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
MiniMax-H3 conditions on image, video and audio references, and the limits it
enforces on them are constructor defaults on a block class the package does not
re-export, so they cannot be imported and are mirrored here instead.
The resolver takes decoded images and local file paths and returns the reference
objects the pipeline reads, checking cheapest first: classification and counts
open no files, container headers are read without decoding, and only then is the
media decoded. Everything runs before the model load, so a rejected request costs
nothing.
- reference limits as a frozen dataclass, keyed by workflow since the rows that
carry ref2va differ only in which repo they load
- media classification and container probing as generic video helpers
- a url is refused before construction: the reference classes fetch one and
decode whatever comes back
- a video is bounded by duration and by what it decodes to, since the pipeline
truncates it to the generated length and the decode is held across the load
- the frame floor is counted on the decoded video at the rate it resamples to,
which is what the conditioner measures
- torchaudio and av are checked up front rather than surfacing as an import
failure once the weights are resident
Vladimir Mandic
CalamitousFelicitousness