Move slow tests to nightly #4526
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sayakpaul
reviewed
Aug 8, 2023
| @@ -539,47 +539,6 @@ def test_stable_diffusion_2_pix2pix_inversion(self): | |||
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| assert np.abs(expected_slice - image_slice.cpu().numpy()).max() < 5e-2 | |||
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| def test_stable_diffusion_pix2pix_full(self): | |||
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Why are we getting rid of it entirely?
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The pipeline wasn't prioritised in this list (under highly important and important)
So I moved all the slow tests to nightly.
sayakpaul
reviewed
Aug 8, 2023
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| def test_two_step_model(self): | ||
| expected_video = load_numpy( | ||
| "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text_to_video/video.npy" | ||
| "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text_to_video/video_2step.npy" | ||
| ) | ||
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| pipe = TextToVideoSDPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b") | ||
| pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config) | ||
| pipe = pipe.to("cuda") | ||
| pipe = pipe.to(torch_device) | ||
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| prompt = "Spiderman is surfing" | ||
| generator = torch.Generator(device="cpu").manual_seed(0) | ||
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| video_frames = pipe(prompt, generator=generator, num_inference_steps=25, output_type="pt").frames | ||
| video_frames = pipe(prompt, generator=generator, num_inference_steps=2, output_type="pt").frames | ||
| video = video_frames.cpu().numpy() | ||
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| assert np.abs(expected_video - video).mean() < 5e-2 |
sayakpaul
reviewed
Aug 8, 2023
Comment on lines
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| @nightly | ||
| @skip_mps | ||
| @require_torch_gpu | ||
| class TextToVideoSDPipelineNightlyTests(unittest.TestCase): | ||
| def test_full_model(self): | ||
| expected_video = load_numpy( | ||
| "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text_to_video/video_2step.npy" | ||
| "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text_to_video/video.npy" | ||
| ) | ||
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| pipe = TextToVideoSDPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b") | ||
| pipe = pipe.to("cuda") | ||
| pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config) | ||
| pipe = pipe.to(torch_device) | ||
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| prompt = "Spiderman is surfing" | ||
| generator = torch.Generator(device="cpu").manual_seed(0) | ||
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| video_frames = pipe(prompt, generator=generator, num_inference_steps=2, output_type="pt").frames | ||
| video_frames = pipe(prompt, generator=generator, num_inference_steps=25, output_type="pt").frames | ||
| video = video_frames.cpu().numpy() | ||
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| assert np.abs(expected_video - video).mean() < 5e-2 |
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If the two step model is passing the assertion, I think it's okay to remove it from nightly unless we have a strong reason to.
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Just to clarify. Do you mean you want to keep the two step and remove the full test or keep the full and remove the two step?
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Remove the full and keep the two steps.
AmericanPresidentJimmyCarter
pushed a commit
to AmericanPresidentJimmyCarter/diffusers
that referenced
this pull request
Apr 26, 2024
* move slow pix2pixzero tests to nightly * move slow panorama tests to nightly * move txt2video full test to nightly * clean up * remove nightly test from text to video pipeline
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What does this PR do?
Move certain slow tests to nightly. The following modules are not present in this list of important pipelines and are some of the slowest tests in the CI/CD pipeline.
The
test_full_modeltest intests/pipelines/text_to_video/test_text_to_video.pyis a similar test totest_two_step_modelexcept that it runs for a greater number of inference steps. I propose moving the long running test to nightly and keeping the shorter 2 step test inSlowTestsFixes # (issue)
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