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be903e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// 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.
#ifndef LAYER_CONVOLUTION_MIPS_H
#define LAYER_CONVOLUTION_MIPS_H
#include "convolution.h"
namespace ncnn {
class Convolution_mips : virtual public Convolution
{
public:
Convolution_mips();
virtual int create_pipeline(const Option& opt);
virtual int destroy_pipeline(const Option& opt);
virtual int forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const;
virtual int forward(const std::vector<Mat>& bottom_blobs, std::vector<Mat>& top_blobs, const Option& opt) const;
protected:
#if NCNN_INT8
int create_pipeline_int8_mips(const Option& opt);
int forward_int8_mips(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const;
#endif
public:
Layer* activation;
Mat weight_data_tm;
Mat weight_sgemm_data;
Mat weight_winograd23_data;
Mat weight_winograd43_data;
Mat weight_winograd63_data;
#if NCNN_INT8
Mat scale_in_data;
#endif
};
} // namespace ncnn
#endif // LAYER_CONVOLUTION_MIPS_H
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