"""BLT-Reasoner: Bottlenecked Latent Thoughts with explicit info objective.

Replaces Abstract-CoT's discrete-sampled z̃ with a continuous latent loop,
adds an InfoNCE z↔y identifiability objective that makes the constant-z
basin mechanically impossible, and enforces a strict y→only-z attention
mask so the latent is the only information channel from prompt to answer.

Modules:
    model.py        — continuous latent loop + 4D bottleneck mask
    losses.py       — InfoNCE, centroid (warmup), LM loss
    data.py         — GSM8K + chat template + GSM8K-final-answer extraction
    train.py        — Phase B training loop (LM + InfoNCE)
    eval.py         — pre-registered z-ablation eval (normal/zero/random/shuffled)
    smoke_test.py   — 30-min identifiability existence proof (decision gate)
"""