| import gc |
| import tempfile |
|
|
| import torch |
|
|
| from diffusers import EulerDiscreteScheduler, StableDiffusionInstructPix2PixPipeline, StableDiffusionPipeline |
| from diffusers.loaders.single_file_utils import _extract_repo_id_and_weights_name |
| from diffusers.utils import load_image |
|
|
| from ..testing_utils import ( |
| backend_empty_cache, |
| enable_full_determinism, |
| nightly, |
| require_torch_accelerator, |
| slow, |
| torch_device, |
| ) |
| from .single_file_testing_utils import ( |
| SDSingleFileTesterMixin, |
| download_original_config, |
| download_single_file_checkpoint, |
| ) |
|
|
|
|
| enable_full_determinism() |
|
|
|
|
| @slow |
| @require_torch_accelerator |
| class TestStableDiffusionPipelineSingleFileSlow(SDSingleFileTesterMixin): |
| pipeline_class = StableDiffusionPipeline |
| ckpt_path = ( |
| "https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.safetensors" |
| ) |
| original_config = ( |
| "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml" |
| ) |
| repo_id = "stable-diffusion-v1-5/stable-diffusion-v1-5" |
|
|
| def setup_method(self): |
| gc.collect() |
| backend_empty_cache(torch_device) |
|
|
| def teardown_method(self): |
| gc.collect() |
| backend_empty_cache(torch_device) |
|
|
| def get_inputs(self, device, generator_device="cpu", dtype=torch.float32, seed=0): |
| generator = torch.Generator(device=generator_device).manual_seed(seed) |
| inputs = { |
| "prompt": "a fantasy landscape, concept art, high resolution", |
| "generator": generator, |
| "num_inference_steps": 2, |
| "strength": 0.75, |
| "guidance_scale": 7.5, |
| "output_type": "np", |
| } |
| return inputs |
|
|
| def test_single_file_format_inference_is_same_as_pretrained(self): |
| super().test_single_file_format_inference_is_same_as_pretrained(expected_max_diff=1e-3) |
|
|
| def test_single_file_legacy_scheduler_loading(self): |
| with tempfile.TemporaryDirectory() as tmpdir: |
| repo_id, weight_name = _extract_repo_id_and_weights_name(self.ckpt_path) |
| local_ckpt_path = download_single_file_checkpoint(repo_id, weight_name, tmpdir) |
| local_original_config = download_original_config(self.original_config, tmpdir) |
|
|
| pipe = self.pipeline_class.from_single_file( |
| local_ckpt_path, |
| original_config=local_original_config, |
| cache_dir=tmpdir, |
| local_files_only=True, |
| scheduler_type="euler", |
| ) |
|
|
| |
| assert isinstance(pipe.scheduler, EulerDiscreteScheduler) |
|
|
| def test_single_file_legacy_scaling_factor(self): |
| new_scaling_factor = 10.0 |
| init_pipe = self.pipeline_class.from_single_file(self.ckpt_path) |
| pipe = self.pipeline_class.from_single_file(self.ckpt_path, scaling_factor=new_scaling_factor) |
|
|
| assert init_pipe.vae.config.scaling_factor != new_scaling_factor |
| assert pipe.vae.config.scaling_factor == new_scaling_factor |
|
|
|
|
| @slow |
| class TestStableDiffusion21PipelineSingleFileSlow(SDSingleFileTesterMixin): |
| pipeline_class = StableDiffusionPipeline |
| ckpt_path = "https://huggingface.co/stabilityai/stable-diffusion-2-1/blob/main/v2-1_768-ema-pruned.safetensors" |
| original_config = "https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml" |
| repo_id = "stabilityai/stable-diffusion-2-1" |
|
|
| def setup_method(self): |
| gc.collect() |
| backend_empty_cache(torch_device) |
|
|
| def teardown_method(self): |
| gc.collect() |
| backend_empty_cache(torch_device) |
|
|
| def get_inputs(self, device, generator_device="cpu", dtype=torch.float32, seed=0): |
| generator = torch.Generator(device=generator_device).manual_seed(seed) |
| inputs = { |
| "prompt": "a fantasy landscape, concept art, high resolution", |
| "generator": generator, |
| "num_inference_steps": 2, |
| "strength": 0.75, |
| "guidance_scale": 7.5, |
| "output_type": "np", |
| } |
| return inputs |
|
|
| def test_single_file_format_inference_is_same_as_pretrained(self): |
| super().test_single_file_format_inference_is_same_as_pretrained(expected_max_diff=1e-3) |
|
|
|
|
| @nightly |
| @slow |
| @require_torch_accelerator |
| class TestStableDiffusionInstructPix2PixPipelineSingleFileSlow(SDSingleFileTesterMixin): |
| pipeline_class = StableDiffusionInstructPix2PixPipeline |
| ckpt_path = "https://huggingface.co/timbrooks/instruct-pix2pix/blob/main/instruct-pix2pix-00-22000.safetensors" |
| original_config = ( |
| "https://raw.githubusercontent.com/timothybrooks/instruct-pix2pix/refs/heads/main/configs/generate.yaml" |
| ) |
| repo_id = "timbrooks/instruct-pix2pix" |
| single_file_kwargs = {"extract_ema": True} |
|
|
| def setup_method(self): |
| gc.collect() |
| backend_empty_cache(torch_device) |
|
|
| def teardown_method(self): |
| gc.collect() |
| backend_empty_cache(torch_device) |
|
|
| def get_inputs(self, device, generator_device="cpu", dtype=torch.float32, seed=0): |
| generator = torch.Generator(device=generator_device).manual_seed(seed) |
| image = load_image( |
| "https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/stable_diffusion_pix2pix/example.jpg" |
| ) |
| inputs = { |
| "prompt": "turn him into a cyborg", |
| "image": image, |
| "generator": generator, |
| "num_inference_steps": 3, |
| "guidance_scale": 7.5, |
| "image_guidance_scale": 1.0, |
| "output_type": "np", |
| } |
| return inputs |
|
|
| def test_single_file_format_inference_is_same_as_pretrained(self): |
| super().test_single_file_format_inference_is_same_as_pretrained(expected_max_diff=1e-3) |
|
|
