/* * Copyright (C) 2010-2020 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_depthwise_conv_wrapper_s8.c * Description: Wrapper API to select appropriate depthwise conv API based * on dimensions. * * $Date: May 29, 2020 * $Revision: V.1.0.1 * * Target Processor: Cortex-M CPUs * * -------------------------------------------------------------------- */ #include "cmsis/CMSIS/DSP/Include/arm_math.h" #include "cmsis/CMSIS/NN/Include/arm_nnfunctions.h" #include "cmsis/CMSIS/NN/Include/arm_nnsupportfunctions.h" /** * @ingroup groupNN */ /** * @addtogroup NNConv * @{ */ /* * s8 Depthwise conv wrapper function * * Refer header file for details. * */ arm_status arm_depthwise_conv_wrapper_s8(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 q7_t *input, const cmsis_nn_dims *filter_dims, const q7_t *filter, const cmsis_nn_dims *bias_dims, const int32_t *bias, const cmsis_nn_dims *output_dims, q7_t *output) { arm_status status = ARM_MATH_SUCCESS; if (1 == dw_conv_params->ch_mult) { #if !defined(ARM_MATH_MVEI) if ((filter_dims->w == 3) && (filter_dims->h == 3) && (dw_conv_params->padding.h <= 1)) { status = arm_depthwise_conv_3x3_s8(ctx, dw_conv_params, quant_params, input_dims, input, filter_dims, filter, bias_dims, bias, output_dims, output); } else #endif { status = arm_depthwise_conv_s8_opt(ctx, dw_conv_params, quant_params, input_dims, input, filter_dims, filter, bias_dims, bias, output_dims, output); } } else { status = arm_depthwise_conv_s8(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_s8_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; int32_t size = 0; if (input_dims->c == output_dims->c) { size = arm_depthwise_conv_s8_opt_get_buffer_size(input_dims, filter_dims); } return size; } /** * @} end of NNConv group */