// 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 #include #include #include "ai_ddk_lib/include/graph/op/all_ops.h" #include "lite/core/op_lite.h" #include "lite/core/tensor.h" namespace paddle { namespace lite { namespace subgraph { namespace npu { // Type and registers of converters for converting Paddle Ops to HiAI IR graph class Graph { public: template std::shared_ptr AddNode(const std::string& name) { auto unique_name = [&](const std::string& key) { int idx = 1; auto it = counts_.find(key); if (it == counts_.end()) { counts_.insert(std::make_pair(key, idx)); } else { idx = ++(it->second); } return key + "_" + std::to_string(idx); }; auto it = nodes_.find(name); if (it != nodes_.end()) { // Generate a new unique name as the key to bind the origin node: // new_name->node nodes_.insert(std::make_pair(unique_name(name + "_var"), it->second)); nodes_.erase(it); } // Create a new node and bind with the name: name->new_node auto node = std::make_shared(unique_name(name + "_op")); nodes_.insert(std::make_pair(name, node)); return node; } // Const node std::shared_ptr AddNode( const std::string& name, const Tensor& tensor, PrecisionType ptype = PRECISION(kFloat), DataLayoutType ltype = DATALAYOUT(kNCHW)); std::shared_ptr AddNode( const std::string& name, const Tensor& tensor, std::vector shape, PrecisionType ptype = PRECISION(kFloat), DataLayoutType ltype = DATALAYOUT(kNCHW)); template std::shared_ptr AddNode( const std::string& name, const std::vector& data, std::vector shape = {}, DataLayoutType ltype = DATALAYOUT(kNCHW)) { const std::type_info& info = typeid(T); PrecisionType ptype = PRECISION(kFloat); if (info == typeid(float)) { ptype = PRECISION(kFloat); } else if (info == typeid(int8_t)) { ptype = PRECISION(kFloat); } else if (info == typeid(int32_t)) { ptype = PRECISION(kInt32); } else { LOG(FATAL) << "[NPU] Unknow data type " << info.name(); } if (shape.empty()) { shape = {static_cast(data.size())}; } else { int size = 1; for (auto i : shape) { size *= i; } CHECK_EQ(data.size(), size); } Tensor tensor; tensor.Resize(shape); std::memcpy(reinterpret_cast(tensor.mutable_data()), reinterpret_cast(data.data()), data.size() * sizeof(T)); return AddNode(name, tensor, ptype, ltype); } template std::shared_ptr AddNode( const std::string& name, T value, std::vector shape = {1}, DataLayoutType ltype = DATALAYOUT(kNCHW)) { int64_t size = 1; for (auto i : shape) { size *= i; } std::vector data(size, value); return AddNode(name, data, shape, ltype); } // Data node std::shared_ptr AddNode( const std::string& name, std::vector shape, PrecisionType ptype = PRECISION(kFloat), DataLayoutType ltype = DATALAYOUT(kNCHW)); std::shared_ptr GetNode(std::string name) { CHECK(HasNode(name)) << "[NPU] Node " << name << " not found."; return nodes_.at(name); } bool HasNode(const std::string& name) { return nodes_.find(name) != nodes_.end(); } private: std::unordered_map> nodes_; std::unordered_map counts_; }; } // namespace npu } // namespace subgraph } // namespace lite } // namespace paddle