Method _save_lora_weights

src/diffusers/loaders/lora_base.py:1061–1093

Helper method to pack and save LoRA weights and metadata. This method centralizes the saving logic for all pipeline types.

(
        cls,
        save_directory: str | os.PathLike,
        lora_layers: dict[str, dict[str, torch.nn.Module | torch.Tensor]],
        lora_metadata: dict[str, dict | None],
        is_main_process: bool = True,
        weight_name: str = None,
        save_function: Callable = None,
        safe_serialization: bool = True,
    )

    @classmethod
    def _save_lora_weights(
        cls,
        save_directory: str | os.PathLike,
        lora_layers: dict[str, dict[str, torch.nn.Module | torch.Tensor]],
        lora_metadata: dict[str, dict | None],
        is_main_process: bool = True,
        weight_name: str = None,
        save_function: Callable = None,
        safe_serialization: bool = True,
    ):
        """
        Helper method to pack and save LoRA weights and metadata. This method centralizes the saving logic for all
        pipeline types.
        """
        state_dict = {}
        final_lora_adapter_metadata = {}

        for prefix, layers in lora_layers.items():
            state_dict.update(cls.pack_weights(layers, prefix))

        for prefix, metadata in lora_metadata.items():
            if metadata:
                final_lora_adapter_metadata.update(_pack_dict_with_prefix(metadata, prefix))

        cls.write_lora_layers(
            state_dict=state_dict,
            save_directory=save_directory,
            is_main_process=is_main_process,
            weight_name=weight_name,
            save_function=save_function,
            safe_serialization=safe_serialization,
            lora_adapter_metadata=final_lora_adapter_metadata if final_lora_adapter_metadata else None,
        )

    @classmethod
    def _optionally_disable_offloading(cls, _pipeline):