…n, finalize_huggingface_model

- patch_gemma4_vllm_lora_support: use functools.wraps on patched_create_lora_manager so
  _call_create_lora_manager's signature inspection still sees vllm_config; pass model
  positionally to lora_manager_cls to avoid "multiple values for 'model'".
- patch_gemma4_vllm_k_eq_v_support: also handle split k_proj/v_proj layout (current
  upstream Gemma4) by duplicating k quant-state to synthetic v entry; keep packed
  qkv_proj path as fallback.
- load_vllm: gate Gemma4 patches on enable_lora / use_bitsandbytes (not is_vision_model),
  so text-only Gemma4 + LoRA / BnB also works.
- extract_gdn_layers: derive qkvz offsets from gdn.key_dim/value_dim when
  ColumnParallelLinear has no output_sizes; manually split in_proj_ba into b/a instead
  of calling get_state_dict with kk=1 (IndexError); preserve BnB quant_state sidecars;
  handle FP8 weight_scale (not only weight_scale_inv) and dynamic/row-wise FP8;
  export linear_attn.norm.weight.
- finalize_huggingface_model: fix layer_idx for standard causal LMs (not only VLM path);
  rebuild Gemma4 vision rotary_emb from vision_config with fp32 buffers; guard
  rotary_pos_emb on vision_config availability; mirror language_model detection from
  set_additional_modules.
- get_model_layer_config: register Gemma4 per_layer_input_gate / per_layer_projection /
  post_per_layer_input_norm; add Qwen3.5 visual.merger.linear_fc1 / linear_fc2 and drop
  the broken linear_fc{kk} template.
- set_dtype_in_config (hf_utils): prefer the modern 'dtype' field; fall back to
  'torch_dtype' only when 'dtype' is absent, avoiding the deprecation warning on
  current transformers.
- vllm_utils state-dict loop: skip layer.mlp extraction for linear-attn-only layers
  (defensive) while still capturing layer_scalar.
- _normalize_state_dict_tensor: guard is_sparse behind isinstance(value, torch.Tensor)
  so non-tensor state-dict values pass through.