// Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2017 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_CONVOLUTIONDEPTHWISE_X86_H
#define LAYER_CONVOLUTIONDEPTHWISE_X86_H

#include "convolutiondepthwise.h"

namespace ncnn {

class ConvolutionDepthWise_x86 : virtual public ConvolutionDepthWise
{
public:
    ConvolutionDepthWise_x86();

    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;

protected:
    int create_group_ops(const Option& opt);
#if NCNN_INT8
    int create_pipeline_int8_x86(const Option& opt);
    int forward_int8_x86(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const;
#endif

public:
    Layer* activation;
    std::vector<ncnn::Layer*> group_ops;

    // packing
    Mat weight_data_packed;

#if NCNN_INT8
    // int8
    Mat weight_data_int8;
#endif
};

} // namespace ncnn

#endif // LAYER_CONVOLUTIONDEPTHWISE_X86_H
