wehub-resource-sync
74 lines
2.4 KiB
C++
74 lines
2.4 KiB
C++
//
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// GridSampleOnnx.cpp
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// MNNConverter
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//
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// Created by MNN on 2021/03/24.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "onnxOpConverter.hpp"
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DECLARE_OP_CONVERTER(GridSampleOnnx);
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MNN::OpType GridSampleOnnx::opType(){
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return MNN::OpType_GridSample;
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}
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MNN::OpParameter GridSampleOnnx::type(){
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return MNN::OpParameter_GridSample;
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}
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void GridSampleOnnx::run(MNN::OpT *dstOp, const onnx::NodeProto *onnxNode, OnnxScope* scope){
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auto gridSampleParam = new MNN::GridSampleT;
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gridSampleParam->mode = MNN::SampleMode_BILINEAR;
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gridSampleParam->paddingMode = MNN::BorderMode_ZEROS;
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gridSampleParam->alignCorners = false;
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for (int i = 0; i < onnxNode->attribute_size(); ++i) {
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const auto &attributeProto = onnxNode->attribute(i);
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const auto &attributeName = attributeProto.name();
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if (attributeName == "mode") {
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switch (attributeProto.i()) {
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case 0:
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gridSampleParam->mode = MNN::SampleMode_BILINEAR;
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break;
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case 1:
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gridSampleParam->mode = MNN::SampleMode_NEAREST;
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break;
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default:
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LOG(FATAL) << "Unknown mode for " << onnxNode->name() << "!";
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break;
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}
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}
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if (attributeName == "padding_mode") {
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switch (attributeProto.i()) {
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case 0:
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gridSampleParam->paddingMode = MNN::BorderMode_ZEROS;
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break;
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case 1:
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gridSampleParam->paddingMode = MNN::BorderMode_CLAMP;
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break;
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case 2:
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gridSampleParam->paddingMode = MNN::BorderMode_REFLECTION;
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break;
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default:
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LOG(FATAL) << "Unknown padding mode for " << onnxNode->name() << "!";
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break;
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}
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}
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if (attributeName == "align_corners") {
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gridSampleParam->alignCorners = attributeProto.i();
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}
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}
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dstOp->main.value = gridSampleParam;
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}
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// REGISTER_CONVERTER(GridSampleOnnx, GridSample);
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// When we export torch.nn.functional.grid_sample to onnx, it's called GridSampler rather than GridSample,
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// thus, we have to add the "r"
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#define REGISTER_CONVERTER_r(name, opType) static onnxOpConverterRegister<name> _Convert_##opType(#opType"r")
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REGISTER_CONVERTER_r(GridSampleOnnx, GridSample);
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