/* Copyright (c) 2022 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 "paddle/phi/api/lib/api_gen_utils.h" namespace paddle { namespace experimental { /* ------------------ for input ----------------------- */ std::shared_ptr TensorToDenseTensor(const Tensor& tensor) { return std::dynamic_pointer_cast(tensor.impl()); } std::shared_ptr TensorToDenseTensor( const paddle::optional& tensor) { if (tensor) { return std::dynamic_pointer_cast(tensor->impl()); } return nullptr; } std::unique_ptr> TensorToDenseTensor( const std::vector& tensors) { auto pt_tensors = std::make_unique>(); pt_tensors->reserve(tensors.size()); for (const auto& t : tensors) { pt_tensors->push_back( *std::dynamic_pointer_cast(t.impl())); } return std::move(pt_tensors); } std::shared_ptr TensorToSelectedRows(const Tensor& tensor) { return std::dynamic_pointer_cast(tensor.impl()); } std::shared_ptr TensorToSelectedRows( const paddle::optional& tensor) { if (tensor) { return std::dynamic_pointer_cast(tensor->impl()); } return nullptr; } /* ----------------- for infer_meta --------------------- */ phi::MetaTensor MakeMetaTensor(const phi::DenseTensor& tensor) { return phi::MetaTensor(tensor); } paddle::optional MakeMetaTensor( const paddle::optional& tensor) { if (tensor) { return {phi::MetaTensor(*tensor)}; } return {paddle::none}; } std::vector MakeMetaTensor( const std::vector& tensors) { std::vector meta_tensors; meta_tensors.reserve(tensors.size()); for (const auto& t : tensors) { meta_tensors.emplace_back(t); } return meta_tensors; } phi::MetaTensor MakeMetaTensor(const phi::SelectedRows& tensor) { return phi::MetaTensor(tensor); } paddle::optional MakeMetaTensor( const paddle::optional& tensor) { if (tensor) { return {phi::MetaTensor(*tensor)}; } return {paddle::none}; } /* ------------------ for output ----------------------- */ phi::DenseTensor* SetKernelOutput(Backend backend, Tensor* out) { if (!out->initialized()) { auto dense_tensor = std::make_shared( phi::make_intrusive(phi::TransToPhiPlace(backend)), phi::DenseTensorMeta()); out->set_impl(dense_tensor); return dense_tensor.get(); } return static_cast(out->impl().get()); } std::vector SetKernelOutput(size_t out_size, Backend backend, std::vector* out) { out->reserve(out_size); std::vector results(out_size); for (size_t i = 0; i < out_size; ++i) { auto tensor_ptr = std::make_shared( phi::make_intrusive(phi::TransToPhiPlace(backend)), phi::DenseTensorMeta()); results[i] = tensor_ptr.get(); out->emplace_back(); out->back().set_impl(tensor_ptr); } return results; } phi::SelectedRows* SetSelectedRowsKernelOutput(Backend backend, Tensor* out) { if (!out->initialized()) { auto select_rows = std::make_shared(); out->set_impl(select_rows); return select_rows.get(); } return static_cast(out->impl().get()); } phi::TensorBase* SetSparseKernelOutput(Tensor* out, TensorType type) { if (!out->initialized()) { if (type == TensorType::SPARSE_COO) { auto sparse_tensor = std::make_shared( phi::DenseTensor(), phi::DenseTensor(), phi::DDim{-1}); out->set_impl(sparse_tensor); return sparse_tensor.get(); } else if (type == TensorType::SPARSE_CSR) { auto sparse_tensor = std::make_shared(phi::DenseTensor(), phi::DenseTensor(), phi::DenseTensor(), phi::DDim{-1}); out->set_impl(sparse_tensor); return sparse_tensor.get(); } else { auto dense_tensor = std::make_shared(); out->set_impl(dense_tensor); return dense_tensor.get(); } } return out->impl().get(); } } // namespace experimental } // namespace paddle