use std::env;
use std::path::Path;
use std::process::Command;

// Per-crate convention: the training loop / sampler / checkpoint all drive GPU
// ops through the model + tensor layers, so the bulk of this crate is gated
// behind `not(no_cuda)`. The LR schedule and the grad-clip *math* are host-only
// and always compile. cfg does not propagate across crates, so re-detect nvcc.
fn main() {
    println!("cargo:rustc-check-cfg=cfg(no_cuda)");

    let cuda_path = env::var("CUDA_HOME")
        .or_else(|_| env::var("CUDA_PATH"))
        .unwrap_or_else(|_| "/usr/local/cuda".to_string());

    if !nvcc_available(&cuda_path) {
        println!("cargo:rustc-cfg=no_cuda");
    }
}

fn nvcc_available(cuda_path: &str) -> bool {
    if Command::new("nvcc").arg("--version").output().is_ok() {
        return true;
    }
    Path::new(&format!("{cuda_path}/bin/nvcc")).exists()
}