diff options
Diffstat (limited to 'hid-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c')
-rw-r--r-- | hid-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c | 120 |
1 files changed, 0 insertions, 120 deletions
diff --git a/hid-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c b/hid-dials/Drivers/CMSIS/NN/Source/SoftmaxFunctions/arm_softmax_q15.c deleted file mode 100644 index 22fa62b..0000000 --- a/hid-dials/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
- */
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