MiniMaxH3Scheduler counts the terminal sigma in num_inference_steps, so
Steps N ran N-1 evaluations while every other model runs N. The shim
hands the scheduler p.steps + 1, the slider starts at 1, and the PDD
pin records the evaluation count while passing the scheduler its grid
argument. Metadata written before this change counted grid points.
Shift is a property of the trained schedule, not of the step count, so
the tab sliders take absolute values, defaulting to the shipped 12 and
3. video_minimax resolves each request from the request value or the
scheduler config inside apply_overrides, which the tab, the api and
the still path all call, so a request without values lands on the
shipped schedule. The api maps sampler_shift onto the video schedule
and gains audio_shift. Applied values are recorded as Video shift and
Audio shift; the PDD pin records what it enforces.
The tab held the only code that built video and audio references, sniffed the
file type itself, and dropped anything it did not recognize: an unknown
extension, a file that had gone missing, and any decode failure were all skipped
without a word, leaving a request that generated from fewer references than were
uploaded.
Reference marshalling now goes through the same funnel the api path uses, and
runs before the load, so a rejected file costs nothing and says which file and
why. The workflow comes from the registry row, which is where the loader reads
it from as well.
- a rejected input returns its reason to the output box, since the general
handler only reaches the log
- references uploaded against a keyframe workflow warn instead of vanishing:
the accordion hides on a row change but the files it held do not
- guard p.close() in the finally, which the model-not-loaded return has always
reached before p exists
CalamitousFelicitousness
Vladimir Mandic