Two little wheels rolled into the trainer today:
🎯 Aspect-ratio bucketing: no more squishing every image into a square! Each pic now hops into the bucket whose ratio fits it best, gets a gentle cover-resize + center-crop, and BucketBatchSampler keeps same-bucket pals together so batches stack nice and tidy.
🏷️ Cute caption magic: Kohya-style tag shuffling, keep_tokens to pin the first few tags, and playful tag / whole-caption dropout — data augmentation now feels like sprinkling sugar 🍬.

Also fixed a sneaky SDXL detail: we now record each image’s real original_size and crop_ltrb and feed them into add_time_ids, instead of pretending everything is a 1024² square.
The cache grew up too — one combined cache_{hash}.pt carrying latents + text-encoder outputs + metadata, always saved to disk so reruns load in a blink, with shape checks that auto-recompute if you resize.
And the UNet now takes a nap 💤 until caching is done, freeing VRAM for the little GPUs that could.

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