Gahow Wang
ec8114ecbc
Expose eval_loss() and add a --eval-ckpt <path> branch to bin/train: load an existing checkpoint into a model of the given arch and score it on the held-out val split, then exit. Lets v0 and v1 be measured on the identical validation set (the acceptance metric) without a separate eval binary. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
23 lines
745 B
Rust
23 lines
745 B
Rust
//! Training stack (Phase T6): LR schedule, global-norm grad clipping, checkpoint
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//! save/load, the GPT-2 BPE data pipeline (reusing xserv's tokenizer), an
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//! autoregressive sampler, and the training loop that wires them onto the T5
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//! `TinyTransformer` + the hand-written AdamW (`xtrain-optim`).
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//!
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//! Host-only pieces (LR schedule, grad-norm math) always compile so the crate
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//! `cargo check`s on a GPU-less host; everything that touches GPU tensors is
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//! gated behind `not(no_cuda)`.
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pub mod clip;
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pub mod data;
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pub mod schedule;
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#[cfg(not(no_cuda))]
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pub mod checkpoint;
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#[cfg(not(no_cuda))]
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pub mod sample;
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#[cfg(not(no_cuda))]
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mod train_loop;
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#[cfg(not(no_cuda))]
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pub use train_loop::{TrainConfig, TrainResult, eval_loss, train};
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