modules/attention.py becomes modules/attention/: hijacks.py keeps the six
sdpa monkeypatch setters, dispatcher.py the diffusers-side processor and
dispatcher setup with the kernels hub hijack, and the package facade
re-exports every public name so call sites are unchanged. The devices
import moves inside set_diffusers_attention, which removes the
devices <-> attention import cycle.
A delta that does not fit its target module cannot apply, and applying only
the layers that do fit leaves the model in a state nothing was trained for,
so try_load_chain drops the whole file when any family reports a mismatch.
Bias deltas were never checked against the target bias and could only surface
at apply time; a module with no bias stays a non-mismatch, since whole
architectures are built bias=False.
- check bias deltas against the module bias in the lora, norm and full loaders
- carry the mismatch count on the network so the chain can refuse the file
- record refused writes in the infotext so a partial apply is not read as clean
- point the krea2 full-diff test at a module that has a bias
network_add_weights defaulted its base tensor to self.weight for the bias
delta as well, so in fuse mode a diff_b was added to the weight matrix and
the result written into the bias. Layers where in and out differ threw a
shape error and had the weight matrix installed as their bias, square layers
broadcast silently, and either way the summary still counted the delta as
applied.
- pick the base tensor from the bias flag
- name the layer, target and both shapes in the mismatch error
- return which of (weight, bias) took a write, count the rest as refused
- report refused= on partially applied and partially removed networks
- cover both apply paths in test/test-lora-apply.py
The triton autotune hijack draws its own rich progress bar on the
logger console during sweeps; a second live display on the same
terminal tramples the benchmark's live tables and leaves stale panel
border lines in scrollback. Disarm the bar in the benchmark process
and keep the hijack's bookkeeping.
Write the text and json reports by default, named to the archive
convention <gpu>-t<torch>-<date> with a collision suffix for the pair,
into $SDNQ_BENCH_DIR, --outdir, or benchmarks/ under the sdnext root.
'none' disables either output and explicit paths behave as before.
Its 2.x sibling always did, so only the 0.9 path hit a cpu weight against cuda
latents. Also logs why a run is refused, which until now travelled only in the
raised error.
TAEHV.decode_video already returns [-1,1] and framepack applied its own x2-1 on
top, landing near [-3,1] where the worker documents [-1,1]. The path was
unreachable until the taesd loader began honoring an explicit variant.
run_ltx reported failure by yielding a string, which is why LTX had no API.
run() is the core underneath: keyword arguments named as video_run.run names
them, a VideoResult back, VideoError out with 499 for an interrupt. The lock,
progress and summary stay in the adapter, whose signature is unchanged since
callers bind to it by keyword. Failure now closes the processing object and
deactivates networks, which abort never did.
The gallery branch took an upload handle or a PIL image, so an encoded string
fell through to .convert and was logged as a failed condition. Strings now go
to the api decoder, which reads base64 and upload refs rather than paths.
Both runners round the requested resolution and the two-stage LTX path derives
its own, so the request never recorded what came out. Read it off the decoded
frames instead.
Add accum configs, value-side stress rows, a recommendation row, block
specs, and a triton-mm variant for the new use_fp16_accum surface. The
unsafe unquantized-pv mode is measured but never starred or recommended;
accum rows skip on sdnq builds without the kwarg. Also move the dequant
compile verdict off the removed sdnq_dequantize_compile option to a note
keyed on SDNQ_USE_TORCH_COMPILE, fixing the crash after 2250d8052.
CalamitousFelicitousness
Vladimir Mandic
Dity0
Claude