nip.image_classification.pretrained_models.PretrainedImageModel

class nip.image_classification.pretrained_models.PretrainedImageModel(hyper_params: HyperParameters, settings: ExperimentSettings)

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)

abstract generate_dataset_embeddings(datasets: Iterable[TensorDictDataset], delete_model: bool = True) → Tensor

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