Update IP Adapter tests to use cosine similarity distance (huggingface#6806)

* update

* update

Author: DN6

tests/pipelines/ip_adapters/test_ip_adapter_stable_diffusion.py

@@ -35,6 +35,7 @@
 from diffusers.utils import load_image
 from diffusers.utils.testing_utils import (
     enable_full_determinism,
+    numpy_cosine_similarity_distance,
     require_torch_gpu,
     slow,
     torch_device,
@@ -119,7 +120,8 @@ def test_text_to_image(self):
 
         expected_slice = np.array([0.80810547, 0.88183594, 0.9296875, 0.9189453, 0.9848633, 1.0, 0.97021484, 1.0, 1.0])
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-plus_sd15.bin")
 
@@ -131,7 +133,8 @@ def test_text_to_image(self):
             [0.30444336, 0.26513672, 0.22436523, 0.2758789, 0.25585938, 0.20751953, 0.25390625, 0.24633789, 0.21923828]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
     def test_image_to_image(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -149,7 +152,8 @@ def test_image_to_image(self):
             [0.22167969, 0.21875, 0.21728516, 0.22607422, 0.21948242, 0.23925781, 0.22387695, 0.25268555, 0.2722168]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-plus_sd15.bin")
 
@@ -161,7 +165,8 @@ def test_image_to_image(self):
             [0.35913086, 0.265625, 0.26367188, 0.24658203, 0.19750977, 0.39990234, 0.15258789, 0.20336914, 0.5517578]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
     def test_inpainting(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -179,19 +184,17 @@ def test_inpainting(self):
             [0.27148438, 0.24047852, 0.22167969, 0.23217773, 0.21118164, 0.21142578, 0.21875, 0.20751953, 0.20019531]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-plus_sd15.bin")
 
         inputs = self.get_dummy_inputs(for_inpainting=True)
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array(
-            [0.27294922, 0.24023438, 0.21948242, 0.23242188, 0.20825195, 0.2055664, 0.21679688, 0.20336914, 0.19360352]
-        )
-
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
     def test_text_to_image_model_cpu_offload(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -233,11 +236,10 @@ def test_text_to_image_full_face(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array(
-            [0.18115234, 0.13500977, 0.13427734, 0.24194336, 0.17138672, 0.16625977, 0.4260254, 0.43359375, 0.4416504]
-        )
+        expected_slice = np.array([0.1958, 0.1475, 0.1396, 0.2412, 0.1658, 0.1533, 0.3997, 0.4055, 0.4128])
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
     def test_unload(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -277,7 +279,9 @@ def test_multi(self):
         expected_slice = np.array(
             [0.5234375, 0.53515625, 0.5629883, 0.57128906, 0.59521484, 0.62109375, 0.57910156, 0.6201172, 0.6508789]
         )
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
 
 @slow
@@ -314,7 +318,8 @@ def test_text_to_image_sdxl(self):
             ]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
 
@@ -339,7 +344,8 @@ def test_text_to_image_sdxl(self):
             [0.0576596, 0.05600825, 0.04479006, 0.05288461, 0.05461192, 0.05137569, 0.04867965, 0.05301541, 0.04939842]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
     def test_image_to_image_sdxl(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="sdxl_models/image_encoder")
@@ -432,7 +438,8 @@ def test_inpainting_sdxl(self):
             [0.14181179, 0.1493012, 0.14283323, 0.14602411, 0.14915377, 0.15015268, 0.14725655, 0.15009224, 0.15164584]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-3)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4
 
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         feature_extractor = self.get_image_processor("laion/CLIP-ViT-bigG-14-laion2B-39B-b160k")
@@ -457,4 +464,5 @@ def test_inpainting_sdxl(self):
 
         expected_slice = np.array([0.1398, 0.1476, 0.1407, 0.1442, 0.1470, 0.1480, 0.1449, 0.1481, 0.1494])
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-4, rtol=1e-4)
+        max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
+        assert max_diff < 5e-4