The infotheory binary is available only when the cli feature is enabled:
cargo build -p infotheory --release --features cli --bin infotheory --lockedFor local development, the same commands can be run through Cargo:
cargo run -p infotheory --features cli -- <command> [args...] [options]The top-level help is intentionally short:
infotheory --helpUse topic help for details:
infotheory help backends
infotheory help compression
infotheory help generation
infotheory help batch
infotheory help aixi
infotheory help warmstart
infotheory help tune
infotheory help diagnostics
infotheory help sequitur
infotheory help searchRepresentative command help also routes to the matching topic:
infotheory ncd --help
infotheory generate --help
infotheory warmstart --help
infotheory tune --helpSingle-file metrics:
infotheory h README.md
infotheory h_rate README.md --rate-backend ctw --method 32
infotheory id README.md --rate-backend fac-ctw --method 32 --msb-firstTwo-file metrics:
infotheory mi a.bin b.bin
infotheory mi a.bin b.bin --rate-backend ctw --method 16
infotheory ned a.bin b.bin
infotheory nte a.bin b.bin
infotheory kl a.bin b.bin
infotheory js a.bin b.binh and the empirical two-file metrics use order-0 byte statistics unless a rate
backend is explicitly selected. h_rate always uses the active rate backend.
Common backend options:
--rate-backend <name>
--compression-backend <name>
--method <value>
--rate-backend-json <path>
--compression-backend-json <path>
--expert-spec <path>
--model-export <path>Use infotheory help backends for the feature-dependent backend list reported
by the binary you built.
Canonical JSON inputs are preferred when a backend is produced by another InfoTheory tool, especially tuner output. Relative asset paths inside canonical backend JSON resolve against the JSON file's directory.
infotheory ncd a.bin b.bin --compression-backend zpaq --method 5
infotheory ncd a.bin b.bin --compression-backend rate-ac --rate-backend ctw --method 16
infotheory compress in.bin out.itc --compression-backend rate-rans --rate-backend fac-ctw --method 32
infotheory decompress out.itc restored.bin --compression-backend rate-rans --rate-backend fac-ctw --method 32Use rate-ac or rate-rans when the compressor should be driven by a
predictive RateBackend.
cat prompt.txt | infotheory generate --rate-backend ctw --method 32 --bytes 8
infotheory generate prompt.txt --rate-backend match --bytes 16 --sample --seed 7Generation supports greedy or sampled continuation, top-k/top-p filtering, and
adaptive continuation. See infotheory help generation.
aixi executes canonical planner_run documents:
infotheory aixi configs/aixi/paper_kuhn_poker.jsonLegacy pre-1.2 AIXI JSON configs are rejected. Convert them with:
./projman.sh legacy_aixi_convert <input_file>warmstart tools export, convert, and merge exact-J_H teacher datasets:
infotheory warmstart teacher planner-run --target target.json --teacher teacher.json --out teacher-dataset.json
infotheory warmstart teacher from-jsonl --target target.json --jsonl run.jsonl --out teacher-dataset.json
infotheory warmstart teacher merge --target target.json --out merged.json --teacher a.json --teacher b.jsontune executes canonical tune JSON or binary spec documents:
infotheory tune examples/tuner/strict-smoke-spec.json --max-evaluations 1The tuner has many executor and certificate controls; keep those in topic help and tuner docs rather than top-level help.
RAYON_NUM_THREADS=4 infotheory ac-log-loss corpus.bin \
--mixture configs/bench/mixture.json \
--out-prefix /tmp/mixture-diagnostic
infotheory sequitur-debug --hex 616263616263 --alphabet-prefix 8ac-log-loss writes <prefix>.trace.tsv, <prefix>.nodes.tsv, and
<prefix>.summary.tsv. ctw-profile is available only when the binary is built
with backend-ctw research-tooling.