131 lines
4.5 KiB
C
131 lines
4.5 KiB
C
/*
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* Copyright (C) 2021-2022 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_convolve_wrapper_s16.c
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* Description: s16 convolution layer wrapper function with the main purpose to call the optimal kernel available in
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* cmsis-nn to perform the convolution.
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*
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* $Date: 13 January 2022
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* $Revision: V.1.2.0
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*
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* Target Processor: Cortex-M cores
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*
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* -------------------------------------------------------------------- */
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#include "arm_nnfunctions.h"
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/**
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* @ingroup groupNN
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*/
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/**
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* @addtogroup NNConv
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* @{
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*/
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/*
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* Convolution layer
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*
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* Refer header file for details.
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*
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*/
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arm_status arm_convolve_wrapper_s16(const cmsis_nn_context *ctx,
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const cmsis_nn_conv_params *conv_params,
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const cmsis_nn_per_channel_quant_params *quant_params,
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const cmsis_nn_dims *input_dims,
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const q15_t *input_data,
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const cmsis_nn_dims *filter_dims,
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const q7_t *filter_data,
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const cmsis_nn_dims *bias_dims,
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const int64_t *bias_data,
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const cmsis_nn_dims *output_dims,
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q15_t *output_data)
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{
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#if defined(ARM_MATH_DSP) && !defined(ARM_MATH_MVEI)
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if (filter_dims->w * filter_dims->h * input_dims->c < 512 &&
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(conv_params->dilation.w == 1 && conv_params->dilation.h == 1))
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{
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return arm_convolve_fast_s16(ctx,
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conv_params,
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quant_params,
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input_dims,
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input_data,
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filter_dims,
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filter_data,
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bias_dims,
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bias_data,
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output_dims,
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output_data);
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}
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else
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{
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return arm_convolve_s16(ctx,
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conv_params,
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quant_params,
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input_dims,
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input_data,
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filter_dims,
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filter_data,
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bias_dims,
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bias_data,
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output_dims,
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output_data);
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}
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#else
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return arm_convolve_s16(ctx,
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conv_params,
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quant_params,
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input_dims,
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input_data,
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filter_dims,
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filter_data,
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bias_dims,
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bias_data,
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output_dims,
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output_data);
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#endif
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}
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int32_t arm_convolve_wrapper_s16_get_buffer_size(const cmsis_nn_conv_params *conv_params,
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const cmsis_nn_dims *input_dims,
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const cmsis_nn_dims *filter_dims,
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const cmsis_nn_dims *output_dims)
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{
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(void)conv_params;
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(void)output_dims;
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#if defined(ARM_MATH_DSP) && !defined(ARM_MATH_MVEI)
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if (filter_dims->w * filter_dims->h * input_dims->c < 512 &&
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(conv_params->dilation.w == 1 && conv_params->dilation.h == 1))
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{
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return arm_convolve_fast_s16_get_buffer_size(input_dims, filter_dims);
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}
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return arm_convolve_s16_get_buffer_size(input_dims, filter_dims);
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#else
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return arm_convolve_s16_get_buffer_size(input_dims, filter_dims);
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#endif
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}
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/**
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* @} end of NNConv group
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*/
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