finalize_updown ran apply_weight_decompose on the unscaled delta and
multiplied the result by alpha/rank afterward. LyCORIS and ComfyUI both
bake alpha/rank into the diff before computing the row norms, so any
DoRA with alpha != rank renormalized against the wrong merged weight
(64% relative delta error for kohya-style alpha=1 rank=8; exact only
when alpha == rank, which full-matrix LoKR forces).
- scale updown by calc_scale() before apply_weight_decompose; apply
only the multiplier afterward
- multiplier lerps the full merged delta (0 disables, 1 equals the
trainer output); LyCORIS weight-mode ratio interpolation leaves the
diff applied at multiplier 0 and is not used
- add a numeric regression test mirroring the LyCORIS forward reference
A diff_b bias delta on a fused BFL target passed through whole and
failed at apply with a shape mismatch. diff_b stores one value per
output feature, so it partitions with the fused rows exactly like the
up-weight; slice it with the chunk in the LoRA loader. The legacy
weight-shaped bias key (LyCORIS sparse-residual heritage) has no
defined partition on a fused target and no known emitter pairs it with
chunk-capable families, so the group is skipped with a warning in the
LoRA, LoKR and LoHA loaders.
- add slice_bias_delta beside slice_dora_scale; warn and skip
non-per-output diff_b shapes
- cover sliced diff_b flowing out as ex_bias and the legacy-bias skip
in the offline suite
A LoKR group whose Kronecker product does not fit the resolved module
previously bound anyway and failed at apply time as a caught per-module
error, leaving the adapter partially applied with only an error log.
Reject the group at load with a warning instead, matching the LoRA
path's shapes_match gate.
- lokr_kron_shape derives (out, in_flat) from full, rank-decomposed or
Tucker-rebuilt factors, folding conv kernel dims into in_flat
- lokr_shapes_match honors SDNQ original shapes and chunk partitions:
equal chunks need total * out rows, row-range slices an exact range;
the input dim is never chunked
- cover non-fused and fused rejection in the offline suite
LyCORIS wd=True saves a dora_scale companion for LoRA/LoHA/LoKR; on
fused BFL targets the chunk paths passed it through whole, so apply
failed with a shape mismatch and the module was dropped. Per-output
magnitudes (wd_on_out=True, the default) partition exactly with the
fused rows; per-input magnitudes couple the chunks through shared
column norms and have no exact split.
- slice per-output dora_scale rows with the chunk in the LoRA, LoKR
and LoHA loaders
- skip per-input DoRA on fused targets with a specific warning
- cover sliced and skipped orientations in the offline suite
The lycoris_ save format is arch-independent: LyCORIS standalone wraps
the loaded diffusers model and emits the wrapped module path with dots
as underscores, so verbatim passthrough is correct for any arch. Only
flux2 handled it; zimage, chroma, ernie and krea2 reported such files
as not loaded.
- add lycoris_ to KNOWN_PREFIXES_DEFAULT and PASSTHROUGH_PREFIXES_DEFAULT
- drop flux2's per-arch prefix append and resolve_targets branch
- add lycoris_ to ANIMA_PREFIXES (anima replaces the default tuple);
network_prefix_for already routes it to the transformer namespace
- cover the passthrough with a zimage loader test
The refine toggle doubles as the slot selector on the UNet/DiT page:
with it active a card click sets sd_unet_secondary instead of sd_unet,
mirroring base/refiner selection on the model page.
detect_quant now reads _quantization_metadata as the authoritative quant
source when present, and resolves marker-file formats from the marked
layers' stored weight dtypes instead of file-wide dtype voting, which
mislabeled fp8 files carrying extra uint8 tensors and had no nvfp4
mapping at all. Schema bump so cached probe entries refresh.
Triton has no e4m3 conversions before sm_89, so any compiled graph
touching fp8 storage weights fails with an InductorError on Ampere.
Select the eager dequant and re-quantize paths for e4m3 weights when
the hardware cannot compile them; other dtypes keep compiled dequant.
SDNQ_ALLOW_FP8_COMPILE overrides the detection.
The secondary unet loads from the networks panel toggle or the settings
page; companion ordering and dynamic visibility pushes in ui_settings.py
are not worth their footprint for one setting.
The hidden change_refiner button passed key='sd_model_checkpoint', so
loading a card with the refine toggle active reloaded the base model
and never set sd_model_refiner.
json_helpers does its own error handling and file locking, so the
try/except wrappers, threading locks and isfile checks were dead
weight; probe cache file paths are now defined in paths.py.
One UNET override cannot serve dual-transformer arches: ideogram4
conditional/unconditional and wan combined-stage experts need separate
files, and previously a single override landed on both experts.
- sd_unet_secondary option with per-slot tracking, consumed-state sync,
arch-change reset, and incompatible-override fallback
- dropdown renders beside the primary, follows it into quicksettings,
and is visible only for dual-transformer model types
- ideogram4 native single-file spec with a quant-aware fused-qkv
converter; such converters run before comfy_quant detection via
TransformerSpec.converter_handles_quant
- quicksettings render in configured order (sort keyed on the option
object and always fell back to alphabetical)
- post-load dtype warning skips quantized transformers
fp8_e4m3fn and fp8_e5m2 differ in kernel support, so a bare fp8 token
is not enough to know whether a file runs on a given architecture;
scaled_fp8 derives its token from the detected format.
Local probes read the marker tensor bytes for the true format string
(nvfp4, mxfp8, int8_tensorwise) instead of inferring from weight
dtypes; remote ranged peeks stay dtype-inferred. precision_token maps
quant format or dominant dtype to the short filename token.
peek-header now returns the full probe (architecture fingerprint,
dtypes, quant scheme) alongside the metadata block, and caches the
response persistently by civitai file id; file content per id is
immutable, so cached probes skip the ranged fetch entirely.
Analyzes safetensors/gguf headers without reading weights: curated
tensor-name fingerprints for common families, container kind detection
(model/lora/vae/text-encoder), element-weighted precision over core
tensors, comfy_quant/scaled-fp8/gguf quant detection, lora base
resolution via trainer metadata with shape arbitration, and full
__metadata__ passthrough. Results cached by mtime in
data/model_probe.json.
- analyze_header is pure and shared by remote ranged peeks and local
file reads
- fingerprints verified against the local library and live civitai
headers; unmatched families report unknown rather than guessing
The API carries no field distinguishing dual-transformer expert files;
conversion tools embed it in the header __metadata__. peek-header
range-fetches the JSON header and returns the metadata block without
downloading the file. Restricted to civitai.com urls.
Versions bundle companion files typed by the file, not the model;
'Text Encoder' had no TYPE_MAP entry so companions landed in the
checkpoint folder where the loader never scans.
Interrupted downloads leave url-hash .tmp resume files that nothing
cleans up; the queue that knows about them is in-memory only.
- iter_type_roots lists every folder downloads resolve into
- partials older than 7 days by mtime are deleted when the download
manager starts; active partials always have a fresh mtime
Multi-variant versions serve one canonical filename per file; the
precision, size class, format, and scan status that distinguish them
were dropped at the model layer.
- CivitFile gains metadata (format, size, fp), pickle and virus scan
results, and scannedAt
History entries stored only the query or tag term, so restoring a
search dropped every filter, and filter-only browsing was never
recorded at all.
- SearchHistory.add takes an optional params dict stored on the entry
- get_search records non-default filters: type, sort, period, base
models, nsfw, username, favorites
- filter-only searches are recorded as 'filter' entries labeled with
the filter values
A 200 reply to a resumed download carries the full file, not the
remainder; appending it to the partial produced a corrupt file that
passed the size check and only failed at hash verification. Truncate
the temp file and restart from byte 0 when a Range request comes back
as 200 instead of 206.
The /model-versions endpoint now serializes availability as null, which
failed str validation and turned every version lookup into a 404. Coerce
null to the default like the creator username validator already does.
Pass through earlyAccessEndsAt and earlyAccessConfig so clients can see
that a download requires a Buzz purchase before requesting the file.
CalamitousFelicitousness
Disty0
Vladimir Mandic