// 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. #include "lite/kernels/xpu/slice_compute.h" #include "lite/backends/xpu/xpu_header_sitter.h" #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace xpu { void SliceCompute::PrepareForRun() { auto& param = this->Param(); auto x_dims = param.X->dims(); x_shape_.reserve(x_dims.size()); x_dim_begin_.reserve(x_dims.size()); x_dim_end_.reserve(x_dims.size()); } void SliceCompute::Run() { auto& param = this->Param(); auto& ctx = this->ctx_->As(); auto x_dims = param.X->dims(); for (size_t i = 0; i < x_dims.size(); ++i) { x_shape_[i] = x_dims[i]; x_dim_begin_[i] = 0; x_dim_end_[i] = x_dims[i]; } for (size_t i = 0; i < param.axes.size(); ++i) { int axis = param.axes[i]; x_dim_begin_[axis] = param.starts[i]; x_dim_end_[axis] = param.ends[i]; } int ndim = param.X->dims().size(); int r = xdnn::slice_forward( ctx.GetRawContext(), /* context */ &x_shape_[0], /* shape */ &x_dim_begin_[0], /* starts */ &x_dim_end_[0], /* ends */ ndim, /* n */ param.X->data(), /* in */ param.Out->mutable_data(TARGET(kXPU)) /* out */); CHECK_EQ(r, 0); } } // namespace xpu } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL( slice, kXPU, kFloat, kNCHW, paddle::lite::kernels::xpu::SliceCompute, def) .BindInput("Input", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))}) .Finalize();