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
Cached networks are shared objects, and network_load overwrote their
multipliers before network_deactivate ran, so fuse-mode removal recomputed
the subtraction delta with the new values: a strength edit froze at its
first applied value and a later removal left residue in the model weights.
network_load now stages the values on the net and network_activate promotes
them, so the removal pass always subtracts the delta that was applied.
Backup mode restores from stored tensors and was unaffected.
LyCORIS extraction with use_sparse_bias saves bias_indices/bias_values/
bias_size per module: the sparse weight-shaped remainder of the SVD
extraction, named bias for historical reasons. The keys were dropped by
both loader paths, so extracted adapters applied without the residual
correction; the dense-bias branch in finalize_updown that consumes it
was unreachable.
- rebuild the COO tensor in NetworkModule.__init__ (int16 indices cast
to long), shared by the native and generic loaders; kept sparse so
the dense += sparse in finalize_updown materializes per module at
apply instead of near-model-size densification at load
- accept the triplet suffixes in LORA_SUFFIXES; fused targets skip
with the weight-shaped-bias warning
- cover an extraction-faithful numeric round-trip and the fused skip
in the offline suite
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
NetworkModule.multiplier matched text encoders via 'transformer' in the
key prefix, which fits dit keys but never lora_te keys, so text encoder
modules followed unet_multiplier[0] and the te= tag strength was ignored.
NetworkModule.__init__ set self.shape only inside 'if hasattr(sd_module, weight)' but then used len(self.shape) unconditionally, raising AttributeError when a LoRA targets a weightless module. Default shape to None and skip the dora_norm_dims computation when absent.
Co-Authored-By: Claude <noreply@anthropic.com>
NetworkOnDisk.fullname stripped only "/" from the post-lora_dir slice,
leaving a leading "\" on Windows. Every prompt typing the file's
natural dot-form name missed both registered aliases. On Linux,
dot-form lookup already missed when the file lived in any subfolder
because only the subfolder-prefixed form was registered.
- network.py: lstrip both separators and normalize backslashes to
forward slashes so fullname has one canonical shape per OS.
- lora_load.py: register a bare-basename-with-dots alias so typing
<lora:my.lora:1> resolves regardless of subfolder placement.
setdefault preserves explicit primary registrations on cross-subfolder
basename collisions.
Existing prompts using the legacy dots-to-underscores form continue
to resolve via entry.name unchanged.
Replaces anima_lora.py's bespoke try_load_lora / group_keys /
resolve_network_key with thin wrappers binding native_loader's generics
to anima's prefix tuples and resolve_targets, mirroring flux2 / zimage /
chroma / ernie. The hand-rolled apply_lora_alphas bake-with-balance
pass goes away; alpha / scale / dora_scale flow through NetworkWeights.w
to NetworkModule.calc_scale at apply time.
native_loader gains an optional network_prefix kwarg (str or
Callable[[prefix_used], str], default "lora_transformer_") used when
constructing network_key. Anima passes a callable picking
lora_transformer_ / lora_llm_adapter_ / lora_te_ per matched prefix.
Single-component siblings keep the default and are unchanged.
network.NetworkModule.apply_weight_decompose grows a dual-path DoRA
convention detector. The pre-fix implementation only handled per-input
dora_scale (DoRA paper / kohya, shape (1, in)), silently broadcasting
per-output LyCORIS / PEFT dora_scale (shape (out, 1)) into an incoherent
element-wise rescaling. Detection is structural: (out, 1, ...) routes
to per-output; everything else (including the square-weight 1D ambiguity)
defaults to per-input for legacy compat. Pre-existing bug surfaced by
the LoKR+DoRA LyCORIS files Anima now loads.
Behavior changes:
- LoHA via the generic try_load_loha (NetworkModuleHada); covers
scenery-anima-base and any other LyCORIS .hada_w* export.
- Kohya lora_te_ prefix recognized. The legacy resolver only matched
BFL text_encoders.qwen3_06b.transformer.model. and silently dropped
lora_te_layers_N_* keys (41% of BlueArcStyle's bases were unloaded).
- LoKR+DoRA LyCORIS files now apply correctly; the per-output dora_scale
is honored instead of silently scrambled.
Adds test/test-anima-native-adapters.py: 37 offline tests across all
five prefixes (LoRA + LoHA), every COSMOS_2_FLAT_RENAME entry, DoRA
threading, marker disambiguation, try_load_chain dispatch, calc_updown
sanity, and both DoRA conventions (per-input / per-output / 1D ambiguous).
Adapter mock mirrors AnimaLLMAdapter's real module tree.
Dispatch anima loras through a dedicated native loader covering kohya,
bfl/ai-toolkit, and hybrid (bfl with alpha plus qwen3 text encoder)
formats. Cosmos 2.0 path rename is mirrored from diffusers in flat
(underscore) form so rewritten paths match network_layer_mapping keys
without further conversion.
Split model_type from cosmos to anima so a future base-cosmos2 lora
path stays separable. Update flow_models, taesd supported list, and the
taesd wanvideo bucket so samplers and preview decoding keep working
after the split.
Extend assign_network_names_to_compvis_modules to walk pipe.llm_adapter
under the lora_llm_adapter_ prefix, and add llm_adapter to
default_components so activate and deactivate include it for anima
models while staying inert elsewhere via the existing getattr guards.
- detect f2 model type for LoRAs via metadata, architecture, and filename/folder
- preprocess bare BFL-format keys with diffusion_model prefix for Flux2LoraLoaderMixin
- handle LoKR format via native NetworkModuleLokr with on-the-fly kron(w1, w2)
- add NetworkModuleLokrChunk for fused QKV split into separate Q/K/V modules
- activate native modules loaded via diffusers path
- improve error message for Flux1/Flux2 architecture mismatch
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