/* * SPDX-FileCopyrightText: Copyright 2024 Arm Limited and/or its affiliates * * 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_transpose_conv_wrapper_s8.c * Description: Wrapper API to select appropriate transpose conv API based * on dimensions. * * $Date: 16 October 2024 * $Revision: V.1.0.0 * * Target : Arm(R) M-Profile Architecture * * -------------------------------------------------------------------- */ #include "arm_nnfunctions.h" #include "arm_nnsupportfunctions.h" /** * @ingroup Public */ /** * @addtogroup NNConv * @{ */ /* * s8 Transpose conv wrapper function * * Refer header file for details. * */ arm_cmsis_nn_status arm_transpose_conv_wrapper_s8(const cmsis_nn_context *ctx, const cmsis_nn_context *reverse_conv_ctx, const cmsis_nn_transpose_conv_params *transpose_conv_params, const cmsis_nn_per_channel_quant_params *quant_params, const cmsis_nn_dims *input_dims, const int8_t *input_data, const cmsis_nn_dims *filter_dims, const int8_t *filter_data, const cmsis_nn_dims *bias_dims, const int32_t *bias_data, const cmsis_nn_dims *output_dims, int8_t *output_data) { if (ctx->buf == NULL) { return ARM_CMSIS_NN_ARG_ERROR; } const bool reverse_conv_possible = ((transpose_conv_params->stride.w <= 2) && (transpose_conv_params->stride.h <= 2)); const bool reverse_conv_efficient = (input_dims->c > REVERSE_TCOL_EFFICIENT_THRESHOLD); if (reverse_conv_possible && reverse_conv_efficient) { if (reverse_conv_ctx->buf == NULL) { return ARM_CMSIS_NN_ARG_ERROR; } const int32_t stride_w = transpose_conv_params->stride.w; const int32_t stride_h = transpose_conv_params->stride.h; const int32_t filter_h = filter_dims->h; const int32_t filter_w = filter_dims->w; const int32_t output_c = output_dims->c; const int32_t input_n = input_dims->n; const int32_t input_h = input_dims->h; const int32_t input_w = input_dims->w; const int32_t input_c = input_dims->c; const int32_t padding_w = transpose_conv_params->padding.w; const int32_t padding_h = transpose_conv_params->padding.h; cmsis_nn_conv_params conv_params; conv_params.padding.h = filter_h - 1 - padding_h; conv_params.padding.w = filter_w - 1 - padding_w; conv_params.input_offset = transpose_conv_params->input_offset; conv_params.output_offset = transpose_conv_params->output_offset; conv_params.stride.h = 1; conv_params.stride.w = 1; conv_params.dilation.h = 1; conv_params.dilation.w = 1; conv_params.activation = transpose_conv_params->activation; const cmsis_nn_dims transposed_input_dims = {input_n, input_h * stride_h, input_w * stride_w, input_c}; const cmsis_nn_dims upscale_dims = {0, stride_h, stride_w, 0}; // Reverse filter in x and y-dimensions int8_t *reversed_filter = reverse_conv_ctx->buf; const int8_t *in_ptr = filter_data; int8_t *out_ptr = reversed_filter; const int32_t filter_size = filter_h * filter_w * input_c; out_ptr += filter_size; for (int32_t i = 0; i < output_c; i++) { for (int32_t y = 0; y < filter_h; y++) { for (int32_t x = 0; x < filter_w; x++) { out_ptr -= input_c; arm_memcpy_s8(out_ptr, in_ptr, input_c * sizeof(int8_t)); in_ptr += input_c; } } out_ptr += 2 * filter_size; } return arm_convolve_s8(ctx, &conv_params, quant_params, &transposed_input_dims, input_data, filter_dims, reversed_filter, bias_dims, bias_data, &upscale_dims, output_dims, output_data); } else { return arm_transpose_conv_s8(ctx, reverse_conv_ctx, transpose_conv_params, quant_params, input_dims, input_data, filter_dims, filter_data, bias_dims, bias_data, output_dims, output_data); } } /** * @} end of NNconv group */