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fix: init for vae during pixart tests (#6215)

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* fix: init for vae during pixart tests

* print the values

* add flatten

* correct assertion value for test_inference

* correct assertion values for test_inference_non_square_images

* run styling

* debug test_inference_with_multiple_images_per_prompt

* fix assertion values for test_inference_with_multiple_images_per_prompt
This commit is contained in:
Sayak Paul
2023-12-19 09:46:57 +05:30
committed by GitHub
parent 57fde871e1
commit 9221da4063
1 changed files with 5 additions and 3 deletions
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8
tests/pipelines/pixart/test_pixart.py
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@@ -64,7 +64,9 @@ class PixArtAlphaPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
norm_elementwise_affine=False,
norm_eps=1e-6,
)
torch.manual_seed(0)
vae = AutoencoderKL()
scheduler = DDIMScheduler()
text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
@@ -186,7 +188,7 @@ class PixArtAlphaPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
image_slice = image[0, -3:, -3:, -1]
self.assertEqual(image.shape, (1, 8, 8, 3))
expected_slice = np.array([0.5303, 0.2658, 0.7979, 0.1182, 0.3304, 0.4608, 0.5195, 0.4261, 0.4675])
expected_slice = np.array([0.6319, 0.3526, 0.3806, 0.6327, 0.4639, 0.483, 0.2583, 0.5331, 0.4852])
max_diff = np.abs(image_slice.flatten() - expected_slice).max()
self.assertLessEqual(max_diff, 1e-3)
@@ -203,7 +205,7 @@ class PixArtAlphaPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
image_slice = image[0, -3:, -3:, -1]
self.assertEqual(image.shape, (1, 32, 48, 3))
expected_slice = np.array([0.3859, 0.2987, 0.2333, 0.5243, 0.6721, 0.4436, 0.5292, 0.5373, 0.4416])
expected_slice = np.array([0.6493, 0.537, 0.4081, 0.4762, 0.3695, 0.4711, 0.3026, 0.5218, 0.5263])
max_diff = np.abs(image_slice.flatten() - expected_slice).max()
self.assertLessEqual(max_diff, 1e-3)
@@ -293,7 +295,7 @@ class PixArtAlphaPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
image_slice = image[0, -3:, -3:, -1]
self.assertEqual(image.shape, (2, 8, 8, 3))
expected_slice = np.array([0.5303, 0.2658, 0.7979, 0.1182, 0.3304, 0.4608, 0.5195, 0.4261, 0.4675])
expected_slice = np.array([0.6319, 0.3526, 0.3806, 0.6327, 0.4639, 0.483, 0.2583, 0.5331, 0.4852])
max_diff = np.abs(image_slice.flatten() - expected_slice).max()
self.assertLessEqual(max_diff, 1e-3)