Rust-bert rrrors on Debian 12 with pre compiled libtorch

[greensegfault]

I get compile time errors on Cargo run, my system is Debian.

Cloning rust-bert and simply running rust-bert > cargo run --example sentence_embeddings works, I get the embedding printed.

When I run the simple program below, I get compile errors.
I have tried with different versions of precompiled libtorch and it doesn't make any difference, v2.1.0, v2.2.0, v2.3.1.

c++ --version
c++ (Debian 12.2.0-14) 12.2.0

Error message on $ cargo run,

  cargo:warning=                 from /home/gseg/lib/libtorch/include/torch/csrc/api/include/torch/autograd.h:5,
  cargo:warning=                 from /home/gseg/lib/libtorch/include/torch/csrc/api/include/torch/all.h:7,
  cargo:warning=                 from /home/gseg/lib/libtorch/include/torch/csrc/api/include/torch/torch.h:3,
  cargo:warning=                 from libtch/torch_api.h:6:
  cargo:warning=/home/gseg/lib/libtorch/include/ATen/ops/_cslt_sparse_mm.h:26:173: note: in passing argument 4 of ‘at::Tensor at::_cslt_sparse_mm(const Tensor&, const Tensor&, const std::optional<Tensor>&, const std::optional<Tensor>&, std::optional<c10::ScalarType>, bool)’
  cargo:warning=   26 | inline at::Tensor _cslt_sparse_mm(const at::Tensor & compressed_A, const at::Tensor & dense_B, const c10::optional<at::Tensor> & bias={}, const c10::optional<at::Tensor> & alpha={}, c10::optional<at::ScalarType> out_dtype=c10::nullopt, bool transpose_result=false) {
  cargo:warning=      |                                                                                                                                           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~
  exit status: 0
  exit status: 1
  cargo:warning=ToolExecError: Command "c++" "-O0" "-ffunction-sections" "-fdata-sections" "-fPIC" "-gdwarf-4" "-fno-omit-frame-pointer" "-m64" "-I" "/home/gseg/lib/libtorch/include" "-I" "/home/gseg/lib/libtorch/include/torch/csrc/api/include" "-Wl,-rpath=/home/gseg/lib/libtorch/lib" "-std=c++17" "-D_GLIBCXX_USE_CXX11_ABI=1" "-o" "/home/gseg/code/bert-test/target/debug/build/torch-sys-3b0471bf716afe6c/out/19072f24a82f85ae-torch_api_generated.o" "-c" "libtch/torch_api_generated.cpp" with args c++ did not execute successfully (status code exit status: 1).
  exit status: 0

  --- stderr


  error occurred: Command "c++" "-O0" "-ffunction-sections" "-fdata-sections" "-fPIC" "-gdwarf-4" "-fno-omit-frame-pointer" "-m64" "-I" "/home/gseg/lib/libtorch/include" "-I" "/home/gseg/lib/libtorch/include/torch/csrc/api/include" "-Wl,-rpath=/home/gseg/lib/libtorch/lib" "-std=c++17" "-D_GLIBCXX_USE_CXX11_ABI=1" "-o" "/home/gseg/code/bert-test/target/debug/build/torch-sys-3b0471bf716afe6c/out/19072f24a82f85ae-torch_api_generated.o" "-c" "libtch/torch_api_generated.cpp" with args c++ did not execute successfully (status code exit status: 1).

Code below

src/main.rs
extern crate anyhow;
use rust_bert::{
    gpt_neo::{
        GptNeoConfigResources, GptNeoMergesResources, GptNeoModelResources, GptNeoVocabResources,
    },
    pipelines::common::{ModelResource, ModelType},
    pipelines::text_generation::{TextGenerationConfig, TextGenerationModel},
    resources::RemoteResource,
};

fn main() -> anyhow::Result<()> {
    let model_resource = Box::new(RemoteResource::from_pretrained(
        GptNeoModelResources::GPT_NEO_2_7B,
    ));
    let config_resource = Box::new(RemoteResource::from_pretrained(
        GptNeoConfigResources::GPT_NEO_2_7B,
    ));
    let vocab_resource = Box::new(RemoteResource::from_pretrained(
        GptNeoVocabResources::GPT_NEO_2_7B,
    ));
    let merges_resource = Box::new(RemoteResource::from_pretrained(
        GptNeoMergesResources::GPT_NEO_2_7B,
    ));

    let generate_config = TextGenerationConfig {
        model_type: ModelType::GPTNeo,
        model_resource: ModelResource::Torch(model_resource),
        config_resource,
        vocab_resource,
        merges_resource: Some(merges_resource),
        num_beams: 5,
        no_repeat_ngram_size: 2,
        max_length: Some(100),
        ..Default::default()
    };
    let model = TextGenerationModel::new(generate_config).unwrap();

    loop {
        let mut line = String::new();
        std::io::stdin().read_line(&mut line).unwrap();
        let split = line.split('/').collect::<Vec<&str>>();
        let slc = split.as_slice();
        let output = model.generate(&slc[1..], Some(slc[0]));
        for sentence in output? {
            println!("{:?}", sentence);
        }
        return Ok(());
    }
}