Importing library from new directory.

[patricknaughton01]

I'm using pybind to call some functions from the GPD (https://github.com/atenpas/gpd) library. I can compile the shared library as expected but am observing some strange behavior depending on where I try to import it from. My directory setup is like this:

project
    build
        lib.so
        test.py

This setup works (I can import lib.so from test.py and use the compiled functions). However, if I move test.py anywhere else (updating the path to the library accordingly), the compiled C++ functions will partially run but segfault before the program finishes. The segfault seems to originate from Eigen, I'm not sure if this is a known issue of pybind11 and Eigen working together.

From gdb:

Thread 18 "python3" received signal SIGSEGV, Segmentation fault.
[Switching to Thread 0x7fff77d36700 (LWP 176530)]
Eigen::internal::dense_assignment_loop<Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<float, -1, -1, 0, -1, -1> >, Eigen::internal::evaluator<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > >, Eigen::internal::assign_op<float, float>, 0>, 0, 0>::run (kernel=<synthetic pointer>...)
    at /usr/include/eigen3/Eigen/src/Core/AssignEvaluator.h:326
326             kernel.assignCoeffByOuterInner(outer, inner);
(gdb) bt
#0  Eigen::internal::dense_assignment_loop<Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<float, -1, -1, 0, -1, -1> >, Eigen::internal::evaluator<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > >, Eigen::internal::assign_op<float, float>, 0>, 0, 0>::run(Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<float, -1, -1, 0, -1, -1> >, Eigen::internal::evaluator<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > >, Eigen::internal::assign_op<float, float>, 0>&) (kernel=<synthetic pointer>...) at /usr/include/eigen3/Eigen/src/Core/AssignEvaluator.h:326
#1  Eigen::internal::call_dense_assignment_loop<Eigen::Matrix<float, -1, -1, 0, -1, -1>, Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> >, Eigen::internal::assign_op<float, float> >(Eigen::Matrix<float, -1, -1, 0, -1, -1>&, Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > const&, Eigen::internal::assign_op<float, float> const&) (func=..., src=..., dst=...) at /usr/include/eigen3/Eigen/src/Core/AssignEvaluator.h:741
#2  Eigen::internal::Assignment<Eigen::Matrix<float, -1, -1, 0, -1, -1>, Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> >, Eigen::internal::assign_op<float, float>, Eigen::internal::Dense2Dense, void>::run(Eigen::Matrix<float, -1, -1, 0, -1, -1>&, Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > const&, Eigen::internal::assign_op<float, float> const&) (func=..., src=..., dst=...) at /usr/include/eigen3/Eigen/src/Core/AssignEvaluator.h:879
#3  Eigen::internal::call_assignment_no_alias<Eigen::Matrix<float, -1, -1, 0, -1, -1>, Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> >, Eigen::internal::assign_op<float, float> >(Eigen::Matrix<float, -1, -1, 0, -1, -1>&, Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > const&, Eigen::internal::assign_op<float, float> const&) (func=..., src=..., dst=...) at /usr/include/eigen3/Eigen/src/Core/AssignEvaluator.h:836
#4  Eigen::PlainObjectBase<Eigen::Matrix<float, -1, -1, 0, -1, -1> >::_set_noalias<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > >(Eigen::DenseBase<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > > const&) (other=..., this=0x7fff77d35c80)
    at /usr/include/eigen3/Eigen/src/Core/PlainObjectBase.h:732
#5  Eigen::PlainObjectBase<Eigen::Matrix<float, -1, -1, 0, -1, -1> >::PlainObjectBase<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > >(Eigen::DenseBase<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > > const&) (other=..., this=0x7fff77d35c80)
    at /usr/include/eigen3/Eigen/src/Core/PlainObjectBase.h:537
#6  Eigen::Matrix<float, -1, -1, 0, -1, -1>::Matrix<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > >(Eigen::EigenBase<Eigen::Map<Eigen::Matrix<float, -1, -1, 1, -1, -1> const, 0, Eigen::Stride<0, 0> > > const&) (other=..., this=0x7fff77d35c80) at /usr/include/eigen3/Eigen/src/Core/Matrix.h:377
#7  gpd::net::ConvLayer::forward(std::vector<float, std::allocator<float> > const&) const (this=0x227f210, x=...) at /home/motion/gpd/src/gpd/net/conv_layer.cpp:36
#8  0x00007ffff73e199b in gpd::net::EigenClassifier::forward(std::vector<float, std::allocator<float> > const&) (this=0x20ecea0, x=...) at /usr/include/c++/9/bits/unique_ptr.h:360
#9  0x00007ffff73e2808 in gpd::net::EigenClassifier::_ZN3gpd3net15EigenClassifier14classifyImagesERKSt6vectorISt10unique_ptrIN2cv3MatESt14default_deleteIS5_EESaIS8_EE._omp_fn.0(void) () at /home/motion/gpd/src/gpd/net/eigen_classifier.cpp:71
#10 0x00007ffff277e78e in  () at /usr/lib/x86_64-linux-gnu/libgomp.so.1
#11 0x00007ffff7d6c609 in start_thread (arg=<optimized out>) at pthread_create.c:477
#12 0x00007ffff7ea8293 in clone () at ../sysdeps/unix/sysv/linux/x86_64/clone.S:95

I'm using python 3.8 and compiling using this in CMakeLists.txt

add_subdirectory(pybind11)
pybind11_add_module(gpd_python SHARED src/pybind.cpp)
target_link_libraries(gpd_python PRIVATE
    ${PROJECT_NAME}_grasp_detector
    ${PROJECT_NAME}_classifier
    ${PROJECT_NAME}_clustering
    ${PROJECT_NAME}_sequential_importance_sampling
    ${PROJECT_NAME}_antipodal
    ${PROJECT_NAME}_candidates_generator
    ${PROJECT_NAME}_finger_hand
    ${PROJECT_NAME}_frame_estimator
    ${PROJECT_NAME}_hand
    ${PROJECT_NAME}_hand_set
    ${PROJECT_NAME}_hand_geometry
    ${PROJECT_NAME}_hand_search
    ${PROJECT_NAME}_local_frame
    ${PROJECT_NAME}_cloud
    ${PROJECT_NAME}_config_file
    ${PROJECT_NAME}_eigen_utils
    ${PROJECT_NAME}_plot
    ${PROJECT_NAME}_point_list
    ${PROJECT_NAME}_image_strategy
    ${PROJECT_NAME}_image_1_channels_strategy
    ${PROJECT_NAME}_image_3_channels_strategy
    ${PROJECT_NAME}_image_12_channels_strategy
    ${PROJECT_NAME}_image_15_channels_strategy
    ${PROJECT_NAME}_image_geometry
    ${PROJECT_NAME}_image_generator)

pybind.cpp has this code:

#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <pybind11/numpy.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <Eigen/Dense>
#include <string>
#include <vector>
#include <array>
#include <memory>
#include <stdexcept>
#include <iostream>
#include "../include/gpd/grasp_detector.h"
#include "../include/gpd/util/cloud.h"
#include "../include/gpd/candidate/hand.h"

// 3 for position, 9 for orientation, 1 for width, 1 for score
#define GRASP_DESC_LEN 14

pybind11::array_t<double> detectGrasps(
    gpd::GraspDetector &detector,
    pybind11::array_t<double, pybind11::array::c_style> pcd)
{
    // TODO: Make these conditions raise actual exceptions
    if (pcd.ndim() != 2) {
        throw std::invalid_argument("PCD must have two dimensions");
    }
    ssize_t len = pcd.shape()[0];
    if (len == 0) {
        throw std::invalid_argument("PCD must more than 0 points");
    }
    if (pcd.shape()[1] < 3) {
        throw std::invalid_argument("Each point must have at least 3 coordinates");
    }
    pcl::PointCloud<pcl::PointXYZRGBA> e_cloud;
    pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud_ptr = e_cloud.makeShared();
    for(ssize_t i = 0; i < len; i++){
        pcl::PointXYZRGBA pt(pcd.at(i, 0), pcd.at(i, 1), pcd.at(i, 2));
        cloud_ptr->push_back(pt);
    }
    gpd::util::Cloud gpd_cloud(cloud_ptr);
    detector.preprocessPointCloud(gpd_cloud);
    std::vector<std::unique_ptr<gpd::candidate::Hand>> grasps = detector.detectGrasps(gpd_cloud);
    std::vector<std::array<double, GRASP_DESC_LEN>> ret;
    for(size_t i = 0; i < grasps.size(); i++){
        const Eigen::Vector3d pos = grasps[i]->getPosition();
        const Eigen::Matrix3d rot = grasps[i]->getOrientation();
        const double w = grasps[i]->getGraspWidth();
        const double score = grasps[i]->getScore();
        std::array<double, GRASP_DESC_LEN> gd = {
            pos[0], pos[1], pos[2],
            rot(0,0), rot(0,1), rot(0,2),
            rot(1,0), rot(1,1), rot(1,2),
            rot(2,0), rot(2,1), rot(2,2),
            w, score
        };
        ret.push_back(gd);
    }
    return pybind11::cast(ret);
}

PYBIND11_MODULE(gpd_python, m) {
    pybind11::class_<gpd::GraspDetector>(m, "GraspDetector")
        .def(pybind11::init<const std::string &>());
    m.def("detectGrasps", &detectGrasps);
}

This issue is confusing to me because the program works perfectly as long as the python file (test.py) is in the build directory. Not sure if people have encountered these types of errors before. Perhaps it is related to relative #include statements in the C++ code? Thanks!

[patricknaughton01]

I think I've resolved this, it seems to be because of a relative path problem. Eigen was trying to load weights from a file that did not exist, which resulted in a segmentation fault when the program tried to access those values.