edge-impulse-sdk/CMSIS/NN/Source/ConvolutionFunctions/arm_depthwise_conv_wrapper_s16.c

#include "edge-impulse-sdk/classifier/ei_classifier_config.h"
#if EI_CLASSIFIER_TFLITE_LOAD_CMSIS_NN_SOURCES
/*
 * SPDX-FileCopyrightText: Copyright 2010-2022 Arm Limited and/or its affiliates <open-source-office@arm.com>
 *
 * 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_depthwise_conv_wrapper_s16.c
 * Description:  Wrapper API to select appropriate depthwise conv API based
 *               on dimensions.
 *
 * $Date:        6 July 2022
 * $Revision:    V.1.0.1
 *
 * Target Processor:  Cortex-M CPUs
 *
 * -------------------------------------------------------------------- */

#include "edge-impulse-sdk/CMSIS/NN/Include/arm_nnfunctions.h"

/**
 *  @ingroup groupNN
 */

/**
 * @addtogroup NNConv
 * @{
 */

#define USE_FAST_DW_CONV_FUNCTION(dw_conv_params, filter_dims, input_dims)                                             \
    (dw_conv_params->ch_mult == 1 && dw_conv_params->dilation.w == 1 && dw_conv_params->dilation.h == 1 &&             \
     filter_dims->w * filter_dims->h * input_dims->c < 512)

/*
 *  s16 Depthwise conv wrapper function
 *
 *  Refer header file for details.
 *
 */
arm_cmsis_nn_status arm_depthwise_conv_wrapper_s16(const cmsis_nn_context *ctx,
                                                   const cmsis_nn_dw_conv_params *dw_conv_params,
                                                   const cmsis_nn_per_channel_quant_params *quant_params,
                                                   const cmsis_nn_dims *input_dims,
                                                   const q15_t *input,
                                                   const cmsis_nn_dims *filter_dims,
                                                   const q7_t *filter,
                                                   const cmsis_nn_dims *bias_dims,
                                                   const int64_t *bias,
                                                   const cmsis_nn_dims *output_dims,
                                                   q15_t *output)
{
    arm_cmsis_nn_status status = ARM_CMSIS_NN_SUCCESS;

    if (USE_FAST_DW_CONV_FUNCTION(dw_conv_params, filter_dims, input_dims))
    {
        status = arm_depthwise_conv_fast_s16(ctx,
                                             dw_conv_params,
                                             quant_params,
                                             input_dims,
                                             input,
                                             filter_dims,
                                             filter,
                                             bias_dims,
                                             bias,
                                             output_dims,
                                             output);
    }
    else
    {
        status = arm_depthwise_conv_s16(ctx,
                                        dw_conv_params,
                                        quant_params,
                                        input_dims,
                                        input,
                                        filter_dims,
                                        filter,
                                        bias_dims,
                                        bias,
                                        output_dims,
                                        output);
    }

    /* Return to application */
    return status;
}

int32_t arm_depthwise_conv_wrapper_s16_get_buffer_size(const cmsis_nn_dw_conv_params *dw_conv_params,
                                                       const cmsis_nn_dims *input_dims,
                                                       const cmsis_nn_dims *filter_dims,
                                                       const cmsis_nn_dims *output_dims)
{
    (void)dw_conv_params;
    (void)input_dims;
    (void)filter_dims;
    (void)output_dims;
    int32_t size = 0;

    if (USE_FAST_DW_CONV_FUNCTION(dw_conv_params, filter_dims, input_dims))
    {
        size = arm_depthwise_conv_fast_s16_get_buffer_size(input_dims, filter_dims);
    }

    return size;
}

/**
 * @} end of NNConv group
 */

#endif // EI_CLASSIFIER_TFLITE_LOAD_CMSIS_NN_SOURCES