// 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 "lite/core/kernel.h" #include "lite/core/op_lite.h" #include "lite/core/op_registry.h" #include "lite/core/type_system.h" #include "lite/operators/squeeze_op.h" namespace paddle { namespace lite { namespace kernels { namespace x86 { template class SqueezeCompute : public KernelLite { public: using param_t = operators::SqueezeParam; void Run() override { auto& param = *param_.get_mutable(); auto x = param.X; auto output = param.Out; auto x_dims = x->dims(); auto* x_data = x->data(); auto* out_data = output->mutable_data(); memcpy(out_data, x_data, x_dims.production() * sizeof(T)); } virtual ~SqueezeCompute() = default; }; template class Squeeze2Compute : public KernelLite { public: using param_t = operators::SqueezeParam; void Run() override { auto& param = *param_.get_mutable(); auto x = param.X; auto output = param.Out; auto xshape = param.XShape; auto x_dims = x->dims(); auto* x_data = x->data(); auto* out_data = output->mutable_data(); auto* xshape_data = xshape->mutable_data(); memcpy(out_data, x_data, x_dims.production() * sizeof(T)); memcpy(xshape_data, x_data, x_dims.production() * sizeof(T)); } virtual ~Squeeze2Compute() = default; }; } // namespace x86 } // namespace kernels } // namespace lite } // namespace paddle