[Tests] Speed up fast pipelines part II #7521
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sayakpaul
commented
Mar 29, 2024
| image_latents_params = TEXT_TO_IMAGE_IMAGE_PARAMS | ||
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| def get_dummy_components(self): | ||
| torch.manual_seed(0) |
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Otherwise for consecutive runs, the underlying pipeline will yield different results.
sayakpaul
commented
Mar 29, 2024
| expected_slice = np.array( | ||
| [0.5381963, 0.4836803, 0.45821992, 0.5577731, 0.51210403, 0.4794795, 0.59282357, 0.5647199, 0.43100584] | ||
| ) | ||
| expected_slice = np.array([0.549, 0.5053, 0.4676, 0.5816, 0.5364, 0.483, 0.5937, 0.5719, 0.4318]) |
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The reason why this needs changing is because we're fixing the seeds when initializing the model level components of the pipeline.
DN6
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Apr 2, 2024
noskill
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Apr 5, 2024
* start printing the tensors. * print full throttle * set static slices for 7 tests. * remove printing. * flatten * disable test for controlnet * what happens when things are seeded properly? * set the right value * style./ * make pia test fail to check things * print. * fix pia. * checking for animatediff. * fix: animatediff. * video synthesis * final piece. * style. * print guess. * fix: assertion for control guess. --------- Co-authored-by: Dhruv Nair <[email protected]>
sayakpaul
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Dec 23, 2024
* start printing the tensors. * print full throttle * set static slices for 7 tests. * remove printing. * flatten * disable test for controlnet * what happens when things are seeded properly? * set the right value * style./ * make pia test fail to check things * print. * fix pia. * checking for animatediff. * fix: animatediff. * video synthesis * final piece. * style. * print guess. * fix: assertion for control guess. --------- Co-authored-by: Dhruv Nair <[email protected]>
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What does this PR do?
Follow-up of #7477.
This PR targets the
test_dict_tuple_outputs_equivalent()method we run for all pipelines. I took the top 10 time-consuming tests from the lot and decided to use static slices ONLY for them. This is because of the rest of the tests, it's under a second. So, it doesn't matter that much.The next PR will be similar to this but for
test_inference_batch_single_identical().