docs: cleanup

modules/lora/native_adapter.py

@@ -1,7 +1,6 @@
 """Shared scaffolding for native adapter loaders.
 
-The four native adapter loaders (z-image, chroma, ernie, flux2) all implement
-the same algorithm:
+Each per-arch native adapter loader implements the same algorithm:
 
 1. Read the safetensors state dict
 2. Test for family-specific markers; bail out if absent
@@ -25,7 +24,7 @@ diffusers paths plus optional chunk descriptors).
 
 Per-arch loader modules import this module and pass their own ``prefixes``,
 ``bare_prefixes``, ``bare_diffusers_prefixes``, and ``resolve_targets`` to the
-generic helpers. Loader business logic itself lands in subsequent commits.
+generic helpers.
 """
 
 import os
@@ -45,7 +44,8 @@ from modules.lora import lora_common as l
 
 
 # Universal prefix list shared by every native arch loader. Per-arch loaders
-# extend this with arch-specific entries (e.g. flux2 adds ``"lycoris_"``).
+# extend this with arch-specific entries when their files use additional
+# vendor-specific naming conventions.
 KNOWN_PREFIXES_DEFAULT = ("diffusion_model.", "transformer.", "lora_unet_")
 
 
@@ -56,9 +56,10 @@ KNOWN_PREFIXES_DEFAULT = ("diffusion_model.", "transformer.", "lora_unet_")
 BARE_DIFFUSERS_PREFIX_USED = "bare_diffusers"
 
 
-# Default network-key prefix. Single-component arches (flux2, zimage, chroma,
-# ernie) keep this default; multi-component arches (anima: transformer plus
-# llm_adapter plus text_encoder) pass a callable that picks per ``prefix_used``.
+# Default network-key prefix. Single-component arches keep this default;
+# multi-component arches (those with separate text-encoder or adapter
+# components alongside the transformer) pass a callable that picks per
+# ``prefix_used``.
 NETWORK_PREFIX_DEFAULT = "lora_transformer_"
 
 

pipelines/ernie/__init__.py

@@ -1,23 +1,17 @@
 """ERNIE-Image pipeline package.
 
-Exports :data:`ERNIE_SPEC` for use by :mod:`pipelines.model_ernie` together
-with :mod:`pipelines.native_transformer`. The spec captures the
-ERNIE-Image-specific knobs that differ from the native-loader defaults:
+Exports :data:`ERNIE_SPEC`. The minimum
+``TransformerSpec(cls=ErnieImageTransformer2DModel)`` works because Ernie
+trainer dumps use BFL-style ``model.diffusion_model.``-prefixed keys
+whose names match the diffusers state_dict verbatim after prefix strip
+(probed against a community finetune: full key overlap with zero
+missing or unexpected). No siblings, no converter, no forbidden markers.
 
-- No converter is needed: community Ernie trainer dumps use BFL-style keys
-  (``model.diffusion_model.``-prefixed) whose names match diffusers'
-  ``ErnieImageTransformer2DModel.state_dict()`` verbatim after prefix strip.
-  Probed against ``jibMixErnie_v20.safetensors`` (the upstream community
-  finetune): 409/409 keys overlap with zero missing or unexpected.
-- No siblings; no forbidden markers; default prefixes
-  (``model.diffusion_model.``, ``diffusion_model.``, ``net.``) cover every
-  exporter seen in the wild.
-
-Before this spec, selecting an Ernie finetune via the UNET dropdown crashed
-in :func:`diffusers.loaders.ModelMixin.from_pretrained` with a misleading
-``OSError: ... is not a valid JSON file`` because
-``ErnieImageTransformer2DModel`` lacks ``from_single_file`` support and the
-fallback path treats the safetensors as a directory looking for
+Without this spec, selecting an Ernie file via the UNET dropdown crashes
+in :func:`diffusers.loaders.ModelMixin.from_pretrained` with a
+misleading ``OSError: ... is not a valid JSON file``, because
+``ErnieImageTransformer2DModel`` lacks ``from_single_file`` and the
+fallback treats the safetensors as a directory looking for
 ``config.json``.
 """
 

pipelines/qwen/__init__.py

@@ -1,17 +1,12 @@
 """Qwen-Image pipeline package.
 
-Exports :data:`QWEN_SPEC` for use by :mod:`pipelines.model_qwen` together
-with :mod:`pipelines.native_transformer`. Qwen-Image is the lone Mode C
-arch: diffusers registers a no-op identity lambda as its
-``SINGLE_FILE_LOADABLE_CLASSES`` converter, so ``from_single_file`` silently
-accepts whatever key naming the community file uses and loads with mangled
-weights instead of raising.
-
-The spec explicitly sets ``converter=None`` to short-circuit the no-op
-pickup; if a real Qwen-Image converter is needed for some trainer dump
-in the wild, it can be plugged in here. Until then, validation surfaces a
-clear error listing unexpected/missing keys instead of letting a malformed
-file load silently.
+Exports :data:`QWEN_SPEC`. diffusers registers a no-op identity lambda
+for ``QwenImageTransformer2DModel`` in ``SINGLE_FILE_LOADABLE_CLASSES``,
+so ``from_single_file`` silently accepts whatever key naming the file
+uses and loads with mismatched weights. The spec sets ``converter=None``
+explicitly to skip that no-op; validation then surfaces mismatches as
+clear errors. A real converter can be plugged in here if a trainer
+format that needs one is encountered.
 """
 
 import diffusers

test/test-anima-native-adapters.py

@@ -8,7 +8,7 @@ custom Qwen3-projection MLP), or ``lora_te_*`` (Qwen3 text encoder). Routing
 is parameterized in ``modules.lora.native_adapter`` via the ``network_prefix``
 callable that ``pipelines.anima.anima_lora`` supplies.
 
-Covers the eight families exposed through native_adapter's generics (LoRA,
+Covers the families exposed through native_adapter's generics (LoRA,
 LoKR, LoHA, OFT, IA3, GLoRA, Norm, Full), focused on:
 
 - LoRA across all five recognized prefixes (BFL transformer / BFL llm_adapter /

test/test-flux2-native-adapters.py

@@ -2,8 +2,8 @@
 """
 Offline unit tests for Flux2/Klein native adapter loaders.
 
-Covers the nine native families (LoRA, LoKR, LoHA, OFT, BOFT, IA3,
-GLoRA, Norm, Full) plus DoRA threading via the universal
+Covers the native families (LoRA, LoKR, LoHA, OFT, BOFT, IA3, GLoRA,
+Norm, Full) plus DoRA threading via the universal
 NetworkModule.finalize_updown hook, and ex_bias accumulation across
 stacked Norm adapters.