// 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 "paddle2onnx/mapper/tensor/assign.h" namespace paddle2onnx { REGISTER_MAPPER(assign, AssignMapper) REGISTER_MAPPER(share_data, AssignMapper) void AssignMapper::Opset7() { auto input_info = GetInput("X"); auto output_info = GetOutput("Out"); if (block_idx_ != 0 && OpType() != "share_data") { // Here's a trick for tensorrt // Consider remove this trick if (input_info[0].dtype == P2ODataType::BOOL) { auto zero = helper_->Constant(ONNX_NAMESPACE::TensorProto::INT64, std::vector(1, 0)); auto cast_input = helper_->AutoCast(input_info[0].name, P2ODataType::BOOL, P2ODataType::INT64); auto result = helper_->MakeNode("Add", {cast_input, zero})->output(0); helper_->AutoCast(result, output_info[0].name, P2ODataType::INT64, output_info[0].dtype); } else { auto zero = helper_->Constant(GetOnnxDtype(input_info[0].dtype), std::vector(1, 0.0)); auto new_input = helper_->Unsqueeze(input_info[0].name, std::vector(1, 0)); auto result = helper_->MakeNode("Add", {new_input, zero})->output(0); helper_->Squeeze(result, output_info[0].name, std::vector(1, 0)); } } else { helper_->MakeNode("Identity", {input_info[0].name}, {output_info[0].name}); } } } // namespace paddle2onnx