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Author SHA1 Message Date
Dhruv Nair
6c5ec82359 update 2024-02-13 04:51:44 +00:00

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@@ -35,6 +35,7 @@ from diffusers.models.attention_processor import AttnProcessor, AttnProcessor2_0
from diffusers.utils import load_image
from diffusers.utils.testing_utils import (
enable_full_determinism,
is_flaky,
numpy_cosine_similarity_distance,
require_torch_gpu,
slow,
@@ -259,6 +260,7 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
]
assert processors == [True] * len(processors)
@is_flaky
def test_multi(self):
image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
pipeline = StableDiffusionPipeline.from_pretrained(
@@ -275,7 +277,7 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
inputs["ip_adapter_image"] = [ip_adapter_image, [ip_adapter_image] * 2]
images = pipeline(**inputs).images
image_slice = images[0, :3, :3, -1].flatten()
expected_slice = np.array([0.1704, 0.1296, 0.1272, 0.2212, 0.1514, 0.1479, 0.4172, 0.4263, 0.4360])
expected_slice = np.array([0.5234, 0.5352, 0.5625, 0.5713, 0.5947, 0.6206, 0.5786, 0.6187, 0.6494])
max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
assert max_diff < 5e-4