Gahow Wang
7d84a64f5c
New xtrain-train crate scaffold. Data pipeline reuses xserv's from-scratch GPT-2/Qwen BPE via a path-dep (../../../xserv/crates/xserv-tokenizer, resolves on both ~/projects and dash5 /opt/wjh/projects): Corpus::load tokenizes the corpus into one id stream and samples fixed-length (input, target) next-token windows (LCG-seeded, reproducible). Trims a range-downloaded file to whole stories (<|endoftext|> boundaries). Also the host-only training math: LrSchedule (linear warmup + cosine decay) and global L2 grad-norm + clip scale, each with a local unit test. Corpus: data/tinystories-valid-3mb.txt — first ~3MB of TinyStories-valid (fetched on dash5 via hf-mirror.com; HF direct unreachable). Substitution noted: a real TinyStories subset, not the full set. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
27 lines
879 B
Rust
27 lines
879 B
Rust
use std::env;
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use std::path::Path;
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use std::process::Command;
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// Per-crate convention: the training loop / sampler / checkpoint all drive GPU
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// ops through the model + tensor layers, so the bulk of this crate is gated
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// behind `not(no_cuda)`. The LR schedule and the grad-clip *math* are host-only
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// and always compile. cfg does not propagate across crates, so re-detect nvcc.
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fn main() {
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println!("cargo:rustc-check-cfg=cfg(no_cuda)");
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let cuda_path = env::var("CUDA_HOME")
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.or_else(|_| env::var("CUDA_PATH"))
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.unwrap_or_else(|_| "/usr/local/cuda".to_string());
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if !nvcc_available(&cuda_path) {
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println!("cargo:rustc-cfg=no_cuda");
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}
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}
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fn nvcc_available(cuda_path: &str) -> bool {
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if Command::new("nvcc").arg("--version").output().is_ok() {
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return true;
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}
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Path::new(&format!("{cuda_path}/bin/nvcc")).exists()
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}
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