat, 30 Dec 2023 23:54:31 -0500 Subject: initial commit --- .../NN/Source/SoftmaxFunctions/arm_softmax_q15.c | 120 ++++++++++++++++++++ .../NN/Source/SoftmaxFunctions/arm_softmax_q7.c | 121 +++++++++++++++++++++ 2 files changed, 241 insertions(+) create mode 100644 Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c create mode 100644 Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c (limited to 'Drivers/CMSIS/NN/Source/SoftmaxFunctions') diff --git a/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c b/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c new file mode 100644 index 0000000..22fa62b --- /dev/null +++ b/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c @@ -0,0 +1,120 @@ +/* + * 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/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c b/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c new file mode 100644 index 0000000..06a69e1 --- /dev/null +++ b/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q7.c @@ -0,0 +1,121 @@ +/* + * 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 v1.2.3