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small note: why JoyImage text-encode nodes emit the bucketed image
Unlike TextEncodeQwenImageEdit, the JoyImage nodes resize to a discrete bucket, so the target size can't be recomputed downstream. Keep the image output and document that it feeds VAEEncode for a matching-size init latent.
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@ -74,6 +74,8 @@ class TextEncodeJoyImageEdit(io.ComfyNode):
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ref_latent = vae.encode(resized_image)
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conditioning = node_helpers.conditioning_set_values(conditioning, {"reference_latents": [ref_latent]}, append=True)
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# Return the bucketed image so VAEEncode can build a matching-size init latent;
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# the bucket size isn't reproducible outside this node.
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return io.NodeOutput(conditioning, resized_image)
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@ -140,8 +142,8 @@ class TextEncodeJoyImageEditPlus(io.ComfyNode):
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conditioning, {"reference_latents": ref_latents}, append=True,
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)
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# The last reference sets the target resolution; return it for VAEEncode and the
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# matching negative encode.
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# The last reference sets the target resolution; return it for VAEEncode
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# since the bucket size isn't reproducible outside this node.
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return io.NodeOutput(conditioning, resized_images[-1])
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