text: // 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.
  
  #pragma once
  #include "mlir/IR/Dialect.h"
  #include "mlir/Pass/Pass.h"
  #include "paddle/infrt/dialect/tensorrt/trt_ops.h"
  
  namespace infrt {
  namespace trt {
  /*
   * trtOpConverterPass.
   *
   * source ir:
   * func @main() -> tensor<?xf32> {
   *   %a = "pd.feed"()...
   *   %d, %f = "trt.create_engine"(%a) {
   *     %m = "pd.conv2d"(%a)...
   *     %n = "pd.conv3d"(%m)...
   *     %s = "pd.conv2d"(%a)...
   *     "Infrt.return" %n, %s
   *   } ...
   *   "pd.fetch" %d, %f
   * }
   *
   * destination ir:
   * func @main() -> tensor<?xf32> {
   *   %a = "pd.feed"()...
   *   %d, %f = "trt.create_engine"(%a) {
   *     %m = "trt.Convolution"(%a)...
   *     %n = "trt.Convolution"(%m)...
   *     %s = "trt.Convolution"(%a)...
   *     "Infrt.return" %n, %s
   *   } ...
   *   "pd.fetch" %d, %f
   * }
   */
  struct TRTOpConverterPass
      : public mlir::PassWrapper<TRTOpConverterPass,
                                 mlir::OperationPass<mlir::FuncOp>> {
    void getDependentDialects(mlir::DialectRegistry &registry) const override {
      registry.insert<TensorRTDialect>();
    }
    ::llvm::StringRef getName() const override { return "trtOpConverterPass"; }
    void runOnOperation() final;
  };
  }  // namespace trt
  }  // namespace infrt
  