Kohya->diffusers LoRA key converter fails for Chroma and Flux1, if LoRA is not attention-only

**Describe the bug** [`_convert_mixture_state_dict_to_diffusers`](https://github.com/huggingface/diffusers/blob/0f1abc4ae8b0eb2a3b40e82a310507281144c423/src/diffusers/loaders/lora_conversion_utils.py#L674) converts flat Kohya-style keys like `lora_transformer_transformer_blocks_0_<sublayer>` into dotted diffusers paths. For each key it first sets: ```python diffusers_key = f"transformer_blocks.{i}" ``` and only appends a sublayer suffix (`.attn.to_q`, `.attn.to_out.0`, etc.) when [`"attn_" in k`](https://github.com/huggingface/diffusers/blob/0f1abc4ae8b0eb2a3b40e82a310507281144c423/src/diffusers/loaders/lora_conversion_utils.py#L741). Any non-attention sublayer in the block (e.g. `norm1.linear`, `proj_mlp`, `ff.net`, ...) has no matching branch, so `diffusers_key` is left as the bare block path `transformer_blocks.{i}` — a container module, not a leaf parameter. The converter still writes this as `transformer_blocks.{i}.lora_A.weight` / `.lora_B.weight`. Downstream, [`_maybe_expand_lora_state_dict`](https://github.com/huggingface/diffusers/blob/0f1abc4ae8b0eb2a3b40e82a310507281144c423/src/diffusers/loaders/lora_pipeline.py#L2179) strips the LoRA suffix to look up the [base parameter](https://github.com/huggingface/diffusers/blob/0f1abc4ae8b0eb2a3b40e82a310507281144c423/src/diffusers/loaders/lora_pipeline.py#L2203): ```python base_weight_param = transformer_state_dict[base_param_name] # base_param_name = "transformer_blocks.0.weight" ``` This raises `KeyError`, since no such parameter exists. **Reproduction** Load any Kohya-style LoRA (prefix `lora_transformer_...`, the format handled by `_convert_mixture_state_dict_to_diffusers`) into a Flux- or Chroma-based pipeline where the LoRA touches a non-attention sublayer (e.g. `norm1.linear`, `proj_mlp`) of a transformer block: ```python from diffusers import DiffusionPipeline import torch pipe = DiffusionPipeline.from_pretrained("<flux-or-chroma-repo>", torch_dtype=torch.bfloat16) pipe.load_lora_weights("<path-to-lora-with-non-attention-sublayer-keys>.safetensors") ``` **Logs** ``` Traceback (most recent call last): File ".../diffusers/loaders/lora_pipeline.py", line 1691, in load_lora_weights transformer_lora_state_dict = self._maybe_expand_lora_state_dict( File ".../diffusers/loaders/lora_pipeline.py", line 2203, in _maybe_expand_lora_state_dict base_weight_param = transformer_state_dict[base_param_name] KeyError: 'transformer_blocks.0.weight' ``` **System Info** - `diffusers` version: 0.38.0.dev0 (main) - Python: 3.12.3 - Platform: Linux-6.8.0-36-generic-x86_64-with-glibc2.39 **Who can help?** @sayakpaul @yiyixuxu --- Drafted by Claude