255 lines
8.6 KiB
C
255 lines
8.6 KiB
C
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/*
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* Copyright (C) 2010-2021 Arm Limited or its affiliates. All rights reserved.
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*
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the License); you may
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* not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an AS IS BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/* ----------------------------------------------------------------------
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* Project: CMSIS NN Library
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* Title: arm_svdf_s8.c
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* Description: S8 basic SVDF layer function
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*
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* $Date: 15. April 2021
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* $Revision: V.1.5.0
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*
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* Target Processor: Cortex-M processors
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*
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* -------------------------------------------------------------------- */
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#include "arm_nnfunctions.h"
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#include "arm_nnsupportfunctions.h"
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/**
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* @ingroup groupNN
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*/
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/**
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* @addtogroup SVDF
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* @{
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*/
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/*
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* S8 SVDF layer function for TensorFlow Lite
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*
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* Refer to header file for details.
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*
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*/
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arm_status arm_svdf_s8(const cmsis_nn_context *input_ctx,
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const cmsis_nn_context *output_ctx,
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const cmsis_nn_svdf_params *svdf_params,
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const cmsis_nn_per_tensor_quant_params *input_quant_params,
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const cmsis_nn_per_tensor_quant_params *output_quant_params,
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const cmsis_nn_dims *input_dims,
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const q7_t *input_data,
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const cmsis_nn_dims *state_dims,
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q15_t *state_data,
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const cmsis_nn_dims *weights_feature_dims,
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const q7_t *weights_feature_data,
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const cmsis_nn_dims *weights_time_dims,
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const q15_t *weights_time_data,
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const cmsis_nn_dims *bias_dims,
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const q31_t *bias_data,
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const cmsis_nn_dims *output_dims,
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q7_t *output_data)
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{
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(void)bias_dims;
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(void)state_dims;
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(void)output_dims;
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const q31_t multiplier_in = input_quant_params->multiplier;
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const q31_t shift_in = input_quant_params->shift;
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const q31_t multiplier_out = output_quant_params->multiplier;
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const q31_t shift_2 = output_quant_params->shift;
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const int32_t zp_in = svdf_params->input_offset;
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const int32_t zp_out = svdf_params->output_offset;
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const int32_t in_activation_min = svdf_params->input_activation.min;
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const int32_t in_activation_max = svdf_params->input_activation.max;
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const int32_t out_activation_min = svdf_params->output_activation.min;
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const int32_t out_activation_max = svdf_params->output_activation.max;
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const int16_t rank = svdf_params->rank;
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const int32_t input_batches = input_dims->n;
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const int32_t input_height = input_dims->h;
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const int32_t feature_batches = weights_feature_dims->n;
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const int32_t time_batches = weights_time_dims->h;
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const int32_t unit_count = feature_batches / rank;
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q31_t *buffer_a = (q31_t *)input_ctx->buf;
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q31_t *buffer_b = (q31_t *)output_ctx->buf;
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memmove((q15_t *)state_data,
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(q15_t *)state_data + 1,
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(size_t)(input_batches * feature_batches * time_batches * (int32_t)sizeof(int16_t)));
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for (int i_batch = 0; i_batch < input_batches; i_batch++)
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{
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q15_t *res_ptr = state_data + (time_batches * i_batch * feature_batches) + (time_batches - 1);
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const q7_t *weight = weights_feature_data;
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const q7_t *input = input_data + i_batch * input_height;
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arm_status res = arm_nn_vec_mat_mult_t_svdf_s8(input,
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weight,
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res_ptr,
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-zp_in,
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0,
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time_batches,
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multiplier_in,
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shift_in,
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input_height,
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feature_batches,
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in_activation_min,
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in_activation_max);
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if (res != ARM_MATH_SUCCESS)
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{
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return res;
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}
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}
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{
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q31_t *ptr_a = buffer_a;
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const q15_t *v2 = state_data;
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for (int i_batch = 0; i_batch < input_batches; i_batch++)
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{
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const q15_t *v1 = weights_time_data;
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for (int i_feature_batch = 0; i_feature_batch < feature_batches; i_feature_batch++)
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{
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*ptr_a = 0;
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int32_t sum = 0;
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#if defined(ARM_MATH_DSP) && !defined(ARM_MATH_MVEI)
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int j = 0;
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int32_t block_count = time_batches >> 1;
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for (int i = 0; i < block_count; i++)
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{
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j += 2;
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q31_t r1 = arm_nn_read_q15x2_ia(&v1);
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q31_t r2 = arm_nn_read_q15x2_ia(&v2);
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sum = __SMLAD(r1, r2, sum);
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}
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// Process the remaining data
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for (; j < time_batches; j++)
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{
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sum += *v1 * *v2;
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v1++;
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v2++;
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}
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#else
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for (int j = 0; j < time_batches; j++)
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{
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sum += *v1 * *v2;
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v1++;
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v2++;
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}
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#endif
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*ptr_a = sum;
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ptr_a++;
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}
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}
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}
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if (bias_data)
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{
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if (unit_count == feature_batches)
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{
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for (int i = 0; i < input_batches; i++)
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{
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q31_t *output_temp = buffer_b + i * feature_batches;
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const q31_t *ptr_a = buffer_a + i * feature_batches;
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const int32_t *bi = bias_data;
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for (int j = 0; j < feature_batches; j++)
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{
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output_temp[j] = ptr_a[j] + bi[j];
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}
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}
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}
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else
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{
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for (int i_batch = 0; i_batch < input_batches; i_batch++)
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{
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q31_t *output_data_temp = buffer_b + i_batch * unit_count;
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q31_t *ptr_a = buffer_a + i_batch * feature_batches;
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for (int i = 0; i < unit_count; i++)
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{
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int32_t sum = bias_data[i];
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for (int j = 0; j < rank; j++)
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{
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sum += *ptr_a;
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ptr_a++;
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}
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output_data_temp[i] = sum;
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}
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}
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}
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}
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else
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{
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for (int i_batch = 0; i_batch < input_batches; i_batch++)
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{
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q31_t *output_data_temp = buffer_b + i_batch * unit_count;
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q31_t *ptr_a = buffer_a + i_batch * feature_batches;
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for (int i = 0; i < unit_count; i++)
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{
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int32_t sum = 0;
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for (int j = 0; j < rank; j++)
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{
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sum += *ptr_a;
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ptr_a++;
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}
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output_data_temp[i] = sum;
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}
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}
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}
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#if defined(ARM_MATH_MVEI)
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int32_t num_elements = input_batches * unit_count;
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const int32_t loop_count = (num_elements + 3) / 4;
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for (int i_op = 0; i_op < loop_count; i_op++)
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{
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mve_pred16_t p = vctp32q((uint32_t)num_elements);
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int32x4_t op = vldrwq_z_s32(buffer_b, p);
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op = arm_requantize_mve(op, multiplier_out, shift_2);
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op = vaddq_n_s32(op, zp_out);
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const int32x4_t min_vec = vdupq_n_s32((int8_t)out_activation_min);
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const int32x4_t max_vec = vdupq_n_s32((int8_t)out_activation_max);
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op = vmaxq_s32(op, min_vec);
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op = vminq_s32(op, max_vec);
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vstrbq_p_s32(output_data, op, p);
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output_data += 4;
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buffer_b += 4;
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num_elements -= 4;
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}
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#else
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for (int i = 0; i < input_batches * unit_count; i++)
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{
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output_data[i] = (q7_t)CLAMP(
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arm_nn_requantize(buffer_b[i], multiplier_out, shift_2) + zp_out, out_activation_max, out_activation_min);
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}
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#endif
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return (ARM_MATH_SUCCESS);
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}
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/**
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* @} end of SVDF group
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*/
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