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)

range_step_by_batch formula:

  • uses the runtime latent batch from EmptySD3LatentImage
  • if runtime batch is 1: value = start
  • else: auto_step = (stop - start) / (runtime_batch - 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)

Multiple Per Sample LoRA Loader (Single Pass) nodes can be stacked. Each node keeps its own LoRA bypass hooks, so different LoRAs and ranges can be applied in sequence.

Wiring

  1. CheckpointLoaderSimple.model -> Per Sample LoRA Loader (Single Pass).model
  2. Output model from this node -> KSampler.model
  3. Set EmptySD3LatentImage.batch_size normally; range_step_by_batch reads the runtime batch during sampling.
S
Description
No description provided
Readme
146 KiB
Languages
Python 100%