wehub-resource-sync
73 lines
3.0 KiB
C++
73 lines
3.0 KiB
C++
/* Copyright (c) 2018 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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#include "paddle/fluid/inference/tensorrt/plugin/roi_align_op_plugin.h"
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namespace paddle::inference::tensorrt {
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/*
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* Roi Align Op
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*/
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class RoiAlignOpConverter : 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 roi_align op to tensorrt plugin";
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framework::OpDesc op_desc(op, nullptr);
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std::string input_name = op_desc.Input("X").front();
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std::string rois_name = op_desc.Input("ROIs").front();
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std::string output_name = op_desc.Output("Out").front();
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const auto pooled_height =
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PADDLE_GET_CONST(int, op_desc.GetAttr("pooled_height"));
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const auto pooled_width =
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PADDLE_GET_CONST(int, op_desc.GetAttr("pooled_width"));
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const auto spatial_scale =
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PADDLE_GET_CONST(float, op_desc.GetAttr("spatial_scale"));
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const auto sampling_ratio =
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PADDLE_GET_CONST(int, op_desc.GetAttr("sampling_ratio"));
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const auto aligned = PADDLE_GET_CONST(bool, op_desc.GetAttr("aligned"));
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const auto input_tensor = engine_->GetITensor(input_name);
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const auto rois_tensor = engine_->GetITensor(rois_name);
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const nvinfer1::DataType data_type_ = engine_->WithFp16()
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? nvinfer1::DataType::kHALF
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: nvinfer1::DataType::kFLOAT;
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std::vector<nvinfer1::ITensor*> inputs{input_tensor, rois_tensor};
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nvinfer1::ILayer* layer = nullptr;
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auto* roi_align_plugin = new plugin::RoiAlignPluginDynamic(data_type_,
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pooled_height,
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pooled_width,
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spatial_scale,
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sampling_ratio,
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aligned);
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auto roi_align_layer = engine_->network()->addPluginV2(
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inputs.data(), inputs.size(), *roi_align_plugin);
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layer = roi_align_layer;
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std::vector<std::string> output_names{output_name};
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ReplenishLayerAndOutput(layer, "roi_align", output_names, 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(roi_align, RoiAlignOpConverter);
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