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rollback to 50 inference steps in IP-Adapter tests
Follow up of 8a36c8c
This is what is used in the official notebook (ip_adapter_demo.ipynb and
ip_adapter-plus_demo.ipynb)
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@ -1236,7 +1236,7 @@ def test_diffusion_ip_adapter(
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clip_image_embedding = ip_adapter.compute_clip_image_embedding(ip_adapter.preprocess_image(woman_image))
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clip_image_embedding = ip_adapter.compute_clip_image_embedding(ip_adapter.preprocess_image(woman_image))
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ip_adapter.set_clip_image_embedding(clip_image_embedding)
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ip_adapter.set_clip_image_embedding(clip_image_embedding)
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sd15.set_inference_steps(30)
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sd15.set_inference_steps(50)
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manual_seed(2)
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manual_seed(2)
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x = torch.randn(1, 4, 64, 64, device=test_device, dtype=torch.float16)
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x = torch.randn(1, 4, 64, 64, device=test_device, dtype=torch.float16)
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@ -1382,7 +1382,7 @@ def test_diffusion_ip_adapter_plus(
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clip_image_embedding = ip_adapter.compute_clip_image_embedding(ip_adapter.preprocess_image(statue_image))
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clip_image_embedding = ip_adapter.compute_clip_image_embedding(ip_adapter.preprocess_image(statue_image))
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ip_adapter.set_clip_image_embedding(clip_image_embedding)
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ip_adapter.set_clip_image_embedding(clip_image_embedding)
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sd15.set_inference_steps(30)
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sd15.set_inference_steps(50)
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manual_seed(42) # seed=42 is used in the official IP-Adapter demo
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manual_seed(42) # seed=42 is used in the official IP-Adapter demo
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x = torch.randn(1, 4, 64, 64, device=test_device, dtype=torch.float16)
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x = torch.randn(1, 4, 64, 64, device=test_device, dtype=torch.float16)
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