anomaly_cpp.cpp
#include <torch/torch.h>

int main(int arg, char *argv[]){    
    torch::autograd::AnomalyMode::set_enabled(true);
    auto x = torch::tensor({5.0}, torch::requires_grad());
    auto y = x * x;
    auto z = y * y;
    y += 1;
    z.backward();
    std::cout << x.grad() << std::endl;
}

$ g++ -g anomaly_cpp.cpp  -I ../pytorch/build/lib.linux-x86_64-3.8/torch/include/torch/csrc/api/include/ -I ../pytorch/build/lib.linux-x86_64-3.8/torch/include/ -L ../pytorch/build/lib.linux-x86_64-3.8/torch/lib/   -ltorch -lc10 -ltorch_cpu

$ LD_LIBRARY_PATH=../pytorch/build/lib.linux-x86_64-3.8/torch/lib/ ../scripts/a.out  
[W anomaly_mode.cpp:24] Warning: Error detected in MulBackward0. Traceback of forward call that caused the error:
frame #0: torch::autograd::AnomalyMetadata::store_stack() + 0x22 (0x7fd3f57f5a32 in ../pytorch/build/lib.linux-x86_64-3.8/torch/lib/libtorch_cpu.so)
frame #1: <unknown function> + 0x1e3a3e9 (0x7fd3f54bb3e9 in ../pytorch/build/lib.linux-x86_64-3.8/torch/lib/libtorch_cpu.so)
frame #2: <unknown function> + 0x1f1f612 (0x7fd3f55a0612 in ../pytorch/build/lib.linux-x86_64-3.8/torch/lib/libtorch_cpu.so)
frame #3: <unknown function> + 0xded642 (0x7fd3f446e642 in ../pytorch/build/lib.linux-x86_64-3.8/torch/lib/libtorch_cpu.so)
frame #4: <unknown function> + 0x15dd2aa (0x7fd3f4c5e2aa in ../pytorch/build/lib.linux-x86_64-3.8/torch/lib/libtorch_cpu.so)
frame #5: at::Tensor::mul(at::Tensor const&) const + 0x9d (0x7fd3f4c6104d in ../pytorch/build/lib.linux-x86_64-3.8/torch/lib/libtorch_cpu.so)
frame #6: <unknown function> + 0x4fbe (0x563f08413fbe in ../scripts/a.out)
frame #7: <unknown function> + 0x50e0 (0x563f084140e0 in ../scripts/a.out)
frame #8: __libc_start_main + 0xea (0x7fd3f329acca in /lib/x86_64-linux-gnu/libc.so.6)
frame #9: <unknown function> + 0x467a (0x563f0841367a in ../scripts/a.out)
 (function _print_stack)
terminate called after throwing an instance of 'std::runtime_error'
  what():  one of the variables needed for gradient computation has been modified by an inplace operation: [CPUFloatType [1]], which is output 0 of MulBackward0, is at version 1; expected version 0 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!
Aborted

Hehehe. Now I need add fix skipping the PyTorch frames, see if I get a line number for my frame and upload the video.