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/*
* 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_depthwise_separable_conv_HWC_q7_ref(const q7_t * Im_in, // input image
const uint16_t dim_im_in, // input image dimention
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, // filter kernel size
const uint16_t padding, // padding sizes
const uint16_t stride, // stride
const q7_t * bias, // bias
const uint16_t bias_shift, // amount of left-shift for bias
const uint16_t out_shift, // amount of right-shift for output
q7_t * Im_out, // output image
const uint16_t dim_im_out, // output image dimension
q15_t * bufferA, //buffer space for input
q7_t * bufferB //buffer space for output
)
{
int i_out_y, i_out_x, i_ch_out;
int i_ker_y, i_ker_x;
for (i_out_y = 0; i_out_y < dim_im_out; i_out_y++)
{
for (i_out_x = 0; i_out_x < dim_im_out; i_out_x++)
{
for (i_ch_out = 0; i_ch_out < ch_im_out; i_ch_out++)
{
// for each output
#ifndef ARM_NN_TRUNCATE
int conv_out = (bias[i_ch_out] << bias_shift) + (0x1 << (out_shift - 1));
#else
int conv_out = bias[i_ch_out] << bias_shift;
#endif
for (i_ker_y = 0; i_ker_y < dim_kernel; i_ker_y++)
{
for (i_ker_x = 0; i_ker_x < dim_kernel; i_ker_x++)
{
int in_row = stride * i_out_y + i_ker_y - padding;
int in_col = stride * i_out_x + i_ker_x - padding;
if (in_row >= 0 && in_col >= 0 && in_row < dim_im_in && in_col < dim_im_in)
{
conv_out += Im_in[(in_row * dim_im_in + in_col) * ch_im_in + i_ch_out] *
wt[(i_ker_y * dim_kernel + i_ker_x) * ch_im_out + i_ch_out];
}
}
}
Im_out[(i_out_y * dim_im_out + i_out_x) * ch_im_out + i_ch_out] =
(q7_t) __SSAT((conv_out >> out_shift), 8);
}
}
}
}
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