bundle.cuda_ml_model: Bundle a cuda.ml model

In cuda.ml: R Interface for the RAPIDS cuML Suite of Libraries

Bundle a cuda.ml model

Description

Converts a model with explicit state into a bundle::bundle() object. KNN and TSVD fits do not currently implement explicit state.

Usage

## S3 method for class 'cuda_ml_model'
bundle(x, ...)

## S3 method for class 'cuda_ml_nvforest'
bundle(x, device = NULL, ...)

Arguments

x	A fitted cuda.ml model.
...	Unused.
device	For an nvForest-backed model, the device on which the bundle will restore. NULL preserves the model's current device. Use "cpu" when bundling a GPU-trained random forest for CPU-only deployment. Other cuda.ml model types do not accept this argument.

Deployment

cuda.ml validates the model state and required backend before loading it. Prepare the backend in the target process with cuda_ml_install() for GPU operation or cuda_ml_install(device = "cpu") for CPU-only nvForest inference.

Random-forest and nvForest states contain device-neutral Treelite model bytes. They retain prediction precision, class labels, preprocessing, and model semantics, but not the inference device, device identifier, tree layout, chunk size, or memory alignment. Select those settings while restoring; omitting device selects GPU inference.

bundle::bundle() stores the same explicit state. For an nvForest-backed model, the bundle also stores its chosen deployment device separately from the device-neutral state. A bundle is not required for deployment; cuda_ml_serialize() returns the complete state artifact directly.

See Also

cuda_ml_serialize, cuda_ml_unserialize

cuda.ml documentation built on Aug. 21, 2026, 9:14 a.m.