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I am trying to follow this answer or this one. But I can't find both these methods 1. t.DebugString() or t.vec() in the docs. Both for the version I'm using 1.8 and the newest one 1.12. I just tried the first answer using debug string like this:

void Compute(OpKernelContext* context) override 

  {

    // Grab the input tensor

    const Tensor& bottom_prediction = context->input(0);

    const Tensor& bottom_target = context->input(1);

    const Tensor& bottom_weight = context->input(2);

    const Tensor& bottom_point = context->input(3);

    const Tensor& bottom_symmetry = context->input(4);

    std::cout << bottom_prediction.DebugString() << ", " << bottom_weight.DebugString() << ", " << bottom_weight.DebugString() << ", " << bottom_point.DebugString()

     << ", " << bottom_symmetry.DebugString() << std::endl;

but I get a segfault running this. GDB first line looks like this:

0x00007ffec42be4e4 in void tensorflow::(anonymous namespace)::PrintOneDim<float>(int, tensorflow::gtl::InlinedVector<long long, 4> const&, long long, int, float const*, long long*, std::string*) ()

and the whole stacktrace is:

(gdb) where

#0  0x00007ffec42be4e4 in void tensorflow::(anonymous namespace)::PrintOneDim<float>(int, tensorflow::gtl::InlinedVector<long long, 4> const&, long long, int, float const*, long long*, std::string*) ()

   from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#1  0x00007ffec42c99a4 in tensorflow::Tensor::SummarizeValue(long long) const ()

   from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#2  0x00007ffec42c9e09 in tensorflow::Tensor::DebugString() const ()

   from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#3  0x00007fffc2b51a9d in AveragedistanceOp<Eigen::GpuDevice, float>::Compute(tensorflow::OpKernelContext*) ()

   from /mnt/drive_c/datasets/<username>/PoseCNN/tools/../lib/average_distance_loss/average_distance_loss.so

#4  0x00007ffec471ec26 in tensorflow::BaseGPUDevice::ComputeHelper(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()

   from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#5  0x00007ffec471ef70 in tensorflow::BaseGPUDevice::Compute(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()

   from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#6  0x00007ffec476897d in tensorflow::(anonymous namespace)::ExecutorState::Process(tensorflow::(anonymous namespace)::ExecutorState::TaggedNode, long long) () from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#7  0x00007ffec476919a in std::_Function_handler<void (), tensorflow::(anonymous namespace)::ExecutorState::ScheduleReady(tensorflow::gtl::InlinedVector<tensorflow::(anonymous namespace)::ExecutorState::TaggedNode, 8> const&, tensorflow::(anonymous namespace)::ExecutorState::TaggedNodeReadyQueue*)::{lambda()#1}>::_M_invoke(std::_Any_data const&) ()

   from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#8  0x00007ffec43ce66a in Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::WorkerLoop(int) ()

   from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#9  0x00007ffec43cd712 in std::_Function_handler<void (), tensorflow::thread::EigenEnvironment::CreateThread(std::function<void ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) () from /home/<username>/envs/python2.7/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so

#10 0x00007ffff676b8f0 in ?? () from /usr/lib/x86_64-linux-gnu/libstdc++.so.6

#11 0x00007ffff79506ba in start_thread (arg=0x7ffe77f97700) at pthread_create.c:333

#12 0x00007ffff768641d in clone () at ../sysdeps/unix/sysv/linux/x86_64/clone.S:109

I am sure it is the print that segfaults, since it runs normally without it.
I don't really understand the output of gdb, but I'm also confused to what methods these answers are alluding to, since I can't find them in the docs.

How can I conveniently print tensors in a custom OP in tensorflow in c++?