mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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6343b0db47
* Add notes for tensors * Optimize some apis * move some warnings * Support build with Paddle2ONNX * Add protobuf support * Fix compile on mac * add clearn package script * Add paddle2onnx code * remove submodule * Add onnx ocde * remove softlink * add onnx code * fix error * Add cmake file * fix patchelf * update paddle2onnx * Delete .gitmodules --------- Co-authored-by: PaddleCI <paddle_ci@example.com> Co-authored-by: pangyoki <pangyoki@126.com> Co-authored-by: jiangjiajun <jiangjiajun@baidu.lcom>
79 lines
2.6 KiB
C++
Executable File
79 lines
2.6 KiB
C++
Executable File
#include <fstream>
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#include <iostream>
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#include <set>
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#include <string>
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#include <cstring>
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#include "paddle2onnx/converter.h"
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#include "paddle2onnx/mapper/exporter.h"
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#include "paddle2onnx/parser/parser.h"
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namespace paddle2onnx {
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int32_t GetDataTypeFromPaddle(int dtype) {
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if (dtype == P2ODataType::FP32) {
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return 0;
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} else if (dtype == P2ODataType::FP64) {
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return 1;
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} else if (dtype == P2ODataType::UINT8) {
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return 2;
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} else if (dtype == P2ODataType::INT8) {
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return 3;
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} else if (dtype == P2ODataType::INT32) {
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return 4;
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} else if (dtype == P2ODataType::INT64) {
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return 5;
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}
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Assert(false, "Only support float/double/uint8/int32/int64 in PaddleReader.");
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return -1;
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}
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PaddleReader::PaddleReader(const char* model_buffer, int buffer_size) {
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PaddleParser parser;
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Assert(parser.Init(model_buffer, buffer_size),
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"Failed to parse PaddlePaddle model.");
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num_inputs = parser.inputs.size();
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num_outputs = parser.outputs.size();
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for (int i = 0; i < num_inputs; ++i) {
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std::strcpy(inputs[i].name, parser.inputs[i].name.c_str());
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inputs[i].rank = parser.inputs[i].Rank();
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inputs[i].shape = new int64_t[inputs[i].rank];
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for (int j = 0; j < inputs[i].rank; ++j) {
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inputs[i].shape[j] = parser.inputs[i].shape[j];
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}
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inputs[i].dtype = GetDataTypeFromPaddle(parser.inputs[i].dtype);
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}
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for (int i = 0; i < num_outputs; ++i) {
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std::strcpy(outputs[i].name, parser.outputs[i].name.c_str());
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outputs[i].rank = parser.outputs[i].Rank();
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outputs[i].shape = new int64_t[outputs[i].rank];
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for (int j = 0; j < outputs[i].rank; ++j) {
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outputs[i].shape[j] = parser.outputs[i].shape[j];
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}
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outputs[i].dtype = GetDataTypeFromPaddle(parser.outputs[i].dtype);
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}
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for (size_t i = 0; i < parser.NumOfOps(0); ++i) {
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if (parser.GetOpDesc(0, i).type().find("quantize") != std::string::npos) {
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is_quantize_model = true;
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break;
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}
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}
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for (size_t i = 0; i < parser.NumOfOps(0); ++i) {
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if (parser.GetOpDesc(0, i).type().find("multiclass_nms3") != std::string::npos) {
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has_nms = true;
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auto& op = parser.GetOpDesc(0, i);
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parser.GetOpAttr(op, "background_label", &nms_params.background_label);
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parser.GetOpAttr(op, "keep_top_k", &nms_params.keep_top_k);
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parser.GetOpAttr(op, "nms_eta", &nms_params.nms_eta);
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parser.GetOpAttr(op, "nms_threshold", &nms_params.nms_threshold);
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parser.GetOpAttr(op, "score_threshold", &nms_params.score_threshold);
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parser.GetOpAttr(op, "nms_top_k", &nms_params.nms_top_k);
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parser.GetOpAttr(op, "normalized", &nms_params.normalized);
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break;
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}
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}
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}
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} // namespace paddle2onnx
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