diff --git a/src/diffusers/loaders/peft.py b/src/diffusers/loaders/peft.py index 3670243de859..211f9da61947 100644 --- a/src/diffusers/loaders/peft.py +++ b/src/diffusers/loaders/peft.py @@ -693,6 +693,8 @@ def unload_lora(self): recurse_remove_peft_layers(self) if hasattr(self, "peft_config"): del self.peft_config + if hasattr(self, "_hf_peft_config_loaded"): + self._hf_peft_config_loaded = None _maybe_remove_and_reapply_group_offloading(self) diff --git a/tests/lora/utils.py b/tests/lora/utils.py index acd6f5f34361..8180f92245a0 100644 --- a/tests/lora/utils.py +++ b/tests/lora/utils.py @@ -291,9 +291,7 @@ def _get_modules_to_save(self, pipe, has_denoiser=False): return modules_to_save - def check_if_adapters_added_correctly( - self, pipe, text_lora_config=None, denoiser_lora_config=None, adapter_name="default" - ): + def add_adapters_to_pipeline(self, pipe, text_lora_config=None, denoiser_lora_config=None, adapter_name="default"): if text_lora_config is not None: if "text_encoder" in self.pipeline_class._lora_loadable_modules: pipe.text_encoder.add_adapter(text_lora_config, adapter_name=adapter_name) @@ -345,7 +343,7 @@ def test_simple_inference_with_text_lora(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config=None) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None) output_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue( @@ -428,7 +426,7 @@ def test_low_cpu_mem_usage_with_loading(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) images_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] @@ -484,7 +482,7 @@ def test_simple_inference_with_text_lora_and_scale(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config=None) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None) output_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue( @@ -522,7 +520,7 @@ def test_simple_inference_with_text_lora_fused(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config=None) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None) pipe.fuse_lora() # Fusing should still keep the LoRA layers @@ -554,7 +552,7 @@ def test_simple_inference_with_text_lora_unloaded(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config=None) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None) pipe.unload_lora_weights() # unloading should remove the LoRA layers @@ -589,7 +587,7 @@ def test_simple_inference_with_text_lora_save_load(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config=None) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None) images_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] @@ -640,7 +638,7 @@ def test_simple_inference_with_partial_text_lora(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config=None) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None) state_dict = {} if "text_encoder" in self.pipeline_class._lora_loadable_modules: @@ -691,7 +689,7 @@ def test_simple_inference_save_pretrained_with_text_lora(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config=None) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None) images_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] with tempfile.TemporaryDirectory() as tmpdirname: @@ -734,7 +732,7 @@ def test_simple_inference_with_text_denoiser_lora_save_load(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) images_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] @@ -775,7 +773,7 @@ def test_simple_inference_with_text_denoiser_lora_and_scale(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) output_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue( @@ -819,7 +817,7 @@ def test_simple_inference_with_text_lora_denoiser_fused(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, denoiser = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, denoiser = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) pipe.fuse_lora(components=self.pipeline_class._lora_loadable_modules) @@ -857,7 +855,7 @@ def test_simple_inference_with_text_denoiser_lora_unloaded(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, denoiser = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, denoiser = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) pipe.unload_lora_weights() # unloading should remove the LoRA layers @@ -893,7 +891,7 @@ def test_simple_inference_with_text_denoiser_lora_unfused( pipe.set_progress_bar_config(disable=None) _, _, inputs = self.get_dummy_inputs(with_generator=False) - pipe, denoiser = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, denoiser = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) pipe.fuse_lora(components=self.pipeline_class._lora_loadable_modules) self.assertTrue(pipe.num_fused_loras == 1, f"{pipe.num_fused_loras=}, {pipe.fused_loras=}") @@ -1010,7 +1008,7 @@ def test_wrong_adapter_name_raises_error(self): pipe.set_progress_bar_config(disable=None) _, _, inputs = self.get_dummy_inputs(with_generator=False) - pipe, _ = self.check_if_adapters_added_correctly( + pipe, _ = self.add_adapters_to_pipeline( pipe, text_lora_config, denoiser_lora_config, adapter_name=adapter_name ) @@ -1032,7 +1030,7 @@ def test_multiple_wrong_adapter_name_raises_error(self): pipe.set_progress_bar_config(disable=None) _, _, inputs = self.get_dummy_inputs(with_generator=False) - pipe, _ = self.check_if_adapters_added_correctly( + pipe, _ = self.add_adapters_to_pipeline( pipe, text_lora_config, denoiser_lora_config, adapter_name=adapter_name ) @@ -1759,7 +1757,7 @@ def test_simple_inference_with_dora(self): output_no_dora_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_dora_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) output_dora_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] @@ -1850,7 +1848,7 @@ def test_simple_inference_with_text_denoiser_lora_unfused_torch_compile(self): pipe.set_progress_bar_config(disable=None) _, _, inputs = self.get_dummy_inputs(with_generator=False) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True) pipe.text_encoder = torch.compile(pipe.text_encoder, mode="reduce-overhead", fullgraph=True) @@ -1937,7 +1935,7 @@ def test_set_adapters_match_attention_kwargs(self): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) lora_scale = 0.5 attention_kwargs = {attention_kwargs_name: {"scale": lora_scale}} @@ -2119,7 +2117,7 @@ def initialize_pipeline(storage_dtype=None, compute_dtype=torch.float32): pipe = pipe.to(torch_device, dtype=compute_dtype) pipe.set_progress_bar_config(disable=None) - pipe, denoiser = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config) + pipe, denoiser = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config) if storage_dtype is not None: denoiser.enable_layerwise_casting(storage_dtype=storage_dtype, compute_dtype=compute_dtype) @@ -2237,7 +2235,7 @@ def test_lora_adapter_metadata_is_loaded_correctly(self, lora_alpha): ) pipe = self.pipeline_class(**components) - pipe, _ = self.check_if_adapters_added_correctly( + pipe, _ = self.add_adapters_to_pipeline( pipe, text_lora_config=text_lora_config, denoiser_lora_config=denoiser_lora_config ) @@ -2290,7 +2288,7 @@ def test_lora_adapter_metadata_save_load_inference(self, lora_alpha): output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] self.assertTrue(output_no_lora.shape == self.output_shape) - pipe, _ = self.check_if_adapters_added_correctly( + pipe, _ = self.add_adapters_to_pipeline( pipe, text_lora_config=text_lora_config, denoiser_lora_config=denoiser_lora_config ) output_lora = pipe(**inputs, generator=torch.manual_seed(0))[0] @@ -2309,6 +2307,25 @@ def test_lora_adapter_metadata_save_load_inference(self, lora_alpha): np.allclose(output_lora, output_lora_pretrained, atol=1e-3, rtol=1e-3), "Lora outputs should match." ) + def test_lora_unload_add_adapter(self): + """Tests if `unload_lora_weights()` -> `add_adapter()` works.""" + scheduler_cls = self.scheduler_classes[0] + components, text_lora_config, denoiser_lora_config = self.get_dummy_components(scheduler_cls) + pipe = self.pipeline_class(**components).to(torch_device) + _, _, inputs = self.get_dummy_inputs(with_generator=False) + + pipe, _ = self.add_adapters_to_pipeline( + pipe, text_lora_config=text_lora_config, denoiser_lora_config=denoiser_lora_config + ) + _ = pipe(**inputs, generator=torch.manual_seed(0))[0] + + # unload and then add. + pipe.unload_lora_weights() + pipe, _ = self.add_adapters_to_pipeline( + pipe, text_lora_config=text_lora_config, denoiser_lora_config=denoiser_lora_config + ) + _ = pipe(**inputs, generator=torch.manual_seed(0))[0] + def test_inference_load_delete_load_adapters(self): "Tests if `load_lora_weights()` -> `delete_adapters()` -> `load_lora_weights()` works." for scheduler_cls in self.scheduler_classes: