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* enable on xpu * add 1 more * add one more * enable more * add 1 more * add more * enable 1 * enable more cases * enable * enable * update comment * one more * enable 1 * add more cases * enable xpu * add one more caswe * add more cases * add 1 * add more * add more cases * add case * enable * add more * add more * add more * enbale more * add more * update code * update test marker * add skip back * update comment * remove single files * remove * style * add * revert * reformat * enable * enable esingle g * add 2 more * update decorator * update * update * update * Update tests/pipelines/deepfloyd_if/test_if.py Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com> * Update src/diffusers/utils/testing_utils.py Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com> * Update tests/pipelines/animatediff/test_animatediff_controlnet.py Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com> * Update tests/pipelines/animatediff/test_animatediff.py Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com> * Update tests/pipelines/animatediff/test_animatediff_controlnet.py Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com> * update float16 * no unitest.skipt * update * apply style check * adapt style --------- Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
import gc
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import unittest
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import torch
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from diffusers import StableDiffusionXLInstructPix2PixPipeline
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from diffusers.utils.testing_utils import (
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backend_empty_cache,
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enable_full_determinism,
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require_torch_accelerator,
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slow,
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torch_device,
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)
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enable_full_determinism()
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@slow
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@require_torch_accelerator
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class StableDiffusionXLInstructPix2PixPipeline(unittest.TestCase):
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pipeline_class = StableDiffusionXLInstructPix2PixPipeline
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ckpt_path = "https://huggingface.co/stabilityai/cosxl/blob/main/cosxl_edit.safetensors"
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original_config = None
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repo_id = "diffusers/sdxl-instructpix2pix-768"
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def setUp(self):
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super().setUp()
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gc.collect()
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backend_empty_cache(torch_device)
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def tearDown(self):
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super().tearDown()
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gc.collect()
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backend_empty_cache(torch_device)
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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_setting_cosxl_edit(self):
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# Default is PNDM for this checkpoint
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pipe = self.pipeline_class.from_single_file(self.ckpt_path, config=self.repo_id, is_cosxl_edit=True)
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assert pipe.is_cosxl_edit is True
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