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>
864808e056