Method delete_adapters

src/diffusers/loaders/lora_base.py:839–875

Delete an adapter's LoRA layers from the pipeline. Args: adapter_names (`list[str, str]`): The names of the adapters to delete. Example: ```py from diffusers import AutoPipelineForText2Image import torch pipelin

(self, adapter_names: list[str] | str)

                    enable_lora_for_text_encoder(model)

    def delete_adapters(self, adapter_names: list[str] | str):
        """
        Delete an adapter's LoRA layers from the pipeline.

        Args:
            adapter_names (`list[str, str]`):
                The names of the adapters to delete.

        Example:

        ```py
        from diffusers import AutoPipelineForText2Image
        import torch

        pipeline = AutoPipelineForText2Image.from_pretrained(
            "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
        ).to("cuda")
        pipeline.load_lora_weights(
            "jbilcke-hf/sdxl-cinematic-1", weight_name="pytorch_lora_weights.safetensors", adapter_names="cinematic"
        )
        pipeline.delete_adapters("cinematic")
        ```
        """
        if not USE_PEFT_BACKEND:
            raise ValueError("PEFT backend is required for this method.")

        if isinstance(adapter_names, str):
            adapter_names = [adapter_names]

        for component in self._lora_loadable_modules:
            model = getattr(self, component, None)
            if model is not None:
                if issubclass(model.__class__, ModelMixin):
                    model.delete_adapters(adapter_names)
                elif issubclass(model.__class__, PreTrainedModel):
                    for adapter_name in adapter_names:
                        delete_adapter_layers(model, adapter_name)

    def get_active_adapters(self) -> list[str]:
        """