wehub-resource-sync
65 lines
2.3 KiB
C++
65 lines
2.3 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 "paddle/fluid/inference/tensorrt/convert/op_converter.h"
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namespace paddle::inference::tensorrt {
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class CastOpConverter : 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(3) << "convert a cast op to tensorrt";
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framework::OpDesc op_desc(op, nullptr);
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auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
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auto out_dtype = PADDLE_GET_CONST(int, op_desc.GetAttr("out_dtype"));
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auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Identity, *input);
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switch (out_dtype) {
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case 0: // BOOL = 0
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layer->setOutputType(0, nvinfer1::DataType::kBOOL);
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layer->getOutput(0)->setType(nvinfer1::DataType::kBOOL);
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break;
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case 2: // INT32 = 2
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case 3: // INT64 = 3 there is no int64 in tensorrt subgraph
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layer->setOutputType(0, nvinfer1::DataType::kINT32);
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layer->getOutput(0)->setType(nvinfer1::DataType::kINT32);
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break;
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case 4: // FP16 = 4
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layer->setOutputType(0, nvinfer1::DataType::kHALF);
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layer->getOutput(0)->setType(nvinfer1::DataType::kHALF);
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break;
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case 5: // FP32 = 5
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case 6: // FP64 = 6
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layer->setOutputType(0, nvinfer1::DataType::kFLOAT);
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layer->getOutput(0)->setType(nvinfer1::DataType::kFLOAT);
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break;
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default:
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LOG(ERROR) << "Unable to convert a fluid data type(" << out_dtype
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<< ") to a nvinfer DataType";
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break;
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}
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auto output_name = op_desc.Output("Out")[0];
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ReplenishLayerAndOutput(layer, "cast", {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(cast, CastOpConverter);
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