/* * SPDX-FileCopyrightText: Copyright 2023-2024 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_convolve_get_buffer_sizes_s8.c * Description: Collection of get buffer size functions for the various s8 convolution layer functions. * * $Date: 27 February 2024 * $Revision: V.2.0.1 * * Target : Arm(R) M-Profile Architecture * * -------------------------------------------------------------------- */ #include "Internal/arm_nn_compiler.h" #include "arm_nnfunctions.h" #include "arm_nnsupportfunctions.h" /** * @ingroup NNConv */ /** * @addtogroup GetBufferSizeNNConv * @{ */ __STATIC_INLINE int32_t arm_convolve_s8_get_buffer_size_mve(const cmsis_nn_dims *input_dims, const cmsis_nn_dims *filter_dims) { int32_t col_length = input_dims->c * filter_dims->w * filter_dims->h; // Get number of complete int16 lanes(multiple of 8) for given col_length. This is dependent on // implementation of arm_nn_mat_mult_nt_t_s8 col_length = (col_length + 7) / 8; // 4 -> number of im2col buffers, 8 -> 8 elements per Q register return 4 * col_length * 8 * (int32_t)sizeof(int8_t); } __STATIC_INLINE int32_t arm_convolve_1_x_n_s8_get_buffer_size_mve(const cmsis_nn_conv_params *conv_params, const cmsis_nn_dims *input_dims, const cmsis_nn_dims *filter_dims, const cmsis_nn_dims *output_dims) { const int32_t input_x = input_dims->w; const int32_t pad_x = conv_params->padding.w; const int32_t kernel_x = filter_dims->w; const int32_t output_x = output_dims->w; const int32_t stride_x = conv_params->stride.w; const int32_t total_pad = ((output_x - 1) * stride_x + kernel_x - input_x); const int32_t asym_pad = total_pad % 2; const int32_t right_pad_num = pad_x + asym_pad != 0 ? MAX(1, (pad_x + asym_pad + stride_x - 1) / stride_x) : 0; const int32_t left_pad_num = pad_x != 0 ? MAX(1, (pad_x + stride_x - 1) / stride_x) : 0; const int32_t no_pad_num = MAX(output_x - (right_pad_num + left_pad_num), 0); if (right_pad_num + no_pad_num + left_pad_num != output_x) { return arm_convolve_s8_get_buffer_size_mve(input_dims, filter_dims); } return 0; } int32_t arm_convolve_s8_get_buffer_size(const cmsis_nn_dims *input_dims, const cmsis_nn_dims *filter_dims) { #if defined(ARM_MATH_MVEI) return arm_convolve_s8_get_buffer_size_mve(input_dims, filter_dims); #else const int32_t rhs_cols = filter_dims->w * filter_dims->h * input_dims->c; const int32_t remainder = rhs_cols % 4; const int32_t aligned_rhs_cols = remainder != 0 ? rhs_cols + 4 - remainder : rhs_cols; return (2 * aligned_rhs_cols) * (int32_t)sizeof(int16_t); #endif } int32_t arm_convolve_1_x_n_s8_get_buffer_size(const cmsis_nn_conv_params *conv_params, const cmsis_nn_dims *input_dims, const cmsis_nn_dims *filter_dims, const cmsis_nn_dims *output_dims) { #if !defined(ARM_MATH_MVEI) (void)conv_params; (void)output_dims; return arm_convolve_s8_get_buffer_size(input_dims, filter_dims); #else return arm_convolve_1_x_n_s8_get_buffer_size_mve(conv_params, input_dims, filter_dims, output_dims); #endif } int32_t arm_convolve_1x1_s8_fast_get_buffer_size(const cmsis_nn_dims *input_dims) { (void)input_dims; return 0; } /* * Get the required buffer size for arm_convolve_wrapper_s8. This is the recommended function convolve wrapper s8 * function. * * Refer to header file for details. * */ int32_t arm_convolve_wrapper_s8_get_buffer_size(const cmsis_nn_conv_params *conv_params, const cmsis_nn_dims *input_dims, const cmsis_nn_dims *filter_dims, const cmsis_nn_dims *output_dims) { #if defined(ARM_MATH_MVEI) return arm_convolve_wrapper_s8_get_buffer_size_mve(conv_params, input_dims, filter_dims, output_dims); #else (void)output_dims; if ((conv_params->padding.w == 0) && (conv_params->padding.h == 0) && (filter_dims->w == 1) && (filter_dims->h == 1) && (conv_params->dilation.w == 1 && conv_params->dilation.h == 1)) { if ((conv_params->stride.w == 1) && (conv_params->stride.h == 1)) { return arm_convolve_1x1_s8_fast_get_buffer_size(input_dims); } else { return 0; } } else if ((input_dims->h == 1) && (conv_params->dilation.w == 1) && (filter_dims->h == 1) && (conv_params->stride.w * input_dims->c % 4 == 0)) { return arm_convolve_1_x_n_s8_get_buffer_size(conv_params, input_dims, filter_dims, output_dims); } else { return arm_convolve_s8_get_buffer_size(input_dims, filter_dims); } #endif } int32_t arm_convolve_wrapper_s8_get_buffer_size_mve(const cmsis_nn_conv_params *conv_params, const cmsis_nn_dims *input_dims, const cmsis_nn_dims *filter_dims, const cmsis_nn_dims *output_dims) { (void)output_dims; if ((conv_params->padding.w == 0) && (conv_params->padding.h == 0) && (filter_dims->w == 1) && (filter_dims->h == 1) && (conv_params->dilation.w == 1 && conv_params->dilation.h == 1)) { if ((conv_params->stride.w == 1) && (conv_params->stride.h == 1)) { return arm_convolve_1x1_s8_fast_get_buffer_size(input_dims); } else { return 0; } } else if ((input_dims->h == 1) && (conv_params->dilation.w == 1) && (filter_dims->h == 1) && (conv_params->stride.w * input_dims->c % 4 == 0)) { return arm_convolve_1_x_n_s8_get_buffer_size_mve(conv_params, input_dims, filter_dims, output_dims); } else { return arm_convolve_s8_get_buffer_size_mve(input_dims, filter_dims); } } int32_t arm_convolve_wrapper_s8_get_buffer_size_dsp(const cmsis_nn_conv_params *conv_params, const cmsis_nn_dims *input_dims, const cmsis_nn_dims *filter_dims, const cmsis_nn_dims *output_dims) { return arm_convolve_wrapper_s8_get_buffer_size(conv_params, input_dims, filter_dims, output_dims); } /** * @} end of GetBufferSizeNNConv group */