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https://github.com/finegrain-ai/refiners.git
synced 2024-11-09 23:12:02 +00:00
fix legacy wording for refonly control
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@ -864,7 +864,7 @@ def test_diffusion_refonly(
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prompt = "Chicken"
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clip_text_embedding = sd15.compute_clip_text_embedding(prompt)
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sai = ReferenceOnlyControlAdapter(sd15.unet).inject()
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refonly_adapter = ReferenceOnlyControlAdapter(sd15.unet).inject()
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guide = sd15.lda.encode_image(condition_image_refonly)
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guide = torch.cat((guide, guide))
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@ -875,7 +875,7 @@ def test_diffusion_refonly(
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for step in sd15.steps:
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noise = torch.randn(2, 4, 64, 64, device=test_device)
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noised_guide = sd15.scheduler.add_noise(guide, noise, step)
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sai.set_controlnet_condition(noised_guide)
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refonly_adapter.set_controlnet_condition(noised_guide)
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x = sd15(
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x,
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step=step,
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@ -903,7 +903,7 @@ def test_diffusion_inpainting_refonly(
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prompt = "" # unconditional
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clip_text_embedding = sd15.compute_clip_text_embedding(prompt)
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sai = ReferenceOnlyControlAdapter(sd15.unet).inject()
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refonly_adapter = ReferenceOnlyControlAdapter(sd15.unet).inject()
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sd15.set_num_inference_steps(n_steps)
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sd15.set_inpainting_conditions(target_image_inpainting_refonly, mask_image_inpainting_refonly)
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@ -921,7 +921,7 @@ def test_diffusion_inpainting_refonly(
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# inpaint variation models")
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noised_guide = torch.cat([noised_guide, torch.zeros_like(noised_guide)[:, 0:1, :, :], guide], dim=1)
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sai.set_controlnet_condition(noised_guide)
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refonly_adapter.set_controlnet_condition(noised_guide)
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x = sd15(
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x,
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step=step,
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@ -13,9 +13,9 @@ from refiners.foundationals.latent_diffusion.cross_attention import CrossAttenti
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@torch.no_grad()
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def test_sai_inject_eject() -> None:
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def test_refonly_inject_eject() -> None:
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unet = SD1UNet(in_channels=9)
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sai = ReferenceOnlyControlAdapter(unet)
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adapter = ReferenceOnlyControlAdapter(unet)
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nb_cross_attention_blocks = len(list(unet.walk(CrossAttentionBlock)))
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assert nb_cross_attention_blocks > 0
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@ -26,21 +26,21 @@ def test_sai_inject_eject() -> None:
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assert len(list(unet.walk(SelfAttentionInjectionAdapter))) == 0
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with pytest.raises(AssertionError) as exc:
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sai.eject()
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adapter.eject()
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assert "not the first element" in str(exc.value)
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sai.inject()
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adapter.inject()
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assert unet.parent == sai
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assert unet.parent == adapter
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assert len(list(unet.walk(SelfAttentionInjectionPassthrough))) == 1
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assert len(list(unet.walk(SaveLayerNormAdapter))) == nb_cross_attention_blocks
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assert len(list(unet.walk(SelfAttentionInjectionAdapter))) == nb_cross_attention_blocks
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with pytest.raises(AssertionError) as exc:
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sai.inject()
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adapter.inject()
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assert "already injected" in str(exc.value)
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sai.eject()
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adapter.eject()
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assert unet.parent is None
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assert len(list(unet.walk(SelfAttentionInjectionPassthrough))) == 0
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