// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. // // 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 // // http://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. #pragma once #include #include #include "lite/backends/arm/math/conv_impl.h" #include "lite/core/context.h" #include "lite/core/kernel.h" #include "lite/core/target_wrapper.h" namespace paddle { namespace lite { namespace kernels { namespace arm { template class DepthwiseConv : public KernelLite { public: typedef void (*conv_dw_impl)(const void* din, void* dout, int num, int ch_out, int h_out, int w_out, int ch_in, int h_in, int w_in, const void* weights, const float* bias, const operators::ConvParam& param, ARMContext* ctx, const float* scale); DepthwiseConv() = default; ~DepthwiseConv() {} virtual void PrepareForRun(); virtual void Run(); private: using param_t = operators::ConvParam; Tensor weights_; Tensor bias_; bool flag_trans_weights_{false}; bool flag_trans_bias_{false}; conv_dw_impl impl_{nullptr}; std::vector w_scale_; }; } // namespace arm } // namespace kernels } // namespace lite } // namespace paddle