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import gc |
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import tempfile |
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import unittest |
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import torch |
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from diffusers import EulerDiscreteScheduler, StableDiffusionPipeline |
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from diffusers.utils.testing_utils import ( |
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enable_full_determinism, |
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require_torch_gpu, |
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slow, |
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) |
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from .single_file_testing_utils import ( |
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SDSingleFileTesterMixin, |
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download_original_config, |
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download_single_file_checkpoint, |
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) |
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enable_full_determinism() |
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@slow |
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@require_torch_gpu |
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class StableDiffusionPipelineSingleFileSlowTests(unittest.TestCase, SDSingleFileTesterMixin): |
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pipeline_class = StableDiffusionPipeline |
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ckpt_path = "https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.safetensors" |
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original_config = ( |
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"https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml" |
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) |
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repo_id = "runwayml/stable-diffusion-v1-5" |
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def setUp(self): |
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super().setUp() |
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gc.collect() |
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torch.cuda.empty_cache() |
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def tearDown(self): |
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super().tearDown() |
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gc.collect() |
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torch.cuda.empty_cache() |
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def get_inputs(self, device, generator_device="cpu", dtype=torch.float32, seed=0): |
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generator = torch.Generator(device=generator_device).manual_seed(seed) |
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inputs = { |
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"prompt": "a fantasy landscape, concept art, high resolution", |
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"generator": generator, |
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"num_inference_steps": 2, |
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"strength": 0.75, |
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"guidance_scale": 7.5, |
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"output_type": "np", |
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} |
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return inputs |
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def test_single_file_format_inference_is_same_as_pretrained(self): |
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super().test_single_file_format_inference_is_same_as_pretrained(expected_max_diff=1e-3) |
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def test_single_file_legacy_scheduler_loading(self): |
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with tempfile.TemporaryDirectory() as tmpdir: |
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ckpt_filename = self.ckpt_path.split("/")[-1] |
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local_ckpt_path = download_single_file_checkpoint(self.repo_id, ckpt_filename, tmpdir) |
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local_original_config = download_original_config(self.original_config, tmpdir) |
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pipe = self.pipeline_class.from_single_file( |
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local_ckpt_path, |
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original_config=local_original_config, |
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cache_dir=tmpdir, |
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local_files_only=True, |
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scheduler_type="euler", |
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) |
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assert isinstance(pipe.scheduler, EulerDiscreteScheduler) |
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def test_single_file_legacy_scaling_factor(self): |
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new_scaling_factor = 10.0 |
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init_pipe = self.pipeline_class.from_single_file(self.ckpt_path) |
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pipe = self.pipeline_class.from_single_file(self.ckpt_path, scaling_factor=new_scaling_factor) |
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assert init_pipe.vae.config.scaling_factor != new_scaling_factor |
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assert pipe.vae.config.scaling_factor == new_scaling_factor |
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@slow |
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class StableDiffusion21PipelineSingleFileSlowTests(unittest.TestCase, SDSingleFileTesterMixin): |
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pipeline_class = StableDiffusionPipeline |
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ckpt_path = "https://huggingface.co/stabilityai/stable-diffusion-2-1/blob/main/v2-1_768-ema-pruned.safetensors" |
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original_config = "https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml" |
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repo_id = "stabilityai/stable-diffusion-2-1" |
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def setUp(self): |
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super().setUp() |
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gc.collect() |
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torch.cuda.empty_cache() |
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def tearDown(self): |
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super().tearDown() |
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gc.collect() |
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torch.cuda.empty_cache() |
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def get_inputs(self, device, generator_device="cpu", dtype=torch.float32, seed=0): |
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generator = torch.Generator(device=generator_device).manual_seed(seed) |
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inputs = { |
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"prompt": "a fantasy landscape, concept art, high resolution", |
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"generator": generator, |
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"num_inference_steps": 2, |
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"strength": 0.75, |
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"guidance_scale": 7.5, |
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"output_type": "np", |
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} |
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return inputs |
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def test_single_file_format_inference_is_same_as_pretrained(self): |
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super().test_single_file_format_inference_is_same_as_pretrained(expected_max_diff=1e-3) |
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