wehub-resource-sync
57 lines
2.0 KiB
C++
57 lines
2.0 KiB
C++
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <NvInferRuntimeCommon.h>
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#include <cstddef>
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#include <iostream>
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#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
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namespace paddle::inference::tensorrt {
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class BitwiseAndConverter : public OpConverter {
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public:
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void operator()(const framework::proto::OpDesc& op,
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const framework::Scope& scope,
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bool test_mode) override {
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VLOG(4) << "convert bitwise_and op to tensorrt layer";
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framework::OpDesc op_desc(op, nullptr);
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nvinfer1::ILayer* layer = nullptr;
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auto* input_tensor = engine_->GetITensor(op_desc.Input("X")[0]);
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nvinfer1::DataType data_type = input_tensor->getType();
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auto* y_tensor = engine_->GetITensor(op_desc.Input("Y")[0]);
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// for bool type
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if (data_type == nvinfer1::DataType::kBOOL) {
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layer = TRT_ENGINE_ADD_LAYER(engine_,
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ElementWise,
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*input_tensor,
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*y_tensor,
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nvinfer1::ElementWiseOperation::kAND);
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} else {
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PADDLE_THROW(common::errors::Fatal(
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"bitwise_and TRT converter is only supported on bool"));
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}
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auto output_name = op_desc.Output("Out")[0];
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ReplenishLayerAndOutput(layer, "bitwise_and", {output_name}, test_mode);
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}
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};
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} // namespace paddle::inference::tensorrt
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REGISTER_TRT_OP_CONVERTER(bitwise_and, BitwiseAndConverter);
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