feat(chroma): native loader for chroma lora

Add a per-model native LoRA path for Chroma that handles both PEFT-style
(diffusion_model.<dotted>.lora_A.weight, no alpha) and kohya-flat
(lora_unet_<flat> with .alpha) layouts, plus LoKR/LoHA/OFT/DoRA.

Resolves issue #4169 (ostris ai-toolkit Chroma LoRAs failed to load).

- new pipelines/chroma/chroma_lora.py with try_load_lora/lokr/loha/oft
- fused-QKV expansion: 3-way equal for img/txt qkv, 4-way unequal
  [3072, 3072, 3072, 12288] for single linear1 (Q+K+V+proj_mlp)
- NetworkModuleLokrSliceChunk for unequal-row LoKR slicing
- path rewrite from Flux-source to ChromaTransformer2DModel naming
- lora_load.py: dispatch chroma to the native loader and narrow the
  kohya-Flux convert gate to f1 only

modules/lora/lora_load.py

@@ -86,10 +86,25 @@ def load_safetensors(name, network_on_disk: network.NetworkOnDisk) -> network.Ne
         if ernie_net is not None:
             lora_cache[name] = ernie_net
         return ernie_net
+    if shared.sd_model_type == 'chroma':
+        from pipelines.chroma import chroma_lora
+        lora_scale = shared.opts.extra_networks_default_multiplier
+        chroma_net = None
+        for try_fn in (chroma_lora.try_load_lora, chroma_lora.try_load_lokr, chroma_lora.try_load_loha, chroma_lora.try_load_oft):
+            sub = try_fn(name, network_on_disk, lora_scale)
+            if sub is None:
+                continue
+            if chroma_net is None:
+                chroma_net = sub
+            else:
+                chroma_net.modules.update(sub.modules)
+        if chroma_net is not None:
+            lora_cache[name] = chroma_net
+        return chroma_net
     net = network.Network(name, network_on_disk)
     net.mtime = os.path.getmtime(network_on_disk.filename)
     state_dict = sd_models.read_state_dict(network_on_disk.filename, what='network')
-    if shared.sd_model_type in ['f1', 'chroma']: # if kohya flux lora, convert state_dict
+    if shared.sd_model_type == 'f1': # if kohya flux lora, convert state_dict
         state_dict = lora_convert._convert_kohya_flux_lora_to_diffusers(state_dict) or state_dict # pylint: disable=protected-access
     if shared.sd_model_type == 'sd3': # if kohya flux lora, convert state_dict
         try: