* Studio: keep the training event pump alive so progress can't silently freeze
The parent-side event pump is the only writer of the in-memory progress state
that SSE /progress, /status, /metrics and the DB history all read. It ran in a
single unsupervised daemon thread with no guard around event handling, so one
malformed event or a transient queue/DB error would terminate it permanently.
The worker subprocess keeps training regardless (mp.Queue puts never block on an
unbounded queue), so a run kept burning GPU for hours while every progress
surface froze on the last step the pump saw.
- Guard each pump iteration: a bad event or queue-read error is logged and
skipped instead of ending the loop. _read_queue now reads any error as
"no event", not just Empty/EOFError/OSError/ValueError.
- Add a _pump_running flag and an _ensure_pump_alive watchdog wired into
is_training_active, so a pump that dies while the worker is alive is restarted
on the next status poll and the UI catches up from the still-open queue.
- Start respawned and restarted pumps under the lock so the watchdog can never
spawn a duplicate during the brief start window.
Adds tests/test_training_pump_resilience.py covering both guarantees.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio training pump: address review (drain guard, start race, read backoff, respawn flag)
Follow-up to the event-pump resilience change, closing four edge cases a
review surfaced in the same pump/queue surface:
- _drain_queue now tolerates any error during the worker-exit drain and
finalizes with whatever it drained, instead of skipping finalization and
leaving the run wedged "active" with a dead worker.
- start_training clears a stale _pump_running flag during reset and assigns
the subprocess handles plus starts the pump under the lock, so a concurrent
status/SSE poll can't spawn a duplicate pump during setup.
- _read_queue goes back to the narrow EOFError/OSError/ValueError catch;
truly unexpected errors are left to _pump_loop's guarded read, which logs
and backs off so a persistently raising queue can't spin a hot loop.
- The xet respawn-failure path clears _pump_running so a later run can't
inherit a stale flag.
Adds regression tests for all four.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: revive a crashed pump after worker exit + stop test module pollution
Two review follow-ups on the training event pump:
- _ensure_pump_alive refused to restart once the worker had exited
(not self._proc.is_alive()), so a pump that crashed just before the worker
finished never drained the terminal complete/error events still sitting in
the queue. progress.is_training stayed True and is_training_active() returned
True forever, leaving the run stuck "running" behind a dead pump. A True
_pump_running flag with a dead thread is an unambiguous crash regardless of
worker state, so restart there too: the fresh pump drains the backlog and
finalizes. Updated the watchdog test to assert the revive-and-finalize.
- The resilience test imports core.training.training while heavy module-level
deps are stubbed, then restores the stubs -- but the cached training module
kept the stubs bound in its globals, so a later test in the same session
could exercise the fakes (e.g. prepare_gpu_selection) instead of the real
code. Evict the training module (and its package) after import when this file
created it, so subsequent tests re-import it cleanly.
* Studio: finalize training run when queue reads keep failing on a dead worker
reviewer.py follow-up. _read_queue only swallows EOFError/OSError/ValueError;
an unexpected error escapes to the pump's outer guard, which logged, slept and
`continue`d. If those reads keep raising after the worker has already exited
(e.g. a broken queue pipe), the loop never reaches the dead-worker finalize
block, so the pump spins on with _pump_running True and progress.is_training
stuck True -- the run looks like it is still training forever. On a read failure
now fall through to finalize when the worker is gone, only backing off and
retrying while it is still alive. Mirrors the data-recipe pump fix; added a
regression test.
* Tighten training pump resilience comments and docstrings
Condense the verbose explanatory comments and docstrings on the training event
pump and its tests to shorter, clearer forms. Comment/whitespace only; verified
no code changed via AST diff. No behaviour change.
* Studio: create the training DB run before starting the event pump
start_training started the event pump before the eager _ensure_db_run_created()
call, so for a worker that completes or fails immediately the pump could race the
main thread into creating and finalizing the same run row (duplicate INSERT, or a
finalize skipped while _db_run_created was still false). Create the run first; the
pump then only ever finalizes. Adds a regression test asserting the pump observes
an already-created run.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
1cb04be328