// Copyright (c) 2021 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/infrt/dialect/tensorrt/trt_graph_fuse_pass.h" #include #include #include #include "llvm/ADT/SetVector.h" #include "mlir/Analysis/SliceAnalysis.h" #include "mlir/IR/Builders.h" #include "paddle/infrt/dialect/pd_ops.h" #include "paddle/infrt/dialect/tensorrt/trt_ops.h" namespace infrt { namespace trt { namespace { // ReverseDfs // do reverse dfs. calls "func" to search when visit a node. // The elements in 'source' can't be nullptr. // Reference the function nameed "FlexibleDFS" but defined in: // paddle/fluid/framework/ir/subgraph_detector.cc. bool reverseDfs(std::vector<::mlir::Operation *> source, const std::function &func) { std::unordered_set visited; while (!source.empty()) { auto node = source.back(); source.pop_back(); if (visited.count(node)) continue; visited.insert(node); if (func(node)) return true; auto values = node->getOperands(); for (auto value : values) { // if the value is a block argument, the node is nullptr. ::mlir::Operation *node = value.getDefiningOp(); if (node != nullptr && !visited.count(node)) { source.emplace_back(node); } } } return false; } // merge the first&second graph op to a new graph op. void mergeTwoAdjacentGraphOp(::mlir::OpBuilder &builder, // NOLINT ::mlir::pd::GraphOp first, ::mlir::pd::GraphOp second) { // comput inputs and outputs ::llvm::SmallVector<::mlir::Value, 4> inputs(first.getOperands()), outputs; for (::mlir::Value input : second.getOperands()) { if (input.getDefiningOp() != first) { inputs.push_back(input); } } ::llvm::DenseMap<::mlir::Value, unsigned int> op_output_mapping; for (::mlir::Value output : first.getResults()) { for (::mlir::Operation *user : output.getUsers()) { if (user != second && user->getParentOp() != second) { op_output_mapping[output] = outputs.size(); outputs.push_back(output); break; } } } auto fetch_op = second.getBody()->getTerminator(); outputs.append(fetch_op->getOperands().begin(), fetch_op->getOperands().end()); ::llvm::SmallVector<::mlir::Type, 4> fetch_types; for (auto value : outputs) { fetch_types.push_back(value.getType()); } // create the new graph op builder.setInsertionPoint(first); auto loc = first.getLoc(); auto graph_op = builder.create<::mlir::pd::GraphOp>(loc, fetch_types, inputs); ::mlir::Block *block = new ::mlir::Block; auto copy_range = second.getBody()->without_terminator(); block->getOperations().splice(block->begin(), second.getBody()->getOperations(), copy_range.begin(), copy_range.end()); copy_range = first.getBody()->without_terminator(); block->getOperations().splice(block->begin(), first.getBody()->getOperations(), copy_range.begin(), copy_range.end()); builder.setInsertionPointToEnd(block); builder.create(loc, outputs); graph_op.body().push_back(block); // mapping the output unsigned int num_result = first.getNumResults(); fetch_op = first.getBody()->getTerminator(); for (unsigned int index = 0; index < num_result; ++index) { auto origin_value = first.getResult(index); if (op_output_mapping.find(origin_value) == op_output_mapping.end()) { origin_value.replaceAllUsesWith(fetch_op->getOperand(index)); } else { auto inner_value = fetch_op->getOperand(index); auto outer_value = graph_op.getResult(op_output_mapping[origin_value]); while (!origin_value.use_empty()) { auto replace_value = origin_value.use_begin()->getOwner()->getParentOp() == graph_op ? inner_value : outer_value; origin_value.use_begin()->set(replace_value); } } } second.replaceAllUsesWith( graph_op.getResults().take_back(second.getNumResults())); first.erase(); second.erase(); } // Topological sort the function op. void topoSortBlock(mlir::Block &body) { // NOLINT llvm::SetVector toSort; if (body.empty()) return; for (auto it = body.rbegin(); it != body.rend(); ++it) { toSort.insert(&*it); } llvm::SetVector result = ::mlir::topologicalSort(std::move(toSort)); for (auto *op : result) { op->moveBefore(body.getTerminator()); } } } // namespace // Implementation of the trtGraphFusePass. void trtGraphFusePass::runOnFunction() { mlir::Block &body = getFunction().front(); ::mlir::OpBuilder builder(&body, body.begin()); bool changed = false; do { changed = false; for (auto &op : body) { ::mlir::pd::GraphOp graph_op = ::llvm::dyn_cast_or_null<::mlir::pd::GraphOp>(&op); if (nullptr == graph_op) continue; for (auto user_op : op.getUsers()) { ::mlir::pd::GraphOp user_graph_op = ::llvm::dyn_cast_or_null<::mlir::pd::GraphOp>(user_op); if (nullptr == user_graph_op) continue; // get all dst input nodes except src. std::vector<::mlir::Operation *> source_nodes; for (auto operand : user_op->getOperands()) { auto input = operand.getDefiningOp(); if (input != &op && input != nullptr) { source_nodes.push_back(input); } } // Reverse DFS from the source_nodes. if (!reverseDfs(source_nodes, [&op](const ::mlir::Operation *n) { return n == &op; })) { mergeTwoAdjacentGraphOp(builder, graph_op, user_graph_op); changed = true; break; } } if (changed) break; } } while (changed); topoSortBlock(body); } } // namespace trt } // namespace infrt