float-increment-per-latent

Node for single-pass LoRA sweep

Per Sample LoRA Loader (Single Pass)

Inputs:

• model
• lora_name
• mode: range, range_step_by_batch, manual_values
• start, stop
• step (used only in range)
• direction (used only in range)
• manual_values (used only in manual_values)
• batch_size (used only in range_step_by_batch)

range_step_by_batch formula:

• if batch_size = 1: value = start
• else: auto_step = (stop - start) / (batch_size - 1)

Examples:

• start=-4, stop=5, batch_size=10 -> step=1
• start=-10, stop=10, batch_size=10 -> step=2.222222...

Outputs:

• model (patched)
• weights_used (string preview)

Wiring

1. CheckpointLoaderSimple.model -> Per Sample LoRA Loader (Single Pass).model
2. Output model from this node -> KSampler.model
3. Keep EmptySD3LatentImage.batch_size aligned with this node's batch_size when using range_step_by_batch.