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[Pix2Pix Zero] Fix slow tests (#2391) 

* fix: slow tests.

* retrieving the slices.

* fix: assertion.

* debugging.

* debugging.

* debugging

* debugging.

* debugging

* debugging.

* debugging.

* debugging

* debugging

* change debugging.

* change debugging.

* fix: tests for pix2pix zero.
This commit is contained in:
Sayak Paul 2023-02-17 15:05:50 +05:30 committed by GitHub
parent d45bb937ab
commit abd5dcbbf1
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1 changed files with 6 additions and 10 deletions
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16
tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py
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@ -236,8 +236,8 @@ class StableDiffusionPix2PixZeroPipelineSlowTests(unittest.TestCase):
for url in [src_emb_url, tgt_emb_url]: for url in [src_emb_url, tgt_emb_url]:
download_from_url(url, url.split("/")[-1]) download_from_url(url, url.split("/")[-1])
src_embeds = torch.load(src_emb_url.split("/1")[-1]) src_embeds = torch.load(src_emb_url.split("/")[-1])
target_embeds = torch.load(tgt_emb_url.split("/1")[-1]) target_embeds = torch.load(tgt_emb_url.split("/")[-1])
inputs = { inputs = {
"prompt": "turn him into a cyborg", "prompt": "turn him into a cyborg",
@ -265,7 +265,7 @@ class StableDiffusionPix2PixZeroPipelineSlowTests(unittest.TestCase):
image_slice = image[0, -3:, -3:, -1].flatten() image_slice = image[0, -3:, -3:, -1].flatten()
assert image.shape == (1, 512, 512, 3) assert image.shape == (1, 512, 512, 3)
expected_slice = np.array([0.4705, 0.4771, 0.4832, 0.4783, 0.4495, 0.447, 0.4658, 0.4568, 0.438]) expected_slice = np.array([0.5742, 0.5757, 0.5747, 0.5781, 0.5688, 0.5713, 0.5742, 0.5664, 0.5747])
assert np.abs(expected_slice - image_slice).max() < 1e-3 assert np.abs(expected_slice - image_slice).max() < 1e-3
@ -283,7 +283,7 @@ class StableDiffusionPix2PixZeroPipelineSlowTests(unittest.TestCase):
image_slice = image[0, -3:, -3:, -1].flatten() image_slice = image[0, -3:, -3:, -1].flatten()
assert image.shape == (1, 512, 512, 3) assert image.shape == (1, 512, 512, 3)
expected_slice = np.array([0.6514, 0.5571, 0.5244, 0.5591, 0.4998, 0.4834, 0.502, 0.468, 0.4663]) expected_slice = np.array([0.6367, 0.5459, 0.5146, 0.5479, 0.4905, 0.4753, 0.4961, 0.4629, 0.4624])
assert np.abs(expected_slice - image_slice).max() < 1e-3 assert np.abs(expected_slice - image_slice).max() < 1e-3
@ -298,18 +298,14 @@ class StableDiffusionPix2PixZeroPipelineSlowTests(unittest.TestCase):
latents = latents.detach().cpu().numpy() latents = latents.detach().cpu().numpy()
assert latents.shape == (1, 4, 64, 64) assert latents.shape == (1, 4, 64, 64)
latents_slice = latents[0, -3:, -3:, -1] latents_slice = latents[0, -3:, -3:, -1]
expected_slice = np.array( expected_slice = np.array([0.1345, 0.268, 0.1539, 0.0726, 0.0959, 0.2261, -0.2673, 0.0277, -0.2062])
[-0.5176, 0.0669, -0.1963, -0.1653, -0.7856, -0.2871, -0.5562, -0.0096, -0.012]
)
assert np.abs(latents_slice.flatten() - expected_slice).max() < 5e-2 assert np.abs(latents_slice.flatten() - expected_slice).max() < 5e-2
elif step == 2: elif step == 2:
latents = latents.detach().cpu().numpy() latents = latents.detach().cpu().numpy()
assert latents.shape == (1, 4, 64, 64) assert latents.shape == (1, 4, 64, 64)
latents_slice = latents[0, -3:, -3:, -1] latents_slice = latents[0, -3:, -3:, -1]
expected_slice = np.array( expected_slice = np.array([0.1393, 0.2637, 0.1617, 0.0724, 0.0987, 0.2271, -0.2666, 0.0299, -0.2104])
[-0.5127, 0.0613, -0.1937, -0.1622, -0.7856, -0.2849, -0.5601, -0.0111, -0.0137]
)
assert np.abs(latents_slice.flatten() - expected_slice).max() < 5e-2 assert np.abs(latents_slice.flatten() - expected_slice).max() < 5e-2