load_pipeline

Load a diffusion model pipeline

Description

This function loads a diffusion model pipeline consisting of a UNet, VAE decoder, and text encoder. It initializes the models and sets up the environment for inference.

Usage

load_pipeline(model_name, m2d, i2i = FALSE, unet_dtype_str,
              use_native_decoder = FALSE, use_native_text_encoder = FALSE,
              use_native_unet = FALSE, ...)

Arguments

  • model_name: The name of the model to load.
  • m2d: A list containing model-to-device mappings and configurations.
  • i2i: Logical indicating whether to load the encoder for img2img().
  • unet_dtype_str: A string representing the data type for the UNet model (e.g., “float32”, “float16”).
  • use_native_decoder: Logical; if TRUE, uses native R torch decoder instead of TorchScript. Native decoder has better GPU compatibility (especially Blackwell).
  • use_native_text_encoder: Logical; if TRUE, uses native R torch text encoder instead of TorchScript. Native text encoder has better GPU compatibility (especially Blackwell).
  • use_native_unet: Logical; if TRUE, uses native R torch UNet instead of TorchScript. Native UNet has better GPU compatibility (especially Blackwell).
  • ...: Additional arguments passed to the model loading functions.

Value

An environment containing the loaded models and configuration.

Examples

pipeline <- load_pipeline("my_model", device = "cuda")