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fix sdxl structural copy
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@ -84,3 +84,16 @@ class DoubleTextEncoder(fl.Chain):
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text_embedding_g, pooled_text_embedding = text_embedding_with_pooling
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text_embedding_g, pooled_text_embedding = text_embedding_with_pooling
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text_embedding = cat((text_embedding_l, text_embedding_g), dim=-1)
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text_embedding = cat((text_embedding_l, text_embedding_g), dim=-1)
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return text_embedding, pooled_text_embedding
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return text_embedding, pooled_text_embedding
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def structural_copy(self: "DoubleTextEncoder") -> "DoubleTextEncoder":
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old_tep = self.ensure_find(TextEncoderWithPooling)
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old_tep.eject()
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copy = super().structural_copy()
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old_tep.inject()
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new_text_encoder_g = copy.ensure_find(CLIPTextEncoderG)
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projection = old_tep.layer(("Parallel", "Chain", "Linear"), fl.Linear)
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new_tep = TextEncoderWithPooling(target=new_text_encoder_g, projection=projection)
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new_tep.inject(copy.layer("Parallel", fl.Parallel))
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return copy
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@ -1590,10 +1590,14 @@ def test_diffusion_sdxl_ip_adapter_plus(
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@no_grad()
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@no_grad()
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def test_sdxl_random_init(
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@pytest.mark.parametrize("structural_copy", [False, True])
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sdxl_ddim: StableDiffusion_XL, expected_sdxl_ddim_random_init: Image.Image, test_device: torch.device
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def test_diffusion_sdxl_random_init(
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sdxl_ddim: StableDiffusion_XL,
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expected_sdxl_ddim_random_init: Image.Image,
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test_device: torch.device,
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structural_copy: bool,
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) -> None:
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) -> None:
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sdxl = sdxl_ddim
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sdxl = sdxl_ddim.structural_copy() if structural_copy else sdxl_ddim
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expected_image = expected_sdxl_ddim_random_init
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expected_image = expected_sdxl_ddim_random_init
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prompt = "a cute cat, detailed high-quality professional image"
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prompt = "a cute cat, detailed high-quality professional image"
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