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74 lines
2.0 KiB
74 lines
2.0 KiB
import comfy.utils |
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def reshape_latent_to(target_shape, latent): |
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if latent.shape[1:] != target_shape[1:]: |
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latent.movedim(1, -1) |
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latent = comfy.utils.common_upscale(latent, target_shape[3], target_shape[2], "bilinear", "center") |
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latent.movedim(-1, 1) |
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return comfy.utils.repeat_to_batch_size(latent, target_shape[0]) |
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class LatentAdd: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": { "samples1": ("LATENT",), "samples2": ("LATENT",)}} |
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RETURN_TYPES = ("LATENT",) |
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FUNCTION = "op" |
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CATEGORY = "latent/advanced" |
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def op(self, samples1, samples2): |
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samples_out = samples1.copy() |
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s1 = samples1["samples"] |
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s2 = samples2["samples"] |
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s2 = reshape_latent_to(s1.shape, s2) |
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samples_out["samples"] = s1 + s2 |
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return (samples_out,) |
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class LatentSubtract: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": { "samples1": ("LATENT",), "samples2": ("LATENT",)}} |
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RETURN_TYPES = ("LATENT",) |
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FUNCTION = "op" |
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CATEGORY = "latent/advanced" |
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def op(self, samples1, samples2): |
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samples_out = samples1.copy() |
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s1 = samples1["samples"] |
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s2 = samples2["samples"] |
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s2 = reshape_latent_to(s1.shape, s2) |
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samples_out["samples"] = s1 - s2 |
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return (samples_out,) |
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class LatentMultiply: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": { "samples": ("LATENT",), |
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"multiplier": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}), |
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}} |
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RETURN_TYPES = ("LATENT",) |
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FUNCTION = "op" |
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CATEGORY = "latent/advanced" |
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def op(self, samples, multiplier): |
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samples_out = samples.copy() |
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s1 = samples["samples"] |
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samples_out["samples"] = s1 * multiplier |
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return (samples_out,) |
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NODE_CLASS_MAPPINGS = { |
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"LatentAdd": LatentAdd, |
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"LatentSubtract": LatentSubtract, |
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"LatentMultiply": LatentMultiply, |
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}
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