| # PP1: probabilistic-proposal correctness oracle |
|
|
| **OFF; CPU reference only.** No serving imports, launch flags, service changes, |
| checkpoints or GPU code. This directory does not enable sampled remote proposals. |
| See [AUDIT.md](AUDIT.md) for the current point-mass q path. |
| The [transport design](TRANSPORT.md) defines q precision, sparse/TP2 ownership |
| and non-anticipating depth. The [GB10 A/B plan](GB10-AB-PLAN.md) identifies |
| the remaining implementation and coordinator-only hardware gates. |
| Synthetic measured counts are in [cpu_results.json](cpu_results.json). |
|
|
| Run from the repository root on Controller: |
|
|
| ```bash |
| source ~/.config/ndm/paths.sh |
| "$HARNESS_PYTHON" -m pytest -q -s offload/dspark/probabilistic/tests |
| "$HARNESS_PYTHON" -m mypy --strict --follow-imports=skip offload/dspark/probabilistic/reference.py |
| "$HARNESS_PYTHON" -m ruff check offload/dspark/probabilistic |
| ``` |
|
|
| No dependency was installed. The reference uses only Python's standard library; |
| pytest, mypy and ruff were already available in HARNESS_PYTHON. |
| |
| `Categorical.dense(weights)` normalizes a full q. `q.sparse_topk(k)` selects |
| support deterministically (lowest global token ID on ties), then normalizes |
| on that support; all other IDs have **exactly zero** probability. Sample only |
| after this operation. The full target vector is retained for residual sampling. |
| `fp32_weights` rounds weights before constructing q, permitting sender/receiver |
| equality tests. It refuses overflow, non-finite values and zero total mass. |
| Weights that underflow individually to zero become zero in the defined q. |
|
|
| For any proposed x with q(x)>0, `acceptance` returns min(1,p(x)/q(x)). |
| `residual` normalizes max(p(v)−q(v),0) over every target vocabulary ID. |
| The mass accepted at v is min(p(v),q(v)). The total rejection mass equals |
| sum_v (p(v)−q(v))+, so adding the correction mass recovers p(v) exactly. |
| The no-rejection case p=q never constructs a zero-mass residual. |
| This is the standard tokenwise algorithm in [Leviathan et al., 2023, |
| algorithm 1 and appendix A.1](https://proceedings.mlr.press/v202/leviathan23a/leviathan23a.pdf). |
| |
| Fractions and integer tickets make the oracle exact for its supplied finite |
| distributions. Float inputs mean their exact binary64 values; FP32 inputs mean |
| the exact rational normalization of the rounded FP32 weights. This does not |
| claim that a GPU's finite-precision softmax, RNG or reduction order is identical. |
| Use the oracle to qualify those implementations separately. It is intentionally |
| unsuitable for full-vocabulary production throughput or timing forecasts. |
| |
| `propose` commits depth in 1..5 before drawing and conditions each q on the |
| actual prior proposals. Only a terminal token can shorten that block. |
| `Verifier` evaluates target and processors on the matching proposed prefix, |
| stops at the first rejection and discards its suffix. It commits only accepted |
| drafts and one correction (or a target bonus if all drafts survive). Accepted |
| EOS stops without a bonus; correction/bonus EOS ends the request too. |
| |
| `RandomStreams` binds proposal, acceptance and correction streams to request, |
| generation and round. Streams use independent deterministic seeds derived from |
| explicit domains; global random state is untouched. The verifier refuses wrong |
| owners, stale prefixes, changed context/stop policies, reused rounds and malformed |
| proposals before drawing. A failure during target/processor evaluation leaves |
| the prefix uncommitted and poisons the session until explicitly reconstructed. |
| This CPU RNG scheme is a test oracle, not a proposed production RNG ABI. |
| |
| Target processors are pure `(prefix, distribution) -> distribution` callbacks. |
| Tests exercise a prefix-dependent grammar and forbidden draft tokens. Effective |
| p must include all actual target constraints; q need not share p's support. |
| The caller supplies a context identity covering target/model/processor policy. |
| An engine must attest that identity and own snapshots of mutable grammar, |
| penalty, stop, Markov and KV state. Unsupported processors must fail or select |
| target-only **before** any proposal draw; this reference cannot validate arbitrary |
| external processor objects or import the real engine on CPU. |
| |
| The tests combine exact enumeration (225 p/q pairs on a three-token grid), |
| normalization/transport checks, frequency tests, conditional joint frequencies |
| at fixed depths 2 and 5, and state/failure regressions. Frequency tolerances are |
| predeclared six binomial standard deviations plus one count; exact algebra, |
| not a finite histogram, establishes the distribution identity. All data are |
| synthetic numbers. No claim about DeepSeek quality or speed follows from them. |
| |
