diff --git a/docs/source/en/training/distributed_inference.md b/docs/source/en/training/distributed_inference.md index 8e68b1bed382..0e1eb7962bf7 100644 --- a/docs/source/en/training/distributed_inference.md +++ b/docs/source/en/training/distributed_inference.md @@ -237,5 +237,3 @@ with torch.no_grad(): ``` By selectively loading and unloading the models you need at a given stage and sharding the largest models across multiple GPUs, it is possible to run inference with large models on consumer GPUs. - -This workflow is also compatible with LoRAs via [`~loaders.StableDiffusionLoraLoaderMixin.load_lora_weights`]. However, only LoRAs without text encoder components are currently supported in this workflow. diff --git a/src/diffusers/loaders/lora_base.py b/src/diffusers/loaders/lora_base.py index a13f8c20112a..e124b6eeacf3 100644 --- a/src/diffusers/loaders/lora_base.py +++ b/src/diffusers/loaders/lora_base.py @@ -31,7 +31,6 @@ delete_adapter_layers, deprecate, is_accelerate_available, - is_accelerate_version, is_peft_available, is_transformers_available, logging, @@ -215,18 +214,9 @@ def _optionally_disable_offloading(cls, _pipeline): is_model_cpu_offload = False is_sequential_cpu_offload = False - def model_has_device_map(model): - if not is_accelerate_available() or is_accelerate_version("<", "0.14.0"): - return False - return getattr(model, "hf_device_map", None) is not None - if _pipeline is not None and _pipeline.hf_device_map is None: for _, component in _pipeline.components.items(): - if ( - isinstance(component, nn.Module) - and hasattr(component, "_hf_hook") - and not model_has_device_map(component) - ): + if isinstance(component, nn.Module) and hasattr(component, "_hf_hook"): if not is_model_cpu_offload: is_model_cpu_offload = isinstance(component._hf_hook, CpuOffload) if not is_sequential_cpu_offload: diff --git a/src/diffusers/loaders/unet.py b/src/diffusers/loaders/unet.py index 55b1a24e60db..2fa7732a6a3b 100644 --- a/src/diffusers/loaders/unet.py +++ b/src/diffusers/loaders/unet.py @@ -39,7 +39,6 @@ get_adapter_name, get_peft_kwargs, is_accelerate_available, - is_accelerate_version, is_peft_version, is_torch_version, logging, @@ -399,18 +398,9 @@ def _optionally_disable_offloading(cls, _pipeline): is_model_cpu_offload = False is_sequential_cpu_offload = False - def model_has_device_map(model): - if not is_accelerate_available() or is_accelerate_version("<", "0.14.0"): - return False - return getattr(model, "hf_device_map", None) is not None - if _pipeline is not None and _pipeline.hf_device_map is None: for _, component in _pipeline.components.items(): - if ( - isinstance(component, nn.Module) - and hasattr(component, "_hf_hook") - and not model_has_device_map(component) - ): + if isinstance(component, nn.Module) and hasattr(component, "_hf_hook"): if not is_model_cpu_offload: is_model_cpu_offload = isinstance(component._hf_hook, CpuOffload) if not is_sequential_cpu_offload: diff --git a/src/diffusers/pipelines/pipeline_loading_utils.py b/src/diffusers/pipelines/pipeline_loading_utils.py index 7d42ed5bcba8..5eba1952e608 100644 --- a/src/diffusers/pipelines/pipeline_loading_utils.py +++ b/src/diffusers/pipelines/pipeline_loading_utils.py @@ -36,7 +36,6 @@ deprecate, get_class_from_dynamic_module, is_accelerate_available, - is_accelerate_version, is_peft_available, is_transformers_available, logging, @@ -948,9 +947,3 @@ def _get_ignore_patterns( ) return ignore_patterns - - -def model_has_device_map(model): - if not is_accelerate_available() or is_accelerate_version("<", "0.14.0"): - return False - return getattr(model, "hf_device_map", None) is not None diff --git a/src/diffusers/pipelines/pipeline_utils.py b/src/diffusers/pipelines/pipeline_utils.py index 791b3e5e9394..2e1858b16148 100644 --- a/src/diffusers/pipelines/pipeline_utils.py +++ b/src/diffusers/pipelines/pipeline_utils.py @@ -85,7 +85,6 @@ _update_init_kwargs_with_connected_pipeline, load_sub_model, maybe_raise_or_warn, - model_has_device_map, variant_compatible_siblings, warn_deprecated_model_variant, ) @@ -407,16 +406,6 @@ def module_is_offloaded(module): return hasattr(module, "_hf_hook") and isinstance(module._hf_hook, accelerate.hooks.CpuOffload) - # device-mapped modules should not go through any device placements. - device_mapped_components = [ - key for key, component in self.components.items() if model_has_device_map(component) - ] - if device_mapped_components: - raise ValueError( - "The following pipeline components have been found to use a device map: " - f"{device_mapped_components}. This is incompatible with explicitly setting the device using `to()`." - ) - # .to("cuda") would raise an error if the pipeline is sequentially offloaded, so we raise our own to make it clearer pipeline_is_sequentially_offloaded = any( module_is_sequentially_offloaded(module) for _, module in self.components.items() @@ -1013,16 +1002,6 @@ def enable_model_cpu_offload(self, gpu_id: Optional[int] = None, device: Union[t The PyTorch device type of the accelerator that shall be used in inference. If not specified, it will default to "cuda". """ - # device-mapped modules should not go through any device placements. - device_mapped_components = [ - key for key, component in self.components.items() if model_has_device_map(component) - ] - if device_mapped_components: - raise ValueError( - "The following pipeline components have been found to use a device map: " - f"{device_mapped_components}. This is incompatible with `enable_model_cpu_offload()`." - ) - is_pipeline_device_mapped = self.hf_device_map is not None and len(self.hf_device_map) > 1 if is_pipeline_device_mapped: raise ValueError( @@ -1125,16 +1104,6 @@ def enable_sequential_cpu_offload(self, gpu_id: Optional[int] = None, device: Un The PyTorch device type of the accelerator that shall be used in inference. If not specified, it will default to "cuda". """ - # device-mapped modules should not go through any device placements. - device_mapped_components = [ - key for key, component in self.components.items() if model_has_device_map(component) - ] - if device_mapped_components: - raise ValueError( - "The following pipeline components have been found to use a device map: " - f"{device_mapped_components}. This is incompatible with `enable_sequential_cpu_offload()`." - ) - if is_accelerate_available() and is_accelerate_version(">=", "0.14.0"): from accelerate import cpu_offload else: diff --git a/tests/pipelines/audioldm2/test_audioldm2.py b/tests/pipelines/audioldm2/test_audioldm2.py index 9af49697f913..fb550dd3219d 100644 --- a/tests/pipelines/audioldm2/test_audioldm2.py +++ b/tests/pipelines/audioldm2/test_audioldm2.py @@ -506,14 +506,9 @@ def test_to_dtype(self): model_dtypes = {key: component.dtype for key, component in components.items() if hasattr(component, "dtype")} self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes.values())) - @unittest.skip("Test currently not supported.") def test_sequential_cpu_offload_forward_pass(self): pass - @unittest.skip("Test currently not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - @nightly class AudioLDM2PipelineSlowTests(unittest.TestCase): diff --git a/tests/pipelines/controlnet/test_controlnet.py b/tests/pipelines/controlnet/test_controlnet.py index 1cb6569716a8..b12655d989d4 100644 --- a/tests/pipelines/controlnet/test_controlnet.py +++ b/tests/pipelines/controlnet/test_controlnet.py @@ -514,18 +514,6 @@ def test_inference_multiple_prompt_input(self): assert image.shape == (4, 64, 64, 3) - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - class StableDiffusionMultiControlNetOneModelPipelineFastTests( IPAdapterTesterMixin, PipelineTesterMixin, PipelineKarrasSchedulerTesterMixin, unittest.TestCase @@ -709,18 +697,6 @@ def test_save_pretrained_raise_not_implemented_exception(self): except NotImplementedError: pass - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - @slow @require_torch_gpu diff --git a/tests/pipelines/controlnet/test_controlnet_img2img.py b/tests/pipelines/controlnet/test_controlnet_img2img.py index 45bc70c809f2..7c4ae716b37d 100644 --- a/tests/pipelines/controlnet/test_controlnet_img2img.py +++ b/tests/pipelines/controlnet/test_controlnet_img2img.py @@ -389,18 +389,6 @@ def test_save_pretrained_raise_not_implemented_exception(self): except NotImplementedError: pass - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - @slow @require_torch_gpu diff --git a/tests/pipelines/controlnet/test_controlnet_inpaint.py b/tests/pipelines/controlnet/test_controlnet_inpaint.py index af8ddb7e6b28..e49106334c2e 100644 --- a/tests/pipelines/controlnet/test_controlnet_inpaint.py +++ b/tests/pipelines/controlnet/test_controlnet_inpaint.py @@ -441,18 +441,6 @@ def test_save_pretrained_raise_not_implemented_exception(self): except NotImplementedError: pass - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - @slow @require_torch_gpu diff --git a/tests/pipelines/controlnet/test_controlnet_sdxl.py b/tests/pipelines/controlnet/test_controlnet_sdxl.py index a8fa23678fc7..c931391ac4d5 100644 --- a/tests/pipelines/controlnet/test_controlnet_sdxl.py +++ b/tests/pipelines/controlnet/test_controlnet_sdxl.py @@ -683,18 +683,6 @@ def test_inference_batch_single_identical(self): def test_save_load_optional_components(self): return self._test_save_load_optional_components() - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - class StableDiffusionXLMultiControlNetOneModelPipelineFastTests( PipelineKarrasSchedulerTesterMixin, PipelineTesterMixin, SDXLOptionalComponentsTesterMixin, unittest.TestCase @@ -899,18 +887,6 @@ def test_negative_conditions(self): self.assertTrue(np.abs(image_slice_without_neg_cond - image_slice_with_neg_cond).max() > 1e-2) - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - @slow @require_torch_gpu diff --git a/tests/pipelines/flux/test_pipeline_flux.py b/tests/pipelines/flux/test_pipeline_flux.py index e864ff85daa4..3ccf3f80ba3c 100644 --- a/tests/pipelines/flux/test_pipeline_flux.py +++ b/tests/pipelines/flux/test_pipeline_flux.py @@ -8,11 +8,9 @@ from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, FluxPipeline, FluxTransformer2DModel -from diffusers.image_processor import VaeImageProcessor from diffusers.utils.testing_utils import ( numpy_cosine_similarity_distance, require_big_gpu_with_torch_cuda, - require_torch_multi_gpu, slow, torch_device, ) @@ -284,172 +282,3 @@ def test_flux_inference(self): max_diff = numpy_cosine_similarity_distance(expected_slice.flatten(), image_slice.flatten()) assert max_diff < 1e-4 - - @require_torch_multi_gpu - @torch.no_grad() - def test_flux_component_sharding(self): - """ - internal note: test was run on `audace`. - """ - - ckpt_id = "black-forest-labs/FLUX.1-dev" - dtype = torch.bfloat16 - prompt = "a photo of a cat with tiger-like look" - - pipeline = FluxPipeline.from_pretrained( - ckpt_id, - transformer=None, - vae=None, - device_map="balanced", - max_memory={0: "16GB", 1: "16GB"}, - torch_dtype=dtype, - ) - prompt_embeds, pooled_prompt_embeds, _ = pipeline.encode_prompt( - prompt=prompt, prompt_2=None, max_sequence_length=512 - ) - - del pipeline.text_encoder - del pipeline.text_encoder_2 - del pipeline.tokenizer - del pipeline.tokenizer_2 - del pipeline - - gc.collect() - torch.cuda.empty_cache() - - transformer = FluxTransformer2DModel.from_pretrained( - ckpt_id, subfolder="transformer", device_map="auto", max_memory={0: "16GB", 1: "16GB"}, torch_dtype=dtype - ) - pipeline = FluxPipeline.from_pretrained( - ckpt_id, - text_encoder=None, - text_encoder_2=None, - tokenizer=None, - tokenizer_2=None, - vae=None, - transformer=transformer, - torch_dtype=dtype, - ) - - height, width = 768, 1360 - # No need to wrap it up under `torch.no_grad()` as pipeline call method - # is already wrapped under that. - latents = pipeline( - prompt_embeds=prompt_embeds, - pooled_prompt_embeds=pooled_prompt_embeds, - num_inference_steps=10, - guidance_scale=3.5, - height=height, - width=width, - output_type="latent", - generator=torch.manual_seed(0), - ).images - latent_slice = latents[0, :3, :3].flatten().float().cpu().numpy() - expected_slice = np.array([-0.377, -0.3008, -0.5117, -0.252, 0.0615, -0.3477, -0.1309, -0.1914, 0.1533]) - - assert numpy_cosine_similarity_distance(latent_slice, expected_slice) < 1e-4 - - del pipeline.transformer - del pipeline - - gc.collect() - torch.cuda.empty_cache() - - vae = AutoencoderKL.from_pretrained(ckpt_id, subfolder="vae", torch_dtype=dtype).to(torch_device) - vae_scale_factor = 2 ** (len(vae.config.block_out_channels) - 1) - image_processor = VaeImageProcessor(vae_scale_factor=vae_scale_factor) - - latents = FluxPipeline._unpack_latents(latents, height, width, vae_scale_factor) - latents = (latents / vae.config.scaling_factor) + vae.config.shift_factor - - image = vae.decode(latents, return_dict=False)[0] - image = image_processor.postprocess(image, output_type="np") - image_slice = image[0, :3, :3, -1].flatten() - expected_slice = np.array([0.127, 0.1113, 0.1055, 0.1172, 0.1172, 0.1074, 0.1191, 0.1191, 0.1152]) - - assert numpy_cosine_similarity_distance(image_slice, expected_slice) < 1e-4 - - @require_torch_multi_gpu - @torch.no_grad() - def test_flux_component_sharding_with_lora(self): - """ - internal note: test was run on `audace`. - """ - - ckpt_id = "black-forest-labs/FLUX.1-dev" - dtype = torch.bfloat16 - prompt = "jon snow eating pizza." - - pipeline = FluxPipeline.from_pretrained( - ckpt_id, - transformer=None, - vae=None, - device_map="balanced", - max_memory={0: "16GB", 1: "16GB"}, - torch_dtype=dtype, - ) - prompt_embeds, pooled_prompt_embeds, _ = pipeline.encode_prompt( - prompt=prompt, prompt_2=None, max_sequence_length=512 - ) - - del pipeline.text_encoder - del pipeline.text_encoder_2 - del pipeline.tokenizer - del pipeline.tokenizer_2 - del pipeline - - gc.collect() - torch.cuda.empty_cache() - - transformer = FluxTransformer2DModel.from_pretrained( - ckpt_id, subfolder="transformer", device_map="auto", max_memory={0: "16GB", 1: "16GB"}, torch_dtype=dtype - ) - pipeline = FluxPipeline.from_pretrained( - ckpt_id, - text_encoder=None, - text_encoder_2=None, - tokenizer=None, - tokenizer_2=None, - vae=None, - transformer=transformer, - torch_dtype=dtype, - ) - pipeline.load_lora_weights("TheLastBen/Jon_Snow_Flux_LoRA", weight_name="jon_snow.safetensors") - - height, width = 768, 1360 - # No need to wrap it up under `torch.no_grad()` as pipeline call method - # is already wrapped under that. - latents = pipeline( - prompt_embeds=prompt_embeds, - pooled_prompt_embeds=pooled_prompt_embeds, - num_inference_steps=10, - guidance_scale=3.5, - height=height, - width=width, - output_type="latent", - generator=torch.manual_seed(0), - ).images - latent_slice = latents[0, :3, :3].flatten().float().cpu().numpy() - expected_slice = np.array([-0.6523, -0.4961, -0.9141, -0.5, -0.2129, -0.6914, -0.375, -0.5664, -0.1699]) - - assert numpy_cosine_similarity_distance(latent_slice, expected_slice) < 1e-4 - - del pipeline.transformer - del pipeline - - gc.collect() - torch.cuda.empty_cache() - - vae = AutoencoderKL.from_pretrained(ckpt_id, subfolder="vae", torch_dtype=dtype).to(torch_device) - vae_scale_factor = 2 ** (len(vae.config.block_out_channels) - 1) - image_processor = VaeImageProcessor(vae_scale_factor=vae_scale_factor) - - latents = FluxPipeline._unpack_latents(latents, height, width, vae_scale_factor) - latents = (latents / vae.config.scaling_factor) + vae.config.shift_factor - - image = vae.decode(latents, return_dict=False)[0] - image = image_processor.postprocess(image, output_type="np") - image_slice = image[0, :3, :3, -1].flatten() - expected_slice = np.array([0.1211, 0.1094, 0.1035, 0.1094, 0.1113, 0.1074, 0.1133, 0.1133, 0.1094]) - - assert numpy_cosine_similarity_distance(image_slice, expected_slice) < 1e-4 diff --git a/tests/pipelines/kandinsky/test_kandinsky_combined.py b/tests/pipelines/kandinsky/test_kandinsky_combined.py index 739f8676cbd3..607a47e08e58 100644 --- a/tests/pipelines/kandinsky/test_kandinsky_combined.py +++ b/tests/pipelines/kandinsky/test_kandinsky_combined.py @@ -139,18 +139,6 @@ def test_float16_inference(self): def test_dict_tuple_outputs_equivalent(self): super().test_dict_tuple_outputs_equivalent(expected_max_difference=5e-4) - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - class KandinskyPipelineImg2ImgCombinedFastTests(PipelineTesterMixin, unittest.TestCase): pipeline_class = KandinskyImg2ImgCombinedPipeline @@ -260,18 +248,6 @@ def test_dict_tuple_outputs_equivalent(self): def test_save_load_optional_components(self): super().test_save_load_optional_components(expected_max_difference=5e-4) - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - class KandinskyPipelineInpaintCombinedFastTests(PipelineTesterMixin, unittest.TestCase): pipeline_class = KandinskyInpaintCombinedPipeline @@ -387,15 +363,3 @@ def test_save_load_optional_components(self): def test_save_load_local(self): super().test_save_load_local(expected_max_difference=5e-3) - - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass diff --git a/tests/pipelines/kandinsky2_2/test_kandinsky_combined.py b/tests/pipelines/kandinsky2_2/test_kandinsky_combined.py index cf2b70f4c990..dbba0831397b 100644 --- a/tests/pipelines/kandinsky2_2/test_kandinsky_combined.py +++ b/tests/pipelines/kandinsky2_2/test_kandinsky_combined.py @@ -159,18 +159,6 @@ def test_callback_inputs(self): def test_callback_cfg(self): pass - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - class KandinskyV22PipelineImg2ImgCombinedFastTests(PipelineTesterMixin, unittest.TestCase): pipeline_class = KandinskyV22Img2ImgCombinedPipeline @@ -293,18 +281,6 @@ def test_callback_inputs(self): def test_callback_cfg(self): pass - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - class KandinskyV22PipelineInpaintCombinedFastTests(PipelineTesterMixin, unittest.TestCase): pipeline_class = KandinskyV22InpaintCombinedPipeline @@ -428,15 +404,3 @@ def test_callback_inputs(self): def test_callback_cfg(self): pass - - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass diff --git a/tests/pipelines/musicldm/test_musicldm.py b/tests/pipelines/musicldm/test_musicldm.py index 70765d981bbc..e51f5103933a 100644 --- a/tests/pipelines/musicldm/test_musicldm.py +++ b/tests/pipelines/musicldm/test_musicldm.py @@ -404,10 +404,6 @@ def test_to_dtype(self): model_dtypes = {key: component.dtype for key, component in components.items() if hasattr(component, "dtype")} self.assertTrue(all(dtype == torch.float16 for dtype in model_dtypes.values())) - @unittest.skip("Test currently not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - @nightly @require_torch_gpu diff --git a/tests/pipelines/stable_cascade/test_stable_cascade_combined.py b/tests/pipelines/stable_cascade/test_stable_cascade_combined.py index d799ae6e623a..d256deed376c 100644 --- a/tests/pipelines/stable_cascade/test_stable_cascade_combined.py +++ b/tests/pipelines/stable_cascade/test_stable_cascade_combined.py @@ -279,15 +279,3 @@ def test_stable_cascade_combined_prompt_embeds(self): ) assert np.abs(output_prompt.images - output_prompt_embeds.images).max() < 1e-5 - - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass diff --git a/tests/pipelines/stable_diffusion_adapter/test_stable_diffusion_adapter.py b/tests/pipelines/stable_diffusion_adapter/test_stable_diffusion_adapter.py index 996afbb9d323..2a1e691e9e8f 100644 --- a/tests/pipelines/stable_diffusion_adapter/test_stable_diffusion_adapter.py +++ b/tests/pipelines/stable_diffusion_adapter/test_stable_diffusion_adapter.py @@ -593,18 +593,6 @@ def test_inference_batch_single_identical( if test_mean_pixel_difference: assert_mean_pixel_difference(output_batch[0][0], output[0][0]) - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - @slow @require_torch_gpu diff --git a/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_adapter.py b/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_adapter.py index 61b5b754c44c..2091af9c0383 100644 --- a/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_adapter.py +++ b/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_adapter.py @@ -642,6 +642,9 @@ def test_adapter_sdxl_lcm(self): assert image.shape == (1, 64, 64, 3) expected_slice = np.array([0.5313, 0.5375, 0.4942, 0.5021, 0.6142, 0.4968, 0.5434, 0.5311, 0.5448]) + debug = [str(round(i, 4)) for i in image_slice.flatten().tolist()] + print(",".join(debug)) + assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2 def test_adapter_sdxl_lcm_custom_timesteps(self): @@ -664,16 +667,7 @@ def test_adapter_sdxl_lcm_custom_timesteps(self): assert image.shape == (1, 64, 64, 3) expected_slice = np.array([0.5313, 0.5375, 0.4942, 0.5021, 0.6142, 0.4968, 0.5434, 0.5311, 0.5448]) - assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2 - - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass + debug = [str(round(i, 4)) for i in image_slice.flatten().tolist()] + print(",".join(debug)) - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass + assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2 diff --git a/tests/pipelines/stable_unclip/test_stable_unclip.py b/tests/pipelines/stable_unclip/test_stable_unclip.py index be5e3783ff5c..bb54d212a786 100644 --- a/tests/pipelines/stable_unclip/test_stable_unclip.py +++ b/tests/pipelines/stable_unclip/test_stable_unclip.py @@ -184,18 +184,6 @@ def test_attention_slicing_forward_pass(self): def test_inference_batch_single_identical(self): self._test_inference_batch_single_identical(expected_max_diff=1e-3) - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - @nightly @require_torch_gpu diff --git a/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py b/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py index 1a662819b00f..a5cbf7761501 100644 --- a/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py +++ b/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py @@ -205,18 +205,6 @@ def test_inference_batch_single_identical(self): def test_xformers_attention_forwardGenerator_pass(self): self._test_xformers_attention_forwardGenerator_pass(test_max_difference=False) - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass - @nightly @require_torch_gpu diff --git a/tests/pipelines/test_pipelines_common.py b/tests/pipelines/test_pipelines_common.py index f5ceda8f2703..295a94c1d2e4 100644 --- a/tests/pipelines/test_pipelines_common.py +++ b/tests/pipelines/test_pipelines_common.py @@ -41,11 +41,8 @@ from diffusers.utils.import_utils import is_accelerate_available, is_accelerate_version, is_xformers_available from diffusers.utils.testing_utils import ( CaptureLogger, - nightly, require_torch, - require_torch_multi_gpu, skip_mps, - slow, torch_device, ) @@ -62,10 +59,6 @@ from ..others.test_utils import TOKEN, USER, is_staging_test -if is_accelerate_available(): - from accelerate.utils import compute_module_sizes - - def to_np(tensor): if isinstance(tensor, torch.Tensor): tensor = tensor.detach().cpu().numpy() @@ -1915,78 +1908,6 @@ def test_StableDiffusionMixin_component(self): ) ) - @require_torch_multi_gpu - @slow - @nightly - def test_calling_to_raises_error_device_mapped_components(self, safe_serialization=True): - components = self.get_dummy_components() - pipe = self.pipeline_class(**components) - max_model_size = max( - compute_module_sizes(module)[""] - for _, module in pipe.components.items() - if isinstance(module, torch.nn.Module) - ) - with tempfile.TemporaryDirectory() as tmpdir: - pipe.save_pretrained(tmpdir, safe_serialization=safe_serialization) - max_memory = {0: max_model_size, 1: max_model_size} - loaded_pipe = self.pipeline_class.from_pretrained(tmpdir, device_map="balanced", max_memory=max_memory) - - with self.assertRaises(ValueError) as err_context: - loaded_pipe.to(torch_device) - - self.assertTrue( - "The following pipeline components have been found" in str(err_context.exception) - and "This is incompatible with explicitly setting the device using `to()`" in str(err_context.exception) - ) - - @require_torch_multi_gpu - @slow - @nightly - def test_calling_mco_raises_error_device_mapped_components(self, safe_serialization=True): - components = self.get_dummy_components() - pipe = self.pipeline_class(**components) - max_model_size = max( - compute_module_sizes(module)[""] - for _, module in pipe.components.items() - if isinstance(module, torch.nn.Module) - ) - with tempfile.TemporaryDirectory() as tmpdir: - pipe.save_pretrained(tmpdir, safe_serialization=safe_serialization) - max_memory = {0: max_model_size, 1: max_model_size} - loaded_pipe = self.pipeline_class.from_pretrained(tmpdir, device_map="balanced", max_memory=max_memory) - - with self.assertRaises(ValueError) as err_context: - loaded_pipe.enable_model_cpu_offload() - - self.assertTrue( - "The following pipeline components have been found" in str(err_context.exception) - and "This is incompatible with `enable_model_cpu_offload()`" in str(err_context.exception) - ) - - @require_torch_multi_gpu - @slow - @nightly - def test_calling_sco_raises_error_device_mapped_components(self, safe_serialization=True): - components = self.get_dummy_components() - pipe = self.pipeline_class(**components) - max_model_size = max( - compute_module_sizes(module)[""] - for _, module in pipe.components.items() - if isinstance(module, torch.nn.Module) - ) - with tempfile.TemporaryDirectory() as tmpdir: - pipe.save_pretrained(tmpdir, safe_serialization=safe_serialization) - max_memory = {0: max_model_size, 1: max_model_size} - loaded_pipe = self.pipeline_class.from_pretrained(tmpdir, device_map="balanced", max_memory=max_memory) - - with self.assertRaises(ValueError) as err_context: - loaded_pipe.enable_sequential_cpu_offload() - - self.assertTrue( - "The following pipeline components have been found" in str(err_context.exception) - and "This is incompatible with `enable_sequential_cpu_offload()`" in str(err_context.exception) - ) - @is_staging_test class PipelinePushToHubTester(unittest.TestCase): diff --git a/tests/pipelines/unidiffuser/test_unidiffuser.py b/tests/pipelines/unidiffuser/test_unidiffuser.py index 5cf017029fdf..2e0ba1cfb8eb 100644 --- a/tests/pipelines/unidiffuser/test_unidiffuser.py +++ b/tests/pipelines/unidiffuser/test_unidiffuser.py @@ -576,15 +576,6 @@ def test_unidiffuser_default_img2text_v1_cuda_fp16(self): expected_text_prefix = '" This This' assert text[0][: len(expected_text_prefix)] == expected_text_prefix - def test_calling_mco_raises_error_device_mapped_components(self): - super().test_calling_mco_raises_error_device_mapped_components(safe_serialization=False) - - def test_calling_to_raises_error_device_mapped_components(self): - super().test_calling_to_raises_error_device_mapped_components(safe_serialization=False) - - def test_calling_sco_raises_error_device_mapped_components(self): - super().test_calling_sco_raises_error_device_mapped_components(safe_serialization=False) - @nightly @require_torch_gpu diff --git a/tests/pipelines/wuerstchen/test_wuerstchen_combined.py b/tests/pipelines/wuerstchen/test_wuerstchen_combined.py index cd7891767f65..0caed159100a 100644 --- a/tests/pipelines/wuerstchen/test_wuerstchen_combined.py +++ b/tests/pipelines/wuerstchen/test_wuerstchen_combined.py @@ -237,15 +237,3 @@ def test_callback_inputs(self): def test_callback_cfg(self): pass - - @unittest.skip("Test not supported.") - def test_calling_mco_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_to_raises_error_device_mapped_components(self): - pass - - @unittest.skip("Test not supported.") - def test_calling_sco_raises_error_device_mapped_components(self): - pass