udpate ip-adapter slow tests (#6760)

* udpate slices

* up

* hopefully last one

---------

Co-authored-by: yiyixuxu <yixu310@gmail,com>

Author: yiyixuxu

tests/pipelines/ip_adapters/test_ip_adapter_stable_diffusion.py

@@ -117,19 +117,21 @@ def test_text_to_image(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.8110, 0.8843, 0.9326, 0.9224, 0.9878, 1.0, 0.9736, 1.0, 1.0])
+        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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-plus_sd15.bin")
 
         inputs = self.get_dummy_inputs()
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.3013, 0.2615, 0.2202, 0.2722, 0.2510, 0.2023, 0.2498, 0.2415, 0.2139])
+        expected_slice = np.array(
+            [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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
     def test_image_to_image(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -143,19 +145,23 @@ def test_image_to_image(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.2253, 0.2251, 0.2219, 0.2312, 0.2236, 0.2434, 0.2275, 0.2575, 0.2805])
+        expected_slice = np.array(
+            [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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-plus_sd15.bin")
 
         inputs = self.get_dummy_inputs(for_image_to_image=True)
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.3550, 0.2600, 0.2520, 0.2412, 0.1870, 0.3831, 0.1453, 0.1880, 0.5371])
+        expected_slice = np.array(
+            [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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
     def test_inpainting(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -169,19 +175,23 @@ def test_inpainting(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.2700, 0.2388, 0.2202, 0.2304, 0.2095, 0.2097, 0.2173, 0.2058, 0.1987])
+        expected_slice = np.array(
+            [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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
         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([0.2744, 0.2410, 0.2202, 0.2334, 0.2090, 0.2053, 0.2175, 0.2033, 0.1934])
+        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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
     def test_text_to_image_model_cpu_offload(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -224,10 +234,10 @@ def test_text_to_image_full_face(self):
         image_slice = images[0, :3, :3, -1].flatten()
 
         expected_slice = np.array(
-            [0.1706543, 0.1303711, 0.12573242, 0.21777344, 0.14550781, 0.14038086, 0.40820312, 0.41455078, 0.42529297]
+            [0.18115234, 0.13500977, 0.13427734, 0.24194336, 0.17138672, 0.16625977, 0.4260254, 0.43359375, 0.4416504]
         )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
     def test_unload(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
@@ -269,9 +279,21 @@ def test_text_to_image_sdxl(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.0965, 0.0956, 0.0849, 0.0908, 0.0944, 0.0927, 0.0888, 0.0929, 0.0920])
+        expected_slice = np.array(
+            [
+                0.09630299,
+                0.09551358,
+                0.08480701,
+                0.09070173,
+                0.09437338,
+                0.09264627,
+                0.08883232,
+                0.09287417,
+                0.09197289,
+            ]
+        )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
 
@@ -292,9 +314,11 @@ def test_text_to_image_sdxl(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.0592, 0.0573, 0.0459, 0.0542, 0.0559, 0.0523, 0.0500, 0.0540, 0.0501])
+        expected_slice = np.array(
+            [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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
     def test_image_to_image_sdxl(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="sdxl_models/image_encoder")
@@ -313,9 +337,21 @@ def test_image_to_image_sdxl(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.0652, 0.0698, 0.0723, 0.0744, 0.0699, 0.0636, 0.0784, 0.0803, 0.0742])
+        expected_slice = np.array(
+            [
+                0.06513795,
+                0.07009393,
+                0.07234055,
+                0.07426041,
+                0.07002589,
+                0.06415862,
+                0.07827643,
+                0.07962808,
+                0.07411247,
+            ]
+        )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
         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")
@@ -337,9 +373,21 @@ def test_image_to_image_sdxl(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.0708, 0.0701, 0.0735, 0.0760, 0.0739, 0.0679, 0.0756, 0.0824, 0.0837])
+        expected_slice = np.array(
+            [
+                0.07126552,
+                0.07025367,
+                0.07348302,
+                0.07580167,
+                0.07467338,
+                0.06918576,
+                0.07480252,
+                0.08279955,
+                0.08547315,
+            ]
+        )
 
-        assert np.allclose(image_slice, expected_slice, atol=1e-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
     def test_inpainting_sdxl(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="sdxl_models/image_encoder")
@@ -359,9 +407,11 @@ def test_inpainting_sdxl(self):
         image_slice = images[0, :3, :3, -1].flatten()
         image_slice.tolist()
 
-        expected_slice = np.array([0.1420, 0.1495, 0.1430, 0.1462, 0.1493, 0.1502, 0.1474, 0.1502, 0.1517])
+        expected_slice = np.array(
+            [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-4, rtol=1e-4)
+        assert np.allclose(image_slice, expected_slice, atol=1e-3)
 
         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")