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@ -241,6 +241,27 @@ class LatentFlip: |
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s = samples |
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s = samples |
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return (s,) |
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return (s,) |
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class LatentComposite: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": { "samples_to": ("LATENT",), |
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"samples_from": ("LATENT",), |
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"x": ("INT", {"default": 0, "min": 0, "max": 4096, "step": 8}), |
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"y": ("INT", {"default": 0, "min": 0, "max": 4096, "step": 8}), |
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}} |
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RETURN_TYPES = ("LATENT",) |
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FUNCTION = "composite" |
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CATEGORY = "latent" |
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def composite(self, samples_to, samples_from, x, y, composite_method="normal"): |
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x = x // 8 |
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y = y // 8 |
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s = samples_to.clone() |
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s[:,:,y:y+samples_from.shape[2],x:x+samples_from.shape[3]] = samples_from[:,:,:samples_to.shape[2] - y, :samples_to.shape[3] - x] |
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return (s,) |
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def common_ksampler(device, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False): |
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def common_ksampler(device, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False): |
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if disable_noise: |
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if disable_noise: |
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noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu") |
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noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu") |
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@ -428,6 +449,7 @@ NODE_CLASS_MAPPINGS = { |
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"ConditioningCombine": ConditioningCombine, |
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"ConditioningCombine": ConditioningCombine, |
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"ConditioningSetArea": ConditioningSetArea, |
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"ConditioningSetArea": ConditioningSetArea, |
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"KSamplerAdvanced": KSamplerAdvanced, |
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"KSamplerAdvanced": KSamplerAdvanced, |
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"LatentComposite": LatentComposite, |
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"LatentRotate": LatentRotate, |
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"LatentRotate": LatentRotate, |
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"LatentFlip": LatentFlip, |
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"LatentFlip": LatentFlip, |
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} |
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} |
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