nip.image_classification.pretrained_models.PretrainedImageModel#
- class nip.image_classification.pretrained_models.PretrainedImageModel(hyper_params: HyperParameters, settings: ExperimentSettings)[source]#
Base class for pretrained image models.
Methods Summary
__init__
(hyper_params, settings)generate_dataset_embeddings
(datasets[, ...])Load the model and generate embeddings for the datasets.
Attributes
allow_other_datasets
embedding_width
embedding_height
name
dataset
Methods
- __init__(hyper_params: HyperParameters, settings: ExperimentSettings)[source]#
- abstract generate_dataset_embeddings(datasets: Iterable[TensorDictDataset], delete_model: bool = True) Tensor [source]#
Load the model and generate embeddings for the datasets.
- Parameters:
datasets (Iterable[TensorDictDataset]) – The datasets to generate embeddings for
delete_model (bool, default=True) – Whether to delete the model after generating embeddings
- Returns:
embeddings (torch.Tensor) – The embeddings for the datasets