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jgrusewski 864808e056 fix(ml): add ensure_training_dtype boundary casts to all model forward methods

After converting all VarBuilder sites from F32 to training_dtype (BF16 on
Ampere+ GPUs), input tensors from callers remain F32, causing dtype
mismatches in matmul/add/mul operations. This commit adds systematic
boundary casts across all 10 model architectures:

- Input boundary: ensure_training_dtype() at each model forward() entry
- Output boundary: to_dtype(F32) at each model forward() exit
- Internal intermediates: hidden state init, gradient extraction,
  positional encodings, causal masks, SSM state matrices, B-spline
  basis values all cast to match computation dtype
- Ensemble adapters: ensure_training_dtype after Tensor::from_vec

36 files, +293/-72 lines. 2640 tests pass, 0 failures, 0 clippy warnings.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-03-03 17:42:41 +01:00

gated_residual.rs

refactor: restructure repo — crates/, bin/, testing/ layout

2026-02-25 11:56:00 +01:00

hft_optimizations.rs

feat(ml): GPU max performance phase 2 — C51 re-enabled, buffer pooling, kernel sizing

2026-03-01 21:25:36 +01:00

lstm_encoder.rs

refactor: restructure repo — crates/, bin/, testing/ layout

2026-02-25 11:56:00 +01:00

mod.rs

fix(ml): add ensure_training_dtype boundary casts to all model forward methods