o }oi@sbddlZddlmZddlmZejjejddej fddZ e dkr/ejj eje d dSdS) N)llm) train_vae)targetreturnc Cs0t}tjtj|j|j|j|j|j d|j dd S)a0 Create a partial function for validating a VAE (Variational Autoencoder) model. This function uses the training recipe defined in `train_vae()` to set up the model, data, trainer, logging, and optimization configurations for validation. It returns a Partial object that can be used by the NeMo run CLI to execute the validation procedure on the provided model and data. Returns: run.Partial: A partial object configured with llm.validate target and all necessary arguments extracted from the VAE training recipe. N)modeldatatrainerlogoptim tokenizerresumemodel_transform) rrunPartialrvalidaterrrr r r )reciper_/home/ubuntu/.local/lib/python3.10/site-packages/nemo/collections/diffusion/vae/validate_vae.py validate_vaesr__main__)default_factory) nemo_runrnemo.collectionsr(nemo.collections.diffusion.vae.train_vaerclifactoryrrr__name__mainrrrrs