woolcoxm
86987154f5
The old subprocess.run(capture_output=True) buffered every score result in
memory until the engine exited, then parsed+scored them all at once. If the
engine crashed (or was killed) at request 39/40 you lost everything -- a
multi-hour run with zero information, which is exactly what happened on the
g64 eval against a disk-I/O-bound 400GB model.
Now streams engine stdout line-by-line via Popen:
- each score result lands in the CSV immediately (flushed), with full
provenance (task/qi/oi/gold/logprob/greedy + a header with snap/tasks/
limit/seed/timestamp)
- a [progress] line every 5 requests: N/total, elapsed, req/s, ETA, last
request scored
- the engine's own [score N req] stderr heartbeat streams live too
- on partial completion (crash/kill at request N): keeps 1..N-1, fills the
rest with -inf, and scores the partial results -- never a wasted run
New --out <path> writes the incremental CSV; without it, behaves as before
(results to stdout only). Backward compatible: all existing args unchanged.
Tools
These scripts support model preparation and offline engineering work. They are not runtime dependencies of the C engine.
convert_fp8_to_int4.py,download_glm52.py: model preparationmake_glm_oracle.py,make_glm_bench_model.py: deterministic fixturesbenchmark_cuda_fixture.py,eval_glm.py,fetch_benchmarks.py: benchmarksgen_unicode.py: tokenizer table generation
Run them from c/, for example:
python3 tools/convert_fp8_to_int4.py --selftest
python3 tools/make_glm_bench_model.py --output /tmp/colibri-bench