Easy Apply StyleAlign

If you generate a batch of images with different prompts and want them to all look like they belong to the same set - same color grading, same rendering style, same overall vibe - the normal fix is a shared LoRA or a shared style prompt suffix, and both are blunt instruments. easy styleAlignedBatchAlign does it differently: it patches the model so images in a batch share attention and normalization statistics with each other during generation, which is a more direct way to get consistent style across varied content than hoping your prompt wording does the job.

Where it comes from. This wraps style_aligned_comfy, a ComfyUI port of Google's StyleAligned technique - the pack's own credits page cites it directly. It's genuinely under-discussed relative to how useful the idea is; across the corpus of community threads I checked, StyleAligned barely registers as a topic, which tells you it's a niche pick rather than a broken one - most people solve "consistent batch style" with a shared LoRA instead, and this node is the alternative worth knowing about if a LoRA isn't available or isn't the fit.

How the settings work. model is required - this patches whatever checkpoint you feed it. share_norm (both, group, layer, disabled) controls whether the batch shares normalization statistics, and at which granularity - group norm, layer norm, or both together - which is the mechanism that keeps color and contrast consistent across the batch. share_attn (q+k, q+k+v, disabled) controls whether attention keys (and optionally values too) get shared across the batch, which is what keeps composition and texture style aligned rather than just color. scale (0-1, default 1) is the overall strength dial - turn it down if the alignment is fighting your individual prompts too hard and flattening out the differences you actually wanted between images.

Output. A single MODEL - the patched version, ready to feed into your sampler like any normal model. This node doesn't touch conditioning or latents itself; it's purely a model-level patch that then interacts with however many images you batch through it.

Install. ComfyUI Manager (search "ComfyUI Easy Use") or manually:

cd ComfyUI/custom_nodes
git clone https://github.com/yolain/ComfyUI-Easy-Use

then restart. No extra models to download - this is a runtime patch on whatever checkpoint you already have loaded, not a separate weights file.

Common issues. The effect only shows up when you're actually sampling a batch - run this on a batch size of 1 and there's nothing else in the batch to share statistics with, so you won't see any alignment effect at all, which can look like the node isn't doing anything. If your batch comes out too uniform - different prompts producing images that look suspiciously alike beyond just "same style" - that's scale set too aggressively relative to how different your prompts actually are; back it down rather than assuming something's broken. And because this is a niche node with a thin community trail, don't expect to find a lot of troubleshooting threads if you hit an edge case - you're mostly working from the mechanism itself (shared norm/attention statistics across the batch) rather than from a body of accumulated community fixes.