fix(model-manager): apply Krea-2 LoRAs in kohya key layout

invokeai/backend/model_manager/configs/lora.py

@@ -954,6 +954,16 @@ def _has_complete_lora_pair(state_dict: dict[str | int, Any], prefixes: tuple[st
     "diffusion_model.tproj.",
     "diffusion_model.txtmlp.",
     "diffusion_model.last.linear.",
+    # kohya/LyCORIS flattens that same native layout into `lora_unet_<path>` (see
+    # krea2_lora_conversion_utils._maybe_convert_kohya_krea2_state_dict). Spelled out per top-level module
+    # rather than as a bare `lora_unet_`, which would match every other architecture's kohya LoRA too.
+    "lora_unet_blocks_",
+    "lora_unet_txtfusion_",
+    "lora_unet_first.",
+    "lora_unet_tmlp_",
+    "lora_unet_tproj_",
+    "lora_unet_txtmlp_",
+    "lora_unet_last_linear.",
     "base_model.model.transformer.transformer_blocks.",
     "text_encoder.",
     "base_model.model.text_encoder.",

invokeai/backend/patches/lora_conversions/krea2_lora_conversion_utils.py

@@ -5,6 +5,9 @@
 ``transformer.<module>.lora_A.weight`` / ``lora_B.weight``. The distinctive Krea-2 module is the
 ``text_fusion`` stage, which we use to disambiguate from Qwen-Image / Z-Image LoRAs (which otherwise
 share the ``transformer.transformer_blocks.`` prefix).
+
+Two other key layouts are normalized onto that one before conversion: the native (ComfyUI) module naming,
+and the kohya / LyCORIS layout that additionally flattens the module path into ``lora_unet_<path>``.
 """
 
 import re
@@ -14,6 +17,11 @@
 
 from invokeai.backend.patches.layers.base_layer_patch import BaseLayerPatch
 from invokeai.backend.patches.layers.utils import any_lora_layer_from_state_dict
+from invokeai.backend.patches.lora_conversions.kohya_key_utils import (
+    INDEX_PLACEHOLDER,
+    ParsingTree,
+    insert_periods_into_kohya_key,
+)
 from invokeai.backend.patches.lora_conversions.krea2_lora_constants import (
     KREA2_LORA_QWEN3VL_PREFIX,
     KREA2_LORA_TRANSFORMER_PREFIX,
@@ -94,7 +102,10 @@ def _maybe_convert_native_krea2_state_dict(
         return state_dict
     converted_state_dict: Dict[str, torch.Tensor] = {}
     for key, value in state_dict.items():
-        converted_key = _native_krea2_key_to_diffusers(key) if _looks_like_native_krea2_key(key) else key
+        # `.pt`/`.ckpt` sources can carry non-string keys. They are never native Krea-2 keys, but the
+        # substring tests in `_looks_like_native_krea2_key` raise TypeError rather than returning False.
+        is_native = isinstance(key, str) and _looks_like_native_krea2_key(key)
+        converted_key = _native_krea2_key_to_diffusers(key) if is_native else key
         if converted_key in converted_state_dict:
             raise ValueError(
                 f"Krea-2 LoRA has conflicting layers that normalize to the same target '{converted_key}'. "
@@ -104,6 +115,112 @@ def _maybe_convert_native_krea2_state_dict(
     return converted_state_dict
 
 
+# --- Kohya / LyCORIS (flattened) -> native key mapping ---------------------------------------------------------
+# sd-scripts and LyCORIS flatten the module path (``path.replace(".", "_")``) and prefix it with
+# ``lora_unet_``, e.g. ``lora_unet_blocks_6_attn_wv.lora_down.weight``. Flattening is lossy — nothing in the key
+# records where a '_' used to be a '.' — so we reconstruct the dotted path against the native module vocabulary
+# below and accept it only if it lands on a leaf. A key we cannot reconstruct with certainty is left untouched
+# rather than rewritten into a plausible-looking key that matches no module.
+_KREA2_KOHYA_PREFIX = "lora_unet_"
+
+# Native Krea-2 transformer/text-fusion block leaves. Only the Linears are listed: the non-Linear natives
+# (``mod.lin``, ``prenorm``/``postnorm``, ``attn.qknorm.*``, ``last.norm``/``last.modulation``) have no Linear
+# counterpart in the diffusers layout — ``mod.lin`` for instance is folded into the ``scale_shift_table``
+# parameter — so an adapter targeting them cannot be applied, and renaming it anyway would turn "unsupported"
+# into a silent no-op.
+_NATIVE_KREA2_BLOCK_SUBTREE: ParsingTree = {
+    "attn": {"wq": {}, "wk": {}, "wv": {}, "wo": {}, "gate": {}},
+    "mlp": {"gate": {}, "up": {}, "down": {}},
+}
+
+# Parsing tree for the native (ComfyUI) Krea-2 module layout, i.e. the keys the renames above understand.
+# Walking it resolves the flattened form's only real ambiguity — ``layerwise_blocks`` / ``refiner_blocks`` are
+# the native components that themselves contain an underscore.
+_KREA2_NATIVE_KOHYA_PARSING_TREE: ParsingTree = {
+    "blocks": {INDEX_PLACEHOLDER: _NATIVE_KREA2_BLOCK_SUBTREE},
+    "txtfusion": {
+        "layerwise_blocks": {INDEX_PLACEHOLDER: _NATIVE_KREA2_BLOCK_SUBTREE},
+        "refiner_blocks": {INDEX_PLACEHOLDER: _NATIVE_KREA2_BLOCK_SUBTREE},
+        "projector": {},
+    },
+    "first": {},
+    # Literal indices rather than INDEX_PLACEHOLDER: these are ``nn.Sequential`` stages, and only the
+    # positions listed in ``_NATIVE_KREA2_TOP_LEVEL_RENAMES`` hold a Linear — the rest are activations with
+    # no weights. Accepting any index would rewrite e.g. ``lora_unet_tmlp_1`` into ``tmlp.1.*``, which the
+    # native pass then does not recognize, leaving a half-converted key instead of the untouched original.
+    "tmlp": {"0": {}, "2": {}},
+    "tproj": {"1": {}},
+    "txtmlp": {"1": {}, "3": {}},
+    "last": {"linear": {}},
+}
+
+
+def _kohya_module_path_is_leaf(module_path: str, parsing_tree: ParsingTree) -> bool:
+    """True if a dotted module path walks the tree all the way to a leaf.
+
+    ``insert_periods_into_kohya_key`` only rejects *leftover* tokens, so a prefix of a real path (e.g.
+    ``blocks.0.attn``) parses cleanly without naming a module. Requiring a leaf rejects those.
+    """
+    subtree = parsing_tree
+    for component in module_path.split("."):
+        # Mirror ``insert_periods_into_kohya_key``'s precedence: an exact match wins over the index
+        # placeholder. Without that, a numeric component would always be looked up as INDEX_PLACEHOLDER and
+        # a tree enumerating the specific indices it accepts (``tmlp`` below) could never reach its leaves.
+        if component in subtree:
+            subtree = subtree[component]
+        elif component.isnumeric() and INDEX_PLACEHOLDER in subtree:
+            subtree = subtree[INDEX_PLACEHOLDER]
+        else:
+            return False
+    return not subtree
+
+
+def _unflatten_kohya_krea2_module_path(flat_path: str) -> str | None:
+    """Reconstruct a dotted native Krea-2 module path from its kohya-flattened form.
+
+    Returns ``None`` when the reconstruction is not a native module path this converter can map, in which case
+    the caller must leave the key alone.
+    """
+    try:
+        module_path = insert_periods_into_kohya_key(flat_path, _KREA2_NATIVE_KOHYA_PARSING_TREE)
+    except ValueError:
+        # Tokens left over: not a native Krea-2 module path.
+        return None
+    return module_path if _kohya_module_path_is_leaf(module_path, _KREA2_NATIVE_KOHYA_PARSING_TREE) else None
+
+
+def _maybe_convert_kohya_krea2_state_dict(
+    state_dict: Dict[str, torch.Tensor],
+) -> Dict[str, torch.Tensor]:
+    """Rewrite kohya/LyCORIS flattened Krea-2 keys to the dotted native layout, leaving all others untouched."""
+    converted_state_dict: Dict[str, torch.Tensor] = {}
+    source_keys: dict[str, str] = {}
+    for key, value in state_dict.items():
+        converted_key = key
+        if isinstance(key, str) and key.startswith(_KREA2_KOHYA_PREFIX):
+            # The flattened module path runs up to the first '.'; the weight suffix (``lora_down.weight``,
+            # ``alpha``, ...) follows it. Some writers emit a doubled separator after the prefix.
+            flat_path, dot, weight_suffix = key[len(_KREA2_KOHYA_PREFIX) :].lstrip("_").partition(".")
+            module_path = _unflatten_kohya_krea2_module_path(flat_path)
+            # Only rewrite when ``_group_by_layer`` can split the suffix back off. Un-flattening introduces
+            # dots into the module path, and the grouper's fallback for an unknown suffix is a blind
+            # ``rsplit(".", 2)`` — on a dotted path that cuts *inside the module name*, fusing two modules
+            # into one bogus layer that aborts the whole load. LyCORIS suffixes such as ``.lokr_w1`` or
+            # ``.hada_w1_a`` hit exactly that. Flattened, they have no interior dot and group harmlessly,
+            # so leaving them verbatim keeps them at the pre-existing warn-and-skip behaviour.
+            if module_path is not None and f".{weight_suffix}" in _SUFFIX_TO_VALUE_KEY:
+                converted_key = f"{module_path}{dot}{weight_suffix}"
+        if converted_key in converted_state_dict:
+            raise ValueError(
+                f"Krea-2 LoRA has conflicting layers that normalize to the same target '{converted_key}' "
+                f"(from '{source_keys[converted_key]}' and '{key}'). This mixed layout is unsupported - "
+                "refusing to silently drop one of the layers."
+            )
+        converted_state_dict[converted_key] = value
+        source_keys[converted_key] = str(key)
+    return converted_state_dict
+
+
 def is_state_dict_likely_krea2_lora(state_dict: dict[str | int, torch.Tensor]) -> bool:
     """Checks if the provided state dict is likely a Krea-2 LoRA.
 
@@ -125,7 +242,9 @@ def lora_model_from_krea2_state_dict(state_dict: Dict[str, torch.Tensor], alpha:
     as ``alpha=rank`` internally (the common diffusers default).
     """
     layers: dict[str, BaseLayerPatch] = {}
-    # Normalize native (ComfyUI) naming to the diffusers layout so the rest of the converter is layout-agnostic.
+    # Normalize the kohya/LyCORIS flattened naming (``lora_unet_blocks_6_attn_wv``) to the dotted native layout,
+    # then the native (ComfyUI) naming to the diffusers layout, so the rest of the converter is layout-agnostic.
+    state_dict = _maybe_convert_kohya_krea2_state_dict(state_dict)
     state_dict = _maybe_convert_native_krea2_state_dict(state_dict)
     grouped_state_dict = _group_by_layer(state_dict)
 

tests/backend/model_manager/configs/test_krea2_lora_config.py

@@ -45,6 +45,42 @@ def _diffusion_model_transformer_only_lora() -> MagicMock:
     return mod
 
 
+def _kohya_transformer_only_lora() -> MagicMock:
+    mod = MagicMock()
+    mod.load_state_dict.return_value = {
+        "lora_unet_blocks_0_attn_wq.lora_down.weight": object(),
+        "lora_unet_blocks_0_attn_wq.lora_up.weight": object(),
+    }
+    return mod
+
+
+@patch("invokeai.backend.model_manager.configs.lora.raise_if_not_file")
+def test_explicit_krea2_override_accepts_kohya_transformer_only_lora(_raise_if_not_file) -> None:
+    """The converter understands the flattened kohya layout, so the override escape hatch must too.
+
+    Auto-detection can't reach a transformer-only kohya adapter: it has no `txtfusion` key, and the
+    gated-attention fallback looks for the dotted `.attn.wq.` spelling that flattening destroys.
+    """
+    config = LoRA_LyCORIS_Krea2_Config.from_model_on_disk(
+        _kohya_transformer_only_lora(), {**_REQUIRED_FIELDS, "base": BaseModelType.Krea2}
+    )
+
+    assert config.base is BaseModelType.Krea2
+
+
+@patch("invokeai.backend.model_manager.configs.lora.raise_if_not_file")
+def test_explicit_krea2_override_still_rejects_a_foreign_kohya_lora(_raise_if_not_file) -> None:
+    """The new `lora_unet_` entries are per-module, so another architecture's kohya LoRA is not swept in."""
+    mod = MagicMock()
+    mod.load_state_dict.return_value = {
+        "lora_unet_double_blocks_0_img_attn_proj.lora_down.weight": object(),
+        "lora_unet_double_blocks_0_img_attn_proj.lora_up.weight": object(),
+    }
+
+    with pytest.raises(NotAMatchError):
+        LoRA_LyCORIS_Krea2_Config.from_model_on_disk(mod, {**_REQUIRED_FIELDS, "base": BaseModelType.Krea2})
+
+
 @patch("invokeai.backend.model_manager.configs.lora.raise_if_not_file")
 def test_explicit_krea2_override_accepts_ambiguous_transformer_only_lora(_raise_if_not_file) -> None:
     config = LoRA_LyCORIS_Krea2_Config.from_model_on_disk(

tests/backend/patches/lora_conversions/lora_state_dicts/krea2_lora_kohya_format.py

@@ -0,0 +1,133 @@
+"""Representative key layout of a kohya (sd-scripts) Krea-2 LoRA.
+
+Captured from `Krea2_Don-Martin_LoRA-step00001200.safetensors` (metadata: `ss_base_model_version=krea2`,
+`ss_network_dim=32`, `ss_network_alpha=32`). The full adapter has 264 modules / 792 tensors covering all 28
+transformer blocks and both text-fusion stages; this fixture keeps the first and last transformer block, one
+layerwise and one refiner text-fusion block, and every top-level module.
+
+kohya flattens the module path (`path.replace(".", "_")`) and prefixes it with `lora_unet_`, over the native
+(ComfyUI) module names - so `lora_unet_blocks_6_attn_wv` denotes `transformer_blocks.6.attn.to_v`.
+"""
+
+state_dict_keys: dict[str, list[int]] = {
+    "lora_unet_blocks_0_attn_gate.alpha": [],
+    "lora_unet_blocks_0_attn_gate.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_0_attn_gate.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_0_attn_wk.alpha": [],
+    "lora_unet_blocks_0_attn_wk.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_0_attn_wk.lora_up.weight": [1536, 32],
+    "lora_unet_blocks_0_attn_wo.alpha": [],
+    "lora_unet_blocks_0_attn_wo.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_0_attn_wo.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_0_attn_wq.alpha": [],
+    "lora_unet_blocks_0_attn_wq.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_0_attn_wq.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_0_attn_wv.alpha": [],
+    "lora_unet_blocks_0_attn_wv.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_0_attn_wv.lora_up.weight": [1536, 32],
+    "lora_unet_blocks_0_mlp_down.alpha": [],
+    "lora_unet_blocks_0_mlp_down.lora_down.weight": [32, 16384],
+    "lora_unet_blocks_0_mlp_down.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_0_mlp_gate.alpha": [],
+    "lora_unet_blocks_0_mlp_gate.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_0_mlp_gate.lora_up.weight": [16384, 32],
+    "lora_unet_blocks_0_mlp_up.alpha": [],
+    "lora_unet_blocks_0_mlp_up.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_0_mlp_up.lora_up.weight": [16384, 32],
+    "lora_unet_blocks_27_attn_gate.alpha": [],
+    "lora_unet_blocks_27_attn_gate.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_27_attn_gate.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_27_attn_wk.alpha": [],
+    "lora_unet_blocks_27_attn_wk.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_27_attn_wk.lora_up.weight": [1536, 32],
+    "lora_unet_blocks_27_attn_wo.alpha": [],
+    "lora_unet_blocks_27_attn_wo.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_27_attn_wo.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_27_attn_wq.alpha": [],
+    "lora_unet_blocks_27_attn_wq.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_27_attn_wq.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_27_attn_wv.alpha": [],
+    "lora_unet_blocks_27_attn_wv.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_27_attn_wv.lora_up.weight": [1536, 32],
+    "lora_unet_blocks_27_mlp_down.alpha": [],
+    "lora_unet_blocks_27_mlp_down.lora_down.weight": [32, 16384],
+    "lora_unet_blocks_27_mlp_down.lora_up.weight": [6144, 32],
+    "lora_unet_blocks_27_mlp_gate.alpha": [],
+    "lora_unet_blocks_27_mlp_gate.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_27_mlp_gate.lora_up.weight": [16384, 32],
+    "lora_unet_blocks_27_mlp_up.alpha": [],
+    "lora_unet_blocks_27_mlp_up.lora_down.weight": [32, 6144],
+    "lora_unet_blocks_27_mlp_up.lora_up.weight": [16384, 32],
+    "lora_unet_first.alpha": [],
+    "lora_unet_first.lora_down.weight": [32, 64],
+    "lora_unet_first.lora_up.weight": [6144, 32],
+    "lora_unet_last_linear.alpha": [],
+    "lora_unet_last_linear.lora_down.weight": [32, 6144],
+    "lora_unet_last_linear.lora_up.weight": [64, 32],
+    "lora_unet_tmlp_0.alpha": [],
+    "lora_unet_tmlp_0.lora_down.weight": [32, 256],
+    "lora_unet_tmlp_0.lora_up.weight": [6144, 32],
+    "lora_unet_tmlp_2.alpha": [],
+    "lora_unet_tmlp_2.lora_down.weight": [32, 6144],
+    "lora_unet_tmlp_2.lora_up.weight": [6144, 32],
+    "lora_unet_tproj_1.alpha": [],
+    "lora_unet_tproj_1.lora_down.weight": [32, 6144],
+    "lora_unet_tproj_1.lora_up.weight": [36864, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_gate.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_gate.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_gate.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wk.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wk.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wk.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wo.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wo.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wo.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wq.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wq.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wq.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wv.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wv.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_layerwise_blocks_0_attn_wv.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_down.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_down.lora_down.weight": [32, 6912],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_down.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_gate.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_gate.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_gate.lora_up.weight": [6912, 32],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_up.alpha": [],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_up.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_layerwise_blocks_0_mlp_up.lora_up.weight": [6912, 32],
+    "lora_unet_txtfusion_projector.alpha": [],
+    "lora_unet_txtfusion_projector.lora_down.weight": [32, 12],
+    "lora_unet_txtfusion_projector.lora_up.weight": [1, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_gate.alpha": [],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_gate.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_gate.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wk.alpha": [],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wk.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wk.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wo.alpha": [],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wo.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wo.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wq.alpha": [],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wq.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wq.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wv.alpha": [],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wv.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_refiner_blocks_1_attn_wv.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_mlp_down.alpha": [],
+    "lora_unet_txtfusion_refiner_blocks_1_mlp_down.lora_down.weight": [32, 6912],
+    "lora_unet_txtfusion_refiner_blocks_1_mlp_down.lora_up.weight": [2560, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_mlp_gate.alpha": [],
+    "lora_unet_txtfusion_refiner_blocks_1_mlp_gate.lora_down.weight": [32, 2560],
+    "lora_unet_txtfusion_refiner_blocks_1_mlp_gate.lora_up.weight": [6912, 32],
+    "lora_unet_txtfusion_refiner_blocks_1_mlp_up.alpha": [],
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+}