| /* |
| * Copyright (C) 2010-2018 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. |
| */ |
| |
| #include "ref_functions.h" |
| |
| void arm_convolve_HWC_q7_ref_nonsquare(const q7_t * Im_in, // input image |
| const uint16_t dim_im_in_x, // input image dimention x |
| const uint16_t dim_im_in_y, // input image dimention y |
| const uint16_t ch_im_in, // number of input image channels |
| const q7_t * wt, // kernel weights |
| const uint16_t ch_im_out, // number of filters, i.e., output image channels |
| const uint16_t dim_kernel_x, // filter kernel size x |
| const uint16_t dim_kernel_y, // filter kernel size y |
| const uint16_t padding_x, // padding sizes x |
| const uint16_t padding_y, // padding sizes y |
| const uint16_t stride_x, // stride x |
| const uint16_t stride_y, // stride y |
| const q7_t * bias, // bias |
| const uint16_t bias_shift, const uint16_t out_shift, q7_t * Im_out, // output image |
| const uint16_t dim_im_out_x, // output image dimension x |
| const uint16_t dim_im_out_y, // output image dimension y |
| q15_t * bufferA, //buffer space for input |
| q7_t * bufferB //buffer space for output |
| ) |
| { |
| int i, j, k, l, m, n; |
| int conv_out; |
| int in_row, in_col; |
| |
| for (i = 0; i < ch_im_out; i++) |
| { |
| for (j = 0; j < dim_im_out_y; j++) |
| { |
| for (k = 0; k < dim_im_out_x; k++) |
| { |
| #ifndef ARM_NN_TRUNCATE |
| conv_out = ((q31_t) (bias[i]) << bias_shift) + (0x1 << (out_shift - 1)); |
| #else |
| conv_out = bias[i] << bias_shift; |
| #endif |
| for (m = 0; m < dim_kernel_y; m++) |
| { |
| for (n = 0; n < dim_kernel_x; n++) |
| { |
| // if-for implementation |
| in_row = stride_y * j + m - padding_y; |
| in_col = stride_x * k + n - padding_x; |
| if (in_row >= 0 && in_col >= 0 && in_row < dim_im_in_y && in_col < dim_im_in_x) |
| { |
| for (l = 0; l < ch_im_in; l++) |
| { |
| conv_out += Im_in[(in_row * dim_im_in_x + in_col) * ch_im_in + l] * |
| wt[i * ch_im_in * dim_kernel_y * dim_kernel_x + (m * dim_kernel_x + n) * ch_im_in + |
| l]; |
| } |
| } |
| } |
| } |
| Im_out[i + (j * dim_im_out_x + k) * ch_im_out] = (q7_t) __SSAT((conv_out >> out_shift), 8); |
| } |
| } |
| } |
| } |